ࡱ>    G $bjbjَ *H]T;P 55555667$;=79 - 751P515151 lpP5 55151-55BJ5P4 aQ)5 Sequence Analysis of Membrane Proteins with the Web Server SPLIT Davor Juretia, Ana Jeron ia and Damir Zucib aPhysics Dept., Faculty of Natural Sciences Mathematics and Education, Univ. of Split, N.Tesle 12, HR-21000, Split, Croatia. bFaculty of Electrical Engineering, Univ. of Osijek, Istarska 3, HR-31000 Osijek, Croatia Running title: Sequence analysis of membrane proteins Mailing address of corresponding author: Prof. Dr. Davor Jureti, Physics Dept., Faculty of Natural Sciences, University of Split, N. Tesle 12, HR-21000 Split, Croatia E-mail: juretic@mapmf.pmfst.hr Phone: 385-21-385133 Fax: 385-21-385431 Key words: sequence analysis, membrane proteins, prediction, secondary structure, preference functions, transmembrane helix, interface helix, hydrophobic moments, antibacterial peptides ABSTRACT In this work, recently solved crystal structures of membrane proteins are examined with respect to the performance of the Web server SPLIT in predicting sequence location, conformation and orientation of membrane associated polypeptide segments. The SPLIT predictor is based on the preference functions method. Preference functions serve to transform the input choice of amino acid attributes into sequence dependent conformational preferences. Transmembrane helical segments are accurately predicted with a good selection of preference functions extracted from compiled database of non-homologous integral membrane proteins. Unlike other algorithms with similar high accuracy, the SPLIT predictor does not require homology information. With preference functions extracted from soluble proteins, the sequence location of shorter non-transmembrane helices can be also found in membrane proteins. In particular, Richardson's preference functions are even better than hydrophobic moments in finding interface helices at water/lipid phase boundary. The Internet access for the SPLIT system is at the address: http://pref.etfos.hr/split INTRODUCTION Different genome projects result in daily addition of new genes and translated protein sequences with ever increasing flow of genomic information and already significant impact on the world's economy1. Approximately 20 to 30% of protein sequences are expected to code for integral membrane proteins2. Sequence homology with solved crystal structure helps to model the 3D structure of the tested protein3. However, crystal structures of integral membrane proteins, known with high resolution, are still limited in number2, so that degree of sequence homology is often too low to allow 3D modelling of a novel membrane protein sequence. A more modest goal of sequence analysis is to determine membrane-associated segments in integral membrane protein. One must answer the question where in the sequence are a) transmembrane segments, b) membrane buried but not membrane spanning segments, and c) surface attached interface segments. In the case of the first question, the answer is provided by algorithms that predict the sequence location of transmembrane segments expected to be in the -helix conformation4-8. Additional information in the form of multiple sequence alignments is usually required for optimal performance5-8. Modern algorithms provide topology information as well, for certain classes of membrane proteins, by predicting not only the sequence location of potential transmembrane helical segments, but also their orientation with respect to outer and inner membrane surfaces4,5,8. No explicit prediction of the nature and secondary structure for different classes of membrane-associated segments is attempted by these algorithms. An improved predictor should be able to provide objective and accurate answers to these questions too. This goal has not been reached yet, but in this work we discuss the capabilities of our Web server, which is versatile in dealing with the above mentioned questions and easy to use. For an operator using such a server it is important to understand its limitations as well as its advantages. We shall illustrate both aspects in the performance of the Web server SPLIT9-11. The Web server SPLIT is very fast because a) it uses very simple preference functions9,12 and hydrophobic moment functions11 in its digital predictor, b) it uses the graphics library created by us to enable a fast graphical presentation of results, and c) it does not require multiple sequence alignments as additional information. Since homologous sequences to a novel sequence are often absent in a databases of protein sequences, improvements in speed and accuracy of single-sequence prediction are important. We have recently reported the SPLIT performance in predicting transmembrane helices (TMH) in the photosynthetic reaction center, light-harvesting protein, cytochrome c oxidase and bc1 mitochondrial complex, and in predicting membrane-buried but not transmembrane helices in some voltage gated channels9-11. In this work, four additional membrane proteins of recently know structure are tested to learn the predictor's accuracy in predicting the sequence location of observed TMH. In addition, the performance in predicting the sequence location of interface helices, and of other membrane-bound regular structures is examined, and the practical mode of the server's operation is outlined. It is shown that the predictor based on preference functions can complement traditional methods in finding the sequence location of transmembrane and interface helices in integral membrane proteins. MATERIALS AND METHODS The Dataset of 31 Integral Membrane Polypeptides with Known Crystal Structure Membrane polypeptides of known crystal structure are still few in number. Here we use the known structures of subunits H, L and M of the photosynthetic reaction center from Rhodobacter viridis13,14 and from Rhodobacter sphaeroides15, the lightharvesting protein from Rhodopseudomonas acidophila16,17 and plant lightharvesting protein from Pisum sativum18, the subunits I, II and III of the cytochrome c oxidase from Paracoccus denitrificans19 and the subunits I, II, III, IV, VIa, VIc, VIIa, VIIb, VIIc and VIII of the cytochrome c oxidase from bovine heart20 , bacteriorhodopsin from Halobacterium salinarium21-23, the subunits from beef heart mitochondrial bc1 complex: 7, 10, 11, cytochrome b, cytochrome c1, and Rieske protein24-27, glycophorin A from human erythrocytes28, potassium channel from Streptomyces lividans29, and ATP synthase subunit c from Escherichia coli30. Except for the bacteriorhodopsin and glycophorin listed polypeptides were not seen before by the PREF algorithm9 during the training procedure. These 31 sequences contained a total of 100 transmembrane helices with 2761 residues in the TMH conformation. Published TMH assignments were used. Selected 22 Interface Helices The membrane surface positioned helices were considered to be interface helices. Such helices were selected among non-transmembrane helices from the database of integral membrane polypeptides with known crystal structure (see above). Program RASMOL31 was used for molecular visualization. It is possible to color amino acids visualized by RASMOL, according to the temperature factor. A small utility program was written to replace experimental temperature factors by hydrophobicity values, based on the Kyte-Doolittle hydropathy scale32. A constant value was added to each hydrophobicity, to bring them into positive range. All values were then multiplied by the same constant factor, so that final range was from 0 to 90, which is suitable for RASMOL. After coloring the proteins according to the hydrophobicity of side chains, it was possible to determine the approximate position of both membrane interfaces separating the solvent from the lipid phase. Potential interface helices were also visualized with RASMOL, and identified with the STRIDE33 program for secondary structure assignment of known structures. The candidate interface helices were hand-picked according to the following criteria: 1) the center of mass distance from the membrane should not exceed 0.5 nm, 2) there should be no other polypeptide chain between an interface helix and a membrane (but transmembrane helices are regarded as the integral part of a membrane), and 3) the angle between the helix axis and membrane surface should not exceed 50 degrees. Secondary structure conformation and segment length of selected segments was in accord with the published assignment in papers where the corresponding high-resolution crystal structures first appeared. We found 50% of selected interface helices in two related photosynthetic reaction center complexes from bacteria. These interface helices are helices cd (149-165) and e (258-268) from subunit L of Rhodobacter sphaeroides , helices cd (152-162) and ect (259-267) from subunit L of Rhodobacter viridis, helices ab (81-89), cd (178-194) and e (293-302) from subunit M of Rhodobacter sphaeroides, and helices ab (81-87), cd (179-190), de' (232-237) and ect (292-298) from subunit M of Rhodobacter viridis. Remaining interface helices are helix D (201-210) of plant lightharvesting complex, helix 39-46 of lightharvesting protein from Rhodopseudomonas acidophila, helices 1-7 and 361-367 from the subunit I, helix 112-125 from subunit IV, and helix 5-13 from the subunit VIIa of the mitochondrial cytochrome c oxidase, helices a (11-20), ab (64-71), cd1 (138-147), and cd2 (156-166) from cytochrome b, and helix 4-15 of subunit 10, also from the bovine mitochondrial bc1 complex. The SPLIT 3.5 Algorithm The definition of preference functions and the training part of the procedure leading to extraction of preference functions has been described before9,10. It will be only briefly outlined here. The training dataset of 100 non-homologous membrane and soluble proteins contained incompletely known membrane proteins non-homologous to the testing dataset of membrane proteins9. For each amino acid residue, in each sequence, its type, secondary structure and sequence environment were collected. Sequence environment of a residue was calculated as an average of five left and five right attributes (such as hydrophobicity) of its neighbors. Histograms of sequence environments for all residues were approximated with Gaussian functions. Conformational preference function for the conformation 'j' of the amino acid type 'i' found within sequence environments X was then defined as: (N/Nj)(Ni j/i j)exp[-(X-i j)2/22i j] Pi j(X) = --------------------------------------- (1) ((Ni k/i k)exp[-(X-i k)2/22i k] k where Nj /N is the fraction of conformation 'j' in the protein dataset, Ni j is the number of amino acids found in each conformation, i j is the average and i j is the sample standard deviation of parameters X. The SPLIT 3.5 algorithm11 consists of transforming, predicting, filtering and refining modules. By means of preference functions, it first transforms the input choice of amino acid parameters into sequence dependent conformational preferences. A total of 88 scales of amino acid attributes is available on the server's home page with relevant references. Some of these scales are for 20 constant conformational preferences, but in the following text, whenever preferences are mentioned, it is assumed that these values are already transformed sequence dependent preferences. The predictor part of the algorithm compares preferences for -helix, -sheet, turn and undefined conformation at each sequence position and assigns the appropriate secondary structure to the highest preference. Predicted TMH segments are result of the filtering procedure, which rejects too short and splits too long predicted helical segments. Other conformational profiles are also used to refine the prediction. Ends of observed TMH are often associated with raising -sheet and turn preferences. SPLIT extends predicted TMH span when the sum of alpha and beta preferences is high (>2.0), and stops the extension when a high turn preference (>1.3) is encountered. High hydrophobic moments34 are often encountered at TMH termini. Hydrophobic moments are calculated at each sequence position i and for each twist angle in the range from 80 to 180 degrees. Hydrophobic moment index, defined as five times hydrophobic moment, is reported for two standard conformations: -helix with 100 degrees twist angle, and -sheet with 180 degree twist angle. The hydrophobic moment function I(k,i) is defined as in our recent publication11: I(k,i) = 6(k,i)exp(-((i)max-(k,i))2 )exp(-((k)opt-(k,i))2 ) (2) where (k,i)max and (k)opt are the maximal hydrophobic moment and the corresponding optimal twist angle respectively, while (k,i) and (k,i) are the hydrophobic moment for standard 'k' conformation and the corresponding twist angle, respectively. In the profiles of I(k) values, produced by the server in the numerical output, average of three values is associated with the central residue in the triplet and denoted as the hydrophobic moment threshold index I3(k). For I3(k) > 2.0 at TMH termini, the predicted TMH span is also extended. When I3(k) is very high (> 3.5) in the middle of the predicted span, the potential TMH segment is reexamined for the maximal height of -helix preferences, and rejected if such maximum is less than 2.6. An extra scale input option enables the predictor to use Richardson's middle helix preferences35 and the corresponding preference functions, extracted from the database of soluble proteins11, for the prediction of interface and extramembrane helices. Sequence dependent Richardson's preferences are denoted as free helix preferences, and are utilized too to extend the TMH span when high enough (>1.3). The prediction accuracy parameter ATM for residues in the TMH structure takes into account the overpredicted oTM, underpredicted uTM and observed number NTM of residues found in the TMH structure: ATM = ( NTM - oTM - uTM )/NTM ( 3 ) Per-segment prediction accuracy is also estimated by using equation (3) when the number of overpredicted and underpredicted TMH segments is known. Interface helices (see above) were considered as predicted when the hydrophobic moment index or the hydrophobic moment threshold index had their maximum equal or higher than 2.0 anywhere along the span of observed interface helical segment. Positive correct prediction of interface helices with Richardson preferences occurred when maximum equal or higher than 0.9 was found inside such observed segments. Correct prediction of -strand segment was scored when corresponding preference maximum equal or greater than the threshold value of 1.4 was found along the span of observed -strand. The product of transmembrane helix preferences and turn preferences had to be higher than 2.0 to indicate the sequence position of helical ends for helices entering or exiting from the membrane. The SPLIT Web Server The original prediction programs9-11, written in FORTRAN 77, were wrapped into modular web server, written in HTML, ANSI C and unix script language. An independent and portable graphics library was created to enable the graphical presentation of the results. The only required input is the protein sequence. Server's speed (predicted conformational profiles are received in seconds) and versatility (many different hydrophobicity scales36 can be used to calculate hydrophobic moment34 and preference profiles) allows easy computer experiments in predicting the secondary structure. The server is accessible at: http://pref.etfos.hr/split Recommended Amino Acid Attribute Scales and Conformational profiles The default choice of scales for operating the server are the Kyte-Doolittle hydropathy scale32 for calculating conformational preference profiles and the Eisenberg consensus hydrophobicity scale37 for calculating hydrophobic moments. The same two lists of 88 scales are avilable for the calculation of preferences and for the calculation of hydrophobic moments, but the rank orders of the scales differ. The default choice of scale is at the top position for each of the two lists. If not specified otherwise, all results presented in this paper have been obtained with the SPLIT 3.5 algorithm version and the above mentioned default choice of amino acid attributes. Notice, however, that the default choice of scales is the most common choice, but not the best choice. For instance, Edelman's scale38 for calculating conformational preferences11 and Cornette's PRIFT scale36 for calculating hydrophobic moments may be used to improve the predictor's performance. All scales except default scales are listed from the top position according to their performance in predicting membrane-spanning segments (first list) and in predicting the sequence location of amphipathic interface helices. An extra scale option (the Richardson scale)35 can be chosen as the third choice of scales when one wishes to predict the sequence location of interface and extramembrane helices as well as to improve the prediction accuracy for the termini of membrane-spanning helices. Correlation between any two scales can be quickly determined by using the SCACOR routine of the server. A total of 13 different conformational profiles is available in the Numeric Data Output of the server. Their meaning is described in the SPLIT35 - Output Description. In addition to three plotted profiles, relevant profiles for the present work can be found as columns 10 (membrane-buried helix times turn preference), 11 to 14 (hydrophobic moment and hydrophobic moment index), and 17 as the last column (Richardson preferences for "free" -helix when extra scale option is used). RESULTS The Performance Tests on Membrane Spanning Helices in Integral Membrane Polypeptides of Known Structure. All of the 100 observed sequence locations for transmembrane helices (Methods) are associated with -helix preference maximums. Maximums in the TMH preferences range from 4.75 to 2.40, while maximums in the free helix preferences (Richardson preferences) range from 2.69 to 1.01. Most of TMH preference profiles have only one clear maximum, while free helix preference profiles often exhibit more than one maximum in the sequence region where TMH is observed. Overall per-residue prediction accuracy is clearly improved when both kind of preference profiles are used in the SPLIT predictor. As measured by our accuracy parameter ATM (Methods) the performance increases from 0.69 (when only the Kyte-Doolittle scale is used) to 0.73 (when Richardson's scale is used as an extra scale too), and to 0.77 (when Edelman's scale is used in combination with the Richardson's scale). The corresponding percentage of correctly predicted TMH residues raises from 76 to 83 and to 85%. Increased per-residue prediction accuracy is gained due to better balance between underpredicted and overpredicted residues. Per-segment prediction accuracy (Eq. 3) is high (0.96) for the default choice of amino acid attributes including Richardson preferences, because only one out of 100 TMH is underpredicted and three TMH are overpredicted. For instance, one TMH is ovepredicted, while another is underpredicted in the Rieske protein11. Overpredicted TMH in the Rieske protein is the only example when corresponding free helix maximum could not be found in the predicted TMH region. Overpredicted TMH in the cytochrome b corresponds to the sequence location of two surface attached amphipathic helices cd1 and cd2. It is rejected as a TMH by the SPLIT algorithm when the PRIFT scale35 is used (instead of Eisenberg's consensus hydrophobicity scale37) to calculate the profile of hydrophobic moments. Another overpredicted TMH in the bovine cytochrome oxidase subunit 1 is not associated with the maximum for membrane-buried helix within the middle region of the preference profile. It is also of interest to test separately bacteriorhodopsin, glycophorin A, bacterial potassium channel and ATP synthase subunit c, because detailed structural knowledge for these polypeptides was not available to us when the SPLIT 3.5 predictor was constructed9-11. All 12 of observed TMH from these four polypeptides are correctly predicted with no overpredictions. Out of 305 amino acid residues observed in the TMH conformation only 19 are underpredicted and 32 are overpredicted with the default scale choice (including Richardsons scale), so that the accuracy parameter is very high ATM = 0.833. Interface Helices Interface residues in the -helix configuration are often found at the N or C terminus of membrane spanning helices. Since such segments are often amphipathic, the calculation of hydrophobic moments may be used to achieve a modest increase in the accuracy of TMH prediction11. As expected, the TMH prediction accuracy, reported in the 4-th column of the B part in the Table I, does not vary much when different amino acid attributes are used for the calculation of hydrophobic moments. The best result is achieved with the # 59 scale that we introduced in an earlier work39 . When interface helices are not fused with membrane-spanning helices it is still of interest to predict their sequence location. A standard set of 22 interface helices is collected from known structures of 31 integral membrane polypeptides (see Methods). This database of helices, oriented approximately parallel and positioned very close to inner or outer membrane surface, is used to test the performance of different conformational indexes. Since amphipathicity is commonly used for such a purpose we first created the predictor for amphipathic segments and compared the performance of all 88 amino acid attribute scales available on the server. Our index I3(), which locates sequence segments with optimal hydrophobic moments11, has a better performance than the hydrophobic moment index itself in finding the interface helices for 56 different cases (scales). It gives the same result for 24 scales, and is worse for 8 scales. In all but one of 43 cases (scales) with best performance our index I3() performes as well or better than hydrophobic moment (Table I). As the predictor for sequence location of interface helices by means of I3() and/or hydrophobic moment, the Eisenberg consensus hydrophobicity scale37 comes only 25-th in the rank order of performance. All interface helices are predicted when all 88 scales are considered, but no scale predicts more than 14 out of 22 helices. Two interface helices from the bovine cytochrome oxidase subunit I are predicted only by the Kuhn & Leigh membrane propensity scale (# 43 scale). All of 22 interface helices are associated with the maximum in Richardson's -helix preferences. However, the predictor based on Richardson preference functions (see Methods) does not see short interface helix ab in the cytochrome b of bovine bc1 complex. It also does not predict short interface helix 361-367 in the subunit I of the cytochrome c oxidase from bovine heart. Reasons for these underpredictions differ. In the case of cytochrome b, the maximum in Richardson s preferences along -helix strech 64-71 is slightly smaller than chosen threshold value of 0.90. In the case of subunit I, the TMH predictor used Richardson s preferences to extend the N-terminal region of predicted TMH so that interface helix 361-367 is fused with TMH. The existence of the maximum in Richardson preferences greater than 0.9 did not help, because TMH prediction by the SPLIT predictor takes precedence. In any case, a positive correct prediction is achieved for 20 interface helices when the predictor based on Richardsons preference functions is used to locate sequence position of interface helices. Table I Prediction of the sequence position for 22 interface helices. Each row in Table I represents one computer experiment with our SPLIT predictor applied to 31 integral membrane polypeptides. Interface helices are predicted with Richardson s preference functions in section A. Values higher than the threshold value of 2.0 for the hydrophobic moment index (H.M.) and for the hydrophobic moment threshold index I3() are used to predict the sequence position of interface helices in section B, and the best 43 amino acid scales are selected among 88 available scales. The Kyte-Doolittle preference functions and Richardson preference functions are applied in each case to predict the sequence position of transmembrane helices as well. The prediction accuracy for the TMH residues is given in the fourth column as the ATM parameter (Eq. 3). ------------------------------------------------------------------------------------------------------------------ SCALES # helices performance AMINO ACID SCALE RANK detected in TMH ORDER prediction CODE / NAME ------------------------------------------------------------------------------------------------------------------ A) 20 (60) RICH, Richardson preferences ------------------------------------------------------------------------------------------------------------------ B) I3() H.M. ATM ------------------------------------------------------------------------------------------------------------------ 1 14 12 0.737 (17) PONG1, Ponnuswamy hydrophobicity 2 14 9 0.724 (69) MATPO, mean rms fluctational disp. F1 3 13 13 0.737 (27) PRIFT, optimal amphipathic helices 4 13 13 0.725 (79) MARTI, single TMH preferences 5 13 13 0.718 (43) KUHLE, Kuhn membrane propensity 6 13 11 0.737 (66) CHOU6, helix preferences / prot. 7 13 7 0.736 (15) CIDA+ , hydrophobicity scale + prot. 8 12 12 0.735 (44) DEBER, M/A ratio in membrane prot. 9 12 12 0.725 (52) EDE25, Edelman optimal predictors 10 12 12 0.725 (41) ZAMYA, increase in volume of water 11 12 11 0.729 ( 3) PONNU, Ponnuswamy hydrophobicity 12 12 11 0.725 (51) EDE31, Edelman optimal predictors 13 12 10 0.732 (32) SWEET, optimal matching hydrop. scale 14 12 10 0.725 (07) GUY-M, average of 4 hydroph. scales 15 12 10 0.723 (22) WOLFE, Wolfeden hydrophobicity scale ------------------------------------------------------------------------------------------------------------------ TABLE I - cont. ------------------------------------------------------------------------------------------------------------------ SCALES # helices performance AMINO ACID SCALE RANK detected in TMH ORDER prediction CODE / NAME ------------------------------------------------------------------------------------------------------------------ B) I3() H.M. ATM ------------------------------------------------------------------------------------------------------------------ 16 12 9 0.735 (42) MIJER, average contact energy 17 12 9 0.734 ( 6) JONES, Jones hydrophobicity scale 18 12 8 0.727 (11) LEVIT, Levitt hydrophobicity scale 19 12 8 0.724 (31) GUYFE, Guy transfer free energy in prot. 20 12 7 0.735 (16) CIDAB, CID hydrophobicity / prot. 21 11 12 0.735 (39) MEIRO, C distance to protein center 22 11 11 0.738 (85) OSMP1, optimal scale for 1 TMH prot. 23 11 11 0.725 (53) EDE21, Edelman optimal predictors 24 11 10 0.727 (35) NNEIG, Cornette eigenvalues 25 11 9 0.731 (26) EISEN, Eisenberg consensus hydrophob. 