Computational Biomedicine, Institute for Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany.
Department of Physics, RWTH Aachen University, 52074 Aachen, Germany.
J Chem Inf Model. 2020 Oct 26;60(10):5103-5116. doi: 10.1021/acs.jcim.0c00661. Epub 2020 Aug 14.
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.
人类 G 蛋白偶联受体 (hGPCRs) 是美国食品和药物管理局 (FDA) 批准药物的最常见靶点。结构生物信息学与分子模拟一起，可以支持针对 hGPCR 的基于结构的药物设计。在这种情况下，几年前，我们开发了一种混合分子力学 (MM)/粗粒化 (CG) 方法来预测低分辨率 hGPCR 模型中的配体构象。该方法基于 GROMOS96 43A1 和 PRODRG 统一原子力场用于 MM 部分。在这里，我们提出了一种新的 MM/CG 实现方法，分别使用 Amber 14SB 和 GAFF 全原子势来表示蛋白质和配体。新的实现方法优于以前的方法，这在不同分辨率的 hGPCR/配体复合物模型上的各种应用中得到了证明，并且它也更加用户友好。因此，它成为预测低分辨率模型中配体构象的有用工具，并提供了类似于全原子分子动力学的配体结合见解，尽管计算成本较低。
