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Protein & Peptide Letters


ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

BSFINDER: Finding Binding Sites of HCV Proteins Using a Support Vector Machine

Author(s): Yu Chen and Kyungsook Han

Volume 16 , Issue 4 , 2009

Page: [373 - 382] Pages: 10

DOI: 10.2174/092986609787848153

Price: $65


Hepatitis C virus (HCV) infection is a major cause of liver disease and a dangerous threat to public health. Hence, the problem of finding interactions between HCV and human proteins has received much attention. In this paper, we present an approach to predicting binding residues in HCV proteins using a support vector machine (SVM) classifier. Based on six biochemical properties of amino acids (sequence profile, accessible surface area, residue binding propensity, sequence entropy, hydrophobicity and conservation weight), the SVM classifier achieved an average accuracy of 93%. Contiguous residues in the sequence act together to determine a binding site, and a window of 11 residues (the target residue and 5 adjacent residues on each side) gave the best result in our study. Our approach has been implemented in a program called BSFinder (Binding Site Finder), which is available at BSFinder will be of considerable help in predicting binding residues and potential interacting partners of a protein.

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