26 11 9 0.729 (56) FASMB, Chou&Fasman preferences 27 11 9 0.726 (21) ROSEM, Roseman hydrophobicity scale 28 11 9 0.724 (71) GRANT, Grantham polarity values 29 11 9 0.723 (20) KIDER, hydrophobicity related scale 30 11 8 0.732 (12) GIBRA, hydrophobicity of aa in proteins 31 11 8 0.729 ( 9) VHEBL, coil to helix in membrane scale 32 11 8 0.726 (45) WERSC, Scheraga ratio of in/out 33 11 7 0.723 (70) WOESE, Woese polarity scale 34 11 7 0.725 ( 2) FAUPL, Fauchere & Pliska hydrophob. 35 11 7 0.725 (28) HOPPW, antigenic determinant scale 36 10 10 0.725 (54) EDE15, Edelman optimal predictors 37 10 9 0.743 (59) JURET, Chou-Fasman values ( + )/2 38 10 8 0.730 (83) MODKD, modified Kyte-Doolittle scale 39 10 8 0.730 (84) MDK4, modified Kyte-Doolittle scale 40 10 8 0.723 (30) ROSEF, mean fractional area loss 41 9 9 0.726 (86) OSMP2, optimal scale for > 1 TMH prot. 42 9 8 0.730 (80) MDK0, Modified Kyte-Doolittle scale 43 9 7 0.718 (87) JACWH2, Jacob & White IFH (0.5) scale ------------------------------------------------------------------------------------------------------------------ Recognition of Other Structural Motifs in Membrane Proteins  Figure 1. Sequence profile of membrane-buried helix preferences (dashed line) and membrane-buried helix times turn preferences (full line) for human potassium channel cik1. Edelman's scale38 was used as the input for calculating these preferences, while Richardson scale35 and corresponding preference functions extracted from soluble proteins was used to refine the digital prediction for the sequence location of transmembrane helices (bold line). Functionally most important segments are the membrane-spanning mobile voltage sensor S4 and the pore segment P thought to contain the pore helix and the selectivity filter. Other types of conformational index profiles produced by the SPLIT algorithm are also useful. For instance, the voltage sensor elements of voltage gated channels40 are associated with a very high maximum in the conformational index profile for the product of membrane-buried -helix preference and turn preference (Figure 1). This index is, as a rule, high at sequence regions known to be close to the ends of membrane-spanning helices. For bitopic membrane proteins (with only one TMH), the doublet of maximums in this index is found such that the characteristic membrane spanning -helix segment of approximately 20 residues separates these maximums (Figure 2). Is sequence location of such maximums always pointing to amino acid residues in the twilight zone of the interface regions (Figure 1 and 2), where relative dielectric constant must change from the value of 2-3 (nonpolar membrane interior) to 80 (water)? The dataset of interface helices described above is convenient to test the predictor based on this index. Seven out of 22 interface helices can be located in the sequence with this predictor when Kyte-Doolittle preference functions are used. This is not impressive result except for the fact that three of seven correctly predicted interface helices are very hard to predict with hydrophobic moments (helix 81-89 from the M subunit of photosynthetic reaction center from R. sphaeroides, and helices 1-7 and 361-367 from the subunit I of bovine heart mitochondria cytochrome oxidase).  Figure 2. Sequence profile of membrane-buried helix preferences (dashed line with open circles) and membrane-buried helix times turn preferences (full line) for human granulocyte-macrophage colony stimulating factor (receptor). The Kyte-Doolittle preference functions have been used. Predicted transmembrane helix from amino acid 301 to 324 (bold line) agrees with the Swiss-Prot assignment 299-324 for the mature receptor. Sequence location of helix times turn preference maximums alongside the span of potential membrane-spanning helix corresponds to interface regions where N and C helix termini are breaking through the lipid phase. Another class of polypeptides - membrane active peptides, forming the amphipathic -helix when attached to membrane surface, have mainly interface seeking residues. Conformational profiles for synthetic antimicrobial peptide PGYa41 exhibit a symmetric secondary structure with both peptide termini having high preference for a membrane-buried helix, while its middle region is likely to be associated with an interface seeking amphipathic -helix (Figure 3). Our threshold index I3() and hydrophobic moment index provide in this case similar information about possible sequence location of the amphipathic -helix. The choice of the amino acid attribute scale for the calculation of hydrophobic moments dictates how high maximums will be found. Maximal hydrophobic moment index of 4.8 at the sequence position 8 (Figure 3) decreases to 4.0 at the sequence position 15, when Cornette's PRIFT scale36 is used to calculate hydrophobic moments. Just the opposite happens with hemolytic peptide melittin where maximal hydrophobic moment of 2.9 at the sequence position 17 increases to 3.8 at the position 11 when the PRIFT scale is used. Preferences for a membrane-buried helix are sufficiently high in the N-terminal part of melittin sequence (Figure 4) for the region to be predicted as the TMH. On another hand, preferences for membrane-buried helix are quite low for the middle region of many antimicrobial peptides (only the example of PGYa is shown in the Figure 3). This is not so for free -helix preferences as calculated with the help of Richardson's preference functions. For instance, these preferences have high values ranging from 1.59 to 3.03 and from 2.23 to 2.88 in the case of PGLa42 and KLA743 antimicrobial peptides, respectively. Figure 3. Conformational index profiles for the designed peptide PGYa41 are for membrane-buried helix propensity (bold full line with open circles), the hydrophobic moment index for amhipathic -helix (full thin line), our threshold index I3() for amphipathic -helix (dashed line), and for Richardson's preferences for the free helix conformation (full thin line with stars). To answer the question how accurate is the present version of the SPLIT predictor in predicting -strands in membrane proteins, we tested the photosynthetic reaction center and porin by using the Kyte-Doolittle preference functions. The percentage of correctly predicted -strands is similar: 78% in photosynthetic reaction center polypeptides and 75% in the porin44. However, the number of overpredicted -strands (a total of 36) was considerably higher than the number of observed (18) and of correctly predicted (14) strands in the photosynthetic reaction center.  Figure 4. Conformational index profiles for the hemolytic protein melittin. The meaning of profile lines is the same as in the Figure 3. Predicted span of transmembrane helix is denoted with the bold line at the 1.0 level. Observed helices are labeled with the dashed line at the 0.5 level. Hence, our accuracy parameter (Eq. 3) was considerably lower for the reaction center (-1.0) than for the porin (0.625), where 12 out of 16 membrane-spanning strands are correctly predicted, 4 strands are underpredicted and 2 strands are overpredicted. For recently solved structure of the outer membrane protein A transmembrane domain45, six out of eight membrane-spanning strands are predicted at their correct sequence locations (Figure 5).  Figure 5. The preference profiles for the outer membrane protein A transmembrane domain. Generally higher -strand preferences (full bold line) than preferences for membrane-buried -helix conformation (dashed line with open circles) predict dominant -sheet structure for this domain. Horizontal lines at the level 0.5 and 1.2 denote the position of observed transmembrane -strands (dashed line) and predicted -strands (full bold line) respectively. In the case of Rieske protein (Figure 6), very high maximums in the turn preference, in the hydrophobic moment for assumed -sheet conformation and in the threshold index for optimal amphipathic -strand conformation are all achieved at the Ile 74, which is considered to be the pivot point for the movement of the soluble part of the Rieske sequence26. The second highest peak in the preferences for membrane-buried helix (at Thr 43) is flanked on both ends (at the Phe 35 and at the Val 59) with high values for our threshold index for the -helix hydrophobic moment (not shown). Richardson's preferences have maximums at Ala 51 and Val 68, inside and close to the C-terminus of observed TMH segment, respectively, but not anywhere in the sequence region 131-148 with false positive TMH prediction. The maximum at Val 68 points at the short helix from Ala 66 to Met 71. Another sequence region 103-115 with high values in Richardson's preferences (>1.4) points to helices Lys 103 to Ala 110, and Val 114 to Gln 116.  Figure 6. Conformational profiles for mature Rieske protein. Observed TMH (dashed line up to the 0.5 level) is the segment from amino acid 25 to 62, while predicted TMH (bold line at the level 1.0) is the segment from amino acid 131 to 148. Observed TMH is associated with the highest peak (full bold line) in the product of preferences for the membrane-buried helix (the Kyte-Doolittle scale input) and for free helix conformation (the Richardson's scale input). The TMH preferences alone (dashed line with open circles) are highest at the sequence positions (131-148) where hydrophobic -sheet is known to envelop the iron-sulfur cluster24-27. Richardson's preferences (full thin line) do not have a maximum associated with the predicted TMH. The pivot point at Ile 7426 for the rotation of functional domain of Rieske protein is seen as the maximum in our threshold index for -strand hydrophobic moment (dotted line profile produced with the PRIFT scale36 input). Topology Prediction With the default choice of scales we correctly predict N-terminus orientation for 26 out of 31 polypeptides with a simple version of the positive-inside rule algorithm4,11. Cases with the charge bias of zero (five such cases are found) are interpreted to mean inside orientation of the N-terminus. Since we have a biased sample - only 9 out of 31 polypeptides are observed with outside orientation of their N-terminus, our error rate in predicting N-terminus orientation would increase if the charge bias of zero is interpreted as the outside orientation. Change in the charge bias when different hydrophobicity scale is used can help to determine correct transmembrane topology. For instance, by using the PRIFT scale36 to calculate hydrophobic moments a charge bias of +4 is found for the cytochrome b (it is the charge bias of zero with the default choice of scales) and correct topology of eight transmembrane helices instead of nine. DISCUSSION The presented results indicate what would be the most practical approach to the sequence analysis of membrane proteins by means of preference functions. Success of preference functions in predicting the formation of -helices must be due to the predominant influence of local interactions. With the default choice of scales, including Richardson's preferences, all of the 100 observed TMH are associated both with an easily selected high TMH preference maximum and with a maximum (often two maximums) for free -helix preferences, while overpredicted TMH lack either one or the other of these maximums. To avoid underpredictions of transmembrane segments it is best to use the Kyte-Doolittle hydropathy scale32 and the corresponding preference functions. Edelman's optimal predictor scale38 and the corresponding preference functions increase the per-residue prediction accuracy by avoiding underprediction of residues observed in the transmembrane helix configuration. Richardson's -helix preferences35 and the corresponding preference functions for soluble proteins are good additional tool for predicting all -helices (transmembrane and extramembrane) longer than 5 residues. It is obvious that even in the case of easily predicted membrane-spanning helices, the single amino acid attribute scale is not sufficient. Tests with several different hydrophobicity scales are recommended for each tested sequence. All of the potential transmembrane helical segments can be easily classified as stable (appearing in almost all runs) and unstable (appearing only with the certain choice of hydrophobicity scale). When different results for segment prediction are obtained with several of the best scales, it is advisable to use evolutionary information if available (related homologous sequences), positive inside rule scoring for different topologies4 and complete information available in the output data file of the SPLIT predictor. Such a procedure would reduce the subjectivity in the choice of different decision (threshold) parameters. A similar conclusion holds for predicting the sequence location of interface residues. Several different conformational index profiles in the SPLIT numerical output can be used to create the predictor for the sequence location of such residues in the -helix conformation. Prediction of interface residues protruding through the membrane surface as the N- or C-terminus of longer membrane-spanning helices is possible by appropriate use of preference functions (see Figures 1 and 2). Prediction of the sequence location of interface helices lying parallel to the membrane surface can be tested when such helices are collected from known crystal structures of membrane proteins. For the dataset of such helices, it is of interest to compare older methods using hydrophobic moments34 with our own hydrophobic moment threshold functions11, and with preference functions method (Table I). The results in the Table I show that: a) Several of the best scales for calculating hydrophobic moments should be used and the results compared because even the best scales are missing about one third of observed interface helices. Widely used Eisenberg's scale37 is able to detect the sequence location of only one half of observed interface helices (Table I). b) Our hydrophobic moment threshold index I3() can be used as an equal or better tool than hydrophobic moment for the detection of interface helices. c) Richardson s preference functions extracted from soluble proteins are a better tool for detecting the sequence location of interface helices than hydrophobic moments. The need to go beyond calculations of the mean hydrophobicity with the Kyte-Doolittle hydropathy values32 and of the hydrophobic moment with the Eisenberg hydrophobicity values37 has been also pointed out by other authors46-48. These traditional tools for the classification and prediction of membrane-buried, interface and membrane active helices are extended and supplemented in this work with calculations of conformational preference profiles and hydrophobic moment functions based on several different amino acid attributes. We have judged the performance in predicting sequence location of interface helices in the terms of the percentage of correct predictions. However, it is easy to increase the percentage of correct prediction, for instance by lowering the threshold value. Then, overpredictions are increased and more meaningful performance parameters, such as the ATM (Eq 3), can actually decrease. Overpredictions in the case of interface helices can be due to predictions of extramembrane helices that are not included into our dataset of interface helices, or can be due to completely wrong predictions of helices where none is found. In the case of the best known crystal structures of photosynthetic reaction center from R. viridis and R. sphaeroides, Richardson's preference functions are predicting larger number of extramembrane helices, where none exist in the sequence (14 overpredictions), than the best scales used for the hydrophobic moments calculations in the Table I (the predictor with the PRIFT scale has 8 overpredictions in the photosynthetic reaction center). Richardson's preference functions can detect almost all -helix segments in membrane proteins, but these functions are not specific detectors of interface helices, and in proteins with predominant -sheet structure can often cause overpredictions of -helices. Another class of interface helices appears in antibacterial peptides. Antimicrobial peptides are promising therapeutic agents with very low potential to induce antibiotic resistance49, but the problem of their low selectivity in interaction with membranes50 is still restricting their use. Here, we illustrate the usefulness of combining several conformational index profiles offered by our algorithm to attack the specificity problem by designing novel peptides. Conformational profiles, such as presented in Figure 3, indicate that common motifs in such profiles may exist that are sufficiently different from motifs found in hemolytic peptides (Figure 4) to guide the design and synthesis of peptide antibiotics. Comparison of Figure 3 profiles with conformational profiles associated with transmembrane helices reveals that the buried helix profile and hydrophobic moment profiles are inverted in the Figure 3. Maximal values for hydrophobic moment profiles are in the middle of the antibacterial sequence and maximal TMH preferences are at its N- and C-terminus. Very low preference for buried-helix conformation associated with middle sequence region probably ensures low hemolytic activity of these cationic peptides unless a high membrane potential and high concentration of negative surface charges are encountered. Such conditions are characteristic of the bacterial plasma-membrane and presumably enable selective entrance and perpendicular orientation of amphipathic monomers with respect to membrane surface. For some critical concentration, spontaneous aggregation of peptide monomers is expected to cause formation of a water filled pore encircled with peptide polar faces. Concerning topology prediction, we did not take into account that some classes of membrane proteins do not follow the 'positive inside rule' 51 and that this rule should be applied to 2n topologies arising when n questionable TMH segments are identified4. Nevertheless, with the present SPLIT version, the topology prediction of known membrane polypeptides is comparable in performance11 to the Rost PHDhtm algorithm52 or to the Jones MEMSAT algorithm5. Our default choice of amino acid scales and preference functions does not wrongly predict transmembrane helices in beta-class membrane proteins such as porins (Figure 5). However, porins are not predicted as membrane proteins and no high accuracy prediction of sequence location for transmembrane beta strands was achieved. Better prediction of the porins secondary structure remains our goal for future improvement of the server SPLIT services. Although the use of -helix preferences extracted from soluble proteins may seem out of place in the case of membrane proteins, the example of Rieske protein (Figure 6) and our present and earlier results11,12 illustrate how TMH prediction can be improved when such preference functions are used. The conformational index, calculated as the product of TMH preferences and Richardson's preferences, exhibits higher and lower values with respect to TMH preferences exactly at the Rieske sequence regions associated, respectively, with TMH underprediction and TMH overprediction. Free helices predicted in soluble and membrane proteins with Richardsons preferences are of interest as possible initiation sites of protein folding, because -helices may function as independent "seeds for folding"53. ACKNOWLEDGEMENTS We are grateful to Bono Lu i of the Ruer Boakovi Institute in Zagreb, who helped us with some references. This work was supported by the Croatian Ministry of Science Grant 177060 to D.J. REFERENCES J. Enriquez, Science 281 (1998) 925-926. D. T. Jones, FEBS Lett. 423 (1998) 281-285. A. C. W. May and T. L. Blundell, Curr. Opin. Biotech. 5 (1994) 355-360. G. von Heijne, J. Mol. Biol. 225 (1992) 487-494. D. T. Jones, W. R. Taylor and J. M. Thornton, Biochemistry 33 (1994) 3038-3049. B. Persson and P. Argos, J. Mol. Biol. 237 (1994) 182-192. B. Rost, R. Casadio, P. Fariselli and C. Sander, Protein Science 4 (1995) 521-533. B. Rost, P. Fariselli and R. Casadio, Protein Science 5 (1996) 1704-1718. D. Jureti, B. Lu i, D. Zuci and N. Trinajsti, Protein transmembrane structure: recognition and prediction by using hydrophobicity scales through preference functions, in: C. Parkanyi (Ed.), Theoretical and Computational Chemistry, Vol 5. Elsevier Science, Amsterdam, 1998, pp. 405-445. D. Jureti, D. Zuci, B. Lu i and N. Trinajsti, Computers Chem. 22 (1998) 279-294. D. Jureti and A. Lu in, Journal of Chemical Information and Computer Sciences 38 (1998) 575-585. D. Jureti, B. K. Lee, N. Trinajsti and R. W. Williams, Biopolymers 33 (1993) 255-273. J. Deisenhofer, O. Epp, K. Miki, R. Huber and H. Michel, Nature 318 (1985) 618-624. J. Deisenhofer, O. Epp, I. Sinning and H. Michel, J. Mol. Biol. 246 (1995) 429-457. J. P. Allen, G. Feher, T. O. Yeates, H. Komiya and D. C. Rees, Proc. Natl. Acad. Sci. USA 84 (1987) 6162-6166. G. McDermott, S. M. Prince, A. A. Freer, A. M. Hawthornthwaite-Lawless, M. Z. Papiz, R. J. Cogdell and N. W. Isaacs, Nature 374 (1995) 517-521. S. M. Prince , M. Z. Papiz , A. A. Freer , G. McDermott , A. M. Hawthornthwaite Lawless, R. J. Cogdell and N. W. Isaacs, J. Mol. Biol. 268 (1997) 412423. W. Khlbrandt, D. N. Wang and Y. Fujiyoshi, Nature 367 (1994) 614-621. S. Iwata, C. Ostermeier, B. Ludwig and H. Michel, Nature 376 (1995) 660-668. T. Tsukihara, H. Aoyama, E. Yamashita, T. Tomizaki, H. Yamaguchi, K. Shinzawa-Itoh, R. Nakashima, R. Yaono and S. Yoshikawa, Science 272 (1996) 1136-1144. R. Henderson, J. M. Baldwin, T. A. Ceska, F. Zemlin, E. Beckmann and K. H. Downing, J. Mol. Biol. 213 (1990) 899-920. E. Pebay-Peyroula, G. Rummel, J. P. Rosenbusch and E. M. Landau, Science 277 (1997) 1676-1681. H. Luecke, H. T. Richter and J. K. Lanyi, Science 280 (1998) 1934-1937. S. Iwata, M. Saznovits, T. A. Link and H. Michel Structure 4 (1996) 567-579. D. Xia, C. A. Yu, H. Kim, J. Z. Xia, A. M. Kachurin, L. Zhang, L. Yu and J. Deisenhofer, Science 277 (1997) 60-66. Z. Zhang, L. Huang, V. M. Shulmeister, Y. I. Chi, K. K. Kim, L. W. Hung, A. R. Crofts, E. A. Berry and S. H. Kim, Nature 392 (1998) 677-684. S. Iwata, J. W. Lee, K. Okada, J. K. Lee, M. Iwata, B. Rasmussen, T. A. Link, S. Ramaswamy and B. K. Jap, Science 281 (1998) 64-71. K. R. MacKenzie, J. H. Prestegar and, D. M. Engelman, Science 276 (1997) 131133. D. A. Doyle, J. M. Cabral, R. A. Pfuetzner, A. Kuo, J. M. Gulbis, S. L. Cohen, B. T. Chait and R. MacKinnon, Science 280 (1998) 69-77. M. E. Girvin, V. K. Rastogi, F. Abildgaard, J. L. Markley and R. H. Fillingame, Biochemistry 37 (1998) 88178824 L. A. Sayle and E. J. Milnerwhite, Trends in Biochemical Sciences 20 (1995) 374-376. J. Kyte and R. F. Doolittle, J. Mol. Biol. 157 (1982) 105-132. D. Frishman and P. Argos, Proteins 23 (1995) 566-579. D. Eisenberg, E. Schwarz, M. Komaromy and R. Wall, J. Mol. Biol. 179 (1984) 125-142. J. S. Richardson and D. C. Richardson, Science 240 (1988) 16481652. J. L. Cornette, K. B. Cease, H. Margalit, J. L. Spouge, J. A. Berzofsky and C. DeLisi, J. Mol. Biol. 195 (1987) 659-685. D. Eisenberg, R. M. Weiss, T. C. Terwilliger and W. Wilcox, Faraday Symp. Chem.Soc. 17 (1982) 109-120. J. Edelman, J. Mol. Biol. 232 (1993) 165-191. D. Jureti, N. Trinajsti and B. Lu i, J. Math. Chem. 14 (1993) 35-45. W. Catterall, Annu. Rev. Biochem. 64 (1995) 493-531. A. Tossi, C. Tarantino and D. Romeo, Eur. J. Biochem. 250 (1997) 540-558. W. L. Maloy and U. P. Kari, Biopolymers 37 (1995) 105-122. M. Dathe, T. Wieprecht, H. Nikolenko, L. Handel, W. L. Maloy, D. L. MacDonald, M. Beyermann and M. Bienert, FEBS Lett. 403 (1997) 208-212. M. S. Weiss and G. E. Schulz, J. Mol. Biol. 227 (1992) 493-509. A. Pautsch and G. E. Schulz, Nature structural biology 5 (1998) 1013-1017. R. Brasseur, J. Biol. Chem. 266 (1991) 16120-16127. M. G. Roberts, D. A. Phoenix and A. R. Pewsey, Comput. Appl. Biosci. 13 (1997) 99-106. D. A. Phoenix, A. Stanworth and F. Harris, Biologicheskie Membrany 15 (1998) 83-89. G. Saberwal and R. Nagaraj, Biochim. Biophys. Acta 1197 (1994) 109-131. T. Wieprecht, M. Dathe, M. Beyermann, E. Krause, W. L. Maloy, D. L. MacDonald and M. Bienert, Biochemistry 36 (1997) 6124-6132. Y. Gavel and G. von Heijne, Eur. J. Biochem. 205 (1992) 1207-1215. B. Rost, R. Casadio and P. Fariselli, Refining neural network predictions for helical transmembrane proteins by dynamic programming, in: D. J. States, P. Agarwal, T. Gaasterland, L. Hunter and R. F. Smith (Eds.), Proceedings Fourth International Conference on Intelligent Systems for Molecular Bilogy, AAAI Press, Menlo Park, California, 1996, pp. 192-200. 53. L. G. Presta and G. D. Rose, Science 240 (1988) 1632-1641. SA}ETAK U radu se ispituje kvaliteta predvianja sekventne lokacije, konformacije i orijentacije membranskih polipeptida poznate kristalne strukture pomou web poslu~itelja SPLIT. Poslu~itelj SPLIT temelji se na metodi sklonosnih funkcija. Navedene funkcije slu~e za pretvorbu po etnog izbora ljestvice aminokiselinskih parametara u konformacijske sklonosti ovisne o sekventnoj okolini. Transmembranske uzvojnice to no se predviaju kada se napravi dobar izbor sklonosnih funkcija koje se pak dobivaju iz datoteke integralnih membranskih proteina. Za razliku od drugih algoritama s sli nom kvalitetom predvianja, prediktor SPLIT ne zahtijeva informacije o homologiji. Sekvencijska lokacija kraih izvanmembranskih uzvojnica takoer se mo~e nai s pomou sklonosnih funkcija odreenih na skupu topljivih proteina. Posebno, Richardsonove sklonosne funkcije bolji su prediktori od hidrofobnih momenata, ak i onda kada se radi o pogaanju sekvencijskog polo~aja uzvojnica koje le~e na povraini membrane. Internet adresa za poslu~itelj SPLIT jest: http://pref.etfos.hr/split PAGE 35  EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph  (*,2*.Y b  pqdjLR&*_c ;@deiwyDF`x}  8 M O 56OJQJ H*OJQJ 5OJQJ 6OJQJ H*OJQJOJQJOJQJ5CJ(OJQJ CJOJQJN,.0*TVTtX Y b c $dh$dh$$d,.0*TVTtX Y b c Y-!!!!!'l,m,n,,,f////d011113368L;>>???BDFGGHLLLL:O;OOOU Y"Y2Y4YZZ ZcyezeeeCiDitqHyIy  d Y-!!!!!'l,m,n,,,f////d0$dh$dhO r !!""##%%Z)q)))**G*H*v****+)+++++`,a,n,,,- ---00$0*0.040H0N0P0R0X0Z0`0h0n0j1l1n1r1x1|1111111111111p2z2 jCJ$OJQJ CJOJQJ H*OJQJ 5OJQJ56OJQJ >*OJQJ H*OJQJ 6OJQJOJQJMd011113368L;>>???BDFGGHLLLL:O;O$dh$dh$dh$z2223$333|;;>>"?(?8?:?R?X?h?j?????BBBBCCDEJEFFFG!G"G#GIGKG]G_GuGwGGGGGGGGGGGKKLLLLLLpNrNNN9O;OOOOCPEPRRRRRRSTUT"Y2Y4YZ Z] 5OJQJ56OJQJ 6OJQJ H*OJQJ H*OJQJOJQJV;OOOU Y"Y2Y4YZZ ZcyezeeeCiDitqHyIyJyKySy~Pv$dh$dh$dh]]``aaaaaa0b2b"d&dleoezeeehh>i@ikkllnnoo.p0pssKyRySy{{~~~(*.ghۉ(*.;<=?HڱjOJQJUhmHnHB*CJ5B*5B*OJQJB*6H*OJQJ 6OJQJ 5OJQJ56OJQJ H*OJQJOJQJ H*OJQJEIyJyKySy~Pv,0܃V{IsՇ78ghۉ_Ŋ{0֍OM sՑ:iғ4]"O;<?