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

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.

Unraveling the Role of Hydrogen Bonds in Thrombin via Two Machine Learning Methods

“…We used a 9 Å cutoff distance and a 7.5 Å switching distance for the van der Waals and electrostatic forces. These parameters are the default values in ACEMD3, and the same choice can be seen in a variety of MD simulation studies on several different systems by a variety of investigators − as well as in our previous studies of thrombin. − …”

In silico characterization of ligand–receptor interactions for U‐47700, N,N‐didesmethyl‐U‐47700, U‐50488 at mu‐ and kappa‐opioid receptors

“…Small effects can be expected, based on the relative sizes of membrane lipids, receptor proteins, and ligands, yet membrane–complex interactions are often more sensitive than direct observation of changes in protein conformations (e.g., by root‐mean‐square deviation (RMSD) analysis) via MD trajectories. [ 34 ] Moreover, as a distinct advantage, membrane–complex interaction analysis requires much shorter MD simulations. The receptor–membrane interaction energies for the MOR and KOR complexes are shown in the second column of Table 2.…”

Discovery of Biologically Optimized Polymyxin Derivatives Facilitated by Peptide Scanning and In Situ Screening Chemistry

“…The position should be carefully determined as the newly introduced moiety should not alter the functions of the original peptides and their interactions with target molecules. However, because the interaction surfaces between peptides and their target molecules are dynamic and broad, even with a modern docking or molecular dynamics (MD) simulations, it is a challenging task to predict suitable substituents and modification sites to improve their activities …”

“…However, because the interaction surfaces between peptides and their target molecules are dynamic and broad, even with a modern docking or molecular dynamics (MD) simulations, it is a challenging task to predict suitable substituents and modification sites to improve their activities. 19 As for the determination of the modification site on peptides, a sophisticated methodology has been developed: peptide scanning. 20−36 In this methodology, a systematic substitution of each amino acid in the peptide sequence for a certain scanning unit is used to investigate the importance of the corresponding amino acid residue.…”