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Pregled bibliografske jedinice broj: 146728

Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues


Piližota, Teuta; Lučić, Bono; Trinajstić, Nenad
Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues // Journal of Chemical Information and Computer Sciences, 44 (2004), 1; 113-121 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 146728 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues

Autori
Piližota, Teuta ; Lučić, Bono ; Trinajstić, Nenad

Izvornik
Journal of Chemical Information and Computer Sciences (0095-2338) 44 (2004), 1; 113-121

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
globular-proteins; selection of frequencies; composition of amino acid residues; secondary structure; helix/strand/coil content; concise models; prediction; multivariate regression; variable selection

Sažetak
The possibility of prediction of protein secondary structure content from composition of their amino acid residues can help in bridging the gap between proteins of known primary sequence having an unknown secondary structure. Almost all recently published models for understanding the relationship between composition (frequency of occurrence) of amino acid residues and secondary structure content of proteins involved composition of all 20 amino acid residues. However, it is well-known that many amino acid residues are mutually similar according to their physicochemical properties (hydrophobicity, hydrophilicity, charge, size, etc.). Because of that, we were motivated to investigate the possibility of reduction of the total number of terms (frequencies of amino acid residues) in the models for describing the relation between the composition of amino acid residues and the percentage of residues belonging to alpha, beta and coil secondary structure. For this purpose, the CROMRsel algorithm (J. Chem. Inf. Comput. Sci. 1999, 39, 121-132) for selection of a small subset of the most important variables/descriptors into the multiregression (MR) models, i.e., frequency of occurrence of amino acid residues in proteins, was used. Analysis was performed on a data set containing 475 proteins, taken from Proteins 1996, 25, 157-168. A complete data set was partitioned into a 317-protein training set and 158-protein test set. The best possible linear models containing I = 1, ..., 20 frequencies were selected among all 20 frequencies of occurrence of amino acid residues on the 317-protein training set, and were used for performing prediction of the corresponding percentage of secondary structure content on the 158-protein test set. For the 317-protein data set the best selected concise models for the alpha, beta, and coil secondary structure contain only 9, 5, and 8 frequencies, respectively. Selected concise models are of the same or better fitted, cross-validated, and predictive statistical parameters than the models containing all 20 frequencies. Additionally, for each I (I = 1, ..., 20) 30 the best possible random models were selected. In each case, the best possible real models are much better than each of the best possible random models, showing clearly that there is no risk of a chance correlation (what one could expect due to the application of an exhaustive search for the best model having I frequencies among all 20!/I!(20-I)! possible models). Finally, the best selected models on the complete 475-protein data set for the alpha, beta, and coil secondary structure contain only 7, 4, and 7 frequencies of amino acid residues, respectively. These models are much simpler and have better fitted and cross-validated errors than the corresponding models from the literature, that were obtained without using a procedure for selection of the most important frequencies of amino acid residues in proteins.

Izvorni jezik
Engleski

Znanstvena područja
Kemija



POVEZANOST RADA


Projekt / tema
0098034

Ustanove
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Bono Lučić (autor)

Avatar Url Nenad Trinajstić (autor)

Citiraj ovu publikaciju

Piližota, Teuta; Lučić, Bono; Trinajstić, Nenad
Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues // Journal of Chemical Information and Computer Sciences, 44 (2004), 1; 113-121 (međunarodna recenzija, članak, znanstveni)
Piližota, T., Lučić, B. & Trinajstić, N. (2004) Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues. Journal of Chemical Information and Computer Sciences, 44 (1), 113-121.
@article{article, year = {2004}, pages = {113-121}, keywords = {globular-proteins, selection of frequencies, composition of amino acid residues, secondary structure, helix/strand/coil content, concise models, prediction, multivariate regression, variable selection}, journal = {Journal of Chemical Information and Computer Sciences}, volume = {44}, number = {1}, issn = {0095-2338}, title = {Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues}, keyword = {globular-proteins, selection of frequencies, composition of amino acid residues, secondary structure, helix/strand/coil content, concise models, prediction, multivariate regression, variable selection} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Uključenost u ostale bibliografske baze podataka:


  • Chemical Abstracts