ƝN.024 dv,0܃V{IsՇ78ghۉ_$Ŋ{0֍OM sՑ:iғ4]"O;<?ƝN.$dh$dhNP$2.8<_akm^`tPTlnڼۼܼx|]hi56OJQJj6OJQJUhmHnHj5OJQJUhmHnH6H*OJQJ H*OJQJ 5OJQJjOJQJUhmHnH H*OJQJOJQJ 6OJQJ6H*OJQJ=.024tvxڼۼݼ޼߼$dh$dhtvxڼۼݼ޼߼Z[]^_`abcdefghjk.j\8:|~ "$&hjlTV%&           ZZ[]^_`abcdefghjk$dh$dhmo >@ gi(*#%OP68YZtx&*0T`ad/>?A 6OJQJ H*OJQJ 5OJQJ H*OJQJOJQJZ.j\8:|~ "$&$pdh$dh$dh&hjlTV%&wx STF^`$ `$$dh$dh&wx STF^` : <   c d       ) *   C D     :;<xql                                                          *AbRBDF`HPhn      3 N Q     }                  ! . / 2         '(*"(), 56OJQJ 5OJQJ 6OJQJOJQJ[` : <   c d       ) *   C D     $$ ` :;<=>QR vw89 $ & F `$$ `<=>QR vw89}vo   +   *   )   (    '   &   %   $   #   "   !                          ) u S`aekl"#'78uPlnrLlntt}  .<=@ 67;956OJQJ 6OJQJOJQJ 5OJQJ[9 !UVLM$$ ` !UVLMtv#########$$T$p$q$$$$$$$$$    3   2   1   0   /   .   -   ,*tv#######$$5$6$R$S$o$dP $& #$!dhdh$ `$6DFLt########$$$$$1$2$3$4$6$7$N$O$P$Q$S$T$k$l$m$n$p$q$$$$$$$${ jZeUjn> CJUVhmHnH jSUj> CJUVhmHnH j+EUj> CJUVhmHnH jE+Uj> CJUVhmHnHjּ> CJUVhmHnHmHnH jUOJQJ 5OJQJOJQJ 6OJQJ,o$p$$$$$$$dh$$$$$$OJQJ jU jUja> CJUVhmHnH+0P/ =!"P#$%+0P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"#$%. 00P/ =!"#$%. 00P/ =!"#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%`!*.hCwmފA~ U8c*xԚ NUǟ1cfq*LT$F2!9E%" BRT$)!a0 woϽnz}{꺭{j-'BGPB'e1EQPP(j+7- %^: :L⟹9 IlB#= ʋ:PhY0iGĖzLt$O^,qz>|Y,ku+r_UN=`_pD^^#]Ucb?s fnO$W %Ӭն_E#nAժc&mtC|7j]ܠ>)/?4={Wus͇nMɯڍ ۈȈmE*2b|qX3Fo˷kۈO8k);}74//x]3^3_9%_N{IDDvy y gum"hE(Њ@K76/͋Pul^-)l"h6xk)Ranj(j\']sfi#Xa6Z--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻ*ڼkkjjڸzfc/ű՗Kqltl8RKql:R[}=[})T'5[}=[})TV_cUe9JΙöެ6 zZ--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻv}SO7o.cr9yFa`EdMO`Kpg",X"|(jc(lc '{0'ۃE>qVę 1.cdQ 1r 2CwB9N"-/;3POp\˵"wA m&h/@G9 :4|C|+O20Cd )/Ack9%cTpns0>BSQ[,} +od۵n؂}l얗!Cfyp\2~"+BeVW60 )rʆ+-**a[ C)h6j;4Ƽ m}T]yxBe%q+83FŘNv24}0f)1V_\|f: ?wb+ .Bz?(N(}HA:^]B֥t](By ns^5*B}FlJ3 zjWҫ;aOG1f0gFjߤa<I5olx9z |ç8z,XW詰JPXgFLخ?ݺ+dZp@8K CyR-*nj'u8BDxZ%@J IoV Zp+p!%xV ,Ga<>uO\>x&~Wr0MOW ^3xDWO!z:☳<|CcXaR6!lVbm8!AS} BD44į0_8f:V~eXPc3T K٬o6-If*0kY ulgҌM#hg*A{:q]LMxʔO/K3/IWCi=|G6fZx &~60הy97Bj٠V]ʌߛz)MjsMd8`.M6gtq@.ĸeHqo7tY'u;GWp{A-̻w㡁; +!̈́f xНܙsӠ[ :n}C> ]z0~ݭG`Ǻq)8t7Jާgn1}[/pG/`_atj=7a`{xs؍3]ߜr& #K._ݐqe8oAqo0:Ai=f.)S=0uq/F#짉 ͽ,h靁v H6A'o tVo=Bw þ^p/dFyW`wa?oz{a23 }a?s0[ հ[K{ fxX㍁uL؈v1O8Qw b\y`yA^ OCL8s$9\ADZ93/aIԄwV(ҒkLJZ[vDZam|h /6i. Y[ diL{|qrؕjLqʺ%h*0JkT{CZ{T"_nTIj+S(Q*+!m ktIi$;X[r㛲,}K;K$(NH(]FTYr{rfIpI7Av׷=W |x1AWU$w&kJ|n]+FWuBzmUyu{VW#W]LurPPjMrB-ҪAm#j[n' SS"_;HԅNAE$ǵPn@}䮀nL^mД}Мr3AVDa[m h{3"_|<'w.h\{vB#tH#2dKrC0~x@;>v䞃GC*S'μyMZEM?"0y(le4F3#bLȍ604> /W![R.Q=﯎M<_zא9D fLg0iHԙ(x")S}!LՈwc*JX튎!(xDZAKtki;?0aKGڧLohV{S"@Y=OZ#Sv[x35"EC:Vօ*Vg5i(KieDDV3}U>$ 'mDW7=K|{Z{u#cDw tU *0B|9Z*IC|uR1enkV2}BRDLV͔Y>&D-D_ƬV_!^jȲ&rD|Q(DTWM'"n!"=QT&j5)j1IUԣ=XKOX5-G$]$§9y?iq Q!"_$Ȧ*U$2LlNZ*D& msDx D<قc"_|dKpX'"OOA2]fUH+T5iUzd]N D@!m"[D|Ֆ3`ݵLݡڑv0>}% GɍV+#I`n}ݞfL)DhԖݮ:I"_amPvGI4sX[;-"J60md7]w$3qa7UdzZAEG(%Qf27E#[2U$2dH!`2B$*TBEzu뜽Y{<{7]sZ&I{iA;Ku6򦒴S]F[#inCܮjvGt6@ڠț˃h-h + jitt@CL?SmLI'{δ\+ʏtr;*`L}YՋhnF zKYƧ\&0)w2 m)V>LR ֱ |YtIG|YVdڈ?lA_/>MW{[io/i/WڄSoht]Ctm kϑ(ߣP|(> Dqutܥn(>}M[gx{h3U3P|3yANw{QE~ѮW]|XmUUUAޜͻ_PQa*+yFۦyRY`ҦBތӆ^Dha(򦭶t w':B[xGhQTySJ[a{ B{v(Ky+U7yjNWf'  ^N⻟S7=C"ohyA%L{g9yLV={dSPҨtEv mj# װTO]ȇ״-- δRȇ-po1G m 3h"3iO#^8ù;,\*ƪ&(ɮ2ppUiCTCQj:G*wZ•K6WmG>|B$WE)yPk*Q5ڮ:L˅(~Mbt? wmr 1UR0 GތRMt]\N[#WP|zwr%^b_N\I}q  FyݴMo=6_CP\%)UA[ISyOkjWݢys4VBޔ3T%7j;IZӿU]Z(}Zțh6fkC{I5 U/MgזByskGAyskO@Uu`Zա{Cpimt!o~ky횎vp:P8Tu:>#DmlD vKg2 UEۃv퉮ENSu}iUFޔhE TytgP>I\:bLVtdpQ m!V(;4oQ8tId;2vz%ojcCgڬk":=[UZXڅP| 6țn1mx4hN' h"fEn"ZY*{lmUIL<_^C7Ŵ+QYMumt:.yݍi.o:[3ԙJ{ZgP4N{Mf(TuLf(~as@[:V0LiJT( έU_Hns:bQWŧ$6LAެ/i t!oj'_3'Yߠ!(UO괛|KkzyXnE\-iuUu7yS\UXFGPXӸv~riQyR\y]hyN[Uovu?ZZ"o&ysn9O[ UqvI=L۽tݏv;u:]fVBQ(>O DکjAj AT=ԪQ5+R+i~{VFZEU%'Ӻ(>9ǙO m>~ _ ;nRb34>MUMkiTQ|hTQѶƊ[aHtomTCu: Sȇu]AD{ zy3I5Ch aڧt-DE+Lj\aT.N; C>S芠 (M(L o^.yL btK׃әss麑~K\[/J$kkȥLhD}7j{ٕBQ|4NG;'9L:bQ|pn:P|ΐ6W6(>]H+xO$^Cy(>gH!3 ηGiUPX'jມțڹ- F1ODmTuuZ*}Le7mOn.>Fͻ'\?g;]7kk>ț}Q+=nMț+ղOțT)?D7 kBm;h kBm볁骂šPl, RDaM=EJP[l0jJP[iT3 +9Zy4""o4#!R:C͘tfțtp=@"ogo W-t) לlj"e]ȇW(t Π f,ڤl6z Ρ-FːG\lp4ͧ:grdt v*yB5Q\uNohQ݃g]Lzp.=zp/zpYF[zpI+}|rvȮ@$Ҵ[NCqZE.½U贡{X}iTQgZEV(36խAP\}@[Zo-mj;u#(Ӽ*U߇j(6k U&㪞(>h$f4 U')Zo+@0_8UJNW8ك~tX;bGQ|u}>I$O=1y(.YX4ݥG}Q]*@k#Qkûu2}S(3Ֆ¨򦆪NϐPIwR;Iu¥AWj'L}芢țUu:y4^RryLAq)N;b(8NAgz;N%PuwJNwgb(8gc(FlJsʡ|( љ|z]NJ ǁխ(CJ:TT$oq+(z:?Tph.@pij7hR9xTDj1=[UySYj.:"͵RvC#Rk/ț"@ a(_^&"o˥ErZ?T@*~n\ȵL?QmLMh7r V]e-E#w(܋&}L'Jc4J0}Z5Nr?MjwNw~.wR;WZ2(WPܭjEۯڇNWk'-(Ik>%\jCh{|wQ;;c\ŽPCq_K:Tg5 ŝч٭ڍ#ʠG<wsSk1(vG}7ij^t-qt3=iUl/Q+Dq'7$#Lu0Kh' Y?ڇٓh= dl>khLlgmE65G6{vC,j=Ǵ~j a$"oZfQ;Vf@664{ CތƠXӲ1g/f.&Vg5ț-$5f_6v4!oruZ}V;ŷhU T Uw5-țv:fAigyjNgYhB3ΦSGlsh;T;L~CqWan:+PGL<wjr7vf>ߡRFqt/{ iUcPܯ]D^ojtC>rKRFqy)2SVJu+hue%^yj ]NXcVGPܭ_E//d-Yޒ hl&1ތV3 ڇo|oQ.iwPngzsU{B.w 9qtL~_=okh_J~hdBNAQ\YޖBLHa4F{ANWg@#)W )eiKZY+> h+AiJe/B+ô`;x%(㳻w@Y<-LS0u% ! LTIͣ<ʣ$MMJMM< M;MQ 5541T꣗g9sY!^<)a̒8~H'9ijeβo]~N!e{rHO#HˬW 0f@1Rk &YH899\ֻ$&.kS$fȶd6Cb:領!{4-2*~ |^,Z29Z.g r6VR6W@'S;_bizN$}Mz4G^(2ݨ{CCsB[< :/U ›Qx0 130a>+,÷Xu؀-؎l^Q)A!.2( : G#fGKA$'4: E]u[*u 01!`:fbbc)V k ;؏:8(YG,|Q*{PS QhxG$rz)gݐB_ kHǛQx0  +,÷Xu؈I{qGqppW`yYaGYT@D5P uq[݀fGKA$b"R701c0CLt§XX,zl6U pp8(B1,v/*{PA4E#D="QIHF z/5c(h{ |OXt1[vg!|E\ePjp>܏h(Z "80 ZR>'Ⱦǭ4֭%nݮh? dUZs'`kz3{a9զ04{Xo%m2mzz>avg;z]{japi8U{h6]US~=S]]_l([4TFzs_[v-e*!B[⺮p#}txtMNLMMJ-J:2_mszb1ѭcb?቉nn*T 4Rղv,ԿB#7ҺzZ]Jj׷+[R:tMLI T[QOĭj;W?}ޙ87Gg}q#[F\Q-"bK޽cp}X4P_ϫ [ηtB: YYYJV^2{i2mL8]ў}+&`YcY}-1敢 {`!65Li()jhGA~ $U8xԙ es{Gq4%Fa23FfFT9O(%%IJA%r#D'P2ڳ׺캮޾mk}?s3;/ u|RTP\YS{3Ա%QUNF"Ց+'zjn5_ρ@XO*^A (:!Oڹ wPP,Oxi\󟭋^h=Zx7?>O7=URRRZhFPj: =++hɍ qWmJ?{%%{0XSGi2YD{Hjϲ-iY q~F{Pe~s*>Y3Y5{euVF,؈Ie6b[IxxiX^FL.x-;E4K41YYFt UԒSQoMa$/~#ywzH^LE yW%/Lkz yBSQosH6;GXb*Kż#΋xEa{!zf:8?1۱O q^6oH^{[h[h%Zɛněn$*%~$=bO~7Hog1:;|DS~==K&JHW 0[bgyvWGZ70Pu#DĆ{Է0V *'t3)fSsTΧX@D ֐Hb/yߨ f0̄f` b8M\lRL*~LmS|FKӚ7{$Ϧ lZgTh[6ֲXM(QQȲ9Ko6Plv(%06O 6x>c5:հî |e[O/֣a8 9a>Ԇ3Bh@3΅aٶ`'hWA^xb_(E@><d}! (&߀S.>x!T C?I}|N}}M}~K1 c>VC+nA`ŭ*x'=d?( S` Φ_&[Al"YL)|F_P~C9%m8<.ÅX- kQ$n@фp>QNkpk17\ GGx1 O~>8bN%7Nc^"Sث7ӕRp{09Nj-<x&NjLco;Lev:o/SZ{zfRҰ9]%vbtS*W7)_=ث┯P2&VX;IqWmÓqW3` {dwUx89Au8]Lc8R[[eUYZqWAM XMd嫙PYt柮|5 Zwb5nt*`V/Ў ՗o[`$$OW;┯>-q*x!VR6{uaIU3x_p+_ػ W7ӕ{ʩi|5~J*V6l Ne+NȬSG}7hjβ*U]^ X]^y1N^SXY^/zǬ&])_ [VT?aouVPofoS;Y$sj'{?8uDV;ث:^Ԟ8E+G}.+G햕>֙*!FtEޣN#6{_FqWUÐ * c2>1G.i7XaL.]W2^]jY/hlrO<ysmV!GaU : QLJ[Mj ;J b*FFO22Z%YYL #Jrԑ(QFV&[3൦*mvAG,\0̂^q4n36Fg]&@1c0.3gRmDSF25L=QL56F`@1/T+'+f G=W^4Q | p2zRw"ʬG^sћ `=w{#̾g=oK_D;Aϟ jN}Ha~r vZD\f%\glC2Ӊ>YPm2&` GAh V(J%e:c2UIr3P'Q:9D=](ލp70XB&aEeOw7qx/0W%ΆI({z΃)L&Ze2<jr 5l@el[h$'wD[!*vth_8~9s lJ ,8EE aG G6-%t5ejj5}ZMVÕX-pkp++e}m{>yY^-}==y犜 7yEuMB %VnR7 U+Ĉ\UJȶ…FUwdE:e.3!^0I\n<gT>G%b9Pu$YXПcE9|R@mNs^qټ[HV%*U ݳ0U?;VzGjjThɪV biJ+{TkУxHQVFn,t%U:DBz|IT#\NT: SIFڌM*5beu*#A.4"HhQ:yc|B:H=F1o\M Ud/,}IuRYO#4?lΐk<gIyT%-T^W+/ӥ5m :RVVjݺAFZ=UgMV!VPz6lkcEZ=޷BU炶buڭR3Yn=妽*mwvunGY,^vz-;it(UNTzSQ/STq~;:ҶU>avujDڅVop`UN* qSJDVU+#ܔR=_[{j/UJ;ʶui۪V sP`},#eٯ$jϙ3I25~kC=Ο빚*p[bʹʑB܉ ܅Y܋a#؀؂mx;,UtN>OW8"Cc1E!J0 wc6cK +Њ6BGPѱQt$Np> C4b$G2}RL AjрXXXMhB3Z;{pq у3KvDb8␈1HA:b31ը/ߚpg}jU;7{YxZ+.MZ`V'SR0UKQ߿/];nt{?"f'pL)ES3'GGOʙILPn >NTG`zm`}'^`Jcs[797HVP{† FNnh]?gV< ٞ3Cv󃃯u\('_嫏VTh/e9%Ssses֜`NH{j#Ã[C#+vOvO+g=45mQO7zwY'c60G&9PwKt?x3z`!=w5\V~.9~ U8 x՚ tTo1 /D DAK-XALBxWhyb( 0+*h)CRbX m8&* P! x@ 9mr6;wwwf}/yKQ'<{,勉?L~Ss#qgѾM) "[.IyNmL/DA3~4m{azqCOow9%s.ͥo/,&|Ԗ"IMW$[Z^" >?m=^"=4E%]tl>'T=Vf}[R}f*bqc حz|F=vo_XC=6ĕ/q3Rvq\v%\ m/fx8Xn(& )鲤 ))RU+W&vue慔7~ߨul^H~\i6y#/?bqzf!ns3;pl]=ۼgع.!eCryҺri2ː6oYl^̹ټu \y[ݙۼΎ/gLc;Q9[AS|[AQ|VVPo+ho+(xEU;g+ho+(߷4ŷqF\Qo:[A2NO\-'3_3_C*֌u34[3ճ͛|ykR=l^+Z)W.+6/ù i֑uŜ{NXye ՝/| cu<_)̈<:he fR5m,[Z,KZS: 6TvSeVV)Ko2 U*ʊ e:̊˲hd_pu hA#kaPȈ(%P')m+ŹZ@)^>dNn[^ @OX-AFEpr'tEn$wQ=A #zpq(dDהs@M@F#7@PȈ?!pp&Opjqp xн #V7MU?PMBt 7\M _Mn]2 u7-45F zd>A`b+ эa #˥p+rУ #pU #nk@7# OV> K> 2"3 .]na&8)Ge tdD^2{ 2b-n9Z27M@F| CBѾTE:MMbA.Nh;גlDQOP'b0tI}ms@bD_=)?E18+Px ܝ ,XWИb?hxT '"XA<.bRPwL(,1.W/!:DL-f){w!Q wXd\  Ȉb-Z #{9z{"Vxx уu#-QQ}pHCptԙjE+k) ԗa==΅CAcAFBAo"zu+%  (8c4q*r4t+ϩEt -r[,.5p"zŽv!:D@ #谽 !½GI܏dYp1jN#Ap;mJAM5`mD9C4J߅Ѝ M/?4яts?)ZhcZ 59Eͤ7z?GeScAtD"v5"Ng͡@Q2 m}n] I9i0 A0rH#'] ڂ$g}[#K4H.At\ w\'Dt7M.#:K'w-AA;\~#)E~bGR }W2td,8 U3DU-ڪA #.Qp=UP/רΠ #Fnp7onQ!:S]@Q3jGU?JTypϫj0HnUcWA5FDD(O8}gڃ³9\h./ AAF~eѻ{y9h!Ȉy%\Ŀm 7@F7>譠z2E #bpٺdD~ n~4RMop~Э #nI {G셕oKzakno:w > Oϗv_nuVgMvet^WH+N3&{͹'mݶں]ݶm\u WF^Y^~ ΰr-\Geo/.܇rIAv8'}ٹ>7TjvgS]Jak,2UA}vغ|D./p [Sus\.hU5]BmB sКP]֝LAصV% P]2].hUVa$g$li:Ѻ"0zPeFV[:Z+*T%gP:Oa[?OF,Z|9t5Ƕ _ڽ%\(H^TUg\ WpZWqE|~1WMKQc(\ h까 mw:vr-ܯy./xjw7 qpj\*ƺki|>ef{v*N9p.7cnurn4pns%p9ׅ%Ia\i]s1Ɋ*;V8¹%K8{O0oޔu>V%pMys++kqNp.\Ja\.׹\o.w\\sp &;ǹں\bpsa.wܹR[ Vp ΍X\ n-½Ε;W ps p{9:s:#] J;W\)a5 ſZ_Tx*W} d{WwOM@nvz[sôɭҧ2hx okv~[{RϝSV3ĎE?;5Sru=?ZѺ[kU ܯ ?~W ..Sk7J^ju=csff|شM"[drA9CrIO'g`r.z;YYrippRG<ffyfo[5^}mW^*гwjh1 a#Ik`!b#xa3:j%^ @b]x6x͛ NߵA)# q)r!&FQd;IȉB;rT;jDmvQkdw=?Lvϳ5Xj,V3 bCb َ1sȋQ#Xm8^kKI_7P[T'JE| }E2-Tbeh=߯kF KF<'ny'~?n^>j8~ _WO8=$Oِ4z_ϋwJ^yHޯ6p(06 M; ٢,ܗvsޔV2f~ίʅf'9}Ա *:ViltF#6-hĬ2qFlVf#G#6/aIJ8F#fш-ڴU]e:5c%۬/Z?T &٫QkX¸;HqX8Uc ֒UTb,Ra\Tc 6mLii"+g,RaE Fl-p?X9̠Cu$քlZ*5W-/>}blX8tƥw7k,ŭˍ[\.!&7,qdxZ~ظUPw*hgTYzVAU * * <Z2B* ZYxVAUPgHfTYxVA+<*г :_Bc{S[k.g5clZ\_jq>qd7,Y+gq-.,7nq|c|@6  ;z%Qja];}'<٨+-vqP3jnWutl{W{{έ:jjc Cn0" l{Su;꺢VC6u`G ci(n>؇GM/Է4v@k3`M``W-q<87(f5QQPf6?D*ZSU,WX67?R2[}ųQe77{+vnkޒFmq$^ԛ.]L7Jv[VIdz|^LYʐ [ʧ{V暇Ey )'U^N[*n6w[P[Q.$ݩz$Ծ>eY2nvF,Ǡzpl2PY5 *[u#J5Yj6Tr$^B%n ]=]v=P~0T\`eWNөX VZ` mH vr/d QɅ #c V(ށJT2jTFf=.JS`)iB!"EK@͔RyX$&JBr U#حr cĮ6wwL&3>&sg$/P+e Y !T"YoMP_?J#.XnK= ^:@%һZ+@Sp7Dݦ5n 6=j*T\==[X^NPJ ܏Jmz[p5 LL؝Z7s:;0#`W`Y:YM`fnkCG"Hv#ٍ`ۑY+u5jgɖ-E`ie5VY1NΕ̽]d]zVC;tH]Hl9j'B6l$!-{G֓'[Dl%Vne"8m*dBV̞Ta>* $,Y`;`"Ed-q)nI3&i0㎀]ܫ^ rI֓ Yg`9ar?y2ldp]en j~dvKgnz2gkDɵFub]}냨}ENjJnD[hs 6}z)QRj-@;9-lMih;~U~+K?t*^`+w\mY!;tWS3Utג}LRWK{ZΙ[UK]RI6jYdMɶS5Yy1UA(Eɸ.ۍAtncT![LzT&ܫ[Uk9`jz+=dSMPۘI0HmޏCw2XY [{U'{<%t,:N;ou?9@^:?9?"_U8z vF~5GLZ(gV`;Z<\%T&fe99љy<އn?snrV {"p׸5mƋfYb ā ju"cE)6(7.JUqQE)7.Jsq_n\"p7.JqsyȳĝQuѻp3|lf j[J-%7..ܸAڹAڍ;;ܸeJ2W t 7桰w>uW,r%s뼿_έnanuN-Vwrح[aN՝v;9Vw[anuGΐJmy7;\Yǭg疒@n UUn\ \r2sҍ+WLqswPxgs^G{@3bdZ:S f2-d JMjf@l;-WP Z }*LQU-sJn@Tg D ]0@<]w+)솁3U cLXBczD슡@c PU@L/1-` rnh#}f}+>c:l";8n8}[$5dpas\b7D@<+OK=ZR\bdW<ɮ<pdػJpU.@Uؽd luɠILd*4):xǘ^ƪ{^n.CxE'}^]S %إZ6cWFc*v]+Ⅿf11NԌ]{jԎ)wPvK \|J/@ٕ0'=Ȯ=T>~vm>{"PP`tePwaZdWnĴ)Y1v1dc^1dzpKbaW0a.f3%0UB )Lv:S g03P Lvq;B 3'+zϝ{;2EUB__#sOe> zȧ?mᴊBrM#NwxY|Tܦۤe457˲rNM,apJ2MeS)ŦTMmJT<-MN@gDm?^7^7;yy6 K k^#lh6nIw_c_mӧHgmچT%Sɯ#Hm:Tʦrl_Gk&^kLqNMKus:K6ӭJ$Nc?ESQNN?NݎwzZ;gtNTӜޥYj( 4>T4ͤEzqZHYj4SlZN餺6sO9;Fuw衔tVU^NO&YQ~NM]ڝ&:ΔTܩæ2vZM#tۮ%R_Z#hx(.]tY iMc޵{6[Yl2{ٛݷt62ZrN)[O9m3zeiw$B;qԝsz tRHwQDבO.ղ)S:5d*YjAR9N(Pur+~zr:Tj=AНNsq2f}Iнlѽa؊]v&ޣ4ܪ[F}5r=i䞘 -t:w&/v]8"L8,lrWʚ$[/L3U1{fjJDwJKm-2nfHOٔM#3U/OpgCqkiEC8֋Z=֫4ܤfrʖ;=N/S;S_qڴ*)bL+q:'vOTR%x?_8娊nyѴEӧ7ݾuON]Sj]C8M~Tsׯnm;Nm}Muɩ78˾{dߝ ~Yh_,_yh{/F֦rvhM;EixJN IBdH_%'FUiLQ J\UdOVYS>1e+ǫ5^ e^Lҟ^>(qL?g$*n2j[T]=U)T[5FPUWNfLTR{5AP=wiGuXuWWj_[ t]_OuM}nl~Lgv쳺~kM|ZWuڪ˪z=n$+h2B_FuzM^W]C?Pé}2Pm9TWfRRmLy@UشQyF0Z3^հުi2]u{~$~ ׃cRDsN0f V[Lc֩oM^P.J"^,yiFjKQ\{[=V6a֍j7H/ ^ۼzx)/~:U[:ɟtR뫎a ȁrQ-rرkQ|} :(\X:ҵ]S S ]<\AP^;f)9lg0CfldKaەY5[f<ڻCGl E~~oqi?YӻkD{oo.-T/53Ќl㙽EKg;ٻl'1Vv1inbvf?ҮESUS[f/m,֎mGfzMؚp<ȯgmOfhal_e֘[/f4F+#ϟ^`v^fh]ͬe;Y:-i1Bi!l[3|M3^An8lf6gS^HHc,6x]lm#-cvv-fjnVa֘Ͷvl;1MgH3ixoJvlO;hgqwi>dVCjzm]O `Ĭ+-m{,,Y:mǬ)̪<غ2W^m0+a{f&--f[l2m2iئ3Kų52 g̗r~{fhd;A>`!hcASwwr~luEb֗6v$|3-`Y m+۝̎N=.1VCSۺZٶfօ֕m=rO]rG%GMwօ)_| wpqqqq=ucà]===9(}03XVMf^[toqqq/|q8/\ .ŵŅppH\$. K%zqqCpCp)!q~=J ~ n n .W+>xꎂA-,ĭíǭ}ۂۂۂ[ۍۃۃ000n~_022{mmme#ϸqiiʩiڸ8wN|jp~8?\#\z{V+VxWpѸnnpppppo^ǥpi~,\. ō MMMčMMM 7777 !N.0p ҍXV+7/9Yo;;;wwww w wwwwwww䦜rNUUU9sZWWWW kkkkkkkkk uuuƵuwSoL<ҙxSiVg? rp98X88܈N Ҭ~?7 W+M---pE"-nn8W߅ۍۍۂ;;;ۍ;;;;;+Ǖqpqppqzu)=i5555pp`\0 DžqQh\4.E8UVg)Ϋ{q<77g?epiNsq,՜V:[[[[[[[ۈ+>mmmJqR6\((kYYYQU559===5N&48sUy|p>z8ujk$7Iz:68mK\.kuuu%p 8iq2.K2p8N9 t777{7777 W+-ŭŭ666vvvĝ]]]ĝ•qpqqq87wܕS3_뫯szW})GrZ gqp\0. Oc>>'Q>pI8\*.K e2qp#q#q#q \\>.---ũ9q)֙4X g?ۈۇ+ŕ:8+Õp3332UUY]]4* N硜S=ccթyUq8o7O1q!P\NNNP\ .g?qX:)|/^gjt\:.gƙqf\:n4n n .7 7 7 77777W+fVVV666vzSl)ͼٛ[k4w19}l=y KE^ԗJ%aHIIddd$O2ER Y(X^EGrXrJrYr[DsHmI#II7I/I?[̮i,(Dt<2gbvגcs'Tԓ4Ťt HIޗHH$$_Jvbv=$9%$)<%i(K%ђ8AX" i]JJVI%$k{'"Um"HH"$% dI$[2V2Y2|Iddd-&䢤\P^]HK$($IdJFJ&H%s$K$+%%[%2U]Σ"U$o$TI+$bvM%c$$3%5M,+"ų~&G0++:-u֯qAF䤙} hNLnIхXm``!o [k _ky_+?G/۞7^ZZl9>=rsZEee 擝242ؾU{\].l9qxU\q8J٧$7&~z$L$Gf:}\JJT.):Z2l)[LAuT"V,S<m4w([&qC|݊y;CKyͳss9k=_s9JlykqNXJXX!HXἵMX/Y)~Ig^:3ggO(閁o%)^V^i%)1^pzIJ|q_/I Nt.5;?Aÿffj2ƻ+*zhzh_onj|+,pu&:KFsW;s3XJc[/ g|zԨiQ?S~ƧGO3>5g|zԨiQ?S~ƧGO3>5g|z4[gV_?k0/Hsܻڼ.qf_롽}}ʻ}׫)22_יL.])O=';8x"n_Mpcxh,Tw+ \P$[e& >s d9 3(&+1 rZ,u4&mYdN}(xsnΥ&L96,:,)md1p%!TN燻Ecrc% J[?V:++ۏ J\GU$DPý#4di* 7Q}4KU ^]Su)J奨."@܍YS{H] *w*("K) R, n= YZ"^"KUu~P)jp} K9TUգ!MՂkYzFՐkT?DRipCM& KTc>Y[µ/,5-tP=spwgAw,U!3~YگmmA@V6puk<Vpw!t"K-Ʀ?Ⱥc_3"DWfy ze1CAA7CI!4|7L}4L[hƃYZc>+Ϭzf_f[,]`]f6 ,]e6VMڿ߅V)DJ0AE@p#!< j<7<"Kpi,&p)c1d)4]Bduׁ;ڃ,pC>,'pP;#N2@pYXqSEU,}k^f^m{i wʼYs +!TƼ wPLڦ=Quܻ?A-@#.@4 dݎǻ7!rXQ;J'L 4 di NwY!GRt[6 K'[pq_\1F wt/tO@䮑~"KWwd5A@;pOf KuQ@]A7T YT M K{~ P^'"tƀܓ= 6vp}@@i|v*Dnk}N .-X T#Ȅ˥Bd)6Y|g6`_:*@]ZzoY{U j\zdWKm=TUm6rkAmۢ=jh=^qj7h,hq/!nxTVYGPOpu;,uJGA/,=q1I8mr&Kp{uun, Q:|!YaʘܠҠ>"ppϚKAAndJ((!tҔ;hJ,m5Bv|#\?,}*YU;2<$D>i>"#B@>i>0@S@[a>aFrʌ3Arpzb, MYZíZrP S =CXbBA}()jF,Q JipyTY\ܵz :ݭ3@/9j% n{0d鰸lҜ TJK U"W ȭqMW K-Ž"IJ{Yp Ij&h2(\>- #kCKܳ[\Re rpͧ% XfZ r*tBJc"|BA+|*TY\UVP#tq w7@h`0#߁$mOuӿyD/iDϧ,Z&iKsv6ZΙ]$E^k7nHغ]II]2˕A_tK@{}cJݥk%Us]"KJjC]+K$uv.ߥ]#iK%Mwi\w~$e!#֍`9/BZ{ټ,J|2(;2 sȗTqsK]@}LEt1s!UתF*?R9u*  nQ[ςrHJPH?T ijvgJ(RyJ W;RԴDJ3}TU*H(F:a>S; ь@mff4RKX3Z 3jf"o~Pכ}Hr_)QޏT\sc.v)i.$2{u^uyIBTt Zn})}@77IYWvi~N4sRMoH-~[ Mn4iӹs6z.gLDyP/'VU4ǥHՂLʐo]WHcM<0j"ZTNd}ZD/w S djl09c>qmɏTM3#]UbUHi|o*|(֔4ƺHqk4zs혿:4~56_'6n1[Ž%s靘<\lF\$r˘KY,^ iK%ri.mw x%W|^gr$WNN5vu| [\.> "t+>K=Iң.ݎ4p59;_-㣹޵Dʺޮ B_~fM?`Cgƻ鏑֩Dygt!~'Eǯq=νG$~~op&diu< di%O/AF, s;{^Y*yJYj&'Cn晠ʠwEY K+P d)wxo|.3n*kiBSA&{f.+⚛yg@ij,UwЍRZ,\0Rq,)l h7vq"2EЋAAƋ"4XJ%p:,5Yj(=ȞAU^TZL] O굠үj\.tȒWRo]t6t;=@,5R;qoM Kf' K},-Qoe,mwTo;Pz< Kd. Kn4Td:f?Qu̻[aPu_\yOշqYBV(&~)2_ )2O i)c!*!MT*"hP%TtKe(T4}xG~g}wUAzKPFPVu"tuC:^)4GXds8T# ȾwmAiNl4ZVVKr(ŖURJeM4j=zòz$ҽDz)z4z e{ޱdZbγZW6FeBMjZdbt@iZ@c^{SݬoPטW|yG1_c$у( !K@w1-Q'z-TG(kQdgtӲ#t*bOL@1-$(kL`LGKeq ~#f:^bQ%Q EԲ2b8NU\Cu]BH+Ped}[>]Iu~#Kn:E7b>[G6˼_5e oZgjoL/U~GQT7 T*aV!M%/쫳= D P~Ux*Vzɷjw]P> xVC(A'z60 @|Bעho4LyQr]8(_od1]F_o(_odZ5݈UF6ѯs2|0==Lu6JP&QlW6{Ga(#<;UP gzVGC.LEW:{vLC_nhƠ_n32Bܲq! 2mD魐e{ JOҧPiCԧ*lt}>svEim1݉bW%A}z7"(_'J?etjO|UC7_CV^?Ctde: 'A>G[ ?[_/ gz˲͓M>J6M$Fd7?Js3YwuCid[v|tUXvlAUP~\ʏVYgنN]ݍL6@vQ xC~EסFQ :pNVV@^G4f4Ց?}ӏe/i4LKF~i893C-}9;|*%׶lv~ pg'jIt4.R6bZkipgtJO̖ #pfQ ,h J-[egZZ=~U]ը~~&TVduT7kOkhEQzE^@ptQnVXvF]t (l,jqdgxtJZ,;J'#QzOc^y;˾GW(]AdQ,J,/S8iYv'zVζhٍ/t}ղr.b~O>IBiov$h:J\D6F@cQ 1,if^dKZbX.6J ڒ&WQkYim@iL_Qz5Y}.Nv5o;tkJF)vKY|۹gJ}Ȟv|GDW>]pV7:wEm~j{ܠͭj; Sf8JUGf>@v]Y]TβQgS]ɋSoՕﮤ:S?Ft]5Tr~Ό=[m FmϓֺU+%}t+C꫶/H'=:Nm7SkxTFE۸}AJ RܳڎJϦƉz,:IR= (Ul UO#xSN@VlTDkQZX }RMr>C%թӚ֤ZBk]9N:jitG5b'k]Tp g嶛 'iǥbXrb@1LiHSRe9jReRzK;U@ݲb-ۖC[Q굷*>K-@߲YgXօ#(EQ+}Yw0ijuQt^zWP =[DgAeYo#ag>e/:W\OvCQ۬Wɭ9JFKAQ 7Ƚ>#̲V2G@aՒA>#l!>,+&C} fٶa#l>,{5#lCZ:dg|DLb6lJ6GT45Fun6C؏}=V7Ⱦf-(|6yt!++/r(%2UCi\YD桦( XC^F=Q5xl̷+>˦Qqlj VB;(VX,R_dEu5z:o8EMqzI&kK@eY}Ϯ-zX'(|H6Nע(櫥udztJ}A]( _KP zVI7QJ&t8Բe[dT`L'{^Fe7'σ{7zϒ=/PكG3 S;P$Y')6Qd%z(_EzvCQډ޲ҮR^-.2lc ( lL( l٬L3(_{6? P/w>J&FTCZ(`MH TmcRSƨ%P*1& I$VG{sjڦ\=߲p.3҇ZQP~oM6D(>7fz.(>3N9TG(5-l(WZǬV+ZA@GM\ mBَPKlԲD8T&Q' & r֥'j]E= A>O0(mt_0kZ/@G55UZ{wYZzA9se> kaV2ZZtYuB+&龷aMEk)o7kޖP~~Vc=zXO1{8+U5{i=NEP7| (gV]:oPLd鞄r`յb P ߻Nl:S#F]3-\=O*Zg.Ie],^Ck"I硦A9TڳgPyPԊBC9g"Q6skUr(TNPgc[]"_ Zkz ~(Z׺S>T(x\eaPα@@'XjW:zrij HZN+iZPMƑqs,y'A93Z2LrYhf\ajk ̤Ynf׬43 g--L킙yi+)=#}JQm{ ([Z2XB&*=C$gsjf+=f3s>lv{rҳSzVR*ܥ ~+U u_ޯYwqYK>l- ?+p| e YAZp p0L`6^J&( .@ A_ (0 ,`+( \ P &0 䂅7:v8 >_+CAl#  AA>X^kF.({p xā` RA}z V`v*!u<  ڂν ĀX0  /B(o- T v tAo0 #AX" vGIp9vh>g\"٫=Ͼu)5..l3.\ti\vRe\\t9l\Rk\j]t3.u.4]..0.7\tBHKq uѥqiKqrѥqK_EXKqIteqd2Ee.%E<"EBRKq)vѥĸ޸weqKq)sѥҸTrȸrѥڸTrڸvѥ޸Իd\\tf\Y3h_]\ ^B6# oid.oj̈́3 'ӟWcUX}U_u]f^0WXwb3VĪ|v09v# [d;q@DbW+&{G4)y3Eof( D8+JD\/V1WRDKXDi&D^%e K"Bn]d-׈A*mm2E&,reZ(3Uܮ~U yO֩yJcNۿG~*M{iO#tTES@*T3Τ1|n˧sjP׬j#VKVJ"uqU#UzU+ی`eAQTURU<^TUU(W3b:&6bzFPUPry>pʹ]WoP[_Eϯb|OX_ۮFɾjVeԳ sW^}J-LSdSL=skP^j΄u}BukUohW atn,`kE.Rk$ΣAQ;:iE=?g/8g1^< `5&=599禦g1;/=+5p&6b<=bV{zrgL5;ӕ q!8ddcF 7|dEFO03x0γo9M#}G|؄$DF&0 ^~=苞oM/bxRQQ8Upszg͚84~q Otz=/B4y#}d(E+Dd"0  # A2*.hCwm* Dn`!*.hCwmފA~ U8c*xԚ NUǟ1cfq*LT$F2!9E%" BRT$)!a0 woϽnz}{꺭{j-'BGPB'e1EQPP(j+7- %^: :L⟹9 IlB#= ʋ:PhY0iGĖzLt$O^,qz>|Y,ku+r_UN=`_pD^^#]Ucb?s fnO$W %Ӭն_E#nAժc&mtC|7j]ܠ>)/?4={Wus͇nMɯڍ ۈȈmE*2b|qX3Fo˷kۈO8k);}74//x]3^3_9%_N{IDDvy y gum"hE(Њ@K76/͋Pul^-)l"h6xk)Ranj(j\']sfi#Xa6Z--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻ*ڼkkjjڸzfc/ű՗Kqltl8RKql:R[}=[})T'5[}=[})TV_cUe9JΙöެ6 zZ--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻv}SO7o.cr9yFa`EdMO`Kpg",X"|(jc(lc '{0'ۃE>qVę 1.cdQ 1r 2CwB9N"-/;3POp\˵"wA m&h/@G9 :4|C|+O20Cd )/Ack9%cTpns0>BSQ[,} +od۵n؂}l얗!Cfyp\2~"+BeVW60 )rʆ+-**a[ C)h6j;4Ƽ m}T]yxBe%q+83FŘNv24}0f)1V_\|f: ?wb+ .Bz?(N(}HA:^]B֥t](By ns^5*B}FlJ3 zjWҫ;aOG1f0gFjߤa<I5olx9z |ç8z,XW詰JPXgFLخ?ݺ+dZp@8K CyR-*nj'u8BDxZ%@J IoV Zp+p!%xV ,Ga<>uO\>x&~Wr0MOW ^3xDWO!z:☳<|CcXaR6!lVbm8!AS} BD44į0_8f:V~eXPc3T K٬o6-If*0kY ulgҌM#hg*A{:q]LMxʔO/K3/IWCi=|G6fZx &~60הy97Bj٠V]ʌߛz)MjsMd8`.M6gtq@.ĸeHqo7tY'u;GWp{A-̻w㡁; +!̈́f xНܙsӠ[ :n}C> ]z0~ݭG`Ǻq)8t7Jާgn1}[/pG/`_atj=7a`{xs؍3]ߜr& #K._ݐqe8oAqo0:Ai=f.)S=0uq/F#짉 ͽ,h靁v H6A'o tVo=Bw þ^p/dFyW`wa?oz{a23 }a?s0[ հ[K{ fxX㍁uL؈v1O8Qw b\y`yA^ OCL8s$9\ADZ93/aIԄwV(ҒkLJZ[vDZam|h /6i. Y[ diL{|qrؕjLqʺ%h*0JkT{CZ{T"_nTIj+S(Q*+!m ktIi$;X[r㛲,}K;K$(NH(]FTYr{rfIpI7Av׷=W |x1AWU$w&kJ|n]+FWuBzmUyu{VW#W]LurPPjMrB-ҪAm#j[n' SS"_;HԅNAE$ǵPn@}䮀nL^mД}Мr3AVDa[m h{3"_|<'w.h\{vB#tH#2dKrC0~x@;>v䞃GC*S'μyMZEM?"0y(le4F3#bLȍ604> /W![R.Q=﯎M<_zא9D fLg0iHԙ(x")S  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$&'()*+,1a56789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`defghijklmnopqrstuvwxyz{|}~Root Entry F@.a@+a3Data %WordDocument*HObjectPool]a@+a_1041415382ac(@=]a]aOle ObjInfoContents4X CPYA 4,210 #  $@X r ??0CIK1H.HT_AA. x ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@h@h@h@i@ i@@i@`i@i@i@i@i@j@ j@@j@`j@j@j@j@j@k@ k@@k@`k@k@k@k@k@l@ l@@l@`l@l@l@l@l@m@ m@@m@`m@m@m@m@m@n@ n@@n@`n@n@n@n@n@o@ o@@o@`o@o@o@o@o@p@p@ p@0p@@p@Pp@`p@pp@p@p@p@p@p@p@p@p@q@q@ q@0q@@q@Pq@`q@pq@q@q@q@q@q@q@q@q@r@r@ r@0r@@r@Pr@`r@pr@r@r@r@r@r@r@r@r@s@s@ s@0s@@s@Ps@`s@ps@s@s@s@s@s@s@s@s@t@t@ t@0t@@t@Pt@`t@pt@t@t@t@t@t@t@t@t@u@u@ u@0u@@u@Pu@`u@pu@u@u@u@u@u@u@u@u@v@v@ v@0v@@v@Pv@`v@pv@v@v@v@v@v@v@v@v@w@w@ w@0w@@w@Pw@`w@pw@w@w@w@w@w@w@w@w@x@x@ x@0x@@x@Px@`x@px@x@x@x@x@x@x@x@x@y@y@ y@0y@@y@Py@`y@py@y@y@y@y@y@y@y@y@z@z@ z@0z@@z@Pz@`z@pz@z@z@z@z@z@z@z@z@{@{@ {@0{@@{@P{@`{@p{@{@{@{@{@{@{@{@{@|@|@ |@0|@@|@P|@`|@p|@|@|@|@|@|@|@|@|@}@}@ }@0}@@}@P}@`}@p}@}@}@}@}@}@}@}@}@~@~@ ~@0~@@~@P~@`~@p~@~@~@~@~@~@~@~@~@ r !`??CIK1H.HT_S r !`??CIK1H.HT_C r !`??CIK1H.HT_D r `??CIK1H.HT_TMH x (\@= ףp=@Gz @(\@ףp= ?RQ?= ףp=?ffffff?333333?Q?)\(?{Gz?Q??{Gz?Q?Q?Q?Q?Q?Q?Q???{Gz???Q?Q?Q?Q?Q? ףp= ?Q?p= ף?= ףp=?RQ?Q?p= ף? ףp= ?(\?333333@(\?HzG?RQ?(\??{Gz?= ףp=?(\?(\?Q?(\?(\?(\?HzG?(\?= ףp=?Q?(\?q= ףp?ףp= ?{Gz?)\(?Q?p= ף?p= ף?Q?Q?? ףp= ?{Gz?Q? ףp= ? ףp= ? ףp= ? ףp= ?Q?Q?Q?Q?Q?Q??Q? ףp= ?)\(?333333?{Gz? ףp= ??Q?(\?ffffff?(\?{Gz?333333?Q??Q?{Gz? ףp= ??333333?(\?zG?zG?Q?)\(?p= ף???q= ףp?(\?Q?{Gz?(\?HzG?ףp= ?ףp= ????RQ?RQ?Q?Q?)\(?? ףp= ??{Gz?Q?Q?Q?Q?Q?Q?{Gz?{Gz?{Gz?Q?Q?Q?Q?Q?{Gz??p= ף?Q?p= ף?p= ף?Q?Q?ffffff?(\?Gz?p= ף??q= ףp?(\?(\?)\(?)\(?\(\?ffffff?RQ?ףp= @q= ףp@= ףp= @@Gz@@q= ףp@{Gz@Q@(\@(\@Gz@p= ף@Q@p= ף@Q@\(\@p= ף @ ףp= @\(\@Gz?ffffff??Q?)\(?{Gz? ףp= ?Q?Q?Q??????RQ?HzG?(\?333333?ףp= ?{Gz?q= ףp??Q?\(\??\(\?Q?Gz?{Gz??Q?HzG?q= ףp?p= ף?Gz?ףp= @HzG@zG @\(\ @ףp= @@Q@333333@RQ@(\ @\(\ @{Gz @Q@Q@q= ףp@(\@(\?Gz?)\(??)\(?333333?(\?{Gz?{Gz??zG?Gz??Q?(\?HzG?RQ@{Gz@Q@ffffff @Q @ffffff @Q @\(\ @)\(@p= ף @ @)\(@(\@(\?(\?\(\?Gz?HzG?p= ף?p= ף?? ףp= ? ףp= ?Q?Q?Q?)\(??ffffff?Q?ףp= ?ffffff?{Gz@(\@Q @ףp= @ @q= ףp @Q @@333333 @ףp= @{Gz@p= ף@ffffff@{Gz???= ףp=?HzG?(\?ףp= ?ףp= ?HzG?p= ף?Gz?= ףp=?HzG?Q?{Gz?ףp= ?ףp= ?333333?{Gz?Gz?q= ףp?{Gz??p= ף? ףp= @Q@Q @RQ@Q@= ףp=@@@ ףp= @zG@@{Gz@Gz@(\@ףp= @(\@Q @(\@{Gz@)\(@ffffff?zG?(\??(\?Q?zG? ףp= ?{Gz?(\?(\?RQ?)\(?)\(?333333?Q?(\?{Gz?Q?Gz?\(\@q= ףp@@(\@Q@{Gz@Q?(\??q= ףp?q= ףp??(\?HzG?)\(?q= ףp?RQ??zG?q= ףp?{Gz?Q?ףp= ? ףp= @Q@q= ףp @(\ @= ףp=@ffffff@(\@q= ףp@{Gz@Q@Q@zG@@Gz@Q @(\ @= ףp=@ ףp= @zG@(\??Gz?ffffff?= ףp=?HzG?Q?Gz?(\?)\(? ףp= ?Q?Q? ףp= ??)\(?333333?{Gz?RQ? ףp= ?ffffff?Gz?Q?q= ףp?q= ףp?{Gz?{Gz?Gz?(\?Q?)\(? ףp= ? ףp= ? ףp= ? ףp= ?Q?{Gz?(\?(\?(\?)\(?Q?ffffff?{Gz?ffffff?ffffff? ףp= ?ףp= ?333333?{Gz?(\?)\(?333333?{Gz?(\?{Gz?q= ףp?RQ?ףp= ?Q?{Gz?Gz?(\?Gz?RQ?ףp= ?(\???p= ף?\(\??(\?Q?HzG?zG?zG?)\(?(\?(\? ףp= ?{Gz???q= ףp?)\(?(\? ףp= ? r `??CIK1H.HT_BET r `??CIK1H.HT_TUR r `??CIK1H.HT_UND r `??CIK1H.HT_H.T r `??CIK1H.HT_MOMA r `??CIK1H.HT_MOMB r `??CIK1H.HT_INDA r `??CIK1H.HT_INDB r `??CIK1H.HT_N x 333333?Q?Q@p= ף? ףp= ? ףp= ?(\?)\(??Q?Q??Q?Q?Q?{Gz?Q?Q?{Gz?{Gz??{Gz?Q???Q?Q?Q?Q?{Gz?{Gz? ףp= ? ףp= ?ffffff?Gz?Gz??Q?(\?= ףp=@Gz@ ףp= ?zG?Gz?(\?ffffff?= ףp=?zG?(\?{Gz?{Gz?{Gz? ףp= ??333333?(\??\(\?RQ?Q?Q?p= ף? ףp= ? ףp= ?(\?333333??{Gz?Q?Q?Q? ףp= ? ףp= ?{Gz?{Gz?Q????Q??Q?Q??Q?{Gz?RQ??p= ף?q= ףp?(\?{Gz? ףp= ?(\?(\?(\?HzG?333333?{Gz?{Gz? ףp= ? ףp= ?RQ?HzG?)\(?ףp= ?)\(?ףp= ?Q?p= ף?q= ףp? ףp= ?Q?HzG?HzG?p= ף?333333?p= ף?{Gz??zG?zG?(\?)\(? ףp= ?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q?Q?Q?Q?Q??Q???{Gz???Q?{Gz??p= ף??Q??HzG?HzG?333333?Q?p= ף?(\?Q?RQ?(\?Q?ףp= ?(\?Q?333333?HzG@)\(?zG?(\?Gz? ףp= ??RQ?zG?HzG?p= ף? ףp= ?p= ף?333333?Q?zG?Q?Q?Gz@Q@)\(?Gz?= ףp=?333333? ףp= ?{Gz? ףp= ?Q?Q?Q???Q???RQ?Q?(\???zG?q= ףp?q= ףp??Q?ffffff?\(\?= ףp=?Gz?(\?p= ף?Q?q= ףp?(\?333333?{Gz?RQ@Q@Gz@(\?p= ף??{Gz@(\@= ףp=@zG?= ףp= @ @(\@Q?Q@Q@\(\@Q?Q?= ףp=?Gz?(\??RQ?(\?RQ??q= ףp?333333?{Gz?p= ף?\(\@Q@Gz@Q?p= ף@)\(@Q@p= ף@RQ?p= ף?HzG?{Gz@ףp= @ ףp= ?@Q?(\?\(\?\(\??)\(?{Gz? ףp= ? ףp= ? ףp= ?{Gz?{Gz?)\(?RQ?333333?q= ףp?(\?\(\?Q@{Gz?? ףp= @ףp= @RQ@HzG@ףp= @ffffff@p= ף@q= ףp @Q@ffffff@ףp= @Q@(\?Q??Q??(\?Gz??\(\??)\(?Gz??)\(?Gz?ףp= ???\(\?Q?Gz@ ףp= @{Gz@(\@zG?Q?(\?Gz?ףp= ?)\(?HzG?\(\??(\?333333? ףp= ?Gz?Q@ףp= @= ףp=@Gz?Gz??p= ף?(\?q= ףp?HzG?zG? ףp= ?{Gz?{Gz?(\? ףp= ?RQ?Q?Q?ffffff?Q?(\?(\?zG? ףp= ?ffffff@RQ@(\?Q?)\(?Q@RQ??zG?(\??333333?Q?(\?Q?RQ?(\?\(\?(\?333333?Gz@)\(@?RQ?)\(@ףp= @Gz@RQ?RQ?RQ?(\?HzG?HzG?zG?)\(?Q@(\@ffffff?Gz?(\?Gz?RQ?333333?333333?(\??HzG?{Gz?Gz?{Gz?333333??Q?Q?? ףp= ? ףp= ??)\(?Q? ףp= ?{Gz?HzG??= ףp=? ףp= ?Gz?)\(??Q?{Gz?Q?Q??)\(???? ףp= ?RQ?zG?)\(?HzG?Q? ףp= ?ffffff?)\(??RQ?HzG?q= ףp?Q?p= ף? ףp= ?Q?333333??RQ?333333?)\(?{Gz?Q? ףp= ??Q?= ףp=?zG?{Gz?)\(?zG??q= ףp?(\??HzG? ףp= ?(\??HzG?q= ףp?(\?(\?zG?)\(?HzG?ףp= ?)\(?Gz?zG? r `??CIK1H.HT_MBET r `??CIK1H.HT_DIG x ?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? r `??CIK1H.HT_SC.1 s Plot1$ `  ` C:\ORIGIN Fr,,s I0@Y@@K~K@@? @jl "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c MȈN ?ő^+ġ? >>  l "M P c & (u~[?/b?,>>  A c ^Bu"@?1c0? >>  l "^ S6 c n/|'$?? >>  l "n/ S5 c .%s?,_? >>  l ". S4 c Y(~B?q >? >>  l "Y(~ S3 c 'Ww? At? >>  l "' S2 c +e6<ݳ-?p= ף? >>  l "+e S1 c B]{?.?]]]]]] $w  l " $ Human cik1 K\+(+)-channel c P  8p?˗d1? , >>Legend  l "@P   , \L(1) %(1) \L(2) %(2) \L(3) %(3) c uL9+66Z@ 8>>D@YL  l "& 8 CONFORMATIONAL INDEX Input: Edelman's scale c `QB;o@ >q >>BXB  l "&  SEQUENCE NUMBER R `# R `# R  `# R   R   R l "@Ed q? R P@  R  l "? R P@2 p@ R   R   R l "@T!? R P@NI R  l "c'? R P@ N 0@ R  R  R  R  R  R  _1041415613 ac(@=`fa`faOle ObjInfo ContentscZG?">CPYA 4,210 #  $@X r zz??0GMCR_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@h@h@h@i@ i@@i@`i@i@i@i@i@j@ j@@j@`j@j@j@j@j@k@ k@@k@`k@k@k@k@k@l@ l@@l@`l@l@l@l@l@m@ m@@m@`m@m@m@m@m@n@ n@@n@`n@n@n@n@n@o@ o@@o@`o@o@o@o@o@p@p@ p@0p@@p@Pp@`p@pp@p@p@p@p@p@p@p@p@q@q@ q@0q@@q@Pq@`q@pq@q@q@q@q@q@q@q@q@r@r@ r@0r@@r@Pr@`r@pr@r@r@r@r@r@r@r@r@s@s@ s@0s@@s@Ps@`s@ps@s@s@s@s@s@s@s@s@t@t@ t@0t@@t@Pt@`t@pt@t@t@t@t@t@t@t@t@u@u@ u@0u@@u@Pu@`u@pu@u@u@u@u@u@u@u@u@v@v@ v@0v@@v@Pv@`v@pv@v@v@v@v@v@v@v@v@w@w@ w@0w@@w@Pw@`w@pw@w@w@w@ r !`zz??GMCR_S r !`zz??GMCR_C r !`zz??GMCR_D r  `zz??GMCR_TMH Q?{Gz?Q?{Gz?Q?(\?p= ף?Gz?Gz?{Gz?(\?(\?(\??= ףp=?{Gz?333333?Q?{Gz?{Gz? ףp= ?Q??Q???Q?Q?Q???Q?)\(?Q?p= ף?{Gz?(\?{Gz?p= ף?Q?)\(? ףp= ?Q????Q?Q?Q?Q?{Gz??Q?Q?Q?Q?{Gz?(\?Q?(\?RQ?)\(?RQ?333333?zG?ffffff?Gz?HzG?(\?\(\?(\? ףp= ??(\?Q?RQ?(\?)\(?{Gz??{Gz?????Q????{Gz?{Gz?{Gz?Q?Q?Q?Q?Q??)\(?HzG?)\(?Gz?(\?Q?zG?Q?Q?q= ףp?HzG?ffffff?Q?Gz?{Gz?(\?Q?RQ?{Gz?p= ף?p= ף??Q?{Gz???333333?(\?RQ?Q?q= ףp?)\(?(\?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz? ףp= ? ףp= ??)\(?Q?Q?Q?)\(?)\(?)\(?Q?RQ?zG?p= ף?333333?(\?ffffff?{Gz?p= ף?q= ףp?Q?zG??(\?{Gz?Q?Q?HzG?(\?(\?HzG???333333?ףp= ?(\?333333?zG?Q?)\(?RQ??p= ף?Gz?Q?Q?RQ?Q?Q?Q?{Gz??{Gz?{Gz??{Gz?{Gz? ףp= ? ףp= ? ףp= ?? ףp= ?q= ףp?p= ף?(\?(\?(\?HzG? ףp= ?)\(?{Gz?Q?{Gz?{Gz?Q?Q?Q?{Gz?{Gz?Q?Q?Q?{Gz?Q?Q? ףp= ? ףp= ?{Gz?{Gz?Q??Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz?{Gz?p= ף?ףp= ?zG?RQ?ףp= ?zG?p= ף?zG?RQ?Q?(\?Q?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q??Q?{Gz?RQ?Q?q= ףp?(\?HzG?zG?ףp= ?(\? ףp= ?(\? ףp= ?(\?Q?ףp= ?ףp= ?p= ף?? ףp= ?p= ף?Q?Q?)\(?Q?p= ף?Q?{Gz?HzG?)\(? ףp= ?Q?Gz@p= ף@Gz @Q@Q@Q@Q@Q@@p= ף@p= ף@q= ףp@q= ףp@Q@{Gz@Gz@)\(@(\@ ףp= @Q @ffffff@ףp= @(\?p= ף?Q?(\?(\?Q?Q?333333?333333?(\?Q?p= ף?RQ?(\? ףp= ?{Gz?Q??Q?Q?{Gz?{Gz?{Gz?Q?Q?{Gz??Q? ףp= ???Q?)\(??{Gz?Q??{Gz?{Gz?{Gz?{Gz?Q?{Gz?{Gz?Q?Q?{Gz?Q?Q?HzG? ףp= ?Gz?Gz?Q? r `zz??GMCR_BET r `zz??GMCR_TUR r `zz??GMCR_UND r `zz??GMCR_H.T r `zz??GMCR_MOMA r `zz??GMCR_MOMB r `zz??GMCR_INDA r `zz??GMCR_INDB r `zz??GMCR_N {Gz?Q?Q? ףp= ?(\??(\?ףp= ? ףp= ? ףp= ??{Gz?Q?RQ?333333?p= ף? ףp= ???Q????{Gz?Q???{Gz?{Gz?Q?)\(?)\(?333333??zG? ףp= ?)\(? ףp= ? ףp= ??Q?Q?Q??Q?{Gz?{Gz?Q?{Gz??Q?{Gz?Q?Q?Q??{Gz?(\?333333?Gz??(\?RQ?p= ף?{Gz?p= ף?Q?333333?\(\?= ףp=??RQ?Q?zG?(\?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz???{Gz?Q?Q?{Gz?{Gz??{Gz?Q?{Gz?{Gz?Q?(\?Q?ffffff?zG? ףp= ?Gz? ףp= ?Q?HzG?p= ף?Gz?Q?Gz?(\??(\?{Gz???RQ?{Gz?333333??Q?Q??Q?(\??)\(?Q?)\(?zG?333333?Q? ףp= ?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q???)\(?p= ף?p= ף?Q?333333?333333?Q?)\(?)\(?{Gz?333333?q= ףp??q= ףp?ףp= ?p= ף??zG?zG?q= ףp??Q?zG?HzG?Q?HzG?(\?ffffff?Gz?)\(?= ףp=?ףp= ?{Gz?ףp= ?Q?RQ?(\?Q?zG?Q?ףp= ?q= ףp??Q?p= ף?Q?Q?Q?Q?{Gz?? ףp= ? ףp= ?? ףp= ? ףp= ? ףp= ??Q?(\? ףp= ?= ףp=?ffffff?(\?{Gz?{Gz?Q??{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?Q?{Gz??Q?)\(?Q? ףp= ?)\(? ףp= ? ףp= ?p= ף?{Gz??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz?333333?(\?Gz?q= ףp?Q?Q?Q?Q?(\?(\?p= ף?{Gz?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?{Gz?Q?{Gz? ףp= ?(\??Q?Q? ףp= ?)\(?ףp= ?= ףp=?ffffff??\(\?zG?(\?(\?Q?Q?(\?)\(?)\(?p= ף?p= ף?333333?{Gz? ףp= ?zG?Q?(\?(\?= ףp=@Gz@?Gz?p= ף?ףp= ?zG?\(\?Gz?{Gz?RQ?(\?= ףp=?(\?q= ףp?Gz??Gz?Q?= ףp=@ffffff?HzG?(\@333333 @Gz@Gz?)\(?(\?zG?= ףp=?Q?)\(?(\? ףp= ?{Gz?)\(? ףp= ??Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q?{Gz?? ףp= ?{Gz?Q??Q?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz???Q?zG?p= ף??zG?Q? r `zz??GMCR_MBET r `zz??GMCR_DIG ???????????????????????? r `zz??GMCR_SC.1 s Plot1$ `  ` C:\ORIGIN Fr,,s 4y@I@ @5Z5Z@@?@UUUUUql "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c l-x ? w  l "l  GMCR, human c P  8p?˗d1? , >>Legend  l "@P   , \L(1) %(1) \L(2) %(2) \L(3) %(3) c LP+/BK@ <>>D@YL  l "& < CONFORMATIONAL INDEX Input: Kyte-Doolittle scale c \a#g@"T! >>BXB  l "&  SEQUENCE NUMBER c ́?5h?<>>_202 &  c ́?5h?<>>_202 &  c ́?5h?<>>_202 &  R z`# R z `# R z `# R   R   R l "@( q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N4 R  l "c'? R P@ N y@ R  R  R  R  R  R  _1041416465ac(@=`fa`faOle ObjInfo ContentsCPYA 4,210 #  $@X r ??0PGY60261_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@ r !