Supervised molecular dynamics (SuMD) approaches in drug design

Abstract

Supervised MD (SuMD) is a computational method that enables the exploration of ligand-receptor recognition pathway in a reduced timescale. The performance speedup is due to the incorporation of a tabu-like supervision algorithm on the ligand-receptor approaching distance into a classic molecular dynamics (MD) simulation. SuMD enables the investigation of ligand-receptor binding events independently from the starting position, chemical structure of the ligand (small molecules or peptides), and also from its receptor-binding affinity. The application of SuMD highlights an appreciable capability of the technique to reproduce the crystallographic structures of several ligand-protein complexes and can provide high-quality protein-ligand models of for which yet experimental confirmation of binding mode is not available.