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Predicting protein interaction sites from residue spatial sequence profile and evolution rate
Author(s) -
Wang Bing,
Chen Peng,
Huang De-Shuang,
Li Jing-jing,
Lok Tat-Ming,
Lyu Michael R.
Publication year - 2006
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/j.febslet.2005.11.081
Subject(s) - residue (chemistry) , phylogenetic tree , sequence (biology) , multiple sequence alignment , protein sequencing , biological system , conserved sequence , support vector machine , computer science , protein structure prediction , protein structure , data mining , bioinformatics , algorithm , computational biology , chemistry , peptide sequence , biology , sequence alignment , artificial intelligence , biochemistry , gene
This paper proposes a novel method that can predict protein interaction sites in heterocomplexes using residue spatial sequence profile and evolution rate approaches. The former represents the information of multiple sequence alignments while the latter corresponds to a residue's evolutionary conservation score based on a phylogenetic tree. Three predictors using a support vector machines algorithm are constructed to predict whether a surface residue is a part of a protein–protein interface. The efficiency and the effectiveness of our proposed approach is verified by its better prediction performance compared with other models. The study is based on a non‐redundant data set of heterodimers consisting of 69 protein chains.