`??PGY60261_B r !`??PGY60261_C r !`??PGY60261_D r `??PGY60261_TMH zG@= ףp=@Q?(\?ffffff??? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?Q?Q?HzG?Gz?(\?ffffff@zG@ r `??PGY60261_BET r `??PGY60261_TUR r `??PGY60261_UND r `??PGY60261_H.T r `??PGY60261_J r `??PGY60261_MOMA ףp= @Q@@@RQ@333333@ffffff@p= ף@)\( @= ףp= @ @ ףp= @q= ףp@(\@(\ @ffffff@\(\@(\@ r `??PGY60261_MOMB r `??PGY60261_INDA = ףp=?(\@ffffff@q= ףp@Gz@@\(\@)\(@(\@= ףp=@ ףp= @Q@p= ף@ףp= @(\@Q@(\ @Q@ffffff@q= ףp? r `??PGY60261_INDB r `??PGY60261_MBET r `??PGY60261_DIG r `??PGY60261_OBS r  `??PGY60261_SC1 q= ףp?\(\?333333?ffffff?ףp= ?Q?Q?HzG?p= ף?Q?ףp= ??Q?? ףp= ?(\?333333??{Gz?zG?)\(?\(\? r `??PGY60261_T.60 s Plot1$ `  ` C:\ORIGIN Fr,,s 9@@@־aVU@@?@m۶m[nl "N 9 S2? ף= ף=Pd1 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c g~X[?]]]]]] (w  l "g ( PGYA antibacterial peptide c P  38p?˗d1? 8 >>Legend  l "@P  3 8 \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) c J0)gm@ >>D@YL  l "& i CONFORMATIONAL INDEX c ]}&@}I| >>BXB  l "&  SEQUENCE NUMBER R  `# R  `# R `# R  `# R   R   R l "@i q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N R  l "c'? R P@ N 9@ R  R  R  R  R  R  _1041416928 ac(@=`fa`faOle ObjInfoContentsCPYA 4,210 #  $@X r ??0A2MLT_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@ r !`??A2MLT_B r !`??A2MLT_C r !`??A2MLT_D r  `??A2MLT_TMH \(\@ףp= @ffffff @(\@Gz@ ףp= @HzG @@@ףp= @@RQ@Q@333333@p= ף@Q?(\?(\??Q?333333?Q?{Gz?{Gz?{Gz? r `??A2MLT_BET r `??A2MLT_TUR r `??A2MLT_UND r `??A2MLT_H.T r `??A2MLT_J r `??A2MLT_MOMA r `??A2MLT_MOMB r `??A2MLT_INDA {Gz?ffffff?\(\@ ףp= @ףp= @(\@\(\@\(\@= ףp=@Gz@q= ףp@ffffff?p= ף?Q?Q@@p= ף@p= ף@?(\@HzG?Gz?Q?? r `??A2MLT_INDB r `??A2MLT_MBET r `??A2MLT_DIG ??????????????????????? r `??A2MLT_OBS ??????????????????????? r  `??A2MLT_SC1 RQ?(\?)\(?zG?ffffff?Q?(\?HzG?{Gz?\(\?{Gz?Q??ffffff?RQ?= ףp=?p= ף?333333?(\?(\?Q?@333333@(\@HzG@@ r `??A2MLT_T.60 s Plot1$<  <  D:\ORIGINFr,,s >@@#7r#7rS@@?۶m۶ kl ": S S2? ף= ף=Pd1 c Fx J Z̿r?ҿ>> L5  5 c Fx BJ Z̿r?ҿ>> L4  4 c Fx J" Z̿r?ҿ>> L3  3 c Fx HJ Z̿r?ҿ>> L2  2 c Fx J( Z̿r?ҿ>> L1  1 c KUM-+?7i6?,>>  A c AD#1?diCNÿ (w  l "A ( melittin hemolytic peptide c l K2`,($?3_ kQ? P + Legend  l "@@l K P \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) \L(5) %(5) \L(6) %(6) c qH D9@ >>D@YL  l "&Ss2 CONFORMATIONAL INDEX c W+@"_' >>BXB  l "&W  SEQUENCE NUMBER R  `# R  `# R  `# R  `# R  `# R   R   R l "@E .? R @:  R  l "+?' ? R P@: @ R   R   R l "@\? R @: R  l "0,! ,Q a? R P@ 4 >@ R  R  R  R  R  R  _1041417070ac(@=na@waOle ObjInfo Contents$3 Oh+'0 (4 P \ ht|5Sequence Analysis of Membrane Proteins with the Web rCPYA 4,210 #  $@X r ??0OMPAX_AA. ` ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@ r !`??OMPAX_B r !`??OMPAX_C r !`??OMPAX_D r `??OMPAX_TMH ` q= ףp?= ףp=? ףp= ?HzG?Q?{Gz?{Gz?{Gz??Q?Q?Q?Q?Q?Q?{Gz? ףp= ? ףp= ? ףp= ?{Gz?{Gz?Q?Q???{Gz?{Gz?{Gz?{Gz?Q?Q?Q?{Gz?? ףp= ?p= ף? ףp= ?Gz?RQ?HzG?zG?Q?zG?(\?333333?Q?ףp= ?ףp= ?(\?Q?Q?(\?(\?(\?333333?(\?HzG? ףp= ?? ףp= ?)\(? ףp= ?{Gz? ףp= ? ףp= ? ףp= ?{Gz???? ףp= ?)\(?Q?(\? ףp= ?zG??Q?(\?Gz?(\????RQ?ffffff?ףp= ?p= ף??RQ?{Gz?RQ?{Gz??HzG?Q?(\? ףp= ?(\?Q?RQ?ףp= ?p= ף?q= ףp?zG?RQ?{Gz?Q?Q?{Gz?{Gz?Q?{Gz?{Gz?{Gz?{Gz?{Gz?333333??ףp= ?Gz?)\(? ףp= ?{Gz?Q@RQ@p= ף?{Gz?Q?(\??Q?q= ףp?zG?Q?{Gz?zG?RQ?333333? ףp= ?????{Gz?{Gz??Q? ףp= ? ףp= ? ףp= ? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?)\(?ףp= ? ףp= ?(\?RQ?333333??(\?Gz?q= ףp?Q??Q? r `??OMPAX_BET ` (\?Q?p= ף?333333??(\? ףp= ?Gz?ףp= ?Gz??Q??p= ף?{Gz?\(\?zG?ףp= ?(\?= ףp=?Gz?{Gz?(\?ffffff?ףp= ?zG?p= ף?\(\?Q?ffffff?{Gz?333333?q= ףp?Q?= ףp=?Q?(\?zG?Q??{Gz?\(\?(\?ףp= ?333333?p= ף?RQ?zG? ףp= ??(\?Gz?Gz?Q?ףp= ?= ףp=?Q?RQ?(\??ffffff?)\(?333333??p= ף?ףp= ?{Gz?{Gz?(\?Q?Q?)\(?Q?\(\?Q??ףp= ?? ףp= ? ףp= ?Gz?333333?ffffff?zG?p= ף?zG?? ףp= ?= ףp=?p= ף?(\?RQ?Q?HzG??333333?(\?Q?)\(??? ףp= ??ףp= ??zG?333333?= ףp=?= ףp=? ףp= ?Q?HzG??ףp= ?zG?Gz?Q??= ףp=?(\?ffffff?333333?(\?p= ף?(\?(\?ffffff?(\?= ףp=?HzG?? ףp= ?Gz?q= ףp???Q? ףp= ?ffffff???Q?q= ףp???ףp= ?333333?(\?)\(?p= ף?Gz?333333? ףp= ?Q?(\?HzG?)\(?q= ףp?(\?333333?Q?{Gz?Q?ffffff?(\??Gz?Gz?\(\?Gz?333333?(\? r `??OMPAX_TUR r `??OMPAX_UND r `??OMPAX_H.T r `??OMPAX_J r `??OMPAX_MOMA r `??OMPAX_MOMB r `??OMPAX_INDA r `??OMPAX_INDB r `??OMPAX_MBET r  `??OMPAX_DIG ` 333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333? r  `??OMPAX_OBS ` ?????????????????????????????????????????????????????????????????????????????????????????????????????? r `??OMPAX_SC1 r `??OMPAX_T.60 s Plot1$ `  ` C:\ORIGIN Fr,,s 9i@I@@2Tv$@п@?@E]tQl "N 9 S2? ף= ף=Pd1 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c ;B]{?.?]]]]]] $w  l "; $ Outer membrane protein A c P  38p?˗d1? 8 >>Legend  l "@P  3 8 \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) c SL+ 9_H? <>>D@YL  l "& < CONFORMATIONAL INDEX Input: Kyte-Doolittle scale c 1U@N޿ >>BXB  l "&  SEQUENCE NUMBER R `# R `# R   `# R   `# R   R   R l "@( q? R P@ п R  l "? R P@2 p@ R   R   R l "@2!? R P@N9 R  l "c'? R P@ N i@ R  R  R  R  R  R  }!LՈwc*JX튎!(xDZAKtki;?0aKGڧLohV{S"@Y=OZ#Sv[x35"EC:Vօ*Vg5i(KieDDV3}U>$ 'mDW7=K|{Z{u#cDw tU *0B|9Z*IC|uR1enkV2}BRDLV͔Y>&D-D_ƬV_!^jȲ&rD|Q(DTWM'"n!"=QT&j5)j1IUԣ=XKOX5-G$]$§9y?iq Q!"_$Ȧ*U$2LlNZ*D& msDx D<قc"_|dKpX'"OOA2]fUH+T5iUzd]N D@!m"[D|Ֆ3`ݵLݡڑv0>}% GɍV+#I`n}ݞfL)DhԖݮ:I"_amPvGI4sX[;-"J60md7]w$3qa7UdzZAEG(%Qf27E#[2U$2dH!`2B$*TBEzu뜽Y{<{7]sZ&I{iA;Ku6򦒴S]F[#inCܮjvGt6@ڠț˃h-h + jitt@CL?SmLI'{δ\+ʏtr;*`L}YՋhnF zKYƧ\&0)w2 m)V>LR ֱ |YtIG|YVdڈ?lA_/>MW{[io/i/WڄSoht]Ctm kϑ(ߣP|(> Dqutܥn(>}M[gx{h3U3P|3yANw{QE~ѮW]|XmUUUAޜͻ_PQa*+yFۦyRY`ҦBތӆ^Dha(򦭶t w':B[xGhQTySJ[a{ B{v(Ky+U7yjNWf'  ^N⻟S7=C"ohyA%L{g9yLV={dSPҨtEv mj# װTO]ȇ״-- δRȇ-po1G m 3h"3iO#^8ù;,\*ƪ&(ɮ2ppUiCTCQj:G*wZ•K6WmG>|B$WE)yPk*Q5ڮ:L˅(~Mbt? wmr 1UR0 GތRMt]\N[#WP|zwr%^b_N\I}q  FyݴMo=6_CP\%)UA[ISyOkjWݢys4VBޔ3T%7j;IZӿU]Z(}Zțh6fkC{I5 U/MgזByskGAyskO@Uu`Zա{Cpimt!o~ky횎vp:P8Tu:>#DmlD vKg2 UEۃv퉮ENSu}iUFޔhE TytgP>I\:bLVtdpQ m!V(;4oQ8tId;2vz%ojcCgڬk":=[UZXڅP| 6țn1mx4hN' h"fEn"ZY*{lmUIL<_^C7Ŵ+QYMumt:.yݍi.o:[3ԙJ{ZgP4N{Mf(TuLf(~as@[:V0LiJT( έU_Hns:bQWŧ$6LAެ/i t!oj'_3'Yߠ!(UO괛|KkzyXnE\-iuUu7yS\UXFGPXӸv~riQyR\y]hyN[Uovu?ZZ"o&ysn9O[ UqvI=L۽tݏv;u:]fVBQ(>O DکjAj AT=ԪQ5+R+i~{VFZEU%'Ӻ(>9ǙO m>~ _ ;nRb34>MUMkiTQ|hTQѶƊ[aHtomTCu: Sȇu]AD{ zy3I5Ch aڧt-DE+Lj\aT.N; C>S芠 (M(L o^.yL btK׃әss麑~K\[/J$kkȥLhD}7j{ٕBQ|4NG;'9L:bQ|pn:P|ΐ6W6(>]H+xO$^Cy(>gH!3 ηGiUPX'jມțڹ- F1ODmTuuZ*}Le7mOn.>Fͻ'\?g;]7kk>ț}Q+=nMț+ղOțT)?D7 kBm;h kBm볁骂šPl, RDaM=EJP[l0jJP[iT3 +9Zy4""o4#!R:C͘tfțtp=@"ogo W-t) לlj"e]ȇW(t Π f,ڤl6z Ρ-FːG\lp4ͧ:grdt v*yB5Q\uNohQ݃g]Lzp.=zp/zpYF[zpI+}|rvȮ@$Ҵ[NCqZE.½U贡{X}iTQgZEV(36խAP\}@[Zo-mj;u#(Ӽ*U߇j(6k U&㪞(>h$f4 U')Zo+@0_8UJNW8ك~tX;bGQ|u}>I$O=1y(.YX4ݥG}Q]*@k#Qkûu2}S(3Ֆ¨򦆪NϐPIwR;Iu¥AWj'L}芢țUu:y4^RryLAq)N;b(8NAgz;N%PuwJNwgb(8gc(FlJsʡ|( љ|z]NJ ǁխ(CJ:TT$oq+(z:?Tph.@pij7hR9xTDj1=[UySYj.:"͵RvC#Rk/ț"@ a(_^&"o˥ErZ?T@*~n\ȵL?QmLMh7r V]e-E#w(܋&}L'Jc4J0}Z5Nr?MjwNw~.wR;WZ2(WPܭjEۯڇNWk'-(Ik>%\jCh{|wQ;;c\ŽPCq_K:Tg5 ŝч٭ڍ#ʠG<wsSk1(vG}7ij^t-qt3=iUl/Q+Dq'7$#Lu0Kh' Y?ڇٓh= dl>khLlgmE65G6{vC,j=Ǵ~j a$"oZfQ;Vf@664{ CތƠXӲ1g/f.&Vg5ț-$5f_6v4!oruZ}V;ŷhU T Uw5-țv:fAigyjNgYhB3ΦSGlsh;T;L~CqWan:+PGL<wjr7vf>ߡRFqt/{ iUcPܯ]D^ojtC>rKRFqy)2SVJu+hue%^yj ]NXcVGPܭ_E//d-Yޒ hl&1ތV3 ڇo|oQ.iwPngzsU{B.w 9qtL~_=okh_J~hdBNAQ\YޖBLHa4F{ANWg@#)W )eiKZY+> h+AiJe/B+ô`;x%(㳻w@Y<-LS0u% ! LTIͣ<ʣ$MMJMM< M;MQ 5541T꣗g9sY!^<)a̒8~H'9ijeβo]~N!e{rHO#HˬW 0f@1Rk &YH899\ֻ$&.kS$fȶd6Cb:領!{4-2*~ |^,Z29Z.g r6VR6W@'S;_bizN$}Mz4G^(2ݨ{CCsB[< :/U ›Qx0 130a>+,÷Xu؀-؎l^Q)A!.2( : G#fGKA$'4: E]u[*u 01!`:fbbc)V k ;؏:8(YG,|Q*{PS QhxG$rz)gݐB_ kHǛQx0  +,÷Xu؈I{qGqppW`yYaGYT@D5P uq[݀fGKA$b"R701c0CLt§XX,zl6U pp8(B1,v/*{PA4E#D="QIHF z/5c(h{ |OXt1[vg!|E\ePjp>܏h(Z "80 ZR>'Ⱦǭ4֭%nݮh? dUZs'`kz3{a9զ04{Xo%m2mzz>avg;z]{japi8U{h6]US~=S]]_l([4TFzs_[v-e*!B[⺮p#}txtMNLMMJ-J:2_mszb1ѭcb?቉nn*T 4Rղv,ԿB#7ҺzZ]Jj׷+[R:tMLI T[QOĭj;W?}ޙ87Gg}q#[F\Q-"bK޽cp}X4P_ϫ [ηtB: YYYJV^2{i2mL8]ў}+&`YcY}-1敢 {DdS"0   # A2b5Li()j>+n`!65Li()jhGA~ $U8xԙ es{Gq4%Fa23FfFT9O(%%IJA%r#D'P2ڳ׺캮޾mk}?s3;/ u|RTP\YS{3Ա%QUNF"Ց+'zjn5_ρ@XO*^A (:!Oڹ wPP,Oxi\󟭋^h=Zx7?>O7=URRRZhFPj: =++hɍ qWmJ?{%%{0XSGi2YD{Hjϲ-iY q~F{Pe~s*>Y3Y5{euVF,؈Ie6b[IxxiX^FL.x-;E4K41YYFt UԒSQoMa$/~#ywzH^LE yW%/Lkz yBSQosH6;GXb*Kż#΋xEa{!zf:8?1۱O q^6oH^{[h[h%Zɛněn$*%~$=bO~7Hog1:;|DS~==K&JHW 0[bgyvWGZ70Pu#DĆ{Է0V *'t3)fSsTΧX@D ֐Hb/yߨ f0̄f` b8M\lRL*~LmS|FKӚ7{$Ϧ lZgTh[6ֲXM(QQȲ9Ko6Plv(%06O 6x>c5:հî |e[O/֣a8 9a>Ԇ3Bh@3΅aٶ`'hWA^xb_(E@><d}! (&߀S.>x!T C?I}|N}}M}~K1 c>VC+nA`ŭ*x'=d?( S` Φ_&[Al"YL)|F_P~C9%m8<.ÅX- kQ$n@фp>QNkpk17\ GGx1 O~>8bN%7Nc^"Sث7ӕRp{09Nj-<x&NjLco;Lev:o/SZ{zfRҰ9]%vbtS*W7)_=ث┯P2&VX;IqWmÓqW3` {dwUx89Au8]Lc8R[[eUYZqWAM XMd嫙PYt柮|5 Zwb5nt*`V/Ў ՗o[`$$OW;┯>-q*x!VR6{uaIU3x_p+_ػ W7ӕ{ʩi|5~J*V6l Ne+NȬSG}7hjβ*U]^ X]^y1N^SXY^/zǬ&])_ [VT?aouVPofoS;Y$sj'{?8uDV;ث:^Ԟ8E+G}.+G햕>֙*!FtEޣN#6{_FqWUÐ * c2>1G.i7XaL.]W2^]jY/hlrO<ysmV!GaU : QLJ[Mj ;J b*FFO22Z%YYL #Jrԑ(QFV&[3൦*mvAG,\0̂^q4n36Fg]&@1c0.3gRmDSF25L=QL56F`@1/T+'+f G=W^4Q | p2zRw"ʬG^sћ `=w{#̾g=oK_D;Aϟ jN}Ha~r vZD\f%\glC2Ӊ>YPm2&` GAh V(J%e:c2UIr3P'Q:9D=](ލp70XB&aEeOw7qx/0W%ΆI({z΃)L&Ze2<jr 5l@el[h$'wD[!*vth_8~9s lJ ,8EE aG G6-%t5ejj5}ZMVÕX-pkp++e}m{>yY^-}==y犜 7yEuMB %VnR7 U+Ĉ\UJȶ…FUwdE:e.3!^0I\n<gT>G%b9Pu$YXПcE9|R@mNs^qټ[HV%*U ݳ0U?;VzGjjThɪV biJ+{TkУxHQVFn,t%U:DBz|IT#\NT: SIFڌM*5beu*#A.4"HhQ:yc|B:H=F1o\M Ud/,}IuRYO#4?lΐk<gIyT%-T^W+/ӥ5m :RVVjݺAFZ=UgMV!VPz6lkcEZ=޷BU炶buڭR3Yn=妽*mwvunGY,^vz-;it(UNTzSQ/STq~;:ҶU>avujDڅVop`UN* qSJDVU+#ܔR=_[{j/UJ;ʶui۪V sP`},#eٯ$jϙ3I25~kC=Ο빚*p[bʹʑB܉ ܅Y܋a#؀؂mx;,UtN>OW8"Cc1E!J0 wc6cK +Њ6BGPѱQt$Np> C4b$G2}RL AjрXXXMhB3Z;{pq у3KvDb8␈1HA:b31ը/ߚpg}jU;7{YxZ+.MZ`V'SR0UKQ߿/];nt{?"f'pL)ES3'GGOʙILPn >NTG`zm`}'^`Jcs[797HVP{† FNnh]?gV< ٞ3Cv󃃯u\('_嫏VTh/e9%Ssses֜`NH{j#Ã[C#+vOvO+g=45mQO7zwY'c60G&9PwKt?x3zDdE"0 O # A21=w5\V )oEn`!=w5\V~.9~ U8 x՚ tTo1 /D DAK-XALBxWhyb( 0+*h)CRbX m8&* P! x@ 9mr6;wwwf}/yKQ'<{,勉?L~Ss#qgѾM) "[.IyNmL/DA3~4m{azqCOow9%s.ͥo/,&|Ԗ"IMW$[Z^" >?m=^"=4E%]tl>'T=Vf}[R}f*bqc حz|F=vo_XC=6ĕ/q3Rvq\v%\ m/fx8Xn(& )鲤 ))RU+W&vue慔7~ߨul^H~\i6y#/?bqzf!ns3;pl]=ۼgع.!eCryҺri2ː6oYl^̹ټu \y[ݙۼΎ/gLc;Q9[AS|[AQ|VVPo+ho+(xEU;g+ho+(߷4ŷqF\Qo:[A2NO\-'3_3_C*֌u34[3ճ͛|ykR=l^+Z)W.+6/ù i֑uŜ{NXye ՝/| cu<_)̈<:he fR5m,[Z,KZS: 6TvSeVV)Ko2 U*ʊ e:̊˲hd_pu hA#kaPȈ(%P')m+ŹZ@)^>dNn[^ @OX-AFEpr'tEn$wQ=A #zpq(dDהs@M@F#7@PȈ?!pp&Opjqp xн #V7MU?PMBt 7\M _Mn]2 u7-45F zd>A`b+ эa #˥p+rУ #pU #nk@7# OV> K> 2"3 .]na&8)Ge tdD^2{ 2b-n9Z27M@F| CBѾTE:MMbA.Nh;גlDQOP'b0tI}ms@bD_=)?E18+Px ܝ ,XWИb?hxT '"XA<.bRPwL(,1.W/!:DL-f){w!Q wXd\  Ȉb-Z #{9z{"Vxx уu#-QQ}pHCptԙjE+k) ԗa==΅CAcAFBAo"zu+%  (8c4q*r4t+ϩEt -r[,.5p"zŽv!:D@ #谽 !½GI܏dYp1jN#Ap;mJAM5`mD9C4J߅Ѝ M/?4яts?)ZhcZ 59Eͤ7z?GeScAtD"v5"Ng͡@Q2 m}n] I9i0 A0rH#'] ڂ$g}[#K4H.At\ w\'Dt7M.#:K'w-AA;\~#)E~bGR }W2td,8 U3DU-ڪA #.Qp=UP/רΠ #Fnp7onQ!:S]@Q3jGU?JTypϫj0HnUcWA5FDD(O8}gڃ³9\h./ AAF~eѻ{y9h!Ȉy%\Ŀm 7@F7>譠z2E #bpٺdD~ n~4RMop~Э #nI {G셕oKzakno:w > Oϗv_nuVgMvet^WH+N3&{͹'mݶں]ݶm\u WF^Y^~ ΰr-\Geo/.܇rIAv8'}ٹ>7TjvgS]Jak,2UA}vغ|D./p [Sus\.hU5]BmB sКP]֝LAصV% P]2].hUVa$g$li:Ѻ"0zPeFV[:Z+*T%gP:Oa[?OF,Z|9t5Ƕ _ڽ%\(H^TUg\ WpZWqE|~1WMKQc(\ h까 mw:vr-ܯy./xjw7 qpj\*ƺki|>ef{v*N9p.7cnurn4pns%p9ׅ%Ia\i]s1Ɋ*;V8¹%K8{O0oޔu>V%pMys++kqNp.\Ja\.׹\o.w\\sp &;ǹں\bpsa.wܹR[ Vp ΍X\ n-½Ε;W ps p{9:s:#] J;W\)a5 ſZ_Tx*W} d{WwOM@nvz[sôɭҧ2hx okv~[{RϝSV3ĎE?;5Sru=?ZѺ[kU ܯ ?~W ..Sk7J^ju=csff|شM"[drA9CrIO'g`r.z;YYrippRG<ffyfo[5^}mW^*гwjh1 a#IkzDd%"0 T # A2b#xa3 $Tn`!b#xa3:j%^ @b]x6x͛ NߵA)# q)r!&FQd;IȉB;rT;jDmvQkdw=?Lvϳ5Xj,V3 bCb َ1sȋQ#Xm8^kKI_7P[T'JE| }E2-Tbeh=߯kF KF<'ny'~?n^>j8~ _WO8=$Oِ4z_ϋwJ^yHޯ6p(06 M; ٢,ܗvsޔV2f~ίʅf'9}Ա *:ViltF#6-hĬ2qFlVf#G#6/aIJ8F#fш-ڴU]e:5c%۬/Z?T &٫QkX¸;HqX8Uc ֒UTb,Ra\Tc 6mLii"+g,RaE Fl-p?X9̠Cu$քlZ*5W-/>}blX8tƥw7k,ŭˍ[\.!&7,qdxZ~ظUPw*hgTYzVAU * * <Z2B* ZYxVAUPgHfTYxVA+<*г :_Bc{S[k.g5clZ\_jq>qd7,Y+gq-.,7nq|c|@6  ;z%Qja];}'<٨+-vqP3jnWutl{W{{έ:jjc Cn0" l{Su;꺢VC6u`G ci(n>؇GM/Է4v@k3`M``W-q<87(f5QQPf6?D*ZSU,WX67?R2[}ųQe77{+vnkޒFmq$^ԛ.]L7Jv[VIdz|^LYʐ [ʧ{V暇Ey )'U^N[*n6w[P[Q.$ݩz$Ծ>eY2nvF,Ǡzpl2PY5 *[u#J5Yj6Tr$^B%n ]=]v=P~0T\`eWNөX VZ` mH vr/d QɅ #c V(ށJT2jTFf=.JS`)iB!"EK@͔RyX$&JBr U#حr cĮ6wwL&3>&sg$/P+e Y !T"YoMP_?J#.XnK= ^:@%һZ+@Sp7Dݦ5n 6=j*T\==[X^NPJ ܏Jmz[p5 LL؝Z7s:;0#`W`Y:YM`fnkCG"Hv#ٍ`ۑY+u5jgɖ-E`ie5VY1NΕ̽]d]zVC;tH]Hl9j'B6l$!-{G֓'[Dl%Vne"8m*dBV̞Ta>* $,Y`;`"Ed-q)nI3&i0㎀]ܫ^ rI֓ Yg`9ar?y2ldp]en j~dvKgnz2gkDɵFub]}냨}ENjJnD[hs 6}z)QRj-@;9-lMih;~U~+K?t*^`+w\mY!;tWS3Utג}LRWK{ZΙ[UK]RI6jYdMɶS5Yy1UA(Eɸ.ۍAtncT![LzT&ܫ[Uk9`jz+=dSMPۘI0HmޏCw2XY [{U'{<%t,:N;ou?9@^:?9?"_U8z vF~5GLZ(gV`;Z<\%T&fe99љy<އn?snrV {"p׸5mƋfYb ā ju"cE)6(7.JUqQE)7.Jsq_n\"p7.JqsyȳĝQuѻp3|lf j[J-%7..ܸAڹAڍ;;ܸeJ2W t 7桰w>uW,r%s뼿_έnanuN-Vwrح[aN՝v;9Vw[anuGΐJmy7;\Yǭg疒@n UUn\ \r2sҍ+WLqswPxgs^G{@3bdZ:S f2-d JMjf@l;-WP Z }*LQU-sJn@Tg D ]0@<]w+)솁3U cLXBczD슡@c PU@L/1-` rnh#}f}+>c:l";8n8}[$5dpas\b7D@<+OK=ZR\bdW<ɮ<pdػJpU.@Uؽd luɠILd*4):xǘ^ƪ{^n.CxE'}^]S %إZ6cWFc*v]+Ⅿf11NԌ]{jԎ)wPvK \|J/@ٕ0'=Ȯ=T>~vm>{"PP`tePwaZdWnĴ)Y1v1dc^1dzpKbaW0a.f3%0UB )Lv:S g03P Lvq;B 3'+zϝ{;2EUB__#sOe> zȧ?mᴊBrM#NwxY|Tܦۤe457˲rNM,apJ2MeS)ŦTMmJT<-MN@gDm?^7^7;yy6 K k^#lh6nIw_c_mӧHgmچT%Sɯ#Hm:Tʦrl_Gk&^kLqNMKus:K6ӭJ$Nc?ESQNN?NݎwzZ;gtNTӜޥYj( 4>T4ͤEzqZHYj4SlZN餺6sO9;Fuw衔tVU^NO&YQ~NM]ڝ&:ΔTܩæ2vZM#tۮ%R_Z#hx(.]tY iMc޵{6[Yl2{ٛݷt62ZrN)[O9m3zeiw$B;qԝsz tRHwQDבO.ղ)S:5d*YjAR9N(Pur+~zr:Tj=AНNsq2f}Iнlѽa؊]v&ޣ4ܪ[F}5r=i䞘 -t:w&/v]8"L8,lrWʚ$[/L3U1{fjJDwJKm-2nfHOٔM#3U/OpgCqkiEC8֋Z=֫4ܤfrʖ;=N/S;S_qڴ*)bL+q:'vOTR%x?_8娊nyѴEӧ7ݾuON]Sj]C8M~Tsׯnm;Nm}Muɩ78˾{dߝ ~Yh_,_yh{/F֦rvhM;EixJN IBdH_%'FUiLQ J\UdOVYS>1e+ǫ5^ e^Lҟ^>(qL?g$*n2j[T]=U)T[5FPUWNfLTR{5AP=wiGuXuWWj_[ t]_OuM}nl~Lgv쳺~kM|ZWuڪ˪z=n$+h2B_FuzM^W]C?Pé}2Pm9TWfRRmLy@UشQyF0Z3^հުi2]u{~$~ ׃cRDsN0f V[Lc֩oM^P.J"^,yiFjKQ\{[=V6a֍j7H/ ^ۼzx)/~:U[:ɟtR뫎a ȁrQ-rرkQ|} :(\X:ҵ]S S ]<\AP^;f)9lg0CfldKaەY5[f<ڻCGl E~~oqi?YӻkD{oo.-T/53Ќl㙽EKg;ٻl'1Vv1inbvf?ҮESUS[f/m,֎mGfzMؚp<ȯgmOfhal_e֘[/f4F+#ϟ^`v^fh]ͬe;Y:-i1Bi!l[3|M3^An8lf6gS^HHc,6x]lm#-cvv-fjnVa֘Ͷvl;1MgH3ixoJvlO;hgqwi>dVCjzm]O `Ĭ+-m{,,Y:mǬ)̪<غ2W^m0+a{f&--f[l2m2iئ3Kų52 g̗r~{fhd;A>`!hcASwwr~luEb֗6v$|3-`Y m+۝̎N=.1VCSۺZٶfօ֕m=rO]rG%GMwօ)_| wpqqqq=ucà]===9(}03XVMf^[toqqq/|q8/\ .ŵŅppH\$. K%zqqCpCp)!q~=J ~ n n .W+>xꎂA-,ĭíǭ}ۂۂۂ[ۍۃۃ000n~_022{mmme#ϸqiiʩiڸ8wN|jp~8?\#\z{V+VxWpѸnnpppppo^ǥpi~,\. ō MMMčMMM 7777 !N.0p ҍXV+7/9Yo;;;wwww w wwwwwww䦜rNUUU9sZWWWW kkkkkkkkk uuuƵuwSoL<ҙxSiVg? rp98X88܈N Ҭ~?7 W+M---pE"-nn8W߅ۍۍۂ;;;ۍ;;;;;+Ǖqpqppqzu)=i5555pp`\0 DžqQh\4.E8UVg)Ϋ{q<77g?epiNsq,՜V:_1041417313ac(@=`ba aOle  ObjInfo Contents[H      !#$%&'()*+,-./0123456789:;<=@BCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`CPYA 4,210 #  $@X r ??0UCRIESKE_A p ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@,t,t,t,t,t,t,t,t,t,t r !`??UCRIESKE_B r !`??UCRIESKE_C r !`??UCRIESKE_D r  `??UCRIESKE_E p {Gz?Q???Q?Q?Q??Q?{Gz?{Gz?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q? ףp= ?)\(?\(\?\(\?(\?(\@HzG@Q @p= ף @Q @RQ @ףp= @Q@ffffff@{Gz@(\?ףp= ?q= ףp?Gz?ffffff?(\?Q?zG?RQ?)\(?Gz?ffffff?(\?(\?q= ףp?RQ?RQ?ףp= ?= ףp=?zG??Q?\(\?Q?Q?\(\?)\(???Q?)\(?Q?Q?)\(?{Gz?Q?Q?Q??Q?{Gz?)\(?Q?Q?Q?Q??{Gz?{Gz?Q?Q?Q?{Gz?Q?{Gz?Q?Q??{Gz?Q?p= ף?333333?{Gz?RQ?RQ?333333?Q?? ףp= ?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?? ףp= ?= ףp=?Q?)\(??RQ@ ףp= @ףp= @Gz @\(\@\(\@Q@\(\@(\ @\(\ @)\(@ףp= @)\(@Q?p= ף?Q?Q? ףp= ?ffffff?RQ?= ףp=?ףp= ?333333?Q?)\(?)\(?(\?p= ף?{Gz?Q?Q???{Gz?{Gz?Q?Q?Q?Q?{Gz?Q?{Gz??333333? ףp= ??zG?Q?Q?p= ף?zG?RQ? ףp= ?RQ??Q?Q?q= ףp?Q?Q?@Q @Gz@@,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_F r `??UCRIESKE_G r `??UCRIESKE_H r `??UCRIESKE_I r `??UCRIESKE_J r `??UCRIESKE_K r `??UCRIESKE_L r `??UCRIESKE_M r `??UCRIESKE_N p ףp= ?{Gz?Q@Gz@Q?RQ?Gz?q= ףp?Q?333333?Q??333333??Q?q= ףp?(\?\(\????333333?)\(?(\?Gz?{Gz?q= ףp?)\(??(\?{Gz?p= ף?Q??RQ??RQ?{Gz??{Gz?Q?HzG?(\?Q?p= ף?@)\(@Q@333333??= ףp=?Q?Q?{Gz?{Gz?Q??{Gz? ףp= ?)\(? ףp= ?Q?(\?Q?(\?RQ?Q?RQ?ffffff?Gz?Q?Q@Gz @HzG @ףp= @zG@(\@= ףp=@Q?p= ף?(\?Gz?333333?= ףp=?{Gz?RQ?Q?Q?(\?ffffff?ffffff?)\(??Q?Q???{Gz?{Gz?Q?Q? ףp= ?Q?Q??Q??Q?Q?q= ףp?\(\?333333?\(\??(\?(\?333333??Q?)\(@@Gz??ffffff?(\?Q?(\?Gz?)\(?{Gz?\(\??HzG?Q? ףp= ?Q?)\(?zG?HzG??p= ף?)\(?)\(?= ףp=?p= ף?HzG?(\?Q?Q?333333?333333?= ףp=?Q?(\?(\@zG?Q?Gz?(\?{Gz?333333?ףp= ?(\?q= ףp?(\?{Gz?ףp= ?= ףp=?= ףp=?Gz?= ףp=?Q?(\@RQ@)\(@)\(@zG@ ףp= @)\( @Q @Q @q= ףp @Q @(\@= ףp=@?{Gz?ףp= ?Gz?{Gz?Q?ףp= ?Q?)\(?,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_O r `??UCRIESKE_P p ??????????????????,t,t,t,t,t,t,t,t,t,t r ``??UCRIESKE_Q p ??????????????????????????????????????,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_R p ףp= ?Q?zG?333333?= ףp=?Q?ףp= ?333333?(\?HzG?HzG?p= ף?Q?)\(?= ףp=?= ףp=?= ףp=?RQ?ffffff?Gz?Gz? ףp= ?Q?Q?ffffff? ףp= ?ffffff?ffffff?(\?RQ? ףp= ? ףp= ??= ףp=?Gz?(\?{Gz?)\(??zG?\(\??= ףp=?333333?p= ף?Q?Q?p= ף??HzG?q= ףp?q= ףp?ףp= ?zG?p= ף?Q?HzG?ףp= ?Q?\(\?zG??(\?333333?)\(?HzG?ffffff?Q?Q?zG?ffffff?Q?RQ?ffffff?ףp= ?Gz?Q?(\??q= ףp?)\(?(\?Gz?{Gz?{Gz?= ףp=?zG?{Gz?(\?q= ףp?Q?Gz?)\(?Q?(\?(\?Q?q= ףp?(\?(\?Q?Gz?\(\?{Gz?Q?ףp= ??(\??(\?Q? ףp= ?(\?? ףp= ??Q?(\?(\?Q?Q? ףp= ?Gz?)\(? ףp= ?)\(??q= ףp?(\?{Gz?p= ף?)\(?\(\? ףp= ??p= ף?Gz?ffffff?)\(?HzG?HzG?(\?(\?)\(?ffffff?Gz?Q?(\?RQ???HzG?\(\?= ףp=??{Gz?Q?Q?(\?Q?Q?ףp= ? ףp= ?Q?p= ף?Q?Q?ffffff?Gz?RQ?ffffff?q= ףp?Q?Gz?ףp= ?HzG???\(\??Q?)\(?Gz?Q?)\(?(\?(\?)\(?\(\??(\?Q?Q?Gz?zG?333333?,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_S p {Gz?Q?Q?{Gz?{Gz?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q??)\(?p= ף??Gz?(\@q= ףp @{Gz@RQ@RQ@Gz@\(\@= ףp=@@(\@q= ףp @(\@Gz@RQ@@ffffff?HzG?Q? ףp= ?Q?)\(?333333?Q?Gz@HzG@Gz@RQ@Gz@Gz@333333@@ffffff@HzG@RQ@333333?Q?(\?)\(?Q??Q? ףp= ?{Gz?{Gz?Q?Q?Q?Q?Q? ףp= ?)\(?Q?{Gz?333333?333333?Q?)\(? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?{Gz??{Gz?Q?)\(?Q?HzG?(\?{Gz?ףp= ?Q?(\?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?? ףp= ?Q?(\??(\?@ffffff@Q@Gz@\(\@Q@@ ףp= @zG?HzG?(\?(\?q= ףp?zG??RQ?333333? ףp= ?q= ףp?Q??p= ף?Q? ףp= ?Q?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q???Q?{Gz? ףp= ?)\(??)\(??Q?? ףp= ?{Gz??Q?333333?{Gz?HzG?Gz?p= ף?(\@= ףp= @q= ףp@333333@,t,t,t,t,t,t,t,t,t,t s Plot1$ `  ` D:\ORIGIN Fr,,s 9 l@I@@-"@@?@E]tQsl "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L6  6 c FY C b`ȿ&Y%ɿ>> L5  5 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c ZCK?+]*? H_  l "  pivot point c [X]r1??,>>  A c uG߃U?W#V w  l "u Rieske protein, bovine c P H 8p?˗d1? P >>Legend  l "@P H  P \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) \L(5) %(5) \L(6) %(6) c J4)*aD@ >>D@YL  l "& i CONFORMATIONAL INDEX c $eX@ѝj7ݿ >>BXB  l "&  SEQUENCE NUMBER R  `# R `# R  `# R ``L># R `# R `# R   R   R l "@l= q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N9 R  l "c'? R P@ N  l@ R  R  R  R  R  R  [[[[[[[ۈ+>mmmJqR6\((kYYYQU559===5N&48sUy|p>z8ujk$7Iz:68mK\.kuuu%p 8iq2.K2p8N9 t777{7777 W+-ŭŭ666vvvĝ]]]ĝ•qpqqq87wܕS3_뫯szW})GrZ gqp\0. Oc>>'Q>pI8\*.K e2qp#q#q#q \\>.---ũ9q)֙4X g?ۈۇ+ŕ:8+Õp3332UUY]]4* N硜S=ccթyUq8o7O1q!P\NNNP\ .g?qX:)|/^gjt\:.gƙqf\:n4n n .7 7 7 77777W+fVVV666vzSl)ͼٛ[k4w19}l=y KE^ԗJ%aHIIddd$O2ER Y(X^EGrXrJrYr[DsHmI#II7I/I?[̮i,(Dt<2gbvגcs'Tԓ4Ťt HIޗHH$$_Jvbv=$9%$)<%i(K%ђ8AX" i]JJVI%$k{'"Um"HH"$% dI$[2V2Y2|Iddd-&䢤\P^]HK$($IdJFJ&H%s$K$+%%[%2U]Σ"U$o$TI+$bvM%c$$3%5M,+"ų~&G0++:-u֯qAF䤙} hNLnIхXm``!o [k _ky_+?G/۞7^ZZl9>=rsZEee 擝242ؾU{\].l9qxU\q8J٧$7&~z$L$Gf:}\JJT.):Z2l)[LAuT"V,S<m4w([&qC|݊y;CKyͳss9k=_s9JlykqNXJXX!HXἵMX/Y)~Ig^:3ggO(閁o%)^V^i%)1^pzIJ|q_/I Nt.5;?Aÿffj2ƻ+*zhzh_onj|+,pu&:KFsW;s3XJc[/ g|zԨiQ?S~ƧGO3>5g|zԨiQ?S~ƧGO3>5g|z4[gV_?k0/Hsܻڼ.qf_롽}}ʻ}׫)22_יL.])O=';8x"n_Mpcxh,Tw+ \P$[e& >s d9 3(&+1 rZ,u4&mYdN}(xsnΥ&L96,:,)md1p%!TN燻Ecrc% J[?V:++ۏ J\GU$DPý#4di* 7Q}4KU ^]Su)J奨."@܍YS{H] *w*("K) R, n= YZ"^"KUu~P)jp} K9TUգ!MՂkYzFՐkT?DRipCM& KTc>Y[µ/,5-tP=spwgAw,U!3~YگmmA@V6puk<Vpw!t"K-Ʀ?Ⱥc_3"DWfy ze1CAA7CI!4|7L}4L[hƃYZc>+Ϭzf_f[,]`]f6 ,]e6VMڿ߅V)DJ0AE@p#!< j<7<"Kpi,&p)c1d)4]Bduׁ;ڃ,pC>,'pP;#N2@pYXqSEU,}k^f^m{i wʼYs +!TƼ wPLڦ=Quܻ?A-@#.@4 dݎǻ7!rXQ;J'L 4 di NwY!GRt[6 K'[pq_\1F wt/tO@䮑~"KWwd5A@;pOf KuQ@]A7T YT M K{~ P^'"tƀܓ= 6vp}@@i|v*Dnk}N .-X T#Ȅ˥Bd)6Y|g6`_:*@]ZzoY{U j\zdWKm=TUm6rkAmۢ=jh=^qj7h,hq/!nxTVYGPOpu;,uJGA/,=q1I8mr&Kp{uun, Q:|!YaʘܠҠ>"ppϚKAAndJ((!tҔ;hJ,m5Bv|#\?,}*YU;2<$D>i>"#B@>i>0@S@[a>aFrʌ3Arpzb, MYZíZrP S =CXbBA}()jF,Q JipyTY\ܵz :ݭ3@/9j% n{0d鰸lҜ TJK U"W ȭqMW K-Ž"IJ{Yp Ij&h2(\>- #kCKܳ[\Re rpͧ% XfZ r*tBJc"|BA+|*TY\UVP#tq w7@h`0#߁$mOuӿyD/iDϧ,Z&iKsv6ZΙ]$E^k7nHغ]II]2˕A_tK@{}cJݥk%Us]"KJjC]+K$uv.ߥ]#iK%Mwi\w~$e!#֍`9/BZ{ټ,J|2(;2 sȗTqsK]@}LEt1s!UתF*?R9u*  nQ[ςrHJPH?T ijvgJ(RyJ W;RԴDJ3}TU*H(F:a>S; ь@mff4RKX3Z 3jf"o~Pכ}Hr_)QޏT\sc.v)i.$2{u^uyIBTt Zn})}@77IYWvi~N4sRMoH-~[ Mn4iӹs6z.gLDyP/'VU4ǥHՂLʐo]WHcM<0j"ZTNd}ZD/w S djl09c>qmɏTM3#]UbUHi|o*|(֔4ƺHqk4zs혿:4~56_'6n1[Ž%s靘<\lF\$r˘KY,^ iK%ri.mw x%W|^gr$WNN5vu| [\.> "t+>K=Iң.ݎ4p59;_-㣹޵Dʺޮ B_~fM?`Cgƻ鏑֩Dygt!~'Eǯq=νG$~~op&diu< di%O/AF, s;{^Y*yJYj&'Cn晠ʠwEY K+P d)wxo|.3n*kiBSA&{f.+⚛yg@ij,UwЍRZ,\0Rq,)l h7vq"2EЋAAƋ"4XJ%p:,5Yj(=ȞAU^TZL] O굠үj\.tȒWRo]t6t;=@,5R;qoM Kf' K},-Qoe,mwTo;Pz< Kd. Kn4Td:f?Qu̻[aPu_\yOշqYBV(&~)2_ )2O i)c!*!MT*"hP%TtKe(T4}xG~g}wUAzKPFPVu"tuC:^)4GXds8T# ȾwmAiNl4ZVVKr(ŖURJeM4j=zòz$ҽDz)z4z e{ޱdZbγZW6FeBMjZdbt@iZ@c^{SݬoPטW|yG1_c$у( !K@w1-Q'z-TG(kQdgtӲ#t*bOL@1-$(kL`LGKeq ~#f:^bQ%Q EԲ2b8NU\Cu]BH+Ped}[>]Iu~#Kn:E7b>[G6˼_5e oZgjoL/U~GQT7 T*aV!M%/쫳= D P~Ux*Vzɷjw]P> xVC(A'z60 @|Bעho4LyQr]8(_od1]F_o(_odZ5݈UF6ѯs2|0==Lu6JP&QlW6{Ga(#<;UP gzVGC.LEW:{vLC_nhƠ_n32Bܲq! 2mD魐e{ JOҧPiCԧ*lt}>svEim1݉bW%A}z7"(_'J?etjO|UC7_CV^?Ctde: 'A>G[ ?[_/ gz˲͓M>J6M$Fd7?Js3YwuCid[v|tUXvlAUP~\ʏVYgنN]ݍL6@vQ xC~EסFQ :pNVV@^G4f4Ց?}ӏe/i4LKF~i893C-}9;|*%׶lv~ pg'jIt4.R6bZkipgtJO̖ #pfQ ,h J-[egZZ=~U]ը~~&TVduT7kOkhEQzE^@ptQnVXvF]t (l,jqdgxtJZ,;J'#QzOc^y;˾GW(]AdQ,J,/S8iYv'zVζhٍ/t}ղr.b~O>IBiov$h:J\D6F@cQ 1,if^dKZbX.6J ڒ&WQkYim@iL_Qz5Y}.Nv5o;tkJF)vKY|۹gJ}Ȟv|GDW>]pV7:wEm~j{ܠͭj; Sf8JUGf>@v]Y]TβQgS]ɋSoՕﮤ:S?Ft]5Tr~Ό=[m FmϓֺU+%}t+C꫶/H'=:Nm7SkxTFE۸}AJ RܳڎJϦƉz,:IR= (Ul UO#xSN@VlTDkQZX }RMr>C%թӚ֤ZBk]9N:jitG5b'k]Tp g嶛 'iǥbXrb@1LiHSRe9jReRzK;U@ݲb-ۖC[Q굷*>K-@߲YgXօ#(EQ+}Yw0ijuQt^zWP =[DgAeYo#ag>e/:W\OvCQ۬Wɭ9JFKAQ 7Ƚ>#̲V2G@aՒA>#l!>,+&C} fٶa#l>,{5#lCZ:dg|DLb6lJ6GT45Fun6C؏}=V7Ⱦf-(|6yt!++/r(%2UCi\YD桦( XC^F=Q5xl̷+>˦Qqlj VB;(VX,R_dEu5z:o8EMqzI&kK@eY}Ϯ-zX'(|H6Nע(櫥udztJ}A]( _KP zVI7QJ&t8Բe[dT`L'{^Fe7'σ{7zϒ=/PكG3 S;P$Y')6Qd%z(_EzvCQډ޲ҮR^-.2lc ( lL( l٬L3(_{6? P/w>J&FTCZ(`MH TmcRSƨ%P*1& I$VG{sjڦ\=߲p.3҇ZQP~oM6D(>7fz.(>3N9TG(5-l(WZǬV+ZA@GM\ mBَPKlԲD8T&Q' & r֥'j]E= A>O0(mt_0kZ/@G55UZ{wYZzA9se> kaV2ZZtYuB+&龷aMEk)o7kޖP~~Vc=zXO1{8+U5{i=NEP7| (gV]:oPLd鞄r`յb P ߻Nl:S#F]3-\=O*Zg.Ie],^Ck"I硦A9TڳgPyPԊBC9g"Q6skUr(TNPgc[]"_ Zkz ~(Z׺S>T(x\eaPα@@'XjW:zrij HZN+iZPMƑqs,y'A93Z2LrYhf\ajk ̤Ynf׬43 g--L킙yi+)=#}JQm{ ([Z2XB&*=C$gsjf+=f3s>lv{rҳSzVR*ܥ ~+U u_ޯYwqYK>l- ?+p| e YAZp p0L`6^J&( .@ A_ (0 ,`+( \ P &0 䂅7:v8 >_+CAl#  AA>X^kF.({p xā` RA}z V`v*!u<  ڂν ĀX0  /B(o- T v tAo0 #AX" vGIp9vh>g\"٫=Ͼu)5..l3.\ti\vRe\\t9l\Rk\j]t3.u.4]..0.7\tBHKq uѥqiKqrѥqK_EXKqIteqd2Ee.%E<"EBRKq)vѥĸ޸weqKq)sѥҸTrȸrѥڸTrڸvѥ޸Իd\\tf\Y3h_]\ ^B6# oid.oj̈́3 'ӟWcUX}U_u]f^0WXwb3VĪ|v09v# [d;q@DbW+&{G4)y3Eof( D8+JD\/V1WRDKXDi&D^%e K"Bn]d-׈A*mm2E&,reZ(3Uܮ~U yO֩yJcNۿG~*M{iO#tTES@*T3Τ1|n˧sjP׬j#VKVJ"uqU#UzU+ی`eAQTURU<^TUU(W3b:&6bzFPUPry>pʹ]WoP[_Eϯb|OX_ۮFɾjVeԳ sW^}J-LSdSL=skP^j΄u}BukUohW atn,`kE.Rk$ΣAQ;:iE=?g/8g1^< `5&=599禦g1;/=+5p&6b<=bV{zrgL5;ӕ q!8ddcF 7|dEFO03x0γo9M#}G|؄$DF&0 ^~=苞oM/bxRQQ8Upszg͚84~q Otz=/B4y#}d(1TableA>SummaryInformation( DocumentSummaryInformation8CompObjjequZAVOD ZA FIZIKUAVONormalAZAVOD ZA FIZIKU2VOMicrosoft Word 8.0f@ @a@aF ՜.+,D՜.+,h$ hp   PMF SPLITA\c  5Sequence Analysis of Membrane Proteins with the Web Title 6> _PID_GUIDAN{9DA97888-EE0A-11D4-8BD3-08002B96244F}  FMicrosoft Word Document MSWordDocWord.Document.89q [4@4Normal1$CJhmH nH <A@<Default Paragraph Font4&@4Footnote Reference4O41.2.3 & F0 h:Wta  :WtY n%*1=D!FFbS]h*w x%Q!\6pa-ZDtԑ1aN~ޓ>nΔ.O z2]A $$ d0;Ov.&` 9o$$Iy&<$ !t57:RTWoqt::::::H  o2$.hCwm*[2$5Li()j>2$=w5\V 62$b#xa3C2$^.o(_;5#)і2$1=3a`]W0@ "(  H  C A ?N  S A ? N  S A ?N  S A ?H   C A ?H   C A ?B S  ?Gxa "4S"4\E"E4Pv#4  ""4un"4mu{CIKSag]s\c) 2  0jo  (+2IZ`m8DZbcjr}*","L"S"Z"e"f"q"|"~"""""""""""""""####*#,#6#8#V#Y#i#p#v####$$$)$M$T$k$r$$$$$$$$$$$$$ %%.%5%P%]%V&]&&&''R(Z((( ))))))))#)%))))))))))).*5*7*9*v*x***$0%0F1I1y1|111111111111111d2g2o2r25566666666?7B7E7H77778;;<<N>\>]>g>>>>>?'?"A+AeAoABBTCaCRI`IIIJJJJ K KKKKKKKK LLL%L2L>LDLLLLLM%MMMMMM NN'N(N/N0N7NNNNNO%O&O-OiPwPPPQQ$U2UzUUQWZWWXX XX Y YYYY>Z@ZHZRZZZZZZZZ[['[a[g[[[_`aaSd]d^dlddddddddd%e0eVeXeeeYf]fffffff&g*gIgKgtg{ggg:hDhEhShehghhhiiqixiiiiiEmSmmmmm"n&ntnnnnooRoVotovooop p pp_phpsp|ppp(q/q0q>qqqqqSrarergr%s-sssssssstttttuu~uuuuyvzvvvw"wxyx||-~5~\~c~*2=dkLW kvЄۄxĈȈ݉Ɋ 7<JX  QVՏ+6ehēʓ!$ILEHhk˜<IȠ֠נjxYgϨ֨vج(5]d$+3>ѳ޳HSIO>Dʿٿ #)#RZ\`bf $'GKPW\e [i#(-2:D 0;@C),w(9@KQVYy8@Yfy~ +9>DLV#&.0@CKSbdlwYbs| $),4:OT\e<ALW!):= )>Iaego 9>CL[^cj  '.2jm28:@BFHNv&9>FOW^cjoz9?| &18?CEFLMWX`bjkstyz|}"#'+2389>?IJRSW[^_ghjkst $%+,<=FGNRVW[^deopxy ()12;<@AEFHIQeklnozb-W@M OCR`hFRTZP]!!V"e"##&!&X'h'''(())6)8)))))++-.00D1F1w1y111223344'5956677<7884;>;;;f?z?BBmDoDAGJG&M-MMMN OQQ\RgRXS`STTUUKWNWWWz[[^^^^``aaaaabbbncc ddmdddd9eMeeeef_fsfff,g@gggghThghhhiii0iziiiijjk5kDkqkk llll mZmmmmm(n;nnnnoXokooop*p~ppppEqXqqq rrtrrrr?sRsssttht{ttt-u@uuuu vZvnvvv*w>wy y{{JAHbrks$v}ͣ%4.1ɰ[ܸ}<GO50XX]OS CEbWYbProf. Davor Juretic)C:\TEMP\AutoRecovery save of CCA98_28.asdProf. Davor Juretic)C:\TEMP\AutoRecovery save of CCA98_28.asdProf. Davor JureticD:\My Documents\CCA98_29.docProf. Davor JureticD:\My Documents\CCA98_29.docProf. Davor JureticD:\My Documents\CCA98_29.docProf. Davor Juretic)C:\TEMP\AutoRecovery save of CCA98_29.asdProf. Davor JureticD:\My Documents\CCA98_29.docProf. Davor JureticA:\CCA98_29.docZAVOD ZA FIZIKUC:\My Documents\CCA98_29.docZAVOD ZA FIZIKUC:\My Documents\CCA30.doc CJOJQJ.0.