Improving the Efficiency of MECoMaP: A Protein Residue-Residue Contact Predictor

Abstract

This work proposes an improvement of the multi-objective evolutionary method for the protein residue-residue contact prediction called MECoMaP. This method bases its prediction on physico chemical properties of amino acids, structural features and evolutionary information of the proteins. The evolutionary algorithm produces a set of decision rules that identifies contacts between amino acids. These decision rules generated by the algorithm represent a set of conditions to predict residue-residue contacts. A new encoding used, a fast evaluation of the examples from the training data set and a treatment of unbalanced classes of data were considered to improve the the efficiency of the algorithm.