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Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach

Jakob Schneider, Ksenia Korshunova, Zeineb Si Chaib, Alejandro Giorgetti, Mercedes Alfonso‐Prieto, Paolo Carloni

2020Journal of Chemical Information and Modeling15 citationsDOI

Abstract

Human G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.

Topics & Concepts

Molecular dynamicsContext (archaeology)Molecular mechanicsLigand (biochemistry)Computational biologyComputer scienceG protein-coupled receptorMolecular modelDrug discoveryBiological systemChemistryForce field (fiction)BiophysicsNanotechnologyReceptorArtificial intelligenceComputational chemistryMaterials scienceBiologyStereochemistryBiochemistryPaleontologyReceptor Mechanisms and SignalingProtein Structure and DynamicsChemical Synthesis and Analysis