@HP LaserJet 6L PCLLPT1:PCL5EMS3HP LaserJet 6L PCLHP LaserJet 6L PCL@g XX @MSUDHP LaserJet 6L PCL&d HP LaserJet 6L PCL@g XX @MSUDHP LaserJet 6L PCL&d u4 )*+-03459:EFGQRUVWlYlZl\l^l`cd l m { } nnʊʌʍzzzzza```@``(@`0`2`h@`6`<`@`D`@`J`@`X`Z`@`f`@`l`n`@`r`t`@`z`@``@``@``@@```\@``d@```t@``@```@``@``@``@``@``@``@``@```@``,@``H@G:Times New Roman5Symbol3& :ArialA& Arial Narrow"A hQ&Q&F\" 2c4Sequence Analysis of Membrane Proteins with the Web ZAVOD ZA FIZIKUZAVOD ZA FIZIKUo$p$$$$$$$,HHHHVIXIZITJ KKKK~KKKLM CJUVhmHnHD84~q Otz=/B4y#}d( Sequence Analysis of Membrane Proteins with the Web Server SPLIT Davor Juretia, Ana Jeron ia and Damir Zucib aPhysics Dept., Faculty of Natural Sciences Mathematics and Education, Univ. of Split, N.Tesle 12, HR-21000, Split, Croatia. bFaculty of Electrical Engineering, Univ. of Osijek, Istarska 3, HR-31000 Osijek, Croatia Running title: Sequence analysis of membrane proteins Mailing address of corresponding author: Prof. Dr. Davor Jureti, Physics Dept., Faculty of Natural Sciences, University of Split, N. Tesle 12, HR-21000 Split, Croatia E-mail: juretic@mapmf.pmfst.hr Phone: 385-21-385133 Fax: 385-21-385431 Key words: sequence analysis, membrane proteins, prediction, secondary structure, preference functions, transmembrane helix, interface helix, hydrophobic moments, antibacterial peptides ABSTRACT In this work, recently solved crystal structures of membrane proteins are examined with respect to the performance of the Web server SPLIT in predicting sequence location, conformation and orientation of membrane associated polypeptide segments. The SPLIT predictor is based on the preference functions method. Preference functions serve to transform the input choice of amino acid attributes into sequence dependent conformational preferences. Transmembrane helical segments are accurately predicted with a good selection of preference functions extracted from compiled database of non-homologous integral membrane proteins. Unlike other algorithms with similar high accuracy, the SPLIT predictor does not require homology information. With preference functions extracted from soluble proteins, the sequence location of shorter non-transmembrane helices can be also found in membrane proteins. In particular, Richardson's preference functions are even better than hydrophobic moments in finding interface helices at water/lipid phase boundary. The Internet access for the SPLIT system is at the address: http://pref.etfos.hr/split INTRODUCTION Different genome projects result in daily addition of new genes and translated protein sequences with ever increasing flow of genomic information and already significant impact on the world's economy1. Approximately 20 to 30% of protein sequences are expected to code for integral membrane proteins2. Sequence homology with solved crystal structure helps to model the 3D structure of the tested protein3. However, crystal structures of integral membrane proteins, known with high resolution, are still limited in number2, so that degree of sequence homology is often too low to allow 3D modelling of a novel membrane protein sequence. A more modest goal of sequence analysis is to determine membrane-associated segments in integral membrane protein. One must answer the question where in the sequence are a) transmembrane segments, b) membrane buried but not membrane spanning segments, and c) surface attached interface segments. In the case of the first question, the answer is provided by algorithms that predict the sequence location of transmembrane segments expected to be in the -helix conformation4-8. Additional information in the form of multiple sequence alignments is usually required for optimal performance5-8. Modern algorithms provide topology information as well, for certain classes of membrane proteins, by predicting not only the sequence location of potential transmembrane helical segments, but also their orientation with respect to outer and inner membrane surfaces4,5,8. No explicit prediction of the nature and secondary structure for different classes of membrane-associated segments is attempted by these algorithms. An improved predictor should be able to provide objective and accurate answers to these questions too. This goal has not been reached yet, but in this work we discuss the capabilities of our Web server, which is versatile in dealing with the above mentioned questions and easy to use. For an operator using such a server it is important to understand its limitations as well as its advantages. We shall illustrate both aspects in the performance of the Web server SPLIT9-11. The Web server SPLIT is very fast because a) it uses very simple preference functions9,12 and hydrophobic moment functions11 in its digital predictor, b) it uses the graphics library created by us to enable a fast graphical presentation of results, and c) it does not require multiple sequence alignments as additional information. Since homologous sequences to a novel sequence are often absent in a databases of protein sequences, improvements in speed and accuracy of single-sequence prediction are important. We have recently reported the SPLIT performance in predicting transmembrane helices (TMH) in the photosynthetic reaction center, light-harvesting protein, cytochrome c oxidase and bc1 mitochondrial complex, and in predicting membrane-buried but not transmembrane helices in some voltage gated channels9-11. In this work, four additional membrane proteins of recently know structure are tested to learn the predictor's accuracy in predicting the sequence location of observed TMH. In addition, the performance in predicting the sequence location of interface helices, and of other membrane-bound regular structures is examined, and the practical mode of the server's operation is outlined. It is shown that the predictor based on preference functions can complement traditional methods in finding the sequence location of transmembrane and interface helices in integral membrane proteins. MATERIALS AND METHODS The Dataset of 31 Integral Membrane Polypeptides with Known Crystal Structure Membrane polypeptides of known crystal structure are still few in number. Here we use the known structures of subunits H, L and M of the photosynthetic reaction center from Rhodobacter viridis13,14 and from Rhodobacter sphaeroides15, the lightharvesting protein from Rhodopseudomonas acidophila16,17 and plant lightharvesting protein from Pisum sativum18, the subunits I, II and III of the cytochrome c oxidase from Paracoccus denitrificans19 and the subunits I, II, III, IV, VIa, VIc, VIIa, VIIb, VIIc and VIII of the cytochrome c oxidase from bovine heart20 , bacteriorhodopsin from Halobacterium salinarium21-23, the subunits from beef heart mitochondrial bc1 complex: 7, 10, 11, cytochrome b, cytochrome c1, and Rieske protein24-27, glycophorin A from human erythrocytes28, potassium channel from Streptomyces lividans29, and ATP synthase subunit c from Escherichia coli30. Except for the bacteriorhodopsin and glycophorin listed polypeptides were not seen before by the PREF algorithm9 during the training procedure. These 31 sequences contained a total of 100 transmembrane helices with 2761 residues in the TMH conformation. Published TMH assignments were used. Selected 22 Interface Helices The membrane surface positioned helices were considered to be interface helices. Such helices were selected among non-transmembrane helices from the database of integral membrane polypeptides with known crystal structure (see above). Program RASMOL31 was used for molecular visualization. It is possible to color amino acids visualized by RASMOL, according to the temperature factor. A small utility program was written to replace experimental temperature factors by hydrophobicity values, based on the Kyte-Doolittle hydropathy scale32. A constant value was added to each hydrophobicity, to bring them into positive range. All values were then multiplied by the same constant factor, so that final range was from 0 to 90, which is suitable for RASMOL. After coloring the proteins according to the hydrophobicity of side chains, it was possible to determine the approximate position of both membrane interfaces separating the solvent from the lipid phase. Potential interface helices were also visualized with RASMOL, and identified with the STRIDE33 program for secondary structure assignment of known structures. The candidate interface helices were hand-picked according to the following criteria: 1) the center of mass distance from the membrane should not exceed 0.5 nm, 2) there should be no other polypeptide chain between an interface helix and a membrane (but transmembrane helices are regarded as the integral part of a membrane), and 3) the angle between the helix axis and membrane surface should not exceed 50 degrees. Secondary structure conformation and segment length of selected segments was in accord with the published assignment in papers where the corresponding high-resolution crystal structures first appeared. We found 50% of selected interface helices in two related photosynthetic reaction center complexes from bacteria. These interface helices are helices cd (149-165) and e (258-268) from subunit L of Rhodobacter sphaeroides , helices cd (152-162) and ect (259-267) from subunit L of Rhodobacter viridis, helices ab (81-89), cd (178-194) and e (293-302) from subunit M of Rhodobacter sphaeroides, and helices ab (81-87), cd (179-190), de' (232-237) and ect (292-298) from subunit M of Rhodobacter viridis. Remaining interface helices are helix D (201-210) of plant lightharvesting complex, helix 39-46 of lightharvesting protein from Rhodopseudomonas acidophila, helices 1-7 and 361-367 from the subunit I, helix 112-125 from subunit IV, and helix 5-13 from the subunit VIIa of the mitochondrial cytochrome c oxidase, helices a (11-20), ab (64-71), cd1 (138-147), and cd2 (156-166) from cytochrome b, and helix 4-15 of subunit 10, also from the bovine mitochondrial bc1 complex. The SPLIT 3.5 Algorithm The definition of preference functions and the training part of the procedure leading to extraction of preference functions has been described before9,10. It will be only briefly outlined here. The training dataset of 100 non-homologous membrane and soluble proteins contained incompletely known membrane proteins non-homologous to the testing dataset of membrane proteins9. For each amino acid residue, in each sequence, its type, secondary structure and sequence environment were collected. Sequence environment of a residue was calculated as an average of five left and five right attributes (such as hydrophobicity) of its neighbors. Histograms of sequence environments for all residues were approximated with Gaussian functions. Conformational preference function for the conformation 'j' of the amino acid type 'i' found within sequence environments X was then defined as: (N/Nj)(Ni j/i j)exp[-(X-i j)2/22i j] Pi j(X) = --------------------------------------- (1) ((Ni k/i k)exp[-(X-i k)2/22i k] k where Nj /N is the fraction of conformation 'j' in the protein dataset, Ni j is the number of amino acids found in each conformation, i j is the average and i j is the sample standard deviation of parameters X. The SPLIT 3.5 algorithm11 consists of transforming, predicting, filtering and refining modules. By means of preference functions, it first transforms the input choice of amino acid parameters into sequence dependent conformational preferences. A total of 88 scales of amino acid attributes is available on the server's home page with relevant references. Some of these scales are for 20 constant conformational preferences, but in the following text, whenever preferences are mentioned, it is assumed that these values are already transformed sequence dependent preferences. The predictor part of the algorithm compares preferences for -helix, -sheet, turn and undefined conformation at each sequence position and assigns the appropriate secondary structure to the highest preference. Predicted TMH segments are result of the filtering procedure, which rejects too short and splits too long predicted helical segments. Other conformational profiles are also used to refine the prediction. Ends of observed TMH are often associated with raising -sheet and turn preferences. SPLIT extends predicted TMH span when the sum of alpha and beta preferences is high (>2.0), and stops the extension when a high turn preference (>1.3) is encountered. High hydrophobic moments34 are often encountered at TMH termini. Hydrophobic moments are calculated at each sequence position i and for each twist angle in the range from 80 to 180 degrees. Hydrophobic moment index, defined as five times hydrophobic moment, is reported for two standard conformations: -helix with 100 degrees twist angle, and -sheet with 180 degree twist angle. The hydrophobic moment function I(k,i) is defined as in our recent publication11: I(k,i) = 6(k,i)exp(-((i)max-(k,i))2 )exp(-((k)opt-(k,i))2 ) (2) where (k,i)max and (k)opt are the maximal hydrophobic moment and the corresponding optimal twist angle respectively, while (k,i) and (k,i) are the hydrophobic moment for standard 'k' conformation and the corresponding twist angle, respectively. In the profiles of I(k) values, produced by the server in the numerical output, average of three values is associated with the central residue in the triplet and denoted as the hydrophobic moment threshold index I3(k). For I3(k) > 2.0 at TMH termini, the predicted TMH span is also extended. When I3(k) is very high (> 3.5) in the middle of the predicted span, the potential TMH segment is reexamined for the maximal height of -helix preferences, and rejected if such maximum is less than 2.6. An extra scale input option enables the predictor to use Richardson's middle helix preferences35 and the corresponding preference functions, extracted from the database of soluble proteins11, for the prediction of interface and extramembrane helices. Sequence dependent Richardson's preferences are denoted as free helix preferences, and are utilized too to extend the TMH span when high enough (>1.3). The prediction accuracy parameter ATM for residues in the TMH structure takes into account the overpredicted oTM, underpredicted uTM and observed number NTM of residues found in the TMH structure: ATM = ( NTM - oTM - uTM )/NTM ( 3 ) Per-segment prediction accuracy is also estimated by using equation (3) when the number of overpredicted and underpredicted TMH segments is known. Interface helices (see above) were considered as predicted when the hydrophobic moment index or the hydrophobic moment threshold index had their maximum equal or higher than 2.0 anywhere along the span of observed interface helical segment. Positive correct prediction of interface helices with Richardson preferences occurred when maximum equal or higher than 0.9 was found inside such observed segments. Correct prediction of -strand segment was scored when corresponding preference maximum equal or greater than the threshold value of 1.4 was found along the span of observed -strand. The product of transmembrane helix preferences and turn preferences had to be higher than 2.0 to indicate the sequence position of helical ends for helices entering or exiting from the membrane. The SPLIT Web Server The original prediction programs9-11, written in FORTRAN 77, were wrapped into modular web server, written in HTML, ANSI C and unix script language. An independent and portable graphics library was created to enable the graphical presentation of the results. The only required input is the protein sequence. Server's speed (predicted conformational profiles are received in seconds) and versatility (many different hydrophobicity scales36 can be used to calculate hydrophobic moment34 and preference profiles) allows easy computer experiments in predicting the secondary structure. The server is accessible at: http://pref.etfos.hr/split Recommended Amino Acid Attribute Scales and Conformational profiles The default choice of scales for operating the server are the Kyte-Doolittle hydropathy scale32 for calculating conformational preference profiles and the Eisenberg consensus hydrophobicity scale37 for calculating hydrophobic moments. The same two lists of 88 scales are avilable for the calculation of preferences and for the calculation of hydrophobic moments, but the rank orders of the scales differ. The default choice of scale is at the top position for each of the two lists. If not specified otherwise, all results presented in this paper have been obtained with the SPLIT 3.5 algorithm version and the above mentioned default choice of amino acid attributes. Notice, however, that the default choice of scales is the most common choice, but not the best choice. For instance, Edelman's scale38 for calculating conformational preferences11 and Cornette's PRIFT scale36 for calculating hydrophobic moments may be used to improve the predictor's performance. All scales except default scales are listed from the top position according to their performance in predicting membrane-spanning segments (first list) and in predicting the sequence location of amphipathic interface helices. An extra scale option (the Richardson scale)35 can be chosen as the third choice of scales when one wishes to predict the sequence location of interface and extramembrane helices as well as to improve the prediction accuracy for the termini of membrane-spanning helices. Correlation between any two scales can be quickly determined by using the SCACOR routine of the server. A total of 13 different conformational profiles is available in the Numeric Data Output of the server. Their meaning is described in the SPLIT35 - Output Description. In addition to three plotted profiles, relevant profiles for the present work can be found as columns 10 (membrane-buried helix times turn preference), 11 to 14 (hydrophobic moment and hydrophobic moment index), and 17 as the last column (Richardson preferences for "free" -helix when extra scale option is used). RESULTS The Performance Tests on Membrane Spanning Helices in Integral Membrane Polypeptides of Known Structure. All of the 100 observed sequence locations for transmembrane helices (Methods) are associated with -helix preference maximums. Maximums in the TMH preferences range from 4.75 to 2.40, while maximums in the free helix preferences (Richardson preferences) range from 2.69 to 1.01. Most of TMH preference profiles have only one clear maximum, while free helix preference profiles often exhibit more than one maximum in the sequence region where TMH is observed. Overall per-residue prediction accuracy is clearly improved when both kind of preference profiles are used in the SPLIT predictor. As measured by our accuracy parameter ATM (Methods) the performance increases from 0.69 (when only the Kyte-Doolittle scale is used) to 0.73 (when Richardson's scale is used as an extra scale too), and to 0.77 (when Edelman's scale is used in combination with the Richardson's scale). The corresponding percentage of correctly predicted TMH residues raises from 76 to 83 and to 85%. Increased per-residue prediction accuracy is gained due to better balance between underpredicted and overpredicted residues. Per-segment prediction accuracy (Eq. 3) is high (0.96) for the default choice of amino acid attributes including Richardson preferences, because only one out of 100 TMH is underpredicted and three TMH are overpredicted. For instance, one TMH is ovepredicted, while another is underpredicted in the Rieske protein11. Overpredicted TMH in the Rieske protein is the only example when corresponding free helix maximum could not be found in the predicted TMH region. Overpredicted TMH in the cytochrome b corresponds to the sequence location of two surface attached amphipathic helices cd1 and cd2. It is rejected as a TMH by the SPLIT algorithm when the PRIFT scale35 is used (instead of Eisenberg's consensus hydrophobicity scale37) to calculate the profile of hydrophobic moments. Another overpredicted TMH in the bovine cytochrome oxidase subunit 1 is not associated with the maximum for membrane-buried helix within the middle region of the preference profile. It is also of interest to test separately bacteriorhodopsin, glycophorin A, bacterial potassium channel and ATP synthase subunit c, because detailed structural knowledge for these polypeptides was not available to us when the SPLIT 3.5 predictor was constructed9-11. All 12 of observed TMH from these four polypeptides are correctly predicted with no overpredictions. Out of 305 amino acid residues observed in the TMH conformation only 19 are underpredicted and 32 are overpredicted with the default scale choice (including Richardson s scale), so that the accuracy parameter is very high ATM = 0.833. Interface Helices Interface residues in the -helix configuration are often found at the N or C terminus of membrane spanning helices. Since such segments are often amphipathic, the calculation of hydrophobic moments may be used to achieve a modest increase in the accuracy of TMH prediction11. As expected, the TMH prediction accuracy, reported in the 4-th column of the B part in the Table I, does not vary much when different amino acid attributes are used for the calculation of hydrophobic moments. The best result is achieved with the # 59 scale that we introduced in an earlier work39 . When interface helices are not fused with membrane-spanning helices it is still of interest to predict their sequence location. A standard set of 22 interface helices is collected from known structures of 31 integral membrane polypeptides (see Methods). This database of helices, oriented approximately parallel and positioned very close to inner or outer membrane surface, is used to test the performance of different conformational indexes. Since amphipathicity is commonly used for such a purpose we first created the predictor for amphipathic segments and compared the performance of all 88 amino acid attribute scales available on the server. Our index I3(), which locates sequence segments with optimal hydrophobic moments11, has a better performance than the hydrophobic moment index itself in finding the interface helices for 56 different cases (scales). It gives the same result for 24 scales, and is worse for 8 scales. In all but one of 43 cases (scales) with best performance our index I3() performes as well or better than hydrophobic moment (Table I). As the predictor for sequence location of interface helices by means of I3() and/or hydrophobic moment, the Eisenberg consensus hydrophobicity scale37 comes only 25-th in the rank order of performance. All interface helices are predicted when all 88 scales are considered, but no scale predicts more than 14 out of 22 helices. Two interface helices from the bovine cytochrome oxidase subunit I are predicted only by the Kuhn & Leigh membrane propensity scale (# 43 scale). All of 22 interface helices are associated with the maximum in Richardson's -helix preferences. However, the predictor based on Richardson preference functions (see Methods) does not see short interface helix ab in the cytochrome b of bovine bc1 complex. It also does not predict short interface helix 361-367 in the subunit I of the cytochrome c oxidase from bovine heart. Reasons for these underpredictions differ. In the case of cytochrome b, the maximum in Richardson s preferences along -helix strech 64-71 is slightly smaller than chosen threshold value of 0.90. In the case of subunit I, the TMH predictor used Richardson s preferences to extend the N-terminal region of predicted TMH so that interface helix 361-367 is fused with TMH. The existence of the maximum in Richardson preferences greater than 0.9 did not help, because TMH prediction by the SPLIT predictor takes precedence. In any case, a positive correct prediction is achieved for 20 interface helices when the predictor based on Richardson s preference functions is used to locate sequence position of interface helices. Table I Prediction of the sequence position for 22 interface helices. Each row in Table I represents one computer experiment with our SPLIT predictor applied to 31 integral membrane polypeptides. Interface helices are predicted with Richardson s preference functions in section A. Values higher than the threshold value of 2.0 for the hydrophobic moment index (H.M.) and for the hydrophobic moment threshold index I3() are used to predict the sequence position of interface helices in section B, and the best 43 amino acid scales are selected among 88 available scales. The Kyte-Doolittle preference functions and Richardson preference functions are applied in each case to predict the sequence position of transmembrane helices as well. The prediction accuracy for the TMH residues is given in the fourth column as the ATM parameter (Eq. 3). ------------------------------------------------------------------------------------------------------------------ SCALES # helices performance AMINO ACID SCALE RANK detected in TMH ORDER prediction CODE / NAME ------------------------------------------------------------------------------------------------------------------ A) 20 (60) RICH, Richardson preferences ------------------------------------------------------------------------------------------------------------------ B) I3() H.M. ATM ------------------------------------------------------------------------------------------------------------------ 1 14 12 0.737 (17) PONG1, Ponnuswamy hydrophobicity 2 14 9 0.724 (69) MATPO, mean rms fluctational disp. F1 3 13 13 0.737 (27) PRIFT, optimal amphipathic helices 4 13 13 0.725 (79) MARTI, single TMH preferences 5 13 13 0.718 (43) KUHLE, Kuhn membrane propensity 6 13 11 0.737 (66) CHOU6, helix preferences / prot. 7 13 7 0.736 (15) CIDA+ , hydrophobicity scale + prot. 8 12 12 0.735 (44) DEBER, M/A ratio in membrane prot. 9 12 12 0.725 (52) EDE25, Edelman optimal predictors 10 12 12 0.725 (41) ZAMYA, increase in volume of water 11 12 11 0.729 ( 3) PONNU, Ponnuswamy hydrophobicity 12 12 11 0.725 (51) EDE31, Edelman optimal predictors 13 12 10 0.732 (32) SWEET, optimal matching hydrop. scale 14 12 10 0.725 (07) GUY-M, average of 4 hydroph. scales 15 12 10 0.723 (22) WOLFE, Wolfeden hydrophobicity scale ------------------------------------------------------------------------------------------------------------------ TABLE I - cont. ------------------------------------------------------------------------------------------------------------------ SCALES # helices performance AMINO ACID SCALE RANK detected in TMH ORDER prediction CODE / NAME ------------------------------------------------------------------------------------------------------------------ B) I3() H.M. ATM ------------------------------------------------------------------------------------------------------------------ 16 12 9 0.735 (42) MIJER, average contact energy 17 12 9 0.734 ( 6) JONES, Jones hydrophobicity scale 18 12 8 0.727 (11) LEVIT, Levitt hydrophobicity scale 19 12 8 0.724 (31) GUYFE, Guy transfer free energy in prot. 20 12 7 0.735 (16) CIDAB, CID hydrophobicity / prot. 21 11 12 0.735 (39) MEIRO, C distance to protein center 22 11 11 0.738 (85) OSMP1, optimal scale for 1 TMH prot. 23 11 11 0.725 (53) EDE21, Edelman optimal predictors 24 11 10 0.727 (35) NNEIG, Cornette eigenvalues 25 11 9 0.731 (26) EISEN, Eisenberg consensus hydrophob. 26 11 9 0.729 (56) FASMB, Chou&Fasman preferences 27 11 9 0.726 (21) ROSEM, Roseman hydrophobicity scale 28 11 9 0.724 (71) GRANT, Grantham polarity values 29 11 9 0.723 (20) KIDER, hydrophobicity related scale 30 11 8 0.732 (12) GIBRA, hydrophobicity of aa in proteins 31 11 8 0.729 ( 9) VHEBL, coil to helix in membrane scale 32 11 8 0.726 (45) WERSC, Scheraga ratio of in/out 33 11 7 0.723 (70) WOESE, Woese polarity scale 34 11 7 0.725 ( 2) FAUPL, Fauchere & Pliska hydrophob. 