Protein ligand docking using simulated jumping

Abstract

Molecular docking is an essential topic of study as it is crucial in numerous biological processes such as signal transduction and gene expression. Computational efforts to predict ligand docking is preferable to costly x-ray crystallography and Nuclear Magnetic Resonance (NMR) yet technology today remains incompetent in exploring vast search spaces for optimal solutions. To create efficient and effective algorithms, research has led to De novo drug design: a technique to extract novel chemical structures from protein banks is largely evolutionary in nature, and has found measurable success in optimal solution searching. A study by Shara Amin in 1999 in her novel method: simulated jumping (SJ) has achieved promising results when tested on combinatorial optimization problems such as the Quadratic Assignment and Asymmetric Travelling Salesman problems. Following her success with SJ, we aim to incorporate SJ into protein ligand docking, another optimization problem.