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Functional Site Prediction by Exploiting Correlations Between Labels of Interacting Residues by Saradindu Kar; Deepak Vijayakeerthi; Ashish V. Tendulkar; Balaraman Ravindran is a scholarly article available to read on EtoBox.

What is Functional Site Prediction by Exploiting Correlations Between Labels of Interacting Residues about?

Functional site prediction is an important problem in the structural genomics era where we have a large number of experimentally determined protein structures with unknown function. The functional sites provide useful insights into protein function. In this paper, we propose a method for prediction of functional residues in a given protein from its three-dimensional (3D) structure. Our method exploits correlation between labels of interacting residues to obtain significant performance improvements over the existing methods on the benchmark dataset. We represent each protein as a weighted undirected residue interaction network, where spatially proximal residues in terms of their Van der Waal radii are connected by an edge. The edge weight captures correlation between the labels of interacting residues. The correlation is estimated based on the features of interacting residues. We then obtain a label assignment by minimizing combined cost of residue-wise label misclassification and violation of label correlation constraints. We solve this problem in two stages, where the first stage minimizes residue-wise label misclassification cost followed by an iterative collective inference sche

Author

Saradindu Kar; Deepak Vijayakeerthi; Ashish V. Tendulkar; Balaraman Ravindran

Publisher

ACM

Published

2012

Language

EN