Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?

Jon Kapla,Flavio Ballante,Jens Carlsson,Ismael Rodríguez-Espigares,Jana Selent,Avner Schlessinger

doi:10.1371/journal.pcbi.1008936

Abstract

The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy. In this work, we explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of GPCR structure prediction (GPCR Dock). Two simulation protocols were used to refine 30 models of the D3 dopamine receptor (D3R) in complex with an antagonist. Close to 60 μs of simulation time was generated and the resulting MD refined models were compared to a D3R crystal structure. In the MD simulations, the receptor models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode. The best refinement protocol improved agreement with the experimentally observed ligand binding mode for a majority of the models. Receptor structures with improved virtual screening performance, which was assessed by molecular docking of ligands and decoys, could also be identified among the MD refined models. Application of weak restraints to the transmembrane helixes in the MD simulations further improved predictions of the ligand binding mode and second extracellular loop. These results provide guidelines for application of MD refinement in prediction of GPCR-ligand complexes and directions for further method development.

Highlights

Three-dimensional structures of proteins have contributed to detailed knowledge about biological processes at the molecular level
We explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of G protein-coupled receptor (GPCR) structure prediction (GPCR Dock)
We investigated if atomistic simulations can be used to refine models of a G protein-coupled receptor (GPCR) in complex with a drug-like ligand

Summary

Introduction

Three-dimensional structures of proteins have contributed to detailed knowledge about biological processes at the molecular level. Protein structure prediction methods can broadly be divided into two classes, template-based (e.g. homology modeling and fold recognition) and ab initio (e.g. fragment assembly and physics-based methods, known as template-free modeling) [3] Both template-based and ab initio models will contain errors (e.g. in secondary structure, side chain packing, and loop regions) and need to be improved to be useful in applications that are sensitive to molecular details. For this reason, there is an increasing interest in methods that can enhance model quality. Consistent improvement of model quality with physics-based techniques could have a major impact on studies of protein function and enhance the predictive power of structure-based drug design

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Conclusion