Prediction of protein-protein interaction sites using patch-based residue characterization.
Identifying protein-protein interaction sites provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Using a patch-based model for residue characterization, we trained random forest classifiers for residue-based interface prediction, which was followed by a clustering procedure to produce patches for patch-based interface prediction. For residue-based interface prediction, our method achieves a specificity rate of 0.7 and a sensitivity rate of 0.78. For patch-based interface prediction, a success rate of 0.80 is achieved. Based on same datasets, we also compare it with several published methods. The results show that our method is a successful predictor for residue-based and patch-based interface prediction.
The State Key Laboratory of Structural Analysis of Industrial Equipment, Dalian University of Technology, 2 Ling-Gong Road, Dalian 116024, China.
Zhijun
Z
Qiu
Xicheng
X
Wang
D000465:Algorithms; D001665:Binding Sites; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D008958:Models, Molecular; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping / Q000379:methods*