Generic placeholder image

Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Prediction of Protein-Protein Interactions Based on Molecular Interface Features and the Support Vector Machine

Author(s): Weiqiang Zhou, Hong Yan, Xiaodan Fan and Quan Hao

Volume 8 , Issue 1 , 2013

Page: [3 - 8] Pages: 6

DOI: 10.2174/1574893611308010003

Price: $65

Abstract

Protein-protein interactions play important roles in many biological progresses. Previous studies about proteinprotein interactions were mainly based on sequence analysis. As more 3D structural information can be obtained from protein-protein complexes, structural analysis becomes feasible and useful. In this study, we used structural alignment to predict protein-binding sites and analyzed interface properties using 3D alpha shape. We have developed a method for protein-protein interaction prediction. The result indicates good performance of our method in discriminating proteinbinding structures from non-protein-binding structures. In the experiment, our method shows best Matthews correlation coefficient of 0.204.

Keywords: Alpha shape, protein-protein interaction, structural alignment, Residue Index, TM-Score, Curvature Index, Support Vector Machine (SVM), Matthews correlation coefficient, False negative, Atom Index


Rights & Permissions Print Export Cite as
© 2022 Bentham Science Publishers | Privacy Policy