35 11 7 0.725 (28) HOPPW, antigenic determinant scale 36 10 10 0.725 (54) EDE15, Edelman optimal predictors 37 10 9 0.743 (59) JURET, Chou-Fasman values ( + )/2 38 10 8 0.730 (83) MODKD, modified Kyte-Doolittle scale 39 10 8 0.730 (84) MDK4, modified Kyte-Doolittle scale 40 10 8 0.723 (30) ROSEF, mean fractional area loss 41 9 9 0.726 (86) OSMP2, optimal scale for > 1 TMH prot. 42 9 8 0.730 (80) MDK0, Modified Kyte-Doolittle scale 43 9 7 0.718 (87) JACWH2, Jacob & White IFH (0.5) scale ------------------------------------------------------------------------------------------------------------------ Recognition of Other Structural Motifs in Membrane Proteins  Figure 1. Sequence profile of membrane-buried helix preferences (dashed line) and membrane-buried helix times turn preferences (full line) for human potassium channel cik1. Edelman's scale38 was used as the input for calculating these preferences, while Richardson scale35 and corresponding preference functions extracted from soluble proteins was used to refine the digital prediction for the sequence location of transmembrane helices (bold line). Functionally most important segments are the membrane-spanning mobile voltage sensor S4 and the pore segment P thought to contain the pore helix and the selectivity filter. Other types of conformational index profiles produced by the SPLIT algorithm are also useful. For instance, the voltage sensor elements of voltage gated channels40 are associated with a very high maximum in the conformational index profile for the product of membrane-buried -helix preference and turn preference (Figure 1). This index is, as a rule, high at sequence regions known to be close to the ends of membrane-spanning helices. For bitopic membrane proteins (with only one TMH), the doublet of maximums in this index is found such that the characteristic membrane spanning -helix segment of approximately 20 residues separates these maximums (Figure 2). Is sequence location of such maximums always pointing to amino acid residues in the twilight zone of the interface regions (Figure 1 and 2), where relative dielectric constant must change from the value of 2-3 (nonpolar membrane interior) to 80 (water)? The dataset of interface helices described above is convenient to test the predictor based on this index. Seven out of 22 interface helices can be located in the sequence with this predictor when Kyte-Doolittle preference functions are used. This is not impressive result except for the fact that three of seven correctly predicted interface helices are very hard to predict with hydrophobic moments (helix 81-89 from the M subunit of photosynthetic reaction center from R. sphaeroides, and helices 1-7 and 361-367 from the subunit I of bovine heart mitochondria cytochrome oxidase).  Figure 2. Sequence profile of membrane-buried helix preferences (dashed line with open circles) and membrane-buried helix times turn preferences (full line) for human granulocyte-macrophage colony stimulating factor (receptor). The Kyte-Doolittle preference functions have been used. Predicted transmembrane helix from amino acid 301 to 324 (bold line) agrees with the Swiss-Prot assignment 299-324 for the mature receptor. Sequence location of helix times turn preference maximums alongside the span of potential membrane-spanning helix corresponds to interface regions where N and C helix termini are breaking through the lipid phase. Another class of polypeptides - membrane active peptides, forming the amphipathic -helix when attached to membrane surface, have mainly interface seeking residues. Conformational profiles for synthetic antimicrobial peptide PGYa41 exhibit a symmetric secondary structure with both peptide termini having high preference for a membrane-buried helix, while its middle region is likely to be associated with an interface seeking amphipathic -helix (Figure 3). Our threshold index I3() and hydrophobic moment index provide in this case similar information about possible sequence location of the amphipathic -helix. The choice of the amino acid attribute scale for the calculation of hydrophobic moments dictates how high maximums will be found. Maximal hydrophobic moment index of 4.8 at the sequence position 8 (Figure 3) decreases to 4.0 at the sequence position 15, when Cornette's PRIFT scale36 is used to calculate hydrophobic moments. Just the opposite happens with hemolytic peptide melittin where maximal hydrophobic moment of 2.9 at the sequence position 17 increases to 3.8 at the position 11 when the PRIFT scale is used. Preferences for a membrane-buried helix are sufficiently high in the N-terminal part of melittin sequence (Figure 4) for the region to be predicted as the TMH. On another hand, preferences for membrane-buried helix are quite low for the middle region of many antimicrobial peptides (only the example of PGYa is shown in the Figure 3). This is not so for free -helix preferences as calculated with the help of Richardson's preference functions. For instance, these preferences have high values ranging from 1.59 to 3.03 and from 2.23 to 2.88 in the case of PGLa42 and KLA743 antimicrobial peptides, respectively. Figure 3. Conformational index profiles for the designed peptide PGYa41 are for membrane-buried helix propensity (bold full line with open circles), the hydrophobic moment index for amhipathic -helix (full thin line), our threshold index I3() for amphipathic -helix (dashed line), and for Richardson's preferences for the free helix conformation (full thin line with stars). To answer the question how accurate is the present version of the SPLIT predictor in predicting -strands in membrane proteins, we tested the photosynthetic reaction center and porin by using the Kyte-Doolittle preference functions. The percentage of correctly predicted -strands is similar: 78% in photosynthetic reaction center polypeptides and 75% in the porin44. However, the number of overpredicted -strands (a total of 36) was considerably higher than the number of observed (18) and of correctly predicted (14) strands in the photosynthetic reaction center.  Figure 4. Conformational index profiles for the hemolytic protein melittin. The meaning of profile lines is the same as in the Figure 3. Predicted span of transmembrane helix is denoted with the bold line at the 1.0 level. Observed helices are labeled with the dashed line at the 0.5 level. Hence, our accuracy parameter (Eq. 3) was considerably lower for the reaction center (-1.0) than for the porin (0.625), where 12 out of 16 membrane-spanning strands are correctly predicted, 4 strands are underpredicted and 2 strands are overpredicted. For recently solved structure of the outer membrane protein A transmembrane domain45, six out of eight membrane-spanning strands are predicted at their correct sequence locations (Figure 5).  Figure 5. The preference profiles for the outer membrane protein A transmembrane domain. Generally higher -strand preferences (full bold line) than preferences for membrane-buried -helix conformation (dashed line with open circles) predict dominant -sheet structure for this domain. Horizontal lines at the level 0.5 and 1.2 denote the position of observed transmembrane -strands (dashed line) and predicted -strands (full bold line) respectively. In the case of Rieske protein (Figure 6), very high maximums in the turn preference, in the hydrophobic moment for assumed -sheet conformation and in the threshold index for optimal amphipathic -strand conformation are all achieved at the Ile 74, which is considered to be the pivot point for the movement of the soluble part of the Rieske sequence26. The second highest peak in the preferences for membrane-buried helix (at Thr 43) is flanked on both ends (at the Phe 35 and at the Val 59) with high values for our threshold index for the -helix hydrophobic moment (not shown). Richardson's preferences have maximums at Ala 51 and Val 68, inside and close to the C-terminus of observed TMH segment, respectively, but not anywhere in the sequence region 131-148 with false positive TMH prediction. The maximum at Val 68 points at the short helix from Ala 66 to Met 71. Another sequence region 103-115 with high values in Richardson's preferences (>1.4) points to helices Lys 103 to Ala 110, and Val 114 to Gln 116.  Figure 6. Conformational profiles for mature Rieske protein. Observed TMH (dashed line up to the 0.5 level) is the segment from amino acid 25 to 62, while predicted TMH (bold line at the level 1.0) is the segment from amino acid 131 to 148. Observed TMH is associated with the highest peak (full bold line) in the product of preferences for the membrane-buried helix (the Kyte-Doolittle scale input) and for free helix conformation (the Richardson's scale input). The TMH preferences alone (dashed line with open circles) are highest at the sequence positions (131-148) where hydrophobic -sheet is known to envelop the iron-sulfur cluster24-27. Richardson's preferences (full thin line) do not have a maximum associated with the predicted TMH. The pivot point at Ile 7426 for the rotation of functional domain of Rieske protein is seen as the maximum in our threshold index for -strand hydrophobic moment (dotted line profile produced with the PRIFT scale36 input). Topology Prediction With the default choice of scales we correctly predict N-terminus orientation for 26 out of 31 polypeptides with a simple version of the positive-inside rule algorithm4,11. Cases with the charge bias of zero (five such cases are found) are interpreted to mean inside orientation of the N-terminus. Since we have a biased sample - only 9 out of 31 polypeptides are observed with outside orientation of their N-terminus, our error rate in predicting N-terminus orientation would increase if the charge bias of zero is interpreted as the outside orientation. Change in the charge bias when different hydrophobicity scale is used can help to determine correct transmembrane topology. For instance, by using the PRIFT scale36 to calculate hydrophobic moments a charge bias of +4 is found for the cytochrome b (it is the charge bias of zero with the default choice of scales) and correct topology of eight transmembrane helices instead of nine. DISCUSSION The presented results indicate what would be the most practical approach to the sequence analysis of membrane proteins by means of preference functions. Success of preference functions in predicting the formation of -helices must be due to the predominant influence of local interactions. With the default choice of scales, including Richardson's preferences, all of the 100 observed TMH are associated both with an easily selected high TMH preference maximum and with a maximum (often two maximums) for free -helix preferences, while overpredicted TMH lack either one or the other of these maximums. To avoid underpredictions of transmembrane segments it is best to use the Kyte-Doolittle hydropathy scale32 and the corresponding preference functions. Edelman's optimal predictor scale38 and the corresponding preference functions increase the per-residue prediction accuracy by avoiding underprediction of residues observed in the transmembrane helix configuration. Richardson's -helix preferences35 and the corresponding preference functions for soluble proteins are good additional tool for predicting all -helices (transmembrane and extramembrane) longer than 5 residues. It is obvious that even in the case of easily predicted membrane-spanning helices, the single amino acid attribute scale is not sufficient. Tests with several different hydrophobicity scales are recommended for each tested sequence. All of the potential transmembrane helical segments can be easily classified as stable (appearing in almost all runs) and unstable (appearing only with the certain choice of hydrophobicity scale). When different results for segment prediction are obtained with several of the best scales, it is advisable to use evolutionary information if available (related homologous sequences), positive inside rule scoring for different topologies4 and complete information available in the output data file of the SPLIT predictor. Such a procedure would reduce the subjectivity in the choice of different decision (threshold) parameters. A similar conclusion holds for predicting the sequence location of interface residues. Several different conformational index profiles in the SPLIT numerical output can be used to create the predictor for the sequence location of such residues in the -helix conformation. Prediction of interface residues protruding through the membrane surface as the N- or C-terminus of longer membrane-spanning helices is possible by appropriate use of preference functions (see Figures 1 and 2). Prediction of the sequence location of interface helices lying parallel to the membrane surface can be tested when such helices are collected from known crystal structures of membrane proteins. For the dataset of such helices, it is of interest to compare older methods using hydrophobic moments34 with our own hydrophobic moment threshold functions11, and with preference functions method (Table I). The results in the Table I show that: a) Several of the best scales for calculating hydrophobic moments should be used and the results compared because even the best scales are missing about one third of observed interface helices. Widely used Eisenberg's scale37 is able to detect the sequence location of only one half of observed interface helices (Table I). b) Our hydrophobic moment threshold index I3() can be used as an equal or better tool than hydrophobic moment for the detection of interface helices. c) Richardson s preference functions extracted from soluble proteins are a better tool for detecting the sequence location of interface helices than hydrophobic moments. The need to go beyond calculations of the mean hydrophobicity with the Kyte-Doolittle hydropathy values32 and of the hydrophobic moment with the Eisenberg hydrophobicity values37 has been also pointed out by other authors46-48. These traditional tools for the classification and prediction of membrane-buried, interface and membrane active helices are extended and supplemented in this work with calculations of conformational preference profiles and hydrophobic moment functions based on several different amino acid attributes. We have judged the performance in predicting sequence location of interface helices in the terms of the percentage of correct predictions. However, it is easy to increase the percentage of correct prediction, for instance by lowering the threshold value. Then, overpredictions are increased and more meaningful performance parameters, such as the ATM (Eq 3), can actually decrease. Overpredictions in the case of interface helices can be due to predictions of extramembrane helices that are not included into our dataset of interface helices, or can be due to completely wrong predictions of helices where none is found. In the case of the best known crystal structures of photosynthetic reaction center from R. viridis and R. sphaeroides, Richardson's preference functions are predicting larger number of extramembrane helices, where none exist in the sequence (14 overpredictions), than the best scales used for the hydrophobic moments calculations in the Table I (the predictor with the PRIFT scale has 8 overpredictions in the photosynthetic reaction center). Richardson's preference functions can detect almost all -helix segments in membrane proteins, but these functions are not specific detectors of interface helices, and in proteins with predominant -sheet structure can often cause overpredictions of -helices. Another class of interface helices appears in antibacterial peptides. Antimicrobial peptides are promising therapeutic agents with very low potential to induce antibiotic resistance49, but the problem of their low selectivity in interaction with membranes50 is still restricting their use. Here, we illustrate the usefulness of combining several conformational index profiles offered by our algorithm to attack the specificity problem by designing novel peptides. Conformational profiles, such as presented in Figure 3, indicate that common motifs in such profiles may exist that are sufficiently different from motifs found in hemolytic peptides (Figure 4) to guide the design and synthesis of peptide antibiotics. Comparison of Figure 3 profiles with conformational profiles associated with transmembrane helices reveals that the buried helix profile and hydrophobic moment profiles are inverted in the Figure 3. Maximal values for hydrophobic moment profiles are in the middle of the antibacterial sequence and maximal TMH preferences are at its N- and C-terminus. Very low preference for buried-helix conformation associated with middle sequence region probably ensures low hemolytic activity of these cationic peptides unless a high membrane potential and high concentration of negative surface charges are encountered. Such conditions are characteristic of the bacterial plasma-membrane and presumably enable selective entrance and perpendicular orientation of amphipathic monomers with respect to membrane surface. For some critical concentration, spontaneous aggregation of peptide monomers is expected to cause formation of a water filled pore encircled with peptide polar faces. Concerning topology prediction, we did not take into account that some classes of membrane proteins do not follow the 'positive inside rule' 51 and that this rule should be applied to 2n topologies arising when n questionable TMH segments are identified4. Nevertheless, with the present SPLIT version, the topology prediction of known membrane polypeptides is comparable in performance11 to the Rost PHDhtm algorithm52 or to the Jones MEMSAT algorithm5. Our default choice of amino acid scales and preference functions does not wrongly predict transmembrane helices in beta-class membrane proteins such as porins (Figure 5). However, porins are not predicted as membrane proteins and no high accuracy prediction of sequence location for transmembrane beta strands was achieved. Better prediction of the porins secondary structure remains our goal for future improvement of the server SPLIT services. Although the use of -helix preferences extracted from soluble proteins may seem out of place in the case of membrane proteins, the example of Rieske protein (Figure 6) and our present and earlier results11,12 illustrate how TMH prediction can be improved when such preference functions are used. The conformational index, calculated as the product of TMH preferences and Richardson's preferences, exhibits higher and lower values with respect to TMH preferences exactly at the Rieske sequence regions associated, respectively, with TMH underprediction and TMH overprediction. Free helices predicted in soluble and membrane proteins with Richardson s preferences are of interest as possible initiation sites of protein folding, because -helices may function as independent "seeds for folding"53. ACKNOWLEDGEMENTS We are grateful to Bono Lu i of the Ruer Boakovi Institute in Zagreb, who helped us with some references. This work was supported by the Croatian Ministry of Science Grant 177060 to D.J. REFERENCES J. Enriquez, Science 281 (1998) 925-926. D. T. Jones, FEBS Lett. 423 (1998) 281-285. A. C. W. May and T. L. Blundell, Curr. Opin. Biotech. 5 (1994) 355-360. G. von Heijne, J. Mol. Biol. 225 (1992) 487-494. D. T. Jones, W. R. Taylor and J. M. Thornton, Biochemistry 33 (1994) 3038-3049. B. Persson and P. Argos, J. Mol. Biol. 237 (1994) 182-192. B. Rost, R. Casadio, P. Fariselli and C. Sander, Protein Science 4 (1995) 521-533. B. Rost, P. Fariselli and R. Casadio, Protein Science 5 (1996) 1704-1718. D. Jureti, B. Lu i, D. Zuci and N. Trinajsti, Protein transmembrane structure: recognition and prediction by using hydrophobicity scales through preference functions, in: C. Parkanyi (Ed.), Theoretical and Computational Chemistry, Vol 5. Elsevier Science, Amsterdam, 1998, pp. 405-445. D. Jureti, D. Zuci, B. Lu i and N. Trinajsti, Computers Chem. 22 (1998) 279-294. D. Jureti and A. Lu in, Journal of Chemical Information and Computer Sciences 38 (1998) 575-585. D. Jureti, B. K. Lee, N. Trinajsti and R. W. Williams, Biopolymers 33 (1993) 255-273. J. Deisenhofer, O. Epp, K. Miki, R. Huber and H. Michel, Nature 318 (1985) 618-624. J. Deisenhofer, O. Epp, I. Sinning and H. Michel, J. Mol. Biol. 246 (1995) 429-457. J. P. Allen, G. Feher, T. O. Yeates, H. Komiya and D. C. Rees, Proc. Natl. Acad. Sci. USA 84 (1987) 6162-6166. G. McDermott, S. M. Prince, A. A. Freer, A. M. Hawthornthwaite-Lawless, M. Z. Papiz, R. J. Cogdell and N. W. Isaacs, Nature 374 (1995) 517-521. S. M. Prince , M. Z. Papiz , A. A. Freer , G. McDermott , A. M. Hawthornthwaite Lawless, R. J. Cogdell and N. W. Isaacs, J. Mol. Biol. 268 (1997) 412423. W. Khlbrandt, D. N. Wang and Y. Fujiyoshi, Nature 367 (1994) 614-621. S. Iwata, C. Ostermeier, B. Ludwig and H. Michel, Nature 376 (1995) 660-668. T. Tsukihara, H. Aoyama, E. Yamashita, T. Tomizaki, H. Yamaguchi, K. Shinzawa-Itoh, R. Nakashima, R. Yaono and S. Yoshikawa, Science 272 (1996) 1136-1144. R. Henderson, J. M. Baldwin, T. A. Ceska, F. Zemlin, E. Beckmann and K. H. Downing, J. Mol. Biol. 213 (1990) 899-920. E. Pebay-Peyroula, G. Rummel, J. P. Rosenbusch and E. M. Landau, Science 277 (1997) 1676-1681. H. Luecke, H. T. Richter and J. K. Lanyi, Science 280 (1998) 1934-1937. S. Iwata, M. Saznovits, T. A. Link and H. Michel Structure 4 (1996) 567-579. D. Xia, C. A. Yu, H. Kim, J. Z. Xia, A. M. Kachurin, L. Zhang, L. Yu and J. Deisenhofer, Science 277 (1997) 60-66. Z. Zhang, L. Huang, V. M. Shulmeister, Y. I. Chi, K. K. Kim, L. W. Hung, A. R. Crofts, E. A. Berry and S. H. Kim, Nature 392 (1998) 677-684. S. Iwata, J. W. Lee, K. Okada, J. K. Lee, M. Iwata, B. Rasmussen, T. A. Link, S. Ramaswamy and B. K. Jap, Science 281 (1998) 64-71. K. R. MacKenzie, J. H. Prestegar and, D. M. Engelman, Science 276 (1997) 131133. D. A. Doyle, J. M. Cabral, R. A. Pfuetzner, A. Kuo, J. M. Gulbis, S. L. Cohen, B. T. Chait and R. MacKinnon, Science 280 (1998) 69-77. M. E. Girvin, V. K. Rastogi, F. Abildgaard, J. L. Markley and R. H. Fillingame, Biochemistry 37 (1998) 88178824 L. A. Sayle and E. J. Milnerwhite, Trends in Biochemical Sciences 20 (1995) 374-376. J. Kyte and R. F. Doolittle, J. Mol. Biol. 157 (1982) 105-132. D. Frishman and P. Argos, Proteins 23 (1995) 566-579. D. Eisenberg, E. Schwarz, M. Komaromy and R. Wall, J. Mol. Biol. 179 (1984) 125-142. J. S. Richardson and D. C. Richardson, Science 240 (1988) 16481652. J. L. Cornette, K. B. Cease, H. Margalit, J. L. Spouge, J. A. Berzofsky and C. DeLisi, J. Mol. Biol. 195 (1987) 659-685. D. Eisenberg, R. M. Weiss, T. C. Terwilliger and W. Wilcox, Faraday Symp. Chem.Soc. 17 (1982) 109-120. J. Edelman, J. Mol. Biol. 232 (1993) 165-191. D. Jureti, N. Trinajsti and B. Lu i, J. Math. Chem. 14 (1993) 35-45. W. Catterall, Annu. Rev. Biochem. 64 (1995) 493-531. A. Tossi, C. Tarantino and D. Romeo, Eur. J. Biochem. 250 (1997) 540-558. W. L. Maloy and U. P. Kari, Biopolymers 37 (1995) 105-122. M. Dathe, T. Wieprecht, H. Nikolenko, L. Handel, W. L. Maloy, D. L. MacDonald, M. Beyermann and M. Bienert, FEBS Lett. 403 (1997) 208-212. M. S. Weiss and G. E. Schulz, J. Mol. Biol. 227 (1992) 493-509. A. Pautsch and G. E. Schulz, Nature structural biology 5 (1998) 1013-1017. R. Brasseur, J. Biol. Chem. 266 (1991) 16120-16127. M. G. Roberts, D. A. Phoenix and A. R. Pewsey, Comput. Appl. Biosci. 13 (1997) 99-106. D. A. Phoenix, A. Stanworth and F. Harris, Biologicheskie Membrany 15 (1998) 83-89. G. Saberwal and R. Nagaraj, Biochim. Biophys. Acta 1197 (1994) 109-131. T. Wieprecht, M. Dathe, M. Beyermann, E. Krause, W. L. Maloy, D. L. MacDonald and M. Bienert, Biochemistry 36 (1997) 6124-6132. Y. Gavel and G. von Heijne, Eur. J. Biochem. 205 (1992) 1207-1215. B. Rost, R. Casadio and P. Fariselli, Refining neural network predictions for helical transmembrane proteins by dynamic programming, in: D. J. States, P. Agarwal, T. Gaasterland, L. Hunter and R. F. Smith (Eds.), Proceedings Fourth International Conference on Intelligent Systems for Molecular Bilogy, AAAI Press, Menlo Park, California, 1996, pp. 192-200. 53. L. G. Presta and G. D. Rose, Science 240 (1988) 1632-1641. SA}ETAK U radu se ispituje kvaliteta predvianja sekventne lokacije, konformacije i orijentacije membranskih polipeptida poznate kristalne strukture pomou web poslu~itelja SPLIT. Poslu~itelj SPLIT temelji se na metodi sklonosnih funkcija. Navedene funkcije slu~e za pretvorbu po etnog izbora ljestvice aminokiselinskih parametara u konformacijske sklonosti ovisne o sekventnoj okolini. Transmembranske uzvojnice to no se predviaju kada se napravi dobar izbor sklonosnih funkcija koje se pak dobivaju iz datoteke integralnih membranskih proteina. Za razliku od drugih algoritama s sli nom kvalitetom predvianja, prediktor SPLIT ne zahtijeva informacije o homologiji. Sekvencijska lokacija kraih izvanmembranskih uzvojnica takoer se mo~e nai s pomou sklonosnih funkcija odreenih na skupu topljivih proteina. Posebno, Richardsonove sklonosne funkcije bolji su prediktori od hidrofobnih momenata, ak i onda kada se radi o pogaanju sekvencijskog polo~aja uzvojnica koje le~e na povraini membrane. Internet adresa za poslu~itelj SPLIT jest: http://pref.etfos.hr/split PAGE 34  EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph   EMBED Origin50.Graph  bMdMNNNNWWWW\cchssssLtNt~}}}}}$dh$dhwwxxxy$yyy zzdzhzzzz{.{2{{{||}}ތ 4b<F|"$68dl"$HJPVZ`tz|~ jCJ$OJQJ CJOJQJ 5OJQJ56OJQJ >*OJQJ H*OJQJ 6OJQJOJQJ H*OJQJM8: ޛ <xԱ$$dh$dh›țʛ̛қԛڛ  JPNTdf~"(JLNRDL޵ 6:Ķȶ ,0J 56OJQJ 6OJQJ 5OJQJ H*OJQJ H*OJQJOJQJVDj¾JLln~RTV>@fh$dh$dh$dh"&n~RVPVlp(,$*@dfx|  > &(*0RTX> @ B H j l p $85B*5B*OJQJB*6H*OJQJ H*OJQJ 6OJQJ56OJQJ 5OJQJOJQJ H*OJQJM> $   v \  Z@B^ J$dh$dh$dhf.h: r X!Z!""#|$F%&&'Z(())*x+$x+B,--.h/40012R3445~66P7R788:8<8>8@8888==$dh$dh$8@8888888:<:::=>>HHjIlInIInN>PBP4R6RxU|U[[[[0\:\<\P\\\^^2_bbccccccehhritiviiimoou˿˧j6OJQJUhmHnHj5OJQJUhmHnH6H*OJQJ H*OJQJ H*OJQJOJQJ6H*OJQJ 5OJQJjOJQJUhmHnH 6OJQJ56OJQJB*CJ;====BjInIpIrInNpNrNtN0\2\4\6\8\:\2_4_6_cccccee$dh$dheeritixizi|i~iiiimm uuuuuuuuu u"u$u&u(u,u.u$dh$dhu(u*u.u>u0z:z8{<{|||||H~P~VlDHfjt~l>Bprx| *  ^p H*OJQJ H*OJQJOJQJ56OJQJ6H*OJQJ 5OJQJjOJQJUhmHnH 6OJQJM.u||||||PRTVlnjlZ2`>@v$dh$dhjlnpBD028:$ `$$dh$pdh$dhptz Pjlt  l248TDv468R:BZ` Xnz| ".0LZ\d4NPV  .@ 6OJQJ 5OJQJOJQJ^Z\8PR,.DF$ `$Fxz8:fhjPRlnvxPRBD $ & F `$$ `@BF*,46BDJBPRX ~ .<>D68@`b  JfhnDjlrdz||x 56OJQJ 6OJQJ 5OJQJOJQJ[02jlbd24&(*,<>>$$ `>@,..0 8ndP $& #$!dhdh$ `$Hvx|  hfnpz|0246:<j jUj> CJUVhmHnH jUj> CJUVhmHnH jUjּ> CJUVhmHnHmHnH jUOJQJ56OJQJ 5OJQJ 6OJQJOJQJ8POTPPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\ANGLES.POTPPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\ANGLES.POTPPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\ANGLES.POTPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\ANGLES.POTPPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\ANGLES.POTPPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\PRESENTATION DESIGNS\BLUSH.POTPPROGRAM FILES\MICROCPYA 4,210 #  $@X r ??0CIK1H.HT_AA. x ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@h@h@h@i@ i@@i@`i@i@i@i@i@j@ j@@j@`j@j@j@j@j@k@ k@@k@`k@k@k@k@k@l@ l@@l@`l@l@l@l@l@m@ m@@m@`m@m@m@m@m@n@ n@@n@`n@n@n@n@n@o@ o@@o@`o@o@o@o@o@p@p@ p@0p@@p@Pp@`p@pp@p@p@p@p@p@p@p@p@q@q@ q@0q@@q@Pq@`q@pq@q@q@q@q@q@q@q@q@r@r@ r@0r@@r@Pr@`r@pr@r@r@r@r@r@r@r@r@s@s@ s@0s@@s@Ps@`s@ps@s@s@s@s@s@s@s@s@t@t@ t@0t@@t@Pt@`t@pt@t@t@t@t@t@t@t@t@u@u@ u@0u@@u@Pu@`u@pu@u@u@u@u@u@u@u@u@v@v@ v@0v@@v@Pv@`v@pv@v@v@v@v@v@v@v@v@w@w@ w@0w@@w@Pw@`w@pw@w@w@w@w@w@w@w@w@x@x@ x@0x@@x@Px@`x@px@x@x@x@x@x@x@x@x@y@y@ y@0y@@y@Py@`y@py@y@y@y@y@y@y@y@y@z@z@ z@0z@@z@Pz@`z@pz@z@z@z@z@z@z@z@z@{@{@ {@0{@@{@P{@`{@p{@{@{@{@{@{@{@{@{@|@|@ |@0|@@|@P|@`|@p|@|@|@|@|@|@|@|@|@}@}@ }@0}@@}@P}@`}@p}@}@}@}@}@}@}@}@}@~@~@ ~@0~@@~@P~@`~@p~@~@~@~@~@~@~@~@~@ r !`??CIK1H.HT_S r !`??CIK1H.HT_C r !