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| Home > Publications database > Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-based Hybrid Molecular Mechanics/Coarse-Grained Approach > print |
| Home > Publications database > Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-based Hybrid Molecular Mechanics/Coarse-Grained Approach > print |
| 001 | 878447 | ||
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| 100 | 1 | _ | |a Schneider, Jakob |0 P:(DE-Juel1)171534 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-based Hybrid Molecular Mechanics/Coarse-Grained Approach |
| 260 | _ | _ | |a Washington, DC |c 2020 |b American Chemical Society64160 |
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| 520 | _ | _ | |a 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. |
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| 773 | _ | _ | |a 10.1021/acs.jcim.0c00661 |g p. acs.jcim.0c00661 |0 PERI:(DE-600)1491237-5 |n 10 |p 5103–5116 |t Journal of chemical information and modeling |v 60 |y 2020 |x 1549-960X |
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