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Factor Analysis Scales of Generalized Amino Acid Information as Applied in Predicting Interactions between the Human Amphiphysin‐1 SH3 Domains and Their Peptide Ligands
Author(s) -
Liang Guizhao,
Chen Guohua,
Niu Weihuan,
Li Zhiliang
Publication year - 2008
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2008.00641.x
Subject(s) - affinities , quantitative structure–activity relationship , binding affinities , peptide , sh3 domain , amphiphysin , chemistry , amino acid , molecular model , computational biology , stereochemistry , biochemistry , biology , signal transduction , receptor , endocytosis , dynamin , proto oncogene tyrosine protein kinase src
Factor analysis scales of generalized amino acid information (FASGAI) involving hydrophobicity, alpha‐helix and beta‐turn propensities, bulky properties, compositional characteristics, local flexibility, and electronic properties, was proposed to represent the structures of the decapeptides binding the human amphiphysin‐1 SH3 domains. Parameters being responsible for the binding affinities were selected by genetic algorithm, and a quantitative structure–affinity relationship (QSAR) model by partial least square was established to predict the peptide–SH3 domain interactions. Diversified properties of the residues between P 2 and P −3 (including P 2 and P −3 ) of the decapeptide (P 4 P 3 P 2 P 1 P 0 P −1 P −2 P −3 P −4 P −5 ) may contribute remarkable effect to the interactions between the SH3 domain and the decapeptide. Particularly, electronic properties of P 2 may provide relatively large positive contributions to the interactions, and reversely, hydrophobicity of P 2 may be largely negative to the interactions. These results showed that FASGAI vectors can well represent the structural characteristics of the decapeptides. Furthermore, the model obtained, which showed low computational complexity, correlated FASGAI descriptors with the binding affinities as well as that FASGAI vectors may also be applied in QSAR studies of peptides.