`??CIK1H.HT_D r `??CIK1H.HT_TMH x (\@= ףp=@Gz @(\@ףp= ?RQ?= ףp=?ffffff?333333?Q?)\(?{Gz?Q??{Gz?Q?Q?Q?Q?Q?Q?Q???{Gz???Q?Q?Q?Q?Q? ףp= ?Q?p= ף?= ףp=?RQ?Q?p= ף? ףp= ?(\?333333@(\?HzG?RQ?(\??{Gz?= ףp=?(\?(\?Q?(\?(\?(\?HzG?(\?= ףp=?Q?(\?q= ףp?ףp= ?{Gz?)\(?Q?p= ף?p= ף?Q?Q?? ףp= ?{Gz?Q? ףp= ? ףp= ? ףp= ? ףp= ?Q?Q?Q?Q?Q?Q??Q? ףp= ?)\(?333333?{Gz? ףp= ??Q?(\?ffffff?(\?{Gz?333333?Q??Q?{Gz? ףp= ??333333?(\?zG?zG?Q?)\(?p= ף???q= ףp?(\?Q?{Gz?(\?HzG?ףp= ?ףp= ????RQ?RQ?Q?Q?)\(?? ףp= ??{Gz?Q?Q?Q?Q?Q?Q?{Gz?{Gz?{Gz?Q?Q?Q?Q?Q?{Gz??p= ף?Q?p= ף?p= ף?Q?Q?ffffff?(\?Gz?p= ף??q= ףp?(\?(\?)\(?)\(?\(\?ffffff?RQ?ףp= @q= ףp@= ףp= @@Gz@@q= ףp@{Gz@Q@(\@(\@Gz@p= ף@Q@p= ף@Q@\(\@p= ף @ ףp= @\(\@Gz?ffffff??Q?)\(?{Gz? ףp= ?Q?Q?Q??????RQ?HzG?(\?333333?ףp= ?{Gz?q= ףp??Q?\(\??\(\?Q?Gz?{Gz??Q?HzG?q= ףp?p= ף?Gz?ףp= @HzG@zG @\(\ @ףp= @@Q@333333@RQ@(\ @\(\ @{Gz @Q@Q@q= ףp@(\@(\?Gz?)\(??)\(?333333?(\?{Gz?{Gz??zG?Gz??Q?(\?HzG?RQ@{Gz@Q@ffffff @Q @ffffff @Q @\(\ @)\(@p= ף @ @)\(@(\@(\?(\?\(\?Gz?HzG?p= ף?p= ף?? ףp= ? ףp= ?Q?Q?Q?)\(??ffffff?Q?ףp= ?ffffff?{Gz@(\@Q @ףp= @ @q= ףp @Q @@333333 @ףp= @{Gz@p= ף@ffffff@{Gz???= ףp=?HzG?(\?ףp= ?ףp= ?HzG?p= ף?Gz?= ףp=?HzG?Q?{Gz?ףp= ?ףp= ?333333?{Gz?Gz?q= ףp?{Gz??p= ף? ףp= @Q@Q @RQ@Q@= ףp=@@@ ףp= @zG@@{Gz@Gz@(\@ףp= @(\@Q @(\@{Gz@)\(@ffffff?zG?(\??(\?Q?zG? ףp= ?{Gz?(\?(\?RQ?)\(?)\(?333333?Q?(\?{Gz?Q?Gz?\(\@q= ףp@@(\@Q@{Gz@Q?(\??q= ףp?q= ףp??(\?HzG?)\(?q= ףp?RQ??zG?q= ףp?{Gz?Q?ףp= ? ףp= @Q@q= ףp @(\ @= ףp=@ffffff@(\@q= ףp@{Gz@Q@Q@zG@@Gz@Q @(\ @= ףp=@ ףp= @zG@(\??Gz?ffffff?= ףp=?HzG?Q?Gz?(\?)\(? ףp= ?Q?Q? ףp= ??)\(?333333?{Gz?RQ? ףp= ?ffffff?Gz?Q?q= ףp?q= ףp?{Gz?{Gz?Gz?(\?Q?)\(? ףp= ? ףp= ? ףp= ? ףp= ?Q?{Gz?(\?(\?(\?)\(?Q?ffffff?{Gz?ffffff?ffffff? ףp= ?ףp= ?333333?{Gz?(\?)\(?333333?{Gz?(\?{Gz?q= ףp?RQ?ףp= ?Q?{Gz?Gz?(\?Gz?RQ?ףp= ?(\???p= ף?\(\??(\?Q?HzG?zG?zG?)\(?(\?(\? ףp= ?{Gz???q= ףp?)\(?(\? ףp= ? r `??CIK1H.HT_BET r `??CIK1H.HT_TUR r `??CIK1H.HT_UND r `??CIK1H.HT_H.T r `??CIK1H.HT_MOMA r `??CIK1H.HT_MOMB r `??CIK1H.HT_INDA r `??CIK1H.HT_INDB r `??CIK1H.HT_N x 333333?Q?Q@p= ף? ףp= ? ףp= ?(\?)\(??Q?Q??Q?Q?Q?{Gz?Q?Q?{Gz?{Gz??{Gz?Q???Q?Q?Q?Q?{Gz?{Gz? ףp= ? ףp= ?ffffff?Gz?Gz??Q?(\?= ףp=@Gz@ ףp= ?zG?Gz?(\?ffffff?= ףp=?zG?(\?{Gz?{Gz?{Gz? ףp= ??333333?(\??\(\?RQ?Q?Q?p= ף? ףp= ? ףp= ?(\?333333??{Gz?Q?Q?Q? ףp= ? ףp= ?{Gz?{Gz?Q????Q??Q?Q??Q?{Gz?RQ??p= ף?q= ףp?(\?{Gz? ףp= ?(\?(\?(\?HzG?333333?{Gz?{Gz? ףp= ? ףp= ?RQ?HzG?)\(?ףp= ?)\(?ףp= ?Q?p= ף?q= ףp? ףp= ?Q?HzG?HzG?p= ף?333333?p= ף?{Gz??zG?zG?(\?)\(? ףp= ?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q?Q?Q?Q?Q??Q???{Gz???Q?{Gz??p= ף??Q??HzG?HzG?333333?Q?p= ף?(\?Q?RQ?(\?Q?ףp= ?(\?Q?333333?HzG@)\(?zG?(\?Gz? ףp= ??RQ?zG?HzG?p= ף? ףp= ?p= ף?333333?Q?zG?Q?Q?Gz@Q@)\(?Gz?= ףp=?333333? ףp= ?{Gz? ףp= ?Q?Q?Q???Q???RQ?Q?(\???zG?q= ףp?q= ףp??Q?ffffff?\(\?= ףp=?Gz?(\?p= ף?Q?q= ףp?(\?333333?{Gz?RQ@Q@Gz@(\?p= ף??{Gz@(\@= ףp=@zG?= ףp= @ @(\@Q?Q@Q@\(\@Q?Q?= ףp=?Gz?(\??RQ?(\?RQ??q= ףp?333333?{Gz?p= ף?\(\@Q@Gz@Q?p= ף@)\(@Q@p= ף@RQ?p= ף?HzG?{Gz@ףp= @ ףp= ?@Q?(\?\(\?\(\??)\(?{Gz? ףp= ? ףp= ? ףp= ?{Gz?{Gz?)\(?RQ?333333?q= ףp?(\?\(\?Q@{Gz?? ףp= @ףp= @RQ@HzG@ףp= @ffffff@p= ף@q= ףp @Q@ffffff@ףp= @Q@(\?Q??Q??(\?Gz??\(\??)\(?Gz??)\(?Gz?ףp= ???\(\?Q?Gz@ ףp= @{Gz@(\@zG?Q?(\?Gz?ףp= ?)\(?HzG?\(\??(\?333333? ףp= ?Gz?Q@ףp= @= ףp=@Gz?Gz??p= ף?(\?q= ףp?HzG?zG? ףp= ?{Gz?{Gz?(\? ףp= ?RQ?Q?Q?ffffff?Q?(\?(\?zG? ףp= ?ffffff@RQ@(\?Q?)\(?Q@RQ??zG?(\??333333?Q?(\?Q?RQ?(\?\(\?(\?333333?Gz@)\(@?RQ?)\(@ףp= @Gz@RQ?RQ?RQ?(\?HzG?HzG?zG?)\(?Q@(\@ffffff?Gz?(\?Gz?RQ?333333?333333?(\??HzG?{Gz?Gz?{Gz?333333??Q?Q?? ףp= ? ףp= ??)\(?Q? ףp= ?{Gz?HzG??= ףp=? ףp= ?Gz?)\(??Q?{Gz?Q?Q??)\(???? ףp= ?RQ?zG?)\(?HzG?Q? ףp= ?ffffff?)\(??RQ?HzG?q= ףp?Q?p= ף? ףp= ?Q?333333??RQ?333333?)\(?{Gz?Q? ףp= ??Q?= ףp=?zG?{Gz?)\(?zG??q= ףp?(\??HzG? ףp= ?(\??HzG?q= ףp?(\?(\?zG?)\(?HzG?ףp= ?)\(?Gz?zG? r `??CIK1H.HT_MBET r `??CIK1H.HT_DIG x ?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? r `??CIK1H.HT_SC.1 s Plot1$ `  ` C:\ORIGIN Fr,,s I0@Y@@K~K@@? @jl "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c MȈN ?ő^+ġ? >>  l "M P c & (u~[?/b?,>>  A c ^Bu"@?1c0? >>  l "^ S6 c n/|'$?? >>  l "n/ S5 c .%s?,_? >>  l ". S4 c Y(~B?q >? >>  l "Y(~ S3 c 'Ww? At? >>  l "' S2 c +e6<ݳ-?p= ף? >>  l "+e S1 c B]{?.?]]]]]] $w  l " $ Human cik1 K\+(+)-channel c P  8p?˗d1? , >>Legend  l "@P   , \L(1) %(1) \L(2) %(2) \L(3) %(3) c uL9+66Z@ 8>>D@YL  l "& 8 CONFORMATIONAL INDEX Input: Edelman's scale c `QB;o@ >q >>BXB  l "&  SEQUENCE NUMBER R `# R `# R  `# R   R   R l "@Ed q? R P@  R  l "? R P@2 p@ R   R   R l "@T!? R P@NI R  l "c'? R P@ N 0@ R  R  R  R  R  R  \CENTAR ZA MOLEKULARNU BIOLOGIJU - SPLIT2.DOCQtMY DOCUMENTS\CENTAR ZA MOLEKULARNU BIOLOGIJU - SPLIT2.DOCDR8MY DOCUMENTS\CV5;ӕ q!8ddcF 7|dEFO03x0γo9M#}G|؄$DF&0 ^~=苞oM/bxRQQ8Upszg͚84~q Otz=/B4y#}d(E+Dd"0  # A2*.hCwm* Dn`!*.hCwmފA~ U8c*xԚ NUǟ1cfq*LT$F2!9E%" BRT$)!a0 woϽnz}{꺭{j-'BGPB'e1EQPP(j+7- %^: :L⟹9 IlB#= ʋ:PhY0iGĖzLt$O^,qz>|Y,ku+r_UN=`_pD^^#]Ucb?s fnO$W %Ӭն_E#nAժc&mtC|7j]ܠ>)/?4={Wus͇nMɯڍ ۈȈmE*2b|qX3Fo˷kۈO8k);}74//x]3^3_9%_N{IDDvy y gum"hE(Њ@K76/͋Pul^-)l"h6xk)Ranj(j\']sfi#Xa6Z--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻ*ڼkkjjڸzfc/ű՗Kqltl8RKql:R[}=[})T'5[}=[})TV_cUe9JΙöެ6 zZ--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻv}SO7o.cr9yFa`EdMO`Kpg",X"|(jc(lc '{0'ۃE>qVę 1.cdQ 1r 2CwB9N"-/;3POp\˵"wA m&h/@G9 :4|C|+O20Cd )/Ack9%cTpns0>BSQ[,} +od۵n؂}l얗!Cfyp\2~"+BeVW60 )rʆ+-**a[ C)h6j;4Ƽ m}T]yxBe%q+83FŘNv24}0f)1V_\|f: ?wb+ .Bz?(N(}HA:^]B֥t](By ns^5*B}FlJ3 zjWҫ;aOG1f0gFjߤa<I5olx9z |ç8z,XW詰JPXgFLخ?ݺ+dZp@8K CyR-*nj'u8BDxZ%@J IoV Zp+p!%xV ,Ga<>uO\>x&~Wr0MOW ^3xDWO!z:☳<|CcXaR6!lVbm8!AS} BD44į0_8f:V~eXPc3T K٬o6-If*0kY ulgҌM#hg*A{:q]LMxʔO/K3/IWCi=|G6fZx &~60הy97Bj٠V]ʌߛz)MjsMd8`.M6gtq@.ĸeHqo7tY'u;GWp{A-̻w㡁; +!̈́f xНܙsӠ[ :n}C> ]z0~ݭG`Ǻq)8t7Jާgn1}[/pG/`_atj=7a`{xs؍3]ߜr& #K._ݐqe8oAqo0:Ai=f.)S=0uq/F#짉 ͽ,h靁v H6A'o tVo=Bw þ^p/dFyW`wa?oz{a23 }a?s0[ հ[K{ fxX㍁uL؈v1O8Qw b\y`yA^ OCL8s$9\ADZ93/aIԄwV(ҒkLJZ[vDZam|h /6i. Y[ diL{|qrؕjLqʺ%h*0JkT{CZ{T"_nTIj+S(Q*+!m ktIi$;X[r㛲,}K;K$(NH(]FTYr{rfIpI7Av׷=W |x1AWU$w&kJ|n]+FWuBzmUyu{VW#W]LurPPjMrB-ҪAm#j[n' SS"_;HԅNAE$ǵPn@}䮀nL^mД}Мr3AVDa[m h{3"_|<'w.h\{vB#tH#2dKrC0~x@;>v䞃GC*S'μyMZEM?"0y(le4F3#bLȍ604> /W![R.Q=﯎M<_zא9D fLg0iHԙ(x")S}!LՈwc*JX튎!(xDZAKtki;?0aKGڧLohV{S"@Y=OZ#Sv[x35"EC:Vօ*Vg5i(KieDDV3}U>$ 'mDW7=K|{Z{u#cDw tU *0B|9Z*IC|uR1enkV2}BRDLV͔Y>&D-D_ƬV_!^jȲ&rD|Q(DTWM'"n!"=QT&j5)j1IUԣ=XKOX5-G$]$§9y?iq Q!"_$Ȧ*U$2LlNZ*D& msDx D<قc"_|dKpX'"OOA2]fUH+T5iUzd]N D@!m"[D|Ֆ3`ݵLݡڑv0>}% GɍV+#I`n}ݞfL)DhԖݮ:I"_amPvGI4sX[;-"J60md7]w$3qa7UdzZAEG(%Qf27E#[2U$2dH!`2B$*TBEzu뜽Y{<{7]sZ&I{iA;Ku6򦒴S]F[#inCܮjvGt6@ڠț˃h-h + jitt@CL?SmLI'{δ\+ʏtr;*`L}YՋhnF zKYƧ\&0)w2 m)V>LR ֱ |YtIG|YVdڈ?lA_/>MW{[io/i/WڄSoht]Ctm kϑ(ߣP|(> Dqutܥn(>}M[gx{h3U3P|3yANw{QE~ѮW]|XmUUUAޜͻ_PQa*+yFۦyRY`ҦBތӆ^Dha(򦭶t w':B[xGhQTySJ[a{ B{v(Ky+U7yjNWf'  ^N⻟S7=C"ohyA%L{g9yLV={dSPҨtEv mj# װTO]ȇ״-- δRȇ-po1G m 3h"3iO#^8ù;,\*ƪ&(ɮ2ppUiCTCQj:G*wZ•K6WmG>|B$WE)yPk*Q5ڮ:L˅(~Mbt? wmr 1UR0 GތRMt]\N[#WP|zwr%^b_N\I}q  FyݴMo=6_CP\%)UA[ISyOkjWݢys4VBޔ3T%7j;IZӿU]Z(}Zțh6fkC{I5 U/MgזByskGAyskO@Uu`Zա{Cpimt!o~ky횎vp:P8Tu:>#DmlD vKg2 UEۃv퉮ENSu}iUFޔhE TytgP>I\:bLVtdpQ m!V(;4oQ8tId;2vz%ojcCgڬk":=[UZXڅP| 6țn1mx4hN' h"fEn"ZY*{lmUIL<_^C7Ŵ+QYMumt:.yݍi.o:[3ԙJ{ZgP4N{Mf(TuLf(~as@[:V0LiJT( έU_Hns:bQWŧ$6LAެ/i t!oj'_3'Yߠ!(UO괛|KkzyXnE\-iuUu7yS\UXFGPXӸv~riQyR\y]hyN[Uovu?ZZ"o&ysn9O[ UqvI=L۽tݏv;u:]fVBQ(>O DکjAj AT=ԪQ5+R+i~{VFZEU%'Ӻ(>9ǙO m>~ _ ;nRb34>MUMkiTQ|hTQѶƊ[aHtomTCu: Sȇu]AD{ zy3I5Ch aڧt-DE+Lj\aT.N; C>S芠 (M(L o^.yL btK׃әss麑~K\[/J$kkȥLhD}7j{ٕBQ|4NG;'9L:bQ|pn:P|ΐ6W6(>]H+xO$^Cy(>gH!3 ηGiUPX'jມțڹ- F1ODmTuuZ*}Le7mOn.>Fͻ'\?g;]7kk>ț}Q+=nMț+ղOțT)?D7 kBm;h kBm볁骂šPl, RDaM=EJP[l0jJP[iT3 +9Zy4""o4#!R:C͘tfțtp=@"ogo W-t) לlj"e]ȇW(t Π f,ڤl6z Ρ-FːG\lp4ͧ:grdt v*yB5Q\uNohQ݃g]Lzp.=zp/zpYF[zpI+}|rvȮ@$Ҵ[NCqZE.½U贡{X}iTQgZEV(36խAP\}@[Zo-mj;u#(Ӽ*U߇j(6k U&㪞(>h$f4 U')Zo+@0_8UJNW8ك~tX;bGQ|u}>I$O=1y(.YX4ݥG}Q]*@k#Qkûu2}S(3Ֆ¨򦆪NϐPIwR;Iu¥AWj'L}芢țUu:y4^RryLAq)N;b(8NAgz;N%PuwJNwgb(8gc(FlJsʡ|( љ|z]NJ ǁխ(CJ:TT$oq+(z:?Tph.@pij7hR9xTDj1=[UySYj.:"͵RvC#Rk/ț"@ a(_^&"o˥ErZ?T@*~n\ȵL?QmLMh7r V]e-E#w(܋&}L'Jc4J0}Z5Nr?MjwNw~.wR;WZ2(WPܭjEۯڇNWk'-(Ik>%\jCh{|wQ;;c\ŽPCq_K:Tg5 ŝч٭ڍ#ʠG<wsSk1(vG}7ij^t-qt3=iUl/Q+Dq'7$#Lu0Kh' Y?ڇٓh= dl>khLlgmE65G6{vC,j=Ǵ~j a$"oZfQ;Vf@664{ CތƠXӲ1g/f.&Vg5ț-$5f_6v4!oruZ}V;ŷhU T Uw5-țv:fAigyjNgYhB3ΦSGlsh;T;L~CqWan:+PGL<wjr7vf>ߡRFqt/{ iUcPܯ]D^ojtC>rKRFqy)2SVJu+hue%^yj ]NXcVGPܭ_E//d-Yޒ hl&1ތV3 ڇo|oQ.iwPngzsU{B.w 9qtL~_=okh_J~hdBNAQ\YޖBLHa4F{ANWg@#)W )eiKZY+> h+AiJe/B+ô`;x%(㳻w@Y<-LS0u% ! LTIͣ<ʣ$MMJMM< M;MQ 5541T꣗g9sY!^<)a̒8~H'9ijeβo]~N!e{rHO#HˬW 0f@1Rk &YH899\ֻ$&.kS$fȶd6Cb:領!{4-2*~ |^,Z29Z.g r6VR6W@'S;_bizN$}Mz4G^(2ݨ{CCsB[< :/U ›Qx0 130a>+,÷Xu؀-؎l^Q)A!.2( : G#fGKA$'4: E]u[*u 01!`:fbbc)V k ;؏:8(YG,|Q*{PS QhxG$rz)gݐB_ kHǛQx0  +,÷Xu؈I{qGqppW`yYaGYT@D5P uq[݀fGKA$b"R701c0CLt§XX,zl6U pp8(B1,v/*{PA4E#D="QIHF z/5c(h{ |OXt1[vg!|E\ePjp>܏h(Z "80 ZR>'Ⱦǭ4֭%nݮh? dUZs'`kz3{a9զ04{Xo%m2mzz>avg;z]{japi8U{h6]US~=S]]_l([4TFzs_[v-e*!B[⺮p#}txtMNLMMJ-J:2_mszb1ѭcb?቉nn*T 4Rղv,ԿB#7ҺzZ]Jj׷+[R:tMLI T[QOĭj;W?}ޙ87Gg}q#[F\Q-"bK޽cp}X4P_ϫ [ηtB: YYYJV^2{i2mL8]ў}+&`YcY}-1敢 {DdS"0   # A2b5Li()j>+n`!65Li()jhGA~ $U8xԙ es{Gq4%Fa23FfFT9O(%%IJA%r#D'P2ڳ׺캮޾mk}?s3;/ u|RTP\YS{3Ա%QUNF"Ց+'zjn5_ρ@XO*^A (:!Oڹ wPP,Oxi\󟭋^h=Zx7?>O7=URRRZhFPj: =+EEDBACK.DOCVTPROGRAM FILES\MICROSOFT OFFICE\OFFICE\WEB PAGE TEMPLATES\CONTENT\FORM - REGISTRATION.DOCPPROGRAM FILES\MICROSOFT OFFICE\OFFICE\WEB PAGE TEMPLATES\CONTENT\FORM - REGISTRATION.DOCPPROGRAM FILES\MICROSOFT OFFICE\OFFICE\B PAGE TEMPLATES\CONTENT\PERSONAL HOME PAGE.DOChSPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\LETTERS & FAXES\CONTEMPORARY FAX.DOTLQPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\LETTERS & FAXES\CONTEMPORARY FAX.DOT"QPROGRAM FILES\MICROSOFT OFFICE\TCPYA 4,210 #  $@X r zz??0GMCR_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@h@h@h@i@ i@@i@`i@i@i@i@i@j@ j@@j@`j@j@j@j@j@k@ k@@k@`k@k@k@k@k@l@ l@@l@`l@l@l@l@l@m@ m@@m@`m@m@m@m@m@n@ n@@n@`n@n@n@n@n@o@ o@@o@`o@o@o@o@o@p@p@ p@0p@@p@Pp@`p@pp@p@p@p@p@p@p@p@p@q@q@ q@0q@@q@Pq@`q@pq@q@q@q@q@q@q@q@q@r@r@ r@0r@@r@Pr@`r@pr@r@r@r@r@r@r@r@r@s@s@ s@0s@@s@Ps@`s@ps@s@s@s@s@s@s@s@s@t@t@ t@0t@@t@Pt@`t@pt@t@t@t@t@t@t@t@t@u@u@ u@0u@@u@Pu@`u@pu@u@u@u@u@u@u@u@u@v@v@ v@0v@@v@Pv@`v@pv@v@v@v@v@v@v@v@v@w@w@ w@0w@@w@Pw@`w@pw@w@w@w@ r !`zz??GMCR_S r !`zz??GMCR_C r !`zz??GMCR_D r  `zz??GMCR_TMH Q?{Gz?Q?{Gz?Q?(\?p= ף?Gz?Gz?{Gz?(\?(\?(\??= ףp=?{Gz?333333?Q?{Gz?{Gz? ףp= ?Q??Q???Q?Q?Q???Q?)\(?Q?p= ף?{Gz?(\?{Gz?p= ף?Q?)\(? ףp= ?Q????Q?Q?Q?Q?{Gz??Q?Q?Q?Q?{Gz?(\?Q?(\?RQ?)\(?RQ?333333?zG?ffffff?Gz?HzG?(\?\(\?(\? ףp= ??(\?Q?RQ?(\?)\(?{Gz??{Gz?????Q????{Gz?{Gz?{Gz?Q?Q?Q?Q?Q??)\(?HzG?)\(?Gz?(\?Q?zG?Q?Q?q= ףp?HzG?ffffff?Q?Gz?{Gz?(\?Q?RQ?{Gz?p= ף?p= ף??Q?{Gz???333333?(\?RQ?Q?q= ףp?)\(?(\?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz? ףp= ? ףp= ??)\(?Q?Q?Q?)\(?)\(?)\(?Q?RQ?zG?p= ף?333333?(\?ffffff?{Gz?p= ף?q= ףp?Q?zG??(\?{Gz?Q?Q?HzG?(\?(\?HzG???333333?ףp= ?(\?333333?zG?Q?)\(?RQ??p= ף?Gz?Q?Q?RQ?Q?Q?Q?{Gz??{Gz?{Gz??{Gz?{Gz? ףp= ? ףp= ? ףp= ?? ףp= ?q= ףp?p= ף?(\?(\?(\?HzG? ףp= ?)\(?{Gz?Q?{Gz?{Gz?Q?Q?Q?{Gz?{Gz?Q?Q?Q?{Gz?Q?Q? ףp= ? ףp= ?{Gz?{Gz?Q??Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz?{Gz?p= ף?ףp= ?zG?RQ?ףp= ?zG?p= ף?zG?RQ?Q?(\?Q?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q??Q?{Gz?RQ?Q?q= ףp?(\?HzG?zG?ףp= ?(\? ףp= ?(\? ףp= ?(\?Q?ףp= ?ףp= ?p= ף?? ףp= ?p= ף?Q?Q?)\(?Q?p= ף?Q?{Gz?HzG?)\(? ףp= ?Q?Gz@p= ף@Gz @Q@Q@Q@Q@Q@@p= ף@p= ף@q= ףp@q= ףp@Q@{Gz@Gz@)\(@(\@ ףp= @Q @ffffff@ףp= @(\?p= ף?Q?(\?(\?Q?Q?333333?333333?(\?Q?p= ף?RQ?(\? ףp= ?{Gz?Q??Q?Q?{Gz?{Gz?{Gz?Q?Q?{Gz??Q? ףp= ???Q?)\(??{Gz?Q??{Gz?{Gz?{Gz?{Gz?Q?{Gz?{Gz?Q?Q?{Gz?Q?Q?HzG? ףp= ?Gz?Gz?Q? r `zz??GMCR_BET r `zz??GMCR_TUR r `zz??GMCR_UND r `zz??GMCR_H.T r `zz??GMCR_MOMA r `zz??GMCR_MOMB r `zz??GMCR_INDA r `zz??GMCR_INDB r `zz??GMCR_N {Gz?Q?Q? ףp= ?(\??(\?ףp= ? ףp= ? ףp= ??{Gz?Q?RQ?333333?p= ף? ףp= ???Q????{Gz?Q???{Gz?{Gz?Q?)\(?)\(?333333??zG? ףp= ?)\(? ףp= ? ףp= ??Q?Q?Q??Q?{Gz?{Gz?Q?{Gz??Q?{Gz?Q?Q?Q??{Gz?(\?333333?Gz??(\?RQ?p= ף?{Gz?p= ף?Q?333333?\(\?= ףp=??RQ?Q?zG?(\?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz???{Gz?Q?Q?{Gz?{Gz??{Gz?Q?{Gz?{Gz?Q?(\?Q?ffffff?zG? ףp= ?Gz? ףp= ?Q?HzG?p= ף?Gz?Q?Gz?(\??(\?{Gz???RQ?{Gz?333333??Q?Q??Q?(\??)\(?Q?)\(?zG?333333?Q? ףp= ?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q???)\(?p= ף?p= ף?Q?333333?333333?Q?)\(?)\(?{Gz?333333?q= ףp??q= ףp?ףp= ?p= ף??zG?zG?q= ףp??Q?zG?HzG?Q?HzG?(\?ffffff?Gz?)\(?= ףp=?ףp= ?{Gz?ףp= ?Q?RQ?(\?Q?zG?Q?ףp= ?q= ףp??Q?p= ף?Q?Q?Q?Q?{Gz?? ףp= ? ףp= ?? ףp= ? ףp= ? ףp= ??Q?(\? ףp= ?= ףp=?ffffff?(\?{Gz?{Gz?Q??{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?Q?{Gz??Q?)\(?Q? ףp= ?)\(? ףp= ? ףp= ?p= ף?{Gz??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz?333333?(\?Gz?q= ףp?Q?Q?Q?Q?(\?(\?p= ף?{Gz?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?{Gz?Q?{Gz? ףp= ?(\??Q?Q? ףp= ?)\(?ףp= ?= ףp=?ffffff??\(\?zG?(\?(\?Q?Q?(\?)\(?)\(?p= ף?p= ף?333333?{Gz? ףp= ?zG?Q?(\?(\?= ףp=@Gz@?Gz?p= ף?ףp= ?zG?\(\?Gz?{Gz?RQ?(\?= ףp=?(\?q= ףp?Gz??Gz?Q?= ףp=@ffffff?HzG?(\@333333 @Gz@Gz?)\(?(\?zG?= ףp=?Q?)\(?(\? ףp= ?{Gz?)\(? ףp= ??Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q?{Gz?? ףp= ?{Gz?Q??Q?{Gz?{Gz?{Gz?{Gz?{Gz?Q?{Gz???Q?zG?p= ף??zG?Q? r `zz??GMCR_MBET r `zz??GMCR_DIG ???????????????????????? r `zz??GMCR_SC.1 s Plot1$ `  ` C:\ORIGIN Fr,,s 4y@I@ @5Z5Z@@?@UUUUUql "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c l-x ? w  l "l  GMCR, human c P  8p?˗d1? , >>Legend  l "@P   , \L(1) %(1) \L(2) %(2) \L(3) %(3) c LP+/BK@ <>>D@YL  l "& < CONFORMATIONAL INDEX Input: Kyte-Doolittle scale c \a#g@"T! >>BXB  l "&  SEQUENCE NUMBER c ́?5h?<>>_202 &  c ́?5h?<>>_202 &  c ́?5h?<>>_202 &  R z`# R z `# R z `# R   R   R l "@( q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N4 R  l "c'? R P@ N y@ R  R  R  R  R  R  NS\SELLING YOUR IDEAS - DALE CARNEGIE TRAINING (R).POTSPROGRAM FILES\MICROSOF+hɍ qWmJ?{%%{0XSGi2YD{Hjϲ-iY q~F{Pe~s*>Y3Y5{euVF,؈Ie6b[IxxiX^FL.x-;E4K41YYFt UԒSQoMa$/~#ywzH^LE yW%/Lkz yBSQosH6;GXb*Kż#΋xEa{!zf:8?1۱O q^6oH^{[h[h%Zɛněn$*%~$=bO~7Hog1:;|DS~==K&JHW 0[bgyvWGZ70Pu#DĆ{Է0V *'t3)fSsTΧX@D ֐Hb/yߨ f0̄f` b8M\lRL*~LmS|FKӚ7{$Ϧ lZgTh[6ֲXM(QQȲ9Ko6Plv(%06O 6x>c5:հî |e[O/֣a8 9a>Ԇ3Bh@3΅aٶ`'hWA^xb_(E@><d}! (&߀S.>x!T C?I}|N}}M}~K1 c>VC+nA`ŭ*x'=d?( S` Φ_&[Al"YL)|F_P~C9%m8<.ÅX- kQ$n@фp>QNkpk17\ GGx1 O~>8bN%7Nc^"Sث7ӕRp{09Nj-<x&NjLco;Lev:o/SZ{zfRҰ9]%vbtS*W7)_=ث┯P2&VX;IqWmÓqW3` {dwUx89Au8]Lc8R[[eUYZqWAM XMd嫙PYt柮|5 Zwb5nt*`V/Ў ՗o[`$$OW;┯>-q*x!VR6{uaIU3x_p+_ػ W7ӕ{ʩi|5~J*V6l Ne+NȬSG}7hjβ*U]^ X]^y1N^SXY^/zǬ&])_ [VT?aouVPofoS;Y$sj'{?8uDV;ث:^Ԟ8E+G}.+G햕>֙*!FtEޣN#6{_FqWUÐ * c2>1G.i7XaL.]W2^]jY/hlrO<ysmV!GaU : QLJ[Mj ;J b*FFO22Z%YYL #Jrԑ(QFV&[3൦*mvAG,\0̂^q4n36Fg]&@1c0.3gRmDSF25L=QL56F`@1/T+'+f G=W^4Q | p2zRw"ʬG^sћ `=w{#̾g=oK_D;Aϟ jN}Ha~r vZD\f%\glC2Ӊ>YPm2&` GAh V(J%e:c2UIr3P'Q:9D=](ލp70XB&aEeOw7qx/0W%ΆI({z΃)L&Ze2<jr 5l@el[h$'wD[!*vth_8~9s lJ ,8EE aG G6-%t5ejj5}ZMVÕX-pkp++e}m{>yY^-}==y犜 7yEuMB %VnR7 U+Ĉ\UJȶ…FUwdE:e.3!^0I\n<gT>G%b9Pu$YXПcE9|R@mNs^qټ[HV%*U ݳ0U?;VzGjjThɪV biJ+{TkУxHQVFn,t%U:DBz|IT#\NT: SIFڌM*5beu*#A.4"HhQ:yc|B:H=F1o\M Ud/,}IuRYO#4?lΐk<gIyT%-T^W+/ӥ5m :RVVjݺAFZ=UgMV!VPz6lkcEZ=޷BU炶buڭR3Yn=妽*mwvunGY,^vz-;it(UNTzSQ/STq~;:ҶU>avujDڅVop`UN* qSJDVU+#ܔR=_[{j/UJ;ʶui۪V sP`},#eٯ$jϙ3I25~kC=Ο빚*p[bʹʑB܉ ܅Y܋a#؀؂mx;,UtN>OW8"Cc1E!J0 wc6cK +Њ6BGPѱQt$Np> C4b$G2}RL AjрXXXMhB3Z;{pq у3KvDb8␈1HA:b31ը/ߚpg}jU;7{YxZ+.MZ`V'SR0UKQ߿/];nt{?"f'pL)ES3'GGOʙILPn >NTG`zm`}'^`Jcs[797HVP{† FNnh]?gV< ٞ3Cv󃃯u\('_嫏VTh/e9%Ssses֜`NH{j#Ã[C#+vOvO+g=45mQO7zwY'c60G&9PwKt?x3zDdIZIKU@ENGAGE[1].TXTfvSZWINDOWS\COOKIES\ZAVOD ZA FIZIKU@EPNET[2].TXTrRfWINDOWS\COOKIES\ZAVOD ZA FIZIKU@EU-ADCENTER(1).TXTdRXWINDOWS\COOKIES\ZAVOD ZA FIZIKU@EXP5_GO.TXTjR^WINDOWS\COOKIES\ZAVOD ZA FIZIKU@FEBS_UNIBE.TXTdRXWINDOWS\CKIES\ZAVOD ZA FIZIKU@FINDSVP.TXTj&R^WINDOWS\COOKIES\ZAVOD ZA FIZIKU@FLYCAST(1).TXTfRZWINDOWS\COOKIES\ZAVOD ZA FIZIKU@FOCALINK.TXTpSdWINDOWS\COOKIES\ZAVOD ZA FIZIKU@GENERALTURIST.TXThT\WINDOWS\COOKIES\ZAVOD ZA FIZIKU@GEOCITIES.TXTrRfWINCPYA 4,210 #  $@X r ??0PGY60261_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@ r !`??PGY60261_B r !`??PGY60261_C r !`??PGY60261_D r `??PGY60261_TMH zG@= ףp=@Q?(\?ffffff??? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?Q?Q?HzG?Gz?(\?ffffff@zG@ r `??PGY60261_BET r `??PGY60261_TUR r `??PGY60261_UND r `??PGY60261_H.T r `??PGY60261_J r `??PGY60261_MOMA ףp= @Q@@@RQ@333333@ffffff@p= ף@)\( @= ףp= @ @ ףp= @q= ףp@(\@(\ @ffffff@\(\@(\@ r `??PGY60261_MOMB r `??PGY60261_INDA = ףp=?(\@ffffff@q= ףp@Gz@@\(\@)\(@(\@= ףp=@ ףp= @Q@p= ף@ףp= @(\@Q@(\ @Q@ffffff@q= ףp? r `??PGY60261_INDB r `??PGY60261_MBET r `??PGY60261_DIG r `??PGY60261_OBS r  `??PGY60261_SC1 q= ףp?\(\?333333?ffffff?ףp= ?Q?Q?HzG?p= ף?Q?ףp= ??Q?? ףp= ?(\?333333??{Gz?zG?)\(?\(\? r `??PGY60261_T.60 s Plot1$ `  ` C:\ORIGIN Fr,,s 9@@@־aVU@@?@m۶m[nl "N 9 S2? ף= ף=Pd1 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c g~X[?]]]]]] (w  l "g ( PGYA antibacterial peptide c P  38p?˗d1? 8 >>Legend  l "@P  3 8 \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) c J0)gm@ >>D@YL  l "& i CONFORMATIONAL INDEX c ]}&@}I| >>BXB  l "&  SEQUENCE NUMBER R  `# R  `# R `# R  `# R   R   R l "@i q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N R  l "c'? R P@ N 9@ R  R  R  R  R  R  KIES\ZAVOD ZA FIZIKU@WWW_STPT(1).TXTvRjWINDOWSE"0 O # A21=w5\V )oEn`!=w5\V~.9~ U8 x՚ tTo1 /D DAK-XALBxWhyb( 0+*h)CRbX m8&* P! x@ 9mr6;wwwf}/yKQ'<{,勉?L~Ss#qgѾM) "[.IyNmL/DA3~4m{azqCOow9%s.ͥo/,&|Ԗ"IMW$[Z^" >?m=^"=4E%]tl>'T=Vf}[R}f*bqc حz|F=vo_XC=6ĕ/q3Rvq\v%\ m/fx8Xn(& )鲤 ))RU+W&vue慔7~ߨul^H~\i6y#/?bqzf!ns3;pl]=ۼgع.!eCryҺri2ː6oYl^̹ټu \y[ݙۼΎ/gLc;Q9[AS|[AQ|VVPo+ho+(xEU;g+ho+(߷4ŷqF\Qo:[A2NO\-'3_3_C*֌u34[3ճ͛|ykR=l^+Z)W.+6/ù i֑uŜ{NXye ՝/| cu<_)̈<:he fR5m,[Z,KZS: 6TvSeVV)Ko2 U*ʊ e:̊˲hd_pu hA#kaPȈ(%P')m+ŹZ@)^>dNn[^ @OX-AFEpr'tEn$wQ=A #zpq(dDהs@M@F#7@PȈ?!pp&Opjqp xн #V7MU?PMBt 7\M _Mn]2 u7-45F zd>A`b+ эa #˥p+rУ #pU #nk@7# OV> K> 2"3 .]na&8)Ge tdD^2{ 2b-n9Z27M@F| CBѾTE:MMbA.Nh;גlDQOP'b0tI}ms@bD_=)?E18+Px ܝ ,XWИb?hxT '"XA<.bRPwL(,1.W/!:DL-f){w!Q wXd\  Ȉb-Z #{9z{"Vxx уu#-QQ}pHCptԙjE+k) ԗa==΅CAcAFBAo"zu+%  (8c4q*r4t+ϩEt -r[,.5p"zŽv!:D@ #谽 !½GI܏dYp1jN#Ap;mJAM5`mD9C4J߅Ѝ M/?4яts?)ZhcZ 59Eͤ7z?GeScAtD"v5"Ng͡@Q2 m}n] I9i0 A0rH#'] ڂ$g}[#K4H.At\ w\'Dt7M.#:K'w-AA;\~#)E~bGR }W2td,8 U3DU-ڪA #.Qp=UP/רΠ #Fnp7onQ!:S]@Q3jGU?JTypϫj0HnUcWA5FDD(O8}gڃ³9\h./ AAF~eѻ{y9h!Ȉy%\Ŀm 7@F7>譠z2E #bpٺdD~ n~4RMop~Э #nI {G셕oKzakno:w > Oϗv_nuVgMvet^WH+N3&{͹'mݶں]ݶm\u WF^Y^~ ΰr-\Geo/.܇rIAv8'}ٹ>7TjvgS]Jak,2UA}vغ|D./p [Sus\.hU5]BmB sКP]֝LAصV% P]2].hUVa$g$li:Ѻ"0zPeFV[:Z+*T%gP:Oa[?OF,Z|9t5Ƕ _ڽ%\(H^TUg\ WpZWqE|~1WMKQc(\ h까 mw:vr-ܯy./xjw7 qpj\*ƺki|>ef{v*N9p.7cnurn4pns%p9ׅ%Ia\i]s1Ɋ*;V8¹%K8{O0oޔu>V%pMys++kqNp.\Ja\.׹\o.w\\sp &;ǹں\bpsa.wܹR[ Vp ΍X\ n-½Ε;W ps p{9:s:#] J;W\)a5 ſZ_Tx*W} d{WwOM@nvz[sôɭҧ2hx okv~[{RϝSV3ĎE?;5Sru=?ZѺ[kU ܯ ?~W ..Sk7J^ju=csff|شM"[drA9CrIO'g`r.z;YYrippRG<ffyfo[5^}mW^*гwjh1 a#IkzDd%"0 T # A2b#xa3 $Tn`!b#xa3:j%^ @b]x6x͛ NߵA)# q)r!&FQd;IȉB;rT;jDmvQkdw=?Lvϳ5Xj,V3 bCb َD-SEQ.HTMQWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\ER6ZULGF\TMP-PART1.TXTVTWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\ER6ZULGF\UPISI_OSOBU[1].HTMVTWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\ER6ZULGF\UPISI_OSOBU[2].HTMVTWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\ER6ZULGF\UPISI_OSOBU[3].HTMESWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\ER6ZULGF\WGETZ28E7E478.HTMSWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\F8H01PUR\PDB1AFOA_SUM[1].HTM RWINDOWS\TEMPORARYCPYA 4,210 #  $@X r ??0A2MLT_AA. ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@ r !`??A2MLT_B r !`??A2MLT_C r !`??A2MLT_D r  `??A2MLT_TMH \(\@ףp= @ffffff @(\@Gz@ ףp= @HzG @@@ףp= @@RQ@Q@333333@p= ף@Q?(\?(\??Q?333333?Q?{Gz?{Gz?{Gz? r `??A2MLT_BET r `??A2MLT_TUR r `??A2MLT_UND r `??A2MLT_H.T r `??A2MLT_J r `??A2MLT_MOMA r `??A2MLT_MOMB r `??A2MLT_INDA {Gz?ffffff?\(\@ ףp= @ףp= @(\@\(\@\(\@= ףp=@Gz@q= ףp@ffffff?p= ף?Q?Q@@p= ף@p= ף@?(\@HzG?Gz?Q?? r `??A2MLT_INDB r `??A2MLT_MBET r `??A2MLT_DIG ??????????????????????? r `??A2MLT_OBS ??????????????????????? r  `??A2MLT_SC1 RQ?(\?)\(?zG?ffffff?Q?(\?HzG?{Gz?\(\?{Gz?Q??ffffff?RQ?= ףp=?p= ף?333333?(\?(\?Q?@333333@(\@HzG@@ r `??A2MLT_T.60 s Plot1$<  <  D:\ORIGINFr,,s >@@#7r#7rS@@?۶m۶ kl ": S S2? ף= ף=Pd1 c Fx J Z̿r?ҿ>> L5  5 c Fx BJ Z̿r?ҿ>> L4  4 c Fx J" Z̿r?ҿ>> L3  3 c Fx HJ Z̿r?ҿ>> L2  2 c Fx J( Z̿r?ҿ>> L1  1 c KUM-+?7i6?,>>  A c AD#1?diCNÿ (w  l "A ( melittin hemolytic peptide c l K2`,($?3_ kQ? P + Legend  l "@@l K P \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) \L(5) %(5) \L(6) %(6) c qH D9@ >>D@YL  l "&Ss2 CONFORMATIONAL INDEX c W+@"_' >>BXB  l "&W  SEQUENCE NUMBER R  `# R  `# R  `# R  `# R  `# R   R   R l "@E .? R @:  R  l "+?' ? R P@: @ R   R   R l "@\? R @: R  l "0,! ,Q a? R P@ 4 >@ R  R  R  R  R  R  \WTETQ90H\UPISI_OSOBU[1].HTMVTWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\WTETQ90H\UPISI_OSOBU[2].HTMVTWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\WTETQ90H\UPISI_OS1sȋQ#Xm8^kKI_7P[T'JE| }E2-Tbeh=߯kF KF<'ny'~?n^>j8~ _WO8=$Oِ4z_ϋwJ^yHޯ6p(06 M; ٢,ܗvsޔV2f~ίʅf'9}Ա *:ViltF#6-hĬ2qFlVf#G#6/aIJ8F#fш-ڴU]e:5c%۬/Z?T &٫QkX¸;HqX8Uc ֒UTb,Ra\Tc 6mLii"+g,RaE Fl-p?X9̠Cu$քlZ*5W-/>}blX8tƥw7k,ŭˍ[\.!&7,qdxZ~ظUPw*hgTYzVAU * * <Z2B* ZYxVAUPgHfTYxVA+<*г :_Bc{S[k.g5clZ\_jq>qd7,Y+gq-.,7nq|c|@6  ;z%Qja];}'<٨+-vqP3jnWutl{W{{έ:jjc Cn0" l{Su;꺢VC6u`G ci(n>؇GM/Է4v@k3`M``W-q<87(f5QQPf6?D*ZSU,WX67?R2[}ųQe77{+vnkޒFmq$^ԛ.]L7Jv[VIdz|^LYʐ [ʧ{V暇Ey )'U^N[*n6w[P[Q.$ݩz$Ծ>eY2nvF,Ǡzpl2PY5 *[u#J5Yj6Tr$^B%n ]=]v=P~0T\`eWNөX VZ` mH vr/d QɅ #c V(ށJT2jTFf=.JS`)iB!"EK@͔RyX$&JBr U#حr cĮ6wwL&3>&sg$/P+e Y !T"YoMP_?J#.XnK= ^:@%һZ+@Sp7Dݦ5n 6=j*T\==[X^NPJ ܏Jmz[p5 LL؝Z7s:;0#`W`Y:YM`fnkCG"Hv#ٍ`ۑY+u5jgɖ-E`ie5VY1NΕ̽]d]zVC;tH]Hl9j'B6l$!-{G֓'[Dl%Vne"8m*dBV̞Ta>* $,Y`;`"Ed-q)nI3&i0㎀]ܫ^ rI֓ Yg`9ar?y2ldp]en j~dvKgnz2gkDɵFub]}냨}ENjJnD[hs 6}z)QRj-@;9-lMih;~U~+K?t*^`+w\mY!;tWS3Utג}LRWK{ZΙ[UK]RI6jYdMɶS5Yy1UA(Eɸ.ۍAtncT![LzT&ܫ[Uk9`jz+=dSMPۘI0HmޏCw2XY [{U'{<%t,:N;ou?9@^:?9?"_U8z MICROSOFT SHARED\STATIONERY\IVY.HTMWPROGRAM FILES\COMMON FILES\MICROSOFT SHARED\STATIONERY\STORY BOOK.HTMVPROGRAM FILES\COMMON FILES\MICROSOFT SHARED\STATIONERY\TECHNICAL.HTMXPROGRAM FILES\COMMON FILES\MICROSOFT SHARED\STATIONERTIKI LOUNGE.HTM'UPROGRAM FILES\MICROSOFT OFFICE\OFFICE\WEB PAGE TEMPLATES\CONTENT\CALENDAR.DOCUPROGRAM FILES\MICROSOFT OFFICE\OFFICE\WEB PAGE TEMPLATES\CONTENT\CALENDAR.DOCJUPROGRAM FILES\MICROSOFT OFFICE\OFFICE\WEB PAGE TEMPLATES\CONTENTCPYA 4,210 #  $@X r ??0OMPAX_AA. ` ?@@@@@@ @"@$@&@(@*@,@.@0@1@2@3@4@5@6@7@8@9@:@;@<@=@>@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@ r !`??OMPAX_B r !`??OMPAX_C r !`??OMPAX_D r `??OMPAX_TMH ` q= ףp?= ףp=? ףp= ?HzG?Q?{Gz?{Gz?{Gz??Q?Q?Q?Q?Q?Q?{Gz? ףp= ? ףp= ? ףp= ?{Gz?{Gz?Q?Q???{Gz?{Gz?{Gz?{Gz?Q?Q?Q?{Gz?? ףp= ?p= ף? ףp= ?Gz?RQ?HzG?zG?Q?zG?(\?333333?Q?ףp= ?ףp= ?(\?Q?Q?(\?(\?(\?333333?(\?HzG? ףp= ?? ףp= ?)\(? ףp= ?{Gz? ףp= ? ףp= ? ףp= ?{Gz???? ףp= ?)\(?Q?(\? ףp= ?zG??Q?(\?Gz?(\????RQ?ffffff?ףp= ?p= ף??RQ?{Gz?RQ?{Gz??HzG?Q?(\? ףp= ?(\?Q?RQ?ףp= ?p= ף?q= ףp?zG?RQ?{Gz?Q?Q?{Gz?{Gz?Q?{Gz?{Gz?{Gz?{Gz?{Gz?333333??ףp= ?Gz?)\(? ףp= ?{Gz?Q@RQ@p= ף?{Gz?Q?(\??Q?q= ףp?zG?Q?{Gz?zG?RQ?333333? ףp= ?????{Gz?{Gz??Q? ףp= ? ףp= ? ףp= ? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?)\(?ףp= ? ףp= ?(\?RQ?333333??(\?Gz?q= ףp?Q??Q? r `??OMPAX_BET ` (\?Q?p= ף?333333??(\? ףp= ?Gz?ףp= ?Gz??Q??p= ף?{Gz?\(\?zG?ףp= ?(\?= ףp=?Gz?{Gz?(\?ffffff?ףp= ?zG?p= ף?\(\?Q?ffffff?{Gz?333333?q= ףp?Q?= ףp=?Q?(\?zG?Q??{Gz?\(\?(\?ףp= ?333333?p= ף?RQ?zG? ףp= ??(\?Gz?Gz?Q?ףp= ?= ףp=?Q?RQ?(\??ffffff?)\(?333333??p= ף?ףp= ?{Gz?{Gz?(\?Q?Q?)\(?Q?\(\?Q??ףp= ?? ףp= ? ףp= ?Gz?333333?ffffff?zG?p= ף?zG?? ףp= ?= ףp=?p= ף?(\?RQ?Q?HzG??333333?(\?Q?)\(??? ףp= ??ףp= ??zG?333333?= ףp=?= ףp=? ףp= ?Q?HzG??ףp= ?zG?Gz?Q??= ףp=?(\?ffffff?333333?(\?p= ף?(\?(\?ffffff?(\?= ףp=?HzG?? ףp= ?Gz?q= ףp???Q? ףp= ?ffffff???Q?q= ףp???ףp= ?333333?(\?)\(?p= ף?Gz?333333? ףp= ?Q?(\?HzG?)\(?q= ףp?(\?333333?Q?{Gz?Q?ffffff?(\??Gz?Gz?\(\?Gz?333333?(\? r `??OMPAX_TUR r `??OMPAX_UND r `??OMPAX_H.T r `??OMPAX_J r `??OMPAX_MOMA r `??OMPAX_MOMB r `??OMPAX_INDA r `??OMPAX_INDB r `??OMPAX_MBET r  `??OMPAX_DIG ` 333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333?333333? r  `??OMPAX_OBS ` ?????????????????????????????????????????????????????????????????????????????????????????????????????? r `??OMPAX_SC1 r `??OMPAX_T.60 s Plot1$ `  ` C:\ORIGIN Fr,,s 9i@I@@2Tv$@п@?@E]tQl "N 9 S2? ף= ף=Pd1 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c ;B]{?.?]]]]]] $w  l "; $ Outer membrane protein A c P  38p?˗d1? 8 >>Legend  l "@P  3 8 \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) c SL+ 9_H? <>>D@YL  l "& < CONFORMATIONAL INDEX Input: Kyte-Doolittle scale c 1U@N޿ >>BXB  l "&  SEQUENCE NUMBER R `# R `# R   `# R   `# R   R   R l "@( q? R P@ п R  l "? R P@2 p@ R   R   R l "@2!? R P@N9 R  l "c'? R P@ N i@ R  R  R  R  R  R  LES\CONTENT.IE5\C6255O5E\LIST16[1].HTM3YWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\C6255O5E\MZT[1].HTMvF~5GLZ(gV`;Z<\%T&fe99љy<އn?snrV {"p׸5mƋfYb ā ju"cE)6(7.JUqQE)7.Jsq_n\"p7.JqsyȳĝQuѻp3|lf j[J-%7..ܸAڹAڍ;;ܸeJ2W t 7桰w>uW,r%s뼿_έnanuN-Vwrح[aN՝v;9Vw[anuGΐJmy7;\Yǭg疒@n UUn\ \r2sҍ+WLqswPxgs^G{@3bdZ:S f2-d JMjf@l;-WP Z }*LQU-sJn@Tg D ]0@<]w+)솁3U cLXBczD슡@c PU@L/1-` rnh#}f}+>c:l";8n8}[$5dpas\b7D@<+OK=ZR\bdW<ɮ<pdػJpU.@Uؽd luɠILd*4):xǘ^ƪ{^n.CxE'}^]S %إZ6cWFc*v]+Ⅿf11NԌ]{jԎ)wPvK \|J/@ٕ0'=Ȯ=T>~vm>{"PP`tePwaZdWnĴ)Y1v1dc^1dzpKbaW0a.f3%0UB )Lv:S g03P Lvq;B 3'+zϝ{;2EUB__#sOe> zȧ?mᴊBrM#NwxY|Tܦۤe457˲rNM,apJ2MeS)ŦTMmJT<-MN@gDm?^7^7;yy6 K k^#lh6nIw_c_mӧHgmچT%Sɯ#Hm:Tʦrl_Gk&^kLqNMKus:K6ӭJ$Nc?ESQNN?NݎwzZ;gtNTӜޥYj( 4>T4ͤEzqZHYj4SlZN餺6sO9;Fuw衔tVU^NO&YQ~NM]ڝ&:ΔTܩæ2vZM#tۮ%R_Z#hx(.]tY iMc޵{6[Yl2{ٛݷt62ZrN)[O9m3zeiw$B;qԝsz tRHwQDבO.ղ)S:5d*YjAR9N(Pur+~zr:Tj=AНNsq2f}Iнlѽa؊]v&ޣ4ܪ[F}5r=i䞘 -t:w&/v]8"L8,lrWʚ$[/L3U1{fjJDwJKm-2nfHOٔM#3U/OpgCqkiEC8֋Z=֫4ܤfrʖ;=N/S;S_qڴ*)bL+q:'vOTR%x?_8娊nyѴEӧ7ݾuON]Sj]C8M~Tsׯnm;Nm}Muɩ78˾{dߝ ~Yh_,_yh{/F֦rvhM;EixJN IBdH_%'FUiLQ J\UdOVYS>1e+ǫ5^ e^Lҟ^>(qL?g$*n2j[T]=U)T[5FPUWNfLTR{5AP=wiGuXuWWj_[ t]_OuM}nl~Lgv쳺~kM|ZWuڪ˪z=n$+h2B_FuzM^W]C?Pé}2Pm9TWfRRmLy@UشQyF0Z3^հުi2]u{~$~ ׃cRDsN0f V[Lc֩oM^P.J"^,yiFjKQ\{[=V6a֍j7H/ ^ۼzx)/~:U[:ɟtR뫎a ȁrQ-rرkQ|} :(\X:ҵ]S S ]<\AP^;f)9lg0CfldKaەY5[f<ڻCGl E~~oqi?YӻkD{oo.-T/53Ќl㙽EKg;ٻl'1Vv1inbvf?ҮESUS[f/m,֎mGfzMؚp<ȯgmOfhal_e֘[/f4F+#ϟ^`v^fh]ͬe;Y:-i1Bi!l[3|M3^An8lf6gS^HHc,6x]lm#-cvv-fjnVa֘Ͷvl;1MgH3ixoJvlO;hgqwi>dVCjzm]O `Ĭ+-m{,,Y:mǬ)̪<غ2W^m0+a{f&--f[l2m2iئ3Kų52 g̗r~{fhd;A>`!hcASwwr~luEb֗6v$|3-`Y m+۝̎N=.1VCSۺZٶfօ֕m=rO]rG%GMwօ)_| wpqqqq=ucà]===9(}03XVMf^[toqqq/|q8/\ .ŵŅppH\$. K%zqqCpCp)!q~=J ~ n n .W+>xꎂA-,ĭíǭ}ۂۂۂ[ۍۃۃ000n~_022{mmme#ϸqiiʩiڸ8wN|jp~8?\#\z{V+VxWpѸnnpppppo^ǥpi~,\. ō MMMčMMM 7777 !N.0p ҍXV+7/9Yo;;;wwww w wwwwwww䦜rNUUU9sZWWWW kkkkkkkkk uuuƵuwSoL<ҙxSiVg? rp98X88܈N Ҭ~?7 W+M---pE"-nn8W߅ۍۍۂ;;;ۍ;;;;;+Ǖqpqppqzu)=i5555pp`\0 DžqQh\4.E8UVg)Ϋ{q<77g?epiNsq,՜V:[[[[[[[ۈ+>mmmJqR6\((kYYYQU559===5N&48sUy|p>z8ujk$7Iz:68mK\.kuuu%p 8iq2.K2p8N9 t777{7777 W+-ŭŭ666vvvĝ]]]ĝ•qpqqq87wܕS3_뫯szW})GrZ gqp\0. Oc>>'Q>pI8\*.K e2qp#q#q#q \\>.---ũ9q)֙4X g?ۈۇ+ŕ:8+Õp3332UUY]]4* N硜S=ccթyUq8o7O1q!P\NNNP\ .g?qX:)|/^gjt\:.gƙqf\:n4n n .7 7 7 77777W+fVVV666vzSl)ͼٛ[k4w19}l=y KE^ԗJ%aHIIddd$O2ER Y(X^EGrXrJrYr[DsHmI#II7I/I?[̮i,(Dt<2gbvגcs'Tԓ4Ťt HIޗHH$$_Jvbv=$9%$)<%i(K%ђ8AX" i]JJVI%$k{'"Um"HH"$% dI$[2V2Y2|Iddd-&䢤\P^]HK$($IdJFJ&H%s$K$+%%[%2U]Σ"U$o$TI+$bvM%c$$3%5M,+"ų~&G0++:-u֯qAF䤙} hNLnIхXm``!o [k _ky_+?G/۞7^ZZl9>=rsZEee 擝242ؾU@?@@@@@A@A@B@B@C@C@D@D@E@E@F@F@G@G@H@H@I@I@J@J@K@K@L@L@M@M@N@N@O@O@P@@P@P@P@Q@@Q@Q@Q@R@@R@R@R@S@@S@S@S@T@@T@T@T@U@@U@U@U@V@@V@V@V@W@@W@W@W@X@@X@X@X@Y@@Y@Y@Y@Z@@Z@Z@Z@[@@[@[@[@\@@\@\@\@]@@]@]@]@^@@^@^@^@_@@_@_@_@`@ `@@`@``@`@`@`@`@a@ a@@a@`a@a@a@a@a@b@ b@@b@`b@b@b@b@b@c@ c@@c@`c@c@c@c@c@d@ d@@d@`d@d@d@d@d@e@ e@@e@`e@e@e@e@e@f@ f@@f@`f@f@f@f@f@g@ g@@g@`g@g@g@g@g@h@ h@@h@`h@h@,t,t,t,t,t,t,t,t,t,t r !