Differential Evolution Based Particle Swarm Optimization Algorithm for Protein Ligand Docking

Abstract

Molecular Docking is a computerized tool used in discovering a drug. Molecular Docking (MD) which helps to predict the small molecule ligand is able to bind to disease target protein. In MD a configuration molecular structure is generated by the conformational search algorithm and then the position is evaluated based on fitness function. Here fitness value is least binding energy during the interaction of protein and Ligand. The more the least binding energy, the more the ligand is stable in the complex. In this research a differential evolution-based particle swarm optimization algorithm is proposed as a search algorithm for conformational space in protein ligand docking. Using a dataset of 1089 bimolecular complexes from PDBbind the lowest binding energy and time efficiency were tested. The proposed algorithm demonstrates superior when tested with six other existing algorithms.