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

Citation

Kapla, Jon et al. (2021), Supporting data: Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?, Dryad, Dataset, https://doi.org/10.5061/dryad.98sf7m0j3

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 transmembrane helix region of the models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode and the second extracellular loop region. 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.

Methods

Data was obtained by running molecular dynamics simulations on a set of models obtained from the GPCR Dock 2010 assessment. Molecular dynamics trajectories in the data set has been treated for periodic boundary conditions and reduced to approximately 1 frame per 200 ps. Solvent has been removed to reduce the size of the files. 

Usage Notes

Together with the molecular dynamics trajectories and input files, analysis results have been uploaded together with example analysis scripts. The data has been compressed into tar.gz archives. The archives come with README file that describes the contents of the archives.