Sampling of conformational ensemble for virtual screening using molecular dynamics simulations and normal mode analysis

TL;DR

This paper introduces new fast protocols combining molecular dynamics and normal mode analysis to generate receptor conformational ensembles for improved virtual screening, validated on two flexible protein targets.

Contribution

It presents novel, efficient protocols that integrate molecular dynamics and normal mode analysis with pocket classification for receptor ensemble generation.

Findings

Protocols are effective depending on protein flexibility.

Generated RCEs can distinguish known ligands from decoys.

Different methods suit different types of protein motions.

Abstract

Aim: Molecular dynamics simulations and normal mode analysis are well-established approaches to generate receptor conformational ensembles (RCEs) for ligand docking and virtual screening. Here, we report new fast molecular dynamics-based and normal mode analysis-based protocols combined with conformational pocket classifications to efficiently generate RCEs. Materials \& methods: We assessed our protocols on two well-characterized protein targets showing local active site flexibility, dihydrofolate reductase and large collective movements, CDK2. The performance of the RCEs was validated by distinguishing known ligands of dihydrofolate reductase and CDK2 among a dataset of diverse chemical decoys. Results \& discussion: Our results show that different simulation protocols can be efficient for generation of RCEs depending on different kind of protein flexibility.