Scatter search for homology modeling

Abstract

Homology modeling is an effective technique in protein structure prediction (PSP). However this technique suffers from poor initial target-template alignments. To improve homology based PSP, we propose a scatter search (SS) metaheuristic algorithm. SS is an evolutionary approach that is based on a population of candidate solutions. These candidates undergo evolutionary operations that combine search intensification and diversification over a number of iterations. The metaheuristic optimizes the initial poor alignments and uses fitness functions. We assess our algorithm on a number of proteins whose structures are present in the Protein Data Bank and which have been used in previous literature. Results obtained by our SS algorithm are compared with other approaches. The 3D models predicted by our algorithm show improved root mean standard deviations with respect to the native structures.