Prediction of Lipid-Binding Sites Based on Support Vector Machine and Position Specific Scoring Matrix

被引：11
|
作者：
Xiong, Wenjia [1 ]
Guo, Yanzhi [1 ]
Li, Menglong [1 ]
机构：
[1] Sichuan Univ, Coll Chem, Chengdu 610064, Peoples R China
来源：
PROTEIN JOURNAL | 2010年 / 29卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Lipid-protein interactions; Lipid-binding sites; Position specific scoring matrix; Support vector machine; PROTEIN INTERACTIONS; SECONDARY STRUCTURE; IDENTIFICATION; EVOLUTIONARY; INFORMATION;
D O I：
10.1007/s10930-010-9269-x
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
Lipid-protein interactions play a vital role in various biological processes, which are involved in cellular functions and can affect the stability, folding and the function of peptides and proteins. In this study, a sequence-based method by using support vector machine and position specific scoring matrix (PSSM) was proposed to predict lipid-binding sites. Considering the influence of surrounding residues of one amino acid, a sliding window was chosen to encode the PSSM profiles. By incorporating the evolutionary information and the local features of residues surrounding one lipid-binding site, the method yielded a high accuracy of 80.86% and the Matthew's Correlation Coefficient of 0.58 by using fivefold cross validation test. The good result indicates the applicability of the method.
引用
收藏
页码：427 / 431
页数：5
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