A feature-based approach to modeling protein-protein interaction hot spots.

ABSTRACT: Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and t

SUBMITTER: Cho KI 

PROVIDER: S-EPMC2677884 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature