Computational prediction of heme-binding residues by exploiting residue interaction network.

ABSTRACT: Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly

SUBMITTER: Liu R 

PROVIDER: S-EPMC3184988 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature