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Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
Jon Kapla1, Ismael Rodríguez-Espigares2, Flavio Ballante1
1Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
Plos Computational Biology
|May 13, 2021
Summary
Molecular dynamics simulations can refine computational models of G protein-coupled receptor (GPCR) and ligand interactions. This method improves ligand binding predictions, aiding drug discovery for GPCR targets.
Area of Science:
- Structural biology
- Computational chemistry
- Pharmacology
Background:
- G protein-coupled receptors (GPCRs) are crucial drug targets, but experimental structures are lacking for most.
- Computational modeling of GPCR-ligand interactions has limitations in accuracy.
- Existing in silico models require refinement for reliable drug development.
Purpose of the Study:
- To investigate the utility of molecular dynamics (MD) simulations for refining in silico models of GPCR-ligand complexes.
- To assess the impact of MD refinement on the accuracy of D3 dopamine receptor (D3R) antagonist binding modes.
- To evaluate improvements in virtual screening performance post-MD refinement.
Main Methods:
- Generated approximately 60 μs of MD simulation data for 30 D3R antagonist models.
- Employed two distinct simulation protocols for model refinement.
- Compared MD-refined models against the experimental D3R crystal structure.
- Assessed virtual screening performance using molecular docking of ligands and decoys.
Main Results:
- MD simulations generally caused receptor models to deviate from the crystal structure.
- MD refinement significantly improved the accuracy of predicted ligand binding modes for a majority of models.
- The best refinement protocol enhanced agreement with experimentally observed ligand binding.
- Virtual screening performance was improved for some MD-refined receptor structures.
- Weak restraints on transmembrane helices further refined ligand binding and extracellular loop predictions.
Conclusions:
- MD simulations offer a viable strategy for enhancing the accuracy of GPCR-ligand complex predictions.
- MD refinement shows promise for improving virtual screening and drug discovery pipelines.
- Specific MD protocols and restraints can optimize predictions of both binding modes and receptor conformations.
- The study provides practical guidelines for applying MD refinement to GPCR-ligand modeling.
