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000878447 1001_ $$0P:(DE-Juel1)171534$$aSchneider, Jakob$$b0$$eCorresponding author
000878447 245__ $$aLigand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-based Hybrid Molecular Mechanics/Coarse-Grained Approach
000878447 260__ $$aWashington, DC$$bAmerican Chemical Society64160$$c2020
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000878447 520__ $$aHuman G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.
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000878447 7001_ $$0P:(DE-Juel1)171535$$aKorshunova, Ksenia$$b1$$ufzj
000878447 7001_ $$0P:(DE-Juel1)173772$$aSi Chaib, Zeineb$$b2$$ufzj
000878447 7001_ $$0P:(DE-Juel1)165199$$aGiorgetti, Alejandro$$b3$$ufzj
000878447 7001_ $$0P:(DE-Juel1)169976$$aAlfonso-Prieto, Mercedes$$b4$$ufzj
000878447 7001_ $$0P:(DE-Juel1)145614$$aCarloni, Paolo$$b5$$ufzj
000878447 773__ $$0PERI:(DE-600)1491237-5$$a10.1021/acs.jcim.0c00661$$gp. acs.jcim.0c00661$$n10$$p5103–5116$$tJournal of chemical information and modeling$$v60$$x1549-960X$$y2020
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