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混合MM/CG网络服务器:用于人类G蛋白偶联受体/配体复合物的分子力学/粗粒度模拟的自动设置

Hybrid MM/CG Webserver: Automatic Set Up of Molecular Mechanics/Coarse-Grained Simulations for Human G Protein-Coupled Receptor/Ligand Complexes.

作者信息

Schneider Jakob, Ribeiro Rui, Alfonso-Prieto Mercedes, Carloni Paolo, Giorgetti Alejandro

机构信息

Computational Biomedicine, Institute for Advanced Simulation IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich, Germany.

JARA-Institute: Molecular Neuroscience and Neuroimaging, Institute for Neuroscience and Medicine INM-11/JARA-BRAIN Institute JBI-2, Forschungszentrum Jülich GmbH, Jülich, Germany.

出版信息

Front Mol Biosci. 2020 Sep 4;7:576689. doi: 10.3389/fmolb.2020.576689. eCollection 2020.

Abstract

Hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations help predict ligand poses in human G protein-coupled receptors (hGPCRs), the most important protein superfamily for pharmacological applications. This approach allows the description of the ligand, the binding cavity, and the surrounding water molecules at atomistic resolution, while coarse-graining the rest of the receptor. Here, we present the Hybrid MM/CG Webserver (mmcg.grs.kfa-juelich.de) that automatizes and speeds up the MM/CG simulation setup of hGPCR/ligand complexes. Initial structures for such complexes can be easily and efficiently generated with other webservers. The Hybrid MM/CG server also allows for equilibration of the systems, either fully automatically or interactively. The results are visualized online (using both interactive 3D visualizations and analysis plots), helping the user identify possible issues and modify the setup parameters accordingly. Furthermore, the prepared system can be downloaded and the simulation continued locally.

摘要

混合分子力学/粗粒度(MM/CG)模拟有助于预测人G蛋白偶联受体(hGPCRs)中的配体构象,hGPCRs是药理学应用中最重要的蛋白质超家族。这种方法能够在原子分辨率下描述配体、结合腔以及周围的水分子,同时对受体的其余部分进行粗粒度处理。在此,我们展示了混合MM/CG网络服务器(mmcg.grs.kfa-juelich.de),它能自动执行并加速hGPCR/配体复合物的MM/CG模拟设置。此类复合物的初始结构可以通过其他网络服务器轻松高效地生成。混合MM/CG服务器还允许系统完全自动或交互式地达到平衡。结果可在线可视化(使用交互式3D可视化和分析图),帮助用户识别可能存在的问题并相应地修改设置参数。此外,准备好的系统可以下载并在本地继续模拟。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5fde/7500467/f3921960365f/fmolb-07-576689-g001.jpg

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