Enhanced Prediction of Hot Spots at Protein-Protein Interfaces Using Extreme Gradient Boosting.

ABSTRACT: Identification of hot spots, a small portion of protein-protein interface residues that contribute the majority of the binding free energy, can provide crucial information for understanding the function of proteins and studying their interactions. Based on our previous method (PredHS), we propose a new computational approach, PredHS2, that can further improve the accuracy of predicting hot spots at protein-protein interfaces. Firstly we build a new training dataset of 313 alanine-mutated interface residues extracted from 34 protein complexes. Then we generate a wide variety of 600 sequence, structure, exposure and energy features, together with Euclidean and Voronoi neighborhood properties. To remove redundant and irrelevant information, we select a set of 26 optimal features utilizing a t

SUBMITTER: Wang H 

PROVIDER: S-EPMC6155324 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature