Current Bioinformatics

Yi-Ping Phoebe Chen
Department of Computer Science and Information Technology
La Trobe University
Melbourne
Australia

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

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

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

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Article Details

VOLUME: 8
ISSUE: 1
Year: 2013
Page: [3 - 8]
Pages: 6
DOI: 10.2174/1574893611308010003
Price: $58