Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy.
CompuNet, Istituto Italiano di Tecnologia , Via Morego 30, 16163, Genova, Italy.
J Chem Inf Model. 2018 Feb 26;58(2):490-500. doi: 10.1021/acs.jcim.7b00674. Epub 2018 Feb 9.
Predicting the geometry of protein-ligand binding complexes is of primary importance for structure-based drug discovery. Molecular dynamics (MD) is emerging as a reliable computational tool for use in conjunction with, or an alternative to, docking methods. However, simulating the protein-ligand binding process often requires very expensive simulations. This drastically limits the practical application of MD-based approaches. Here, we propose a general framework to accelerate the generation of putative protein-ligand binding modes using potential-scaled MD simulations. The proposed dynamical protocol has been applied to two pharmaceutically relevant systems (GSK-3β and the N-terminal domain of HSP90α). Our approach is fully independent of any predefined reaction coordinate (or collective variable). It identified the correct binding mode of several ligands and can thus save valuable computational time in dynamic docking simulations.
预测蛋白质-配体结合复合物的结构对于基于结构的药物发现至关重要。分子动力学（MD）作为一种可靠的计算工具，正在与对接方法结合使用或作为其替代方法而兴起。然而，模拟蛋白质-配体结合过程通常需要非常昂贵的模拟。这极大地限制了基于 MD 的方法的实际应用。在这里，我们提出了一种使用势标度 MD 模拟加速生成可能的蛋白质-配体结合模式的通用框架。所提出的动力学方案已应用于两个具有药物相关性的系统（GSK-3β 和 HSP90α 的 N 端结构域）。我们的方法完全不依赖于任何预定义的反应坐标（或集体变量）。它确定了几个配体的正确结合模式，因此可以在动态对接模拟中节省宝贵的计算时间。