`??UCRIESKE_B r !`??UCRIESKE_C r !`??UCRIESKE_D r  `??UCRIESKE_E p {Gz?Q???Q?Q?Q??Q?{Gz?{Gz?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q?Q? ףp= ?)\(?\(\?\(\?(\?(\@HzG@Q @p= ף @Q @RQ @ףp= @Q@ffffff@{Gz@(\?ףp= ?q= ףp?Gz?ffffff?(\?Q?zG?RQ?)\(?Gz?ffffff?(\?(\?q= ףp?RQ?RQ?ףp= ?= ףp=?zG??Q?\(\?Q?Q?\(\?)\(???Q?)\(?Q?Q?)\(?{Gz?Q?Q?Q??Q?{Gz?)\(?Q?Q?Q?Q??{Gz?{Gz?Q?Q?Q?{Gz?Q?{Gz?Q?Q??{Gz?Q?p= ף?333333?{Gz?RQ?RQ?333333?Q?? ףp= ?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?? ףp= ?= ףp=?Q?)\(??RQ@ ףp= @ףp= @Gz @\(\@\(\@Q@\(\@(\ @\(\ @)\(@ףp= @)\(@Q?p= ף?Q?Q? ףp= ?ffffff?RQ?= ףp=?ףp= ?333333?Q?)\(?)\(?(\?p= ף?{Gz?Q?Q???{Gz?{Gz?Q?Q?Q?Q?{Gz?Q?{Gz??333333? ףp= ??zG?Q?Q?p= ף?zG?RQ? ףp= ?RQ??Q?Q?q= ףp?Q?Q?@Q @Gz@@,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_F r `??UCRIESKE_G r `??UCRIESKE_H r `??UCRIESKE_I r `??UCRIESKE_J r `??UCRIESKE_K r `??UCRIESKE_L r `??UCRIESKE_M r `??UCRIESKE_N p ףp= ?{Gz?Q@Gz@Q?RQ?Gz?q= ףp?Q?333333?Q??333333??Q?q= ףp?(\?\(\????333333?)\(?(\?Gz?{Gz?q= ףp?)\(??(\?{Gz?p= ף?Q??RQ??RQ?{Gz??{Gz?Q?HzG?(\?Q?p= ף?@)\(@Q@333333??= ףp=?Q?Q?{Gz?{Gz?Q??{Gz? ףp= ?)\(? ףp= ?Q?(\?Q?(\?RQ?Q?RQ?ffffff?Gz?Q?Q@Gz @HzG @ףp= @zG@(\@= ףp=@Q?p= ף?(\?Gz?333333?= ףp=?{Gz?RQ?Q?Q?(\?ffffff?ffffff?)\(??Q?Q???{Gz?{Gz?Q?Q? ףp= ?Q?Q??Q??Q?Q?q= ףp?\(\?333333?\(\??(\?(\?333333??Q?)\(@@Gz??ffffff?(\?Q?(\?Gz?)\(?{Gz?\(\??HzG?Q? ףp= ?Q?)\(?zG?HzG??p= ף?)\(?)\(?= ףp=?p= ף?HzG?(\?Q?Q?333333?333333?= ףp=?Q?(\?(\@zG?Q?Gz?(\?{Gz?333333?ףp= ?(\?q= ףp?(\?{Gz?ףp= ?= ףp=?= ףp=?Gz?= ףp=?Q?(\@RQ@)\(@)\(@zG@ ףp= @)\( @Q @Q @q= ףp @Q @(\@= ףp=@?{Gz?ףp= ?Gz?{Gz?Q?ףp= ?Q?)\(?,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_O r `??UCRIESKE_P p ??????????????????,t,t,t,t,t,t,t,t,t,t r ``??UCRIESKE_Q p ??????????????????????????????????????,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_R p ףp= ?Q?zG?333333?= ףp=?Q?ףp= ?333333?(\?HzG?HzG?p= ף?Q?)\(?= ףp=?= ףp=?= ףp=?RQ?ffffff?Gz?Gz? ףp= ?Q?Q?ffffff? ףp= ?ffffff?ffffff?(\?RQ? ףp= ? ףp= ??= ףp=?Gz?(\?{Gz?)\(??zG?\(\??= ףp=?333333?p= ף?Q?Q?p= ף??HzG?q= ףp?q= ףp?ףp= ?zG?p= ף?Q?HzG?ףp= ?Q?\(\?zG??(\?333333?)\(?HzG?ffffff?Q?Q?zG?ffffff?Q?RQ?ffffff?ףp= ?Gz?Q?(\??q= ףp?)\(?(\?Gz?{Gz?{Gz?= ףp=?zG?{Gz?(\?q= ףp?Q?Gz?)\(?Q?(\?(\?Q?q= ףp?(\?(\?Q?Gz?\(\?{Gz?Q?ףp= ??(\??(\?Q? ףp= ?(\?? ףp= ??Q?(\?(\?Q?Q? ףp= ?Gz?)\(? ףp= ?)\(??q= ףp?(\?{Gz?p= ף?)\(?\(\? ףp= ??p= ף?Gz?ffffff?)\(?HzG?HzG?(\?(\?)\(?ffffff?Gz?Q?(\?RQ???HzG?\(\?= ףp=??{Gz?Q?Q?(\?Q?Q?ףp= ? ףp= ?Q?p= ף?Q?Q?ffffff?Gz?RQ?ffffff?q= ףp?Q?Gz?ףp= ?HzG???\(\??Q?)\(?Gz?Q?)\(?(\?(\?)\(?\(\??(\?Q?Q?Gz?zG?333333?,t,t,t,t,t,t,t,t,t,t r `??UCRIESKE_S p {Gz?Q?Q?{Gz?{Gz?{Gz?Q?Q?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?Q??)\(?p= ף??Gz?(\@q= ףp @{Gz@RQ@RQ@Gz@\(\@= ףp=@@(\@q= ףp @(\@Gz@RQ@@ffffff?HzG?Q? ףp= ?Q?)\(?333333?Q?Gz@HzG@Gz@RQ@Gz@Gz@333333@@ffffff@HzG@RQ@333333?Q?(\?)\(?Q??Q? ףp= ?{Gz?{Gz?Q?Q?Q?Q?Q? ףp= ?)\(?Q?{Gz?333333?333333?Q?)\(? ףp= ?{Gz?Q?Q?Q?Q?Q?Q?{Gz??{Gz?Q?)\(?Q?HzG?(\?{Gz?ףp= ?Q?(\?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q?? ףp= ?Q?(\??(\?@ffffff@Q@Gz@\(\@Q@@ ףp= @zG?HzG?(\?(\?q= ףp?zG??RQ?333333? ףp= ?q= ףp?Q??p= ף?Q? ףp= ?Q?Q??{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?{Gz?Q???Q?{Gz? ףp= ?)\(??)\(??Q?? ףp= ?{Gz??Q?333333?{Gz?HzG?Gz?p= ף?(\@= ףp= @q= ףp@333333@,t,t,t,t,t,t,t,t,t,t s Plot1$ `  ` D:\ORIGIN Fr,,s 9 l@I@@-"@@?@E]tQsl "N 9 S2? ף= ף=Pd1 c FY  b`ȿ&Y%ɿ>> L6  6 c FY C b`ȿ&Y%ɿ>> L5  5 c FY  +b`ȿ&Y%ɿ>> L4  4 c FY  b`ȿ&Y%ɿ>> L3  3 c FY , qb`ȿ&Y%ɿ>> L2  2 c FY  b`ȿ&Y%ɿ>> L1  1 c ZCK?+]*? H_  l "  pivot point c [X]r1??,>>  A c uG߃U?W#V w  l "u Rieske protein, bovine c P H 8p?˗d1? P >>Legend  l "@P H  P \L(1) %(1) \L(2) %(2) \L(3) %(3) \L(4) %(4) \L(5) %(5) \L(6) %(6) c J4)*aD@ >>D@YL  l "& i CONFORMATIONAL INDEX c $eX@ѝj7ݿ >>BXB  l "&  SEQUENCE NUMBER R  `# R `# R  `# R ``L># R `# R `# R   R   R l "@l= q? R P@  R  l "? R P@2 p@ R   R   R l "@k? R P@N9 R  l "c'? R P@ N  l@ R  R  R  R  R  R  WINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\QJ6BCHEZ\PARAMS[1].HTMMVWINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\QJ6BCHEZ\PEOPLE.HTM_CMP_BALANCE110_VBTN[1].GIFCUWINDOWS\TEMPORARY INTERNET FILES\CONT#8w4@Ѣx3H;]tDkDEkyezJZ>{\].l9qxU\q8J٧$7&~z$L$Gf:}\JJT.):Z2l)[LAuT"V,S<m4w([&qC|݊y;CKyͳss9k=_s9JlykqNXJXX!HXἵMX/Y)~Ig^:3ggO(閁o%)^V^i%)1^pzIJ|q_/I Nt.5;?Aÿffj2ƻ+*zhzh_onj|+,pu&:KFsW;s3XJc[/ g|zԨiQ?S~ƧGO3>5g|zԨiQ?S~ƧGO3>5g|z4[gV_?k0/Hsܻڼ.qf_롽}}ʻ}׫)22_יL.])O=';8x"n_Mpcxh,Tw+ \P$[e& >s d9 3(&+1 rZ,u4&mYdN}(xsnΥ&L96,:,)md1p%!TN燻Ecrc% J[?V:++ۏ J\GU$DPý#4di* 7Q}4KU ^]Su)J奨."@܍YS{H] *w*("K) R, n= YZ"^"KUu~P)jp} K9TUգ!MՂkYzFՐkT?DRipCM& KTc>Y[µ/,5-tP=spwgAw,U!3~YگmmA@V6puk<Vpw!t"K-Ʀ?Ⱥc_3"DWfy ze1CAA7CI!4|7L}4L[hƃYZc>+Ϭzf_f[,]`]f6 ,]e6VMڿ߅V)DJ0AE@p#!< j<7<"Kpi,&p)c1d)4]Bduׁ;ڃ,pC>,'pP;#N2@pYXqSEU,}k^f^m{i wʼYs +!TƼ wPLڦ=Quܻ?A-@#.@4 dݎǻ7!rXQ;J'L 4 di NwY!GRt[6 K'[pq_\1F wt/tO@䮑~"KWwd5A@;pOf KuQ@]A7T YT M K{~ P^'"tƀܓ= 6vp}@@i|v*Dnk}N .-X T#Ȅ˥Bd)6Y|g6`_:*@]ZzoY{U j\zdWKm=TUm6rkAmۢ=jh=^qj7h,hq/!nxTVYGPOpu;,uJGA/,=q1I8mr&Kp{uun, Q:|!YaʘܠҠ>"ppϚKAAndJ((!tҔ;hJ,m5Bv|#\?,}*YU;2<$D>i>"#B@>i>0@S@[a>aFrʌ3Arpzb, MYZíZrP S =CXbBA}()jF,Q JipyTY\ܵz :ݭ3@/9j% n{0d鰸lҜ TJK U"W ȭqMW K-Ž"IJ{Yp Ij&h2(\>- #kCKܳ[\Re rpͧ% XfZ r*tBJc"|BA+|*TY\UVP#tq w7@h`0#߁$mOuӿyD/iDϧ,Z&iKsv6ZΙ]$E^k7nHغ]II]2˕A_tK@{}cJݥk%Us]"KJjC]+K$uv.ߥ]#iK%Mwi\w~$e!#֍`9/BZ{ټ,J|2(;2 sȗTqsK]@}LEt1s!UתF*?R9u*  nQ[ςrHJPH?T ijvgJ(RyJ W;RԴDJ3}TU*H(F:a>S; ь@mff4RKX3Z 3jf"o~Pכ}Hr_)QޏT\sc.v)i.$2{u^uyIBTt Zn})}@77IYWvi~N4sRMoH-~[ Mn4iӹs6z.gLDyP/'VU4ǥHՂLʐo]WHcM<0j"ZTNd}ZD/w S djl09c>qmɏTM3#]UbUHi|o*|(֔4ƺHqk4zs혿:4~56_'6n1[Ž%s靘<\lF\$r˘KY,^ iK%ri.mw x%W|^gr$WNN5vu| [\.> "t+>K=Iң.ݎ4p59;_-㣹޵Dʺޮ B_~fM?`Cgƻ鏑֩Dygt!~'Eǯq=νG$~~op&diu< di%O/AF, s;{^Y*yJYj&'Cn晠ʠwEY K+P d)wxo|.3n*kiBSA&{f.+⚛yg@ij,UwЍRZ,\0Rq,)l h7vq"2EЋAAƋ"4XJ%p:,5Yj(=ȞAU^TZL] O굠үj\.tȒWRo]t6t;=@,5R;qoM Kf' K},-Qoe,mwTo;Pz< Kd. Kn4Td:f?Qu̻[aPu_\yOշqYBV(&~)2_ )2O i)c!*!MT*"hP%TtKe(T4}xG~g}wUAzKPFPVu"tuC:^)4GXds8T# ȾwmAiNl4ZVVKr(ŖURJeM4j=zòz$ҽDz)z4z e{ޱdZbγZW6FeBMjZdbt@iZ@c^{SݬoPטW|yG1_c$у( !K@w1-Q'z-TG(kQdgtӲ#t*bOL@1-$(kL`LGKeq ~#f:^bQ%Q EԲ2b8NU\Cu]BH+Ped}[>]Iu~#Kn:E7b>[G6˼_5e oZgjoL/U~GQT7 T*aV!M%/쫳= D P~Ux*Vzɷjw]P> xVC(A'z60 @|Bעho4LyQr]8(_od1]F_o(_odZ5݈UF6ѯs2|0==Lu6JP&QlW6{Ga(#<;UP gzVGC.LEW:{vLC_nhƠ_n32Bܲq! 2mD魐e{ JOҧPiCԧ*lt}>svEim1݉bW%A}z7"(_'J?etjO|UC7_CV^?Ctde: 'A>G[ ?[_/ gz˲͓M>J6M$Fd7?Js3YwuCid[v|tUXvlAUP~\ʏVYgنN]ݍL6@vQ xC~EסFQ :pNVV@^G4f4Ց?}ӏe/i4LKF~i893C-}9;|*%׶lv~ pg'jIt4.R6bZkipgtJO̖ #pfQ ,h J-[egZZ=~U]ը~~&TVduT7kOkhEQzE^@ptQnVXvF]t (l,jqdgxtJZ,;J'#QzOc^y;˾GW(]AdQ,J,/S8iYv'zVζhٍ/t}ղr.b~O>IBiov$h:J\D6F@cQ 1,if^dKZbX.6J ڒ&WQkYim@iL_Qz5Y}.Nv5o;tkJF)vKY|۹gJ}Ȟv|GDW>]pV7:wEm~j{ܠͭj; Sf8JUGf>@v]Y]TβQgS]ɋSoՕﮤ:S?Ft]5Tr~Ό=[m FmϓֺU+%}t+C꫶/H'=:Nm7SkxTFE۸}AJ RܳڎJϦƉz,:IR= (Ul UO#xSN@VlTDkQZX }RMr>C%թӚ֤ZBk]9N:jitG5b'k]Tp g嶛 'iǥbXrb@1LiHSRe9jReRzK;U@ݲb-ۖC[Q굷*>K-@߲YgXօ#(EQ+}Yw0ijuQt^zWP =[DgAeYo#ag>e/:W\OvCQ۬Wɭ9JFKAQ 7Ƚ>#̲V2G@aՒA>#l!>,+&C} fٶa#l>,{5#lCZ:dg|DLb6lJ6GT45Fun6C؏}=V7Ⱦf-(|6yt!++/r(%2UCi\YD桦( XC^F=Q5xl̷+>˦Qqlj VB;(VX,R_dEu5z:o8EMqzI&kK@eY}Ϯ-zX'(|H6Nע(櫥udztJ}A]( _KP zVI7QJ&t8Բe[dT`L'{^Fe7'σ{7zϒ=/PكG3 S;P$Y')6Qd%z(_EzvCQډ޲ҮR^-.2lc ( lL( l٬L3(_{6? P/w>J&FTCZ(`MH TmcRSƨ%P*1& I$VG{sjڦ\=߲p.3҇ZQP~oM6D(>7fz.(>3N9TG(5-l(WZǬV+ZA@GM\ mBَPKlԲD8T&Q' & r֥'j]E= A>O0(mt_0kZ/@G55UZ{wYZzA9se> kaV2ZZtYuB+&龷aMEk)o7kޖP~~Vc=zXO1{8+U5{i=NEP7| (gV]:oPLd鞄r`յb P ߻Nl:S#F]3-\=O*Zg.Ie],^Ck"I硦A9TڳgPyPԊBC9g"Q6skUr(TNPgc[]"_ Zkz ~(Z׺S>T(x\eaPα@@'XjW:zrij HZN+iZPMƑqs,y'A93Z2LrYhf\ajk ̤Ynf׬43 g--L킙yi+)=#}JQm{ ([Z2XB&*=C$gsjf+=f3s>lv{rҳSzVR*ܥ ~+U u_ޯYwqYK>l- ?+p| e YAZp p0L`6^J&( .@ A_ (0 ,`+( \ P &0 䂅7:v8 >_+CAl#  AA>X^kF.({p xā` RA}z V`v*!u<  ڂν ĀX0  /B(o- T v tAo0 #AX" vGIp9vh>g\"٫=Ͼu)5..l3.\ti\vRe\\t9l\Rk\j]t3.u.4]..0.7\tBHKq uѥqiKqrѥqK_EXKqIteqd2Ee.%E<"EBRKq)vѥĸ޸weqKq)sѥҸTrȸrѥڸTrڸvѥ޸Իd\\tf\Y3h_]\ ^B6# oid.oj̈́3 'ӟWcUX}U_u]f^0WXwb3VĪ|v09v# [d;q@DbW+&{G4)y3Eof( D8+JD\/V1WRDKXDi&D^%e K"Bn]d-׈A*mm2E&,reZ(3Uܮ~U yO֩yJcNۿG~*M{iO#tTES@*T3Τ1|n˧sjP׬j#VKVJ"uqU#UzU+ی`eAQTURU<^TUU(W3b:&6bzFPUPry>pʹ]WoP[_Eϯb|OX_ۮFɾjVeԳ sW^}J-LSdSL=skP^j΄u}BukUohW atn,`kE.Rk$ΣAQ;:iE=?g/8g1^< `5&=599禦g1;/=+5p&6b<=bV{zrgL5;ӕ q!8ddcF 7|dEFO03x0γo9M#}G|؄$DF&0 ^~=苞oM/bxRQQ8Upszg͚84~q Otz=/B4y#}d(B&SI=147X60&RN=6633.HTMXWINDOWS\TEMPORARY INTERNET FILES\CO8:rtdhjlnptvOJQJ j<Uja> CJUVhmHnH jUjn> CJUVhmHnH jU j Uj> CJUVhmHnH+0P/ =!"P#$%+0P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"#$%. 00P/ =!"#$%. 00P/ =!"#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%. 00P/ =!"P#$%+0P/ =!"P#$%`!*.hCwmފA~ U8c*xԚ NUǟ1cfq*LT$F2!9E%" BRT$)!a0 woϽnz}{꺭{j-'BGPB'e1EQPP(j+7- %^: :L⟹9 IlB#= ʋ:PhY0iGĖzLt$O^,qz>|Y,ku+r_UN=`_pD^^#]Ucb?s fnO$W %Ӭն_E#nAժc&mtC|7j]ܠ>)/?4={Wus͇nMɯڍ ۈȈmE*2b|qX3Fo˷kۈO8k);}74//x]3^3_9%_N{IDDvy y gum"hE(Њ@K76/͋Pul^-)l"h6xk)Ranj(j\']sfi#Xa6Z--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻ*ڼkkjjڸzfc/ű՗Kqltl8RKql:R[}=[})T'5[}=[})TV_cUe9JΙöެ6 zZ--Z2ؼ m mWۼ0kaΛ6CټZR6o:i:AڼaaXK6 ke8o1_Ŏͻv}SO7o.cr9yFa`EdMO`Kpg",X"|(jc(lc '{0'ۃE>qVę 1.cdQ 1r 2CwB9N"-/;3POp\˵"wA m&h/@G9 :4|C|+O20Cd )/Ack9%cTpns0>BSQ[,} +od۵n؂}l얗!Cfyp\2~"+BeVW60 )rʆ+-**a[ C)h6j;4Ƽ m}T]yxBe%q+83FŘNv24}0f)1V_\|f: ?wb+ .Bz?(N(}HA:^]B֥t](By ns^5*B}FlJ3 zjWҫ;aOG1f0gFjߤa<I5olx9z |ç8z,XW詰JPXgFLخ?ݺ+dZp@8K CyR-*nj'u8BDxZ%@J IoV Zp+p!%xV ,Ga<>uO\>x&~Wr0MOW ^3xDWO!z:☳<|CcXaR6!lVbm8!AS} BD44į0_8f:V~eXPc3T K٬o6-If*0kY ulgҌM#hg*A{:q]LMxʔO/K3/IWCi=|G6fZx &~60הy97Bj٠V]ʌߛz)MjsMd8`.M6gtq@.ĸeHqo7tY'u;GWp{A-̻w㡁; +!̈́f xНܙsӠ[ :n}C> ]z0~ݭG`Ǻq)8t7Jާgn1}[/pG/`_atj=7a`{xs؍3]ߜr& #K._ݐqe8oAqo0:Ai=f.)S=0uq/F#짉 ͽ,h靁v H6A'o tVo=Bw þ^p/dFyW`wa?oz{a23 }a?s0[ հ[K{ fxX㍁uL؈v1O8Qw b\y`yA^ OCL8s$9\ADZ93/aIԄwV(ҒkLJZ[vDZam|h /6i. Y[ diL{|qrؕjLqʺ%h*0JkT{CZ{T"_nTIj+S(Q*+!m ktIi$;X[r㛲,}K;K$(NH(]FTYr{rfIpI7Av׷=W |x1AWU$w&kJ|n]+FWuBzmUyu{VW#W]LurPPjMrB-ҪAm#j[n' SS"_;HԅNAE$ǵPn@}䮀nL^mД}Мr3AVDa[m h{3"_|<'w.h\{vB#tH#2dKrC0~x@;>v䞃GC*S'μyMZEM?"0y(le4F3#bLȍ604> /W![R.Q=﯎M<_zא9D fLg0iHԙ(x")S}!LՈwc*JX튎!(xDZAKtki;?0aKGڧLohV{S"@Y=OZ#Sv[x35"EC:Vօ*Vg5i(KieDDV3}U>$ 'mDW7=K|{Z{u#cDw tU *0B|9Z*IC|uR1enkV2}BRDLV͔Y>&D-D_ƬV_!^jȲ&rD|Q(DTWM'"n!"=QT&j5)j1IUԣ=XKOX5-G$]$§9y?iq Q!"_$Ȧ*U$2LlNZ*D& msDx D<قc"_|dKpX'"OOA2]fUH+T5iUzd]N D@!m"[D|Ֆ3`ݵLݡڑv0>}% GɍV+#I`n}ݞfL)DhԖݮ:I"_amPvGI4sX[;-"J60md7]w$3qa7UdzZAEG(%Qf27E#[2U$2dH!`2B$*TBEzu뜽Y{<{7]sZ&I{iA;Ku6򦒴S]F[#inCܮjvGt6@ڠț˃h-h + jitt@CL?SmLI'{δ\+ʏtr;*`L}YՋhnF zKYƧ\&0)w2 m)V>LR ֱ |YtIG|YVdڈ?lA_/>MW{[io/i/WڄSoht]Ctm kϑ(ߣP|(> Dqutܥn(>}M[gx{h3U3P|3yANw{QE~ѮW]|XmUUUAޜͻ_PQa*+yFۦyRY`ҦBތӆ^Dha(򦭶t w':B[xGhQTySJ[a{ B{v(Ky+U7yjNWf'  ^N⻟S7=C"ohyA%L{g9yLV={dSPҨtEv mj# װTO]ȇ״-- δRȇ-po1G m 3h"3iO#^8ù;,\*ƪ&(ɮ2ppUiCTCQj:G*wZ•K6WmG>|B$WE)yPk*Q5ڮ:L˅(~Mbt? wmr 1UR0 GތRMt]\N[#WP|zwr%^b_N\I}q  FyݴMo=6_CP\%)UA[ISyOkjWݢys4VBޔ3T%7j;IZӿU]Z(}Zțh6fkC{I5 U/MgזByskGAyskO@Uu`Zա{Cpimt!o~ky횎vp:P8Tu:>#DmlD vKg2 UEۃv퉮ENSu}iUFޔhE TytgP>I\:bLVtdpQ m!V(;4oQ8tId;2vz%ojcCgڬk":=[UZXڅP| 6țn1mx4hN' h"fEn"ZY*{lmUIL<_^C7Ŵ+QYMumt:.yݍi.o:[3ԙJ{ZgP4N{Mf(TuLf(~as@[:V0LiJT( έU_Hns:bQWŧ$6LAެ/i t!oj'_3'Yߠ!(UO괛|KkzyXnE\-iuUu7yS\UXFGPXӸv~riQyR\y]hyN[Uovu?ZZ"o&ysn9O[ UqvI=L۽tݏv;u:]fVBQ(>O DکjAj AT=ԪQ5+R+i~{VFZEU%'Ӻ(>9ǙO m>~ _ ;nRb34>MUMkiTQ|hTQѶƊ[aHtomTCu: Sȇu]AD{ zy3I5Ch aڧt-DE+Lj\aT.N; C>S芠 (M(L o^.yL btK׃әss麑~K\[/J$kkȥLhD}7j{ٕBQ|4NG;'9L:bQ|pn:P|ΐ6W6(>]H+xO$^Cy(>gH!3 ηGiUPX'jມțڹ- F1ODmTuuZ*}Le7mOn.>Fͻ'\?g;]7kk>ț}Q+=nMț+ղOțT)?D7 kBm;h kBm볁骂šPl, RDaM=EJP[l0jJP[iT3 +9Zy4""o4#!R:C͘tfțtp=@"ogo W-t) לlj"e]ȇW(t Π f,ڤl6z Ρ-FːG\lp4ͧ:grdt v*yB5Q\uNohQ݃g]Lzp.=zp/zpYF[zpI+}|rvȮ@$Ҵ[NCqZE.½U贡{X}iTQgZEV(36խAP\}@[Zo-mj;u#(Ӽ*U߇j(6k U&㪞(>h$f4 U')Zo+@0_8UJNW8ك~tX;bGQ|u}>I$O=1y(.YX4ݥG}Q]*@k#Qkûu2}S(3Ֆ¨򦆪NϐPIwR;Iu¥AWj'L}芢țUu:y4^RryLAq)N;b(8NAgz;N%PuwJNwgb(8gc(FlJsʡ|( љ|z]NJ ǁխ(CJ:TT$oq+(z:?Tph.@pij7hR9xTDj1=[UySYj.:"͵RvC#Rk/ț"@ a(_^&"o˥ErZ?T@*~n\ȵL?QmLMh7r V]e-E#w(܋&}L'Jc4J0}Z5Nr?MjwNw~.wR;WZ2(WPܭjEۯڇNWk'-(Ik>%\jCh{|wQ;;c\ŽPCq_K:Tg5 ŝч٭ڍ#ʠG<wsSk1(vG}7ij^t-qt3=iUl/Q+Dq'7$#Lu0Kh' Y?ڇٓh= dl>khLlgmE65G6{vC,j=Ǵ~j a$"oZfQ;Vf@664{ CތƠXӲ1g/f.&Vg5ț-$5f_6v4!oruZ}V;ŷhU T Uw5-țv:fAigyjNgYhB3ΦSGlsh;T;L~CqWan:+PGL<wjr7vf>ߡRFqt/{ iUcPܯ]D^ojtC>rKRFqy)2SVJu+hue%^yj ]NXcVGPܭ_E//d-Yޒ hl&1ތV3 ڇo|oQ.iwPngzsU{B.w 9qtL~_=okh_J~hdBNAQ\YޖBLHa4F{ANWg@#)W )eiKZY+> h+AiJe/B+ô`;x%(㳻w@Y<-LS0u% ! LTIͣ<ʣ$MMJMM< M;MQ 5541T꣗g9sY!^<)a̒8~H'9ijeβo]~N!e{rHO#HˬW 0f@1Rk &YH899\ֻ$&.kS$fȶd6Cb:領!{4-2*~ |^,Z29Z.g r6VR6W@'S;_bizN$}Mz4G^(2ݨ{CCsB[< :/U ›Qx0 130a>+,÷Xu؀-؎l^Q)A!.2( : G#fGKA$'4: E]u[*u 01!`:fbbc)V k ;؏:8(YG,|Q*{PS QhxG$rz)gݐB_ kHǛQx0  +,÷Xu؈I{qGqppW`yYaGYT@D5P uq[݀fGKA$b"R701c0CLt§XX,zl6U pp8(B1,v/*{PA4E#D="QIHF z/5c(h{ |OXt1[vg!|E\ePjp>܏h(Z "80 ZR>'Ⱦǭ4֭%nݮh? dUZs'`kz3{a9զ04{Xo%m2mzz>avg;z]{japi8U{h6]US~=S]]_l([4TFzs_[v-e*!B[⺮p#}txtMNLMMJ-J:2_mszb1ѭcb?቉nn*T 4Rղv,ԿB#7ҺzZ]Jj׷+[R:tMLI T[QOĭj;W?}ޙ87Gg}q#[F\Q-"bK޽cp}X4P_ϫ [ηtB: YYYJV^2{i2mL8]ў}+&`YcY}-1敢 {`!65Li()jhGA~ $U8xԙ es{Gq4%Fa23FfFT9O(%%IJA%r#D'P2ڳ׺캮޾mk}?s3;/ u|RTP\YS{3Ա%QUNF"Ց+'zjn5_ρ@XO*^A (:!Oڹ wPP,Oxi\󟭋^h=Zx7?>O7=URRRZhFPj: =++hɍ qWmJ?{%%{0XSGi2YD{Hjϲ-iY q~F{Pe~s*>Y3Y5{euVF,؈Ie6b[IxxiX^FL.x-;E4K41YYFt UԒSQoMa$/~#ywzH^LE yW%/Lkz yBSQosH6;GXb*Kż#΋xEa{!zf:8?1۱O q^6oH^{[h[h%Zɛněn$*%~$=bO~7Hog1:;|DS~==K&JHW 0[bgyvWGZ70Pu#DĆ{Է0V *'t3)fSsTΧX@D ֐Hb/yߨ f0̄f` b8M\lRL*~LmS|FKӚ7{$Ϧ lZgTh[6ֲXM(QQȲ9Ko6Plv(%06O 6x>c5:հî |e[O/֣a8 9a>Ԇ3Bh@3΅aٶ`'hWA^xb_(E@><d}! (&߀S.>x!T C?I}|N}}M}~K1 c>VC+nA`ŭ*x'=d?( S` Φ_&[Al"YL)|F_P~C9%m8<.ÅX- kQ$n@фp>QNkpk17\ GGx1 O~>8bN%7Nc^"Sث7ӕRp{09Nj-<x&NjLco;Lev:o/SZ{zfRҰ9]%vbtS*W7)_=ث┯P2&VX;IqWmÓqW3` {dwUx89Au8]Lc8R[[eUYZqWAM XMd嫙PYt柮|5 Zwb5nt*`V/Ў ՗o[`$$OW;┯>-q*x!VR6{uaIU3x_p+_ػ W7ӕ{ʩi|5~J*V6l Ne+NȬSG}7hjβ*U]^ X]^y1N^SXY^/zǬ&])_ [VT?aouVPofoS;Y$sj'{?8uDV;ث:^Ԟ8E+G}.+G햕>֙*!FtEޣN#6{_FqWUÐ * c2>1G.i7XaL.]W2^]jY/hlrO<ysmV!GaU : QLJ[Mj ;J b*FFO22Z%YYL #Jrԑ(QFV&[3൦*mvAG,\0̂^q4n36Fg]&@1c0.3gRmDSF25L=QL56F`@1/T+'+f G=W^4Q | p2zRw"ʬG^sћ `=w{#̾g=oK_D;Aϟ jN}Ha~r vZD\f%\glC2Ӊ>YPm2&` GAh V(J%e:c2UIr3P'Q:9D=](ލp70XB&aEeOw7qx/0W%ΆI({z΃)L&Ze2<jr 5l@el[h$'wD[!*vth_8~9s lJ ,8EE aG G6-%t5ejj5}ZMVÕX-pkp++e}m{>yY^-}==y犜 7yEuMB %VnR7 U+Ĉ\UJȶ…FUwdE:e.3!^0I\n<gT>G%b9Pu$YXПcE9|R@mNs^qټ[HV%*U ݳ0U?;VzGjjThɪV biJ+{TkУxHQVFn,t%U:DBz|IT#\NT: SIFڌM*5beu*#A.4"HhQ:yc|B:H=F1o\M Ud/,}IuRYO#4?lΐk<gIyT%-T^W+/ӥ5m :RVVjݺAFZ=UgMV!VPz6lkcEZ=޷BU炶buڭR3Yn=妽*mwvunGY,^vz-;it(UNTzSQ/STq~;:ҶU>avujDڅVop`UN* qSJDVU+#ܔR=_[{j/UJ;ʶui۪V sP`},#eٯ$jϙ3I25~kC=Ο빚*p[bʹʑB܉ ܅Y܋a#؀؂mx;,UtN>OW8"Cc1E!J0 wc6cK +Њ6BGPѱQt$Np> C4b$G2}RL AjрXXXMhB3Z;{pq у3KvDb8␈1HA:b31ը/ߚpg}jU;7{YxZ+.MZ`V'SR0UKQ߿/];nt{?"f'pL)ES3'GGOʙILPn >NTG`zm`}'^`Jcs[797HVP{† FNnh]?gV< ٞ3Cv󃃯u\('_嫏VTh/e9%Ssses֜`NH{j#Ã[C#+vOvO+g=45mQO7zwY'c60G&9PwKt?x3z`!=w5\V~.9~ U8 x՚ tTo1 /D DAK-XALBxWhyb( 0+*h)CRbX m8&* P! x@ 9mr6;wwwf}/yKQ'<{,勉?L~Ss#qgѾM) "[.IyNmL/DA3~4m{azqCOow9%s.ͥo/,&|Ԗ"IMW$[Z^" >?m=^"=4E%]tl>'T=Vf}[R}f*bqc حz|F=vo_XC=6ĕ/q3Rvq\v%\ m/fx8Xn(& )鲤 ))RU+W&vue慔7~ߨul^H~\i6y#/?bqzf!ns3;pl]=ۼgع.!eCryҺri2ː6oYl^̹ټu \y[ݙۼΎ/gLc;Q9[AS|[AQ|VVPo+ho+(xEU;g+ho+(߷4ŷqF\Qo:[A2NO\-'3_3_C*֌u34[3ճ͛|ykR=l^+Z)W.+6/ù i֑uŜ{NXye ՝/| cu<_)̈<:he fR5m,[Z,KZS: 6TvSeVV)Ko2 U*ʊ e:̊˲hd_pu hA#kaPȈ(%P')m+ŹZ@)^>dNn[^ @OX-AFEpr'tEn$wQ=A #zpq(dDהs@M@F#7@PȈ?!pp&Opjqp xн #V7MU?PMBt 7\M _Mn]2 u7-45F zd>A`b+ эa #˥p+rУ #pU #nk@7# OV> K> 2"3 .]na&8)Ge tdD^2{ 2b-n9Z27M@F| CBѾTE:MMbA.Nh;גlDQOP'b0tI}ms@bD_=)?E18+Px ܝ ,XWИb?hxT '"XA<.bRPwL(,1.W/!:DL-f){w!Q wXd\  Ȉb-Z #{9z{"Vxx уu#-QQ}pHCptԙjE+k) ԗa==΅CAcAFBAo"zu+%  (8c4q*r4t+ϩEt -r[,.5p"zŽv!:D@ #谽 !½GI܏dYp1jN#Ap;mJAM5`mD9C4J߅Ѝ M/?4яts?)ZhcZ 59Eͤ7z?GeScAtD"v5"Ng͡@Q2 m}n] I9i0 A0rH#'] ڂ$g}[#K4H.At\ w\'Dt7M.#:K'w-AA;\~#)E~bGR }W2td,8 U3DU-ڪA #.Qp=UP/רΠ #Fnp7onQ!:S]@Q3jGU?JTypϫj0HnUcWA5FDD(O8}gڃ³9\h./ AAF~eѻ{y9h!Ȉy%\Ŀm 7@F7>譠z2E #bpٺdD~ n~4RMop~Э #nI {G셕oKzakno:w > Oϗv_nuVgMvet^WH+N3&{͹'mݶں]ݶm\u WF^Y^~ ΰr-\Geo/.܇rIAv8'}ٹ>7TjvgS]Jak,2UA}vغ|D./p [Sus\.hU5]BmB sКP]֝LAصV% P]2].hUVa$g$li:Ѻ"0zPeFV[:Z+*T%gP:Oa[?OF,Z|9t5Ƕ _ڽ%\(H^TUg\ WpZWqE|~1WMKQc(\ h까 mw:vr-ܯy./xjw7 qpj\*ƺki|>ef{v*N9p.7cnurn4pns%p9ׅ%Ia\i]s1Ɋ*;V8¹%K8{O0oޔu>V%pMys++kqNp.\Ja\.׹\o.w\\sp &;ǹں\bpsa.wܹR[ Vp ΍X\ n-½Ε;W ps p{9:s:#] J;W\)a5 ſZ_Tx*W} d{WwOM@nvz[sôɭҧ2hx okv~[{RϝSV3ĎE?;5Sru=?ZѺ[kU ܯ ?~W ..Sk7J^ju=csff|شM"[drA9CrIO'g`r.z;YYrippRG<ffyfo[5^}mW^*гwjh1 a#Ik`!b#xa3:j%^ @b]x6x͛ NߵA)# q)r!&FQd;IȉB;rT;jDmvQkdw=?Lvϳ5Xj,V3 bCb َ1sȋQ#Xm8^kKI_7P[T'JE| }E2-Tbeh=߯kF KF<'ny'~?n^>j8~ _WO8=$Oِ4z_ϋwJ^yHޯ6p(06 M; ٢,ܗvsޔV2f~ίʅf'9}Ա *:ViltF#6-hĬ2qFlVf#G#6/aIJ8F#fш-ڴU]e:5c%۬/Z?T &٫QkX¸;HqX8Uc ֒UTb,Ra\Tc 6mLii"+g,RaE Fl-p?X9̠Cu$քlZ*5W-/>}blX8tƥw7k,ŭˍ[\.!&7,qdxZ~ظUPw*hgTYzVAU * * <Z2B* ZYxVAUPgHfTYxVA+<*г :_Bc{S[k.g5clZ\_jq>qd7,Y+gq-.,7nq|c|@6  ;z%Qja];}'<٨+-vqP3jnWutl{W{{έ:jjc Cn0" l{Su;꺢VC6u`G ci(n>؇GM/Է4v@k3`M``W-q<87(f5QQPf6?D*ZSU,WX67?R2[}ųQe77{+vnkޒFmq$^ԛ.]L7Jv[VIdz|^LYʐ [ʧ{V暇Ey )'U^N[*n6w[P[Q.$ݩz$Ծ>eY2nvF,Ǡzpl2PY5 *[u#J5Yj6Tr$^B%n ]=]v=P~0T\`eWNөX VZ` mH vr/d QɅ #c V(ށJT2jTFf=.JS`)iB!"EK@͔RyX$&JBr U#حr cĮ6wwL&3>&sg$/P+e Y !T"YoMP_?J#.XnK= ^:@%һZ+@Sp7Dݦ5n 6=j*T\==[X^NPJ ܏Jmz[p5 LL؝Z7s:;0#`W`Y:YM`fnkCG"Hv#ٍ`ۑY+u5jgɖ-E`ie5VY1NΕ̽]d]zVC;tH]Hl9j'B6l$!-{G֓'[Dl%Vne"8m*dBV̞Ta>* $,Y`;`"Ed-q)nI3&i0㎀]ܫ^ rI֓ Yg`9ar?y2ldp]en j~dvKgnz2gkDɵFub]}냨}ENjJnD[hs 6}z)QRj-@;9-lMih;~U~+K?t*^`+w\mY!;tWS3Utג}LRWK{ZΙ[UK]RI6jYdMɶS5Yy1UA(Eɸ.ۍAtncT![LzT&ܫ[Uk9`jz+=dSMPۘI0HmޏCw2XY [{U'{<%t,:N;ou?9@^:?9?"_U8z vF~5GLZ(gV`;Z<\%T&fe99љy<އn?snrV {"p׸5mƋfYb ā ju"cE)6(7.JUqQE)7.Jsq_n\"p7.JqsyȳĝQuѻp3|lf j[J-%7..ܸAڹAڍ;;ܸeJ2W t 7桰w>uW,r%s뼿_έnanuN-Vwrح[aN՝v;9Vw[anuGΐJmy7;\Yǭg疒@n UUn\ \r2sҍ+WLqswPxgs^G{@3bdZ:S f2-d JMjf@l;-WP Z }*LQU-sJn@Tg D ]0@<]w+)솁3U cLXBczD슡@c PU@L/1-` rnh#}f}+>c:l";8n8}[$5dpas\b7D@<+OK=ZR\bdW<ɮ<pdػJpU.@Uؽd luɠILd*4):xǘ^ƪ{^n.CxE'}^]S %إZ6cWFc*v]+Ⅿf11NԌ]{jԎ)wPvK \|J/@ٕ0'=Ȯ=T>~vm>{"PP`tePwaZdWnĴ)Y1v1dc^1dzpKbaW0a.f3%0UB )Lv:S g03P Lvq;B 3'+zϝ{;2EUB__#sOe> zȧ?mᴊBrM#NwxY|Tܦۤe457˲rNM,apJ2MeS)ŦTMmJT<-MN@gDm?^7^7;yy6 K k^#lh6nIw_c_mӧHgmچT%Sɯ#Hm:Tʦrl_Gk&^kLqNMKus:K6ӭJ$Nc?ESQNN?NݎwzZ;gtNTӜޥYj( 4>T4ͤEzqZHYj4SlZN餺6sO9;Fuw衔tVU^NO&YQ~NM]ڝ&:ΔTܩæ2vZM#tۮ%R_Z#hx(.]tY iMc޵{6[Yl2{ٛݷt62ZrN)[O9m3zeiw$B;qԝsz tRHwQDבO.ղ)S:5d*YjAR9N(Pur+~zr:Tj=AНNsq2f}Iнlѽa؊]v&ޣ4ܪ[F}5r=i䞘 -t:w&/v]8"L8,lrWʚ$[/L3U1{fjJDwJKm-2nfHOٔM#3U/OpgCqkiEC8֋Z=֫4ܤfrʖ;=N/S;S_qڴ*)bL+q:'vOTR%x?_8娊nyѴEӧ7ݾuON]Sj]C8M~Tsׯnm;Nm}Muɩ78˾{dߝ ~Yh_,_yh{/F֦rvhM;EixJN IBdH_%'FUiLQ J\UdOVYS>1e+ǫ5^ e^Lҟ^>(qL?g$*n2j[T]=U)T[5FPUWNfLTR{5AP=wiGuXuWWj_[ t]_OuM}nl~Lgv쳺~kM|ZWuڪ˪z=n$+h2B_FuzM^W]C?Pé}2Pm9TWfRRmLy@UشQyF0Z3^հުi2]u{~$~ ׃cRDsN0f V[Lc֩oM^P.J"^,yiFjKQ\{[=V6a֍j7H/ ^ۼzx)/~:U[:ɟtR뫎a ȁrQ-rرkQ|} :(\X:ҵ]S S ]<\AP^;f)9lg0CfldKaەY5[f<ڻCGl E~~oqi?YӻkD{oo.-T/53Ќl㙽EKg;ٻl'1Vv1inbvf?ҮESUS[f/m,֎mGfzMؚp<ȯgmOfhal_e֘[/f4F+#ϟ^`v^fh]ͬe;Y:-i1Bi!l[3|M3^An8lf6gS^HHc,6x]lm#-cvv-fjnVa֘Ͷvl;1MgH3ixoJvlO;hgqwi>dVCjzm]O `Ĭ+-m{,,Y:mǬ)̪<غ2W^m0+a{f&--f[l2m2iئ3Kų52 g̗r~{fhd;A>`!hcASwwr~luEb֗6v$|3-`Y m+۝̎N=.1VCSۺZٶfօ֕m=rO]rG%GMwօ)_| wpqqqq=ucà]===9(}03XVMf^[toqqq/|q8/\ .ŵŅppH\$. K%zqqCpCp)!q~=J ~ n n .W+>xꎂA-,ĭíǭ}ۂۂۂ[ۍۃۃ000n~_022{mmme#ϸqiiʩiڸ8wN|jp~8?\#\z{V+VxWpѸnnpppppo^ǥpi~,\. ō MMMčMMM 7777 !N.0p ҍXV+7/9Yo;;;wwww w wwwwwww䦜rNUUU9sZWWWW kkkkkkkkk uuuƵuwSoL<ҙxSiVg? rp98X88܈N Ҭ~?7 W+M---pE"-nn8W߅ۍۍۂ;;;ۍ;;;;;+Ǖqpqppqzu)=i5555pp`\0 DžqQh\4.E8UVg)Ϋ{q<77g?epiNsq,՜V:[[[[[[[ۈ+>mmmJqR6\((kYYYQU559===5N&48sUy|p>z8ujk$7Iz:68mK\.kuuu%p 8iq2.K2p8N9 t777{7777 W+-ŭŭ666vvvĝ]]]ĝ•qpqqq87wܕS3_뫯szW})GrZ gqp\0. Oc>>'Q>pI8\*.K e2qp#q#q#q \\>.---ũ9q)֙4X g?ۈۇ+ŕ:8+Õp3332UUY]]4* N硜S=ccթyUq8o7O1q!P\NNNP\ .g?qX:)|/^gjt\:.gƙqf\:n4n n .7 7 7 77777W+fVVV666vzSl)ͼٛ[k4w19}l=y KE^ԗJ%aHIIddd$O2ER Y(X^EGrXrJrYr[DsHmI#II7I/I?[̮i,(Dt<2gbvגcs'Tԓ4Ťt HIޗHH$$_Jvbv=$9%$)<%i(K%ђ8AX" i]JJVI%$k{'"Um"HH"$% dI$[2V2Y2|Iddd-&䢤\P^]HK$($IdJFJ&H%s$K$+%%[%2U]Σ"U$o$TI+$bvM%c$$3%5M,+"ų~&G0++:-u֯qAF䤙} hNLnIхXm``!o [k _ky_+?G/۞7^ZZl9>=rsZEee 擝242ؾU{\].l9qxU\q8J٧$7&~z$L$Gf:}\JJT.):Z2l)[LAuT"V,S<m4w([&qC|݊y;CKyͳss9k=_s9JlykqNXJXX!HXἵMX/Y)~Ig^:3ggO(閁o%)^V^i%)1^pzIJ|q_/I Nt.5;?Aÿffj2ƻ+*zhzh_onj|+,pu&:KFsW;s3XJc[/ g|zԨiQ?S~ƧGO3>5g|zԨiQ?S~ƧGO3>5g|z4[gV_?k0/Hsܻڼ.qf_롽}}ʻ}׫)22_יL.])O=';8x"n_Mpcxh,Tw+ \P$[e& >s d9 3(&+1 rZ,u4&mYdN}(xsnΥ&L96,:,)md1p%!TN燻Ecrc% J[?V:++ۏ J\GU$DPý#4di* 7Q}4KU ^]Su)J奨."@܍YS{H] *w*("K) R, n= YZ"^"KUu~P)jp} K9TUգ!MՂkYzFՐkT?DRipCM& KTc>Y[µ/,5-tP=spwgAw,U!3~YگmmA@V6puk<Vpw!t"K-Ʀ?Ⱥc_3"DWfy ze1CAA7CI!4|7L}4L[hƃYZc>+Ϭzf_f[,]`]f6 ,]e6VMڿ߅V)DJ0AE@p#!< j<7<"Kpi,&p)c1d)4]Bduׁ;ڃ,pC>,'pP;#N2@pYXqSEU,}k^f^m{i wʼYs +!TƼ wPLڦ=Quܻ?A-@#.@4 dݎǻ7!rXQ;J'L 4 di NwY!GRt[6 K'[pq_\1F wt/tO@䮑~"KWwd5A@;pOf KuQ@]A7T YT M K{~ P^'"tƀܓ= 6vp}@@i|v*Dnk}N .-X T#Ȅ˥Bd)6Y|g6`_:*@]ZzoY{U j\zdWKm=TUm6rkAmۢ=jh=^qj7h,hq/!nxTVYGPOpu;,uJGA/,=q1I8mr&Kp{uun, Q:|!YaʘܠҠ>"ppϚKAAndJ((!tҔ;hJ,m5Bv|#\?,}*YU;2<$D>i>"#B@>i>0@S@[a>aFrʌ3Arpzb, MYZíZrP S =CXbBA}()jF,Q JipyTY\ܵz :ݭ3@/9j% n{0d鰸lҜ TJK U"W ȭqMW K-Ž"IJ{Yp Ij&h2(\>- #kCKܳ[\Re rpͧ% XfZ r*tBJc"|BA+|*TY\UVP#tq w7@h`0#߁$mOuӿyD/iDϧ,Z&iKsv6ZΙ]$E^k7nHغ]II]2˕A_tK@{}cJݥk%Us]"KJjC]+K$uv.ߥ]#iK%Mwi\w~$e!#֍`9/BZ{ټ,J|2(;2 sȗTqsK]@}LEt1s!UתF*?R9u*  nQ[ςrHJPH?T ijvgJ(RyJ W;RԴDJ3}TU*H(F:a>S; ь@mff4RKX3Z 3jf"o~Pכ}Hr_)QޏT\sc.v)i.$2{u^uyIBTt Zn})}@77IYWvi~N4sRMoH-~[ Mn4iӹs6z.gLDyP/'VU4ǥHՂLʐo]WHcM<0j"ZTNd}ZD/w S djl09c>qmɏTM3#]UbUHi|o*|(֔4ƺHqk4zs혿:4~56_'6n1[Ž%s靘<\lF\$r˘KY,^ iK%ri.mw x%W|^gr$WNN5vu| [\.> "t+>K=Iң.ݎ4p59;_-㣹޵Dʺޮ B_~fM?`Cgƻ鏑֩Dygt!~'Eǯq=νG$~~op&diu< di%O/AF, s;{^Y*yJYj&'Cn晠ʠwEY K+P d)wxo|.3n*kiBSA&{f.+⚛yg@ij,UwЍRZ,\0Rq,)l h7vq"2EЋAAƋ"4XJ%p:,5Yj(=ȞAU^TZL] O굠үj\.tȒWRo]t6t;=@,5R;qoM Kf' K},-Qoe,mwTo;Pz< Kd. Kn4Td:f?Qu̻[aPu_\yOշqYBV(&~)2_ )2O i)c!*!MT*"hP%TtKe(T4}xG~g}wUAzKPFPVu"tuC:^)4GXds8T# ȾwmAiNl4ZVVKr(ŖURJeM4j=zòz$ҽDz)z4z e{ޱdZbγZW6FeBMjZdbt@iZ@c^{SݬoPטW|yG1_c$у( !K@w1-Q'z-TG(kQdgtӲ#t*bOL@1-$(kL`LGKeq ~#f:^bQ%Q EԲ2b8NU\Cu]BH+Ped}[>]Iu~#Kn:E7b>[G6˼_5e oZgjoL/U~GQT7 T*aV!M%/쫳= D P~Ux*Vzɷjw]P> xVC(A'z60 @|Bעho4LyQr]8(_od1]F_o(_odZ5݈UF6ѯs2|0==Lu6JP&QlW6{Ga(#<;UP gzVGC.LEW:{vLC_nhƠ_n32Bܲq! 2mD魐e{ JOҧPiCԧ*lt}>svEim1݉bW%A}z7"(_'J?etjO|UC7_CV^?Ctde: 'A>G[ ?[_/ gz˲͓M>J6M$Fd7?Js3YwuCid[v|tUXvlAUP~\ʏVYgنN]ݍL6@vQ xC~EסFQ :pNVV@^G4f4Ց?}ӏe/i4LKF~i893C-}9;|*%׶lv~ pg'jIt4.R6bZkipgtJO̖ #pfQ ,h J-[egZZ=~U]ը~~&TVduT7kOkhEQzE^@ptQnVXvF]t (l,jqdgxtJZ,;J'#QzOc^y;˾GW(]AdQ,J,/S8iYv'zVζhٍ/t}ղr.b~O>IBiov$h:J\D6F@cQ 1,if^dKZbX.6J ڒ&WQkYim@iL_Qz5Y}.Nv5o;tkJF)vKY|۹gJ}Ȟv|GDW>]pV7:wEm~j{ܠͭj; Sf8JUGf>@v]Y]TβQgS]ɋSoՕﮤ:S?Ft]5Tr~Ό=[m FmϓֺU+%}t+C꫶/H'=:Nm7SkxTFE۸}AJ RܳڎJϦƉz,:IR= (Ul UO#xSN@VlTDkQZX }RMr>C%թӚ֤ZBk]9N:jitG5b'k]Tp g嶛 'iǥbXrb@1LiHSRe9jReRzK;U@ݲb-ۖC[Q굷*>K-@߲YgXօ#(EQ+}Yw0ijuQt^zWP =[DgAeYo#ag>e/:W\OvCQ۬Wɭ9JFKAQ 7Ƚ>#̲V2G@aՒA>#l!>,+&C} fٶa#l>,{5#lCZ:dg|DLb6lJ6GT45Fun6C؏}=V7Ⱦf-(|6yt!++/r(%2UCi\YD桦( XC^F=Q5xl̷+>˦Qqlj VB;(VX,R_dEu5z:o8EMqzI&kK@eY}Ϯ-zX'(|H6Nע(櫥udztJ}A]( _KP zVI7QJ&t8Բe[dT`L'{^Fe7'σ{7zϒ=/PكG3 S;P$Y')6Qd%z(_EzvCQډ޲ҮR^-.2lc ( lL( l٬L3(_{6? P/w>J&FTCZ(`MH TmcRSƨ%P*1& I$VG{sjڦ\=߲p.3҇ZQP~oM6D(>7fz.(>3N9TG(5-l(WZǬV+ZA@GM\ mBَPKlԲD8T&Q' & r֥'j]E= A>O0(mt_0kZ/@G55UZ{wYZzA9se> kaV2ZZtYuB+&龷aMEk)o7kޖP~~Vc=zXO1{8+U5{i=NEP7| (gV]:oPLd鞄r`յb P ߻Nl:S#F]3-\=O*Zg.Ie],^Ck"I硦A9TڳgPyPԊBC9g"Q6skUr(TNPgc[]"_ Zkz ~(Z׺S>T(x\eaPα@@'XjW:zrij HZN+iZPMƑqs,y'A93Z2LrYhf\ajk ̤Ynf׬43 g--L킙yi+)=#}JQm{ ([Z2XB&*=C$gsjf+=f3s>lv{rҳSzVR*ܥ ~+U u_ޯYwqYK>l- ?+p| e YAZp p0L`6^J&( .@ A_ (0 ,`+( \ P &0 䂅7:v8 >_+CAl#  AA>X^kF.({p xā` RA}z V`v*!u<  ڂν ĀX0  /B(o- T v tAo0 #AX" vGIp9vh>g\"٫=Ͼu)5..l3.\ti\vRe\\t9l\Rk\j]t3.u.4]..0.7\tBHKq uѥqiKqrѥqK_EXKqIteqd2Ee.%E<"EBRKq)vѥĸ޸weqKq)sѥҸTrȸrѥڸTrڸvѥ޸Իd\\tf\Y3h_]\ ^B6# oid.oj̈́3 'ӟWcUX}U_u]f^0WXwb3VĪ|v09v# [d;q@DbW+&{G4)y3Eof( D8+JD\/V1WRDKXDi&D^%e K"Bn]d-׈A*mm2E&,reZ(3Uܮ~U yO֩yJcNۿG~*M{iO#tTES@*T3Τ1|n˧sjP׬j#VKVJ"uqU#UzU+ی`eAQTURU<^TUU(W3b:&6bzFPUPry>pʹ]WoP[_Eϯb|OX_ۮFɾjVeԳ sW^}J-LSdSL=skP^j΄u}BukUohW atn,`kE.Rk$ΣAQ;:iE=?g/8g1^< `5&=599禦g1;/=+5p&6b<=bV{zrgL5;ӕ q!8ddcF 7|dEFO03x0γo9M#}G|؄$DF&0 ^~=苞oM/bxRQQ8Upszg͚84~q Otz=/B4y#}d(ONTENT.IE5\QJ6BCHEZ\DVINDEX.HTM]WINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\QJ6BCHEZ\ECOBAS.HTMi]|WINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\QJ6BCHEZ\HNB.HTMP^WINDOWS\TEMPORARY INTERNET FILES\CONTENT.IE5\QJ6BCHEZ\INDE [4@4Normal1$CJhmH nH <A@<Default Paragraph Font4&@4Footnote Reference4O41.2.3 & F0 h:Wta  :WtY o%*1>D"FFcS]h+w x%Q!\6pa0-0Z00001D1t111212a22223N3~3334>4n4444.5efgqrstTtXYbcY - l%m%n%o%%%g((((3)))))** -e./w1x111134i6277 84;5;K;L;==>>>D!F"F*F+FFFFN Q QQQbScSmY]]]]] a}aaa&bbbncc d dndd:eee`ff-gggUhhhiiii[jkjljjkEkkk$llll[mm)nnnYoopppFqq rurr@sstitt.uuu[vv*w+wwwxx x x xGxHxKxzzzzzY}"#$%stqrtuvwxyz{|}~PQRSgh!" !E[\& :;CDjo,-GHuv '( !"56Z[456HI cd./opyzb````````@ Oh+'0 (4 P \ ht|5Sequence Analysis of Membrane Proteins with the Web requZAVOD ZA FIZIKUAVONormalAZAVOD ZA FIZIKU3VOMicrosoft Word 8.0f@_@a@(ՔcF  C A ? ՜.+,D՜.+,h$ hp   PMF SPLITA\c  5Sequence Analysis of Membrane Proteins with the Web Title 6> _PID_GUIDAN{9DA97888-EE0A-11D4-8BD3-08002B96244F}```````````````         `                    `           ! " # $ % & '` ( ) * + , - . / 0 1 2 3@@@ O z2]A $w$8up@j   d0;Ov.&` 9o$bMx+=e.uF>   Iy&<$ !t57:RTWoqt::::::H  o2$.hCwm*[52$5Li()j>_2$=w5\V 6y2$b#xa3C2$^.o(_;5#)і2$1=3a`]W0ӷ@ "(  H  C A ?N  S A ? N  S A ?N  S A ?H   C A ?H   C A ?B S  ?Hxa "4S"4\E"E4Pv#4  ""4un"4mu{CIKSag]s\c) 2  0jo  (+2IZ`m8DZbcjr}*","L"S"Z"e"f"q"|"~"""""""""""""""####*#,#6#8#V#Y#i#p#v####$$$)$M$T$k$r$$$$$$$$$$$$$ %%.%5%P%]%W&^&&&''S([((())))))))$)&)))))))))))/*6*8*:*w*y***%0&0G1J1z1}111111111111111e2h2p2s25566666666@7C7F7I77778;;<<O>]>^>h>>>>> ?(?#A,AfApABBUCbCSIaIIIJJJJ K KKKKKKKK LLL&L3L?LELLLLLM&MMMMMM NN(N)N0N1N8NNNNNO&O'O.OjPxPPPQQ%U3U{UURW[WWXX!XY Y YYYY?ZAZIZSZZZZZZZZ[[([b[h[[[_ `aaTd^d_dmddddddddd&e1eWeYeeeZf^fffffff'g+gJgLgug|ggg;hEhFhThfhhhhhiiriyiiiiiFmTmmmmm#n'nunnnnooSoWouowooop p pp`piptp}ppp)q0q1q?qqqqqTrbrfrhr&s.sssssssstttttuuuuuuzv{vvvw#wxyx||-~5~\~c~*2=dkLW kvЄۄxĈȈ݉Ɋ 7<JX  QVՏ+6ehēʓ!$ILEHhk˜<IȠ֠נjxYgϨ֨vج(5]d$+3>ѳ޳HSIO>Dʿٿ #)#RZ\`bf $'GKPW\e [i#(-2:D 0;@C),w(9@KQVYy8@Yfy~ +9>DLV#&.0@CKSbdlwYbs| $),4:OT\e<ALW!):= )>Iaego 9>CL[^cj  '.2jm28:@BFHNv&9>FOW^cjoz9?| &18?CEFLMWX`bjkstyz|}"#'+2389>?IJRSW[^_ghjkst $%+,<=FGNRVW[^deopxy ()12;<@AEFHIQeklnozb-W@M OCR`hFRTZP]!!V"e"##&"&Y'i'''(())7)9)))))++-.00E1G1x1z1112233 44(5:56687=7885;?;;;g?{?BBnDpDBGKG'M.MMMN OQQ]RhRYSaSTTUULWOWWW{[[^^^^``aaaaabbbocc d dndddd:eNeeeef`ftfff-gAgggghUhhhhhiii1i{iiiijjk6kEkrkk llll m[mnmmm)na?a@`@@aB`@DaOaQaSaUaY`[`]`caiai`XjaXp`Xra.ua>uay`{`}aaaaJ`Jab`b````aa`L`````Ra`````a``lana|``a```G:Times New Roman5Symbol3& :ArialA& Arial Narrow"A hQ&Q&F\" 2c.4Sequence Analysis of Membrane Proteins with the Web ZAVOD ZA FIZIKUZAVOD ZA FIZIKUCE\TEMPLATES\OTHER DOCUMENTS\CONTEMPORARY RESUME.DOTaPROGRAM FILES\MICROSOFT OFFICE\TEMPLATES\OTHER DOCUMENTS\CONTEMPORARY RESUME.DG $bjbjَ *]4&4&4& ))3_****^+///XXXX5XYzZ$+`bZ/;////Z+T*^+*+T+T+T/l*p^+X/X+T+TWQXBJX^+*4cN"4&_LX      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTkXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+S/0123456789:;<=>?@ABCDEFGHIJKLMNOPQRTUVWXYZ[\]^_`abcdefghijlmnopqrstuvwxyz{|}~  > Root Entry F@.acData  %~mWordDocument*ObjectPool]a@+a      !"#c&'()*+,0Tableb#$%&'()*+,-./0123456789:;<BCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`bdefghijklmnopqrstuvwxyz{|}~"equZAVOD ZA FIZIKUAVONormalAZAVOD ZA FIZIKU3VOMicrosoft Word 8.0f@_@a@(ՔcF ՜.+,D՜.+,h$ hp   PMF SPLITA\c  5Sequence Analysis of Membrane Proteins with the Web Title 6> _PID_GUIDAN{9DA97888-EE0A-11D4-8BD3-08002B96244F}  FMicrosoft Word Document MSWordDocWord.Document.89q Oh+'0 (4 P \ ht|5Sequence Analysis of Membrane Proteins with the Web r_1041415382ac(@= /c /c_1041415613ac(@= /c /c_1041416465ac(@= /c /c_1041416928ac(@= /c /c _1041417070 ac(@= /cVc_1041417313 ac(@=VcVcOle ObjInfo Ole ObjInfoContentsOle Contents.[HOle ObjInfo Contents$3ObjInfoContentsOle  ObjInfoContentsZGOle  ObjInfo ContentsWX  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~a