Prediction of Lipid-Binding Sites Based on Support Vector Machine and Position Specific Scoring Matrix |
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Authors: | Wenjia Xiong Yanzhi Guo Menglong Li |
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Institution: | (1) College of Chemistry, Sichuan University, 610064 Chengdu, China; |
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Abstract: | 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. |
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Keywords: | |
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