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Positional specific amino acid attributes improve the computational design of antimicrobial peptides


Lučić, Bono; Bojović, Viktor; Vukičević, Damir; Juretić, Davor
Positional specific amino acid attributes improve the computational design of antimicrobial peptides // Australia-Croatia Workshop on Antimicrobial Peptides and Summer School in Biophysics in Biophysics (AMP2010) : Book of Abstracts / Juretić, Davor ; Šeparović, Frances (ur.).
Split: Faculty of Sciences, 2010. str. 43-43 (poster, nije recenziran, sažetak, znanstveni)


Naslov
Positional specific amino acid attributes improve the computational design of antimicrobial peptides

Autori
Lučić, Bono ; Bojović, Viktor ; Vukičević, Damir ; Juretić, Davor

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Australia-Croatia Workshop on Antimicrobial Peptides and Summer School in Biophysics in Biophysics (AMP2010) : Book of Abstracts / Juretić, Davor ; Šeparović, Frances - Split : Faculty of Sciences, 2010, 43-43

ISBN
978-953-7155-15-5

Skup
Australia-Croatia Workshop on Antimicrobial Peptides

Mjesto i datum
Split, Hrvatska, 09.-14.08.2010

Vrsta sudjelovanja
Poster

Vrsta recenzije
Nije recenziran

Ključne riječi
Amino acid attributes; antimicrobial peptides; design

Sažetak
A novel method and web server for prediction of TI values for helical antimicrobial peptides isolated from different frog species is designed based on amino acid frequencies and motifs for antibiotics and hemolytics. We find that alpha-amphipathic segments predicted by the Split server (http://split.pmfst.hr/split/) and G, Q, H, D, E amino acid frequencies are positively correlated, while high preferences for transmembrane helix conformation are negatively correlated with measured TI values. A composite index is developed as a specific combination of these positional and frequency attributes. This composite index is additionally combined with D-predictor described in [1], and very good correlation was obtained between experimental and calculated TI values on the training set containing 36 nonhomologous peptides (less than 70% pairwise identity). Correlation coefficient is ~ 0.9 both on linear and log-log scale. Finally, we performed prediction of TI values on 54 peptides from external set which resulted in correlation of about 0.85 on linear and log-log scale. [1] Juretić D, Vukičević D, Ilić, N, Antcheva N, Tossi A (2009) J Chem Inf Model 49, 2873

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Kemija, Biologija



POVEZANOST RADA


Projekt / tema
098-1770495-2919 - Razvoj metoda za modeliranje svojstava bioaktivnih molekula i proteina (Bono Lučić, )
177-0000000-0884 - Diskretni matematički modeli u kemiji (Damir Vukičević, )
177-1770495-0476 - Razvoj i primjene principa maksimalne proizvodnje entropije (Davor Juretić, )

Ustanove
Institut "Ruđer Bošković", Zagreb,
Prirodoslovno-matematički fakultet, Split