Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen, 518172, China.
Department of Chemistry, University College London, London, WC1H 0AJ, UK.
J Comput Aided Mol Des. 2022 Jul;36(7):537-547. doi: 10.1007/s10822-022-00464-3. Epub 2022 Jul 11.
When employing molecular dynamics (MD) simulations for computer-aided drug design, the quality of the used force fields is highly important. Here we present reparametrisations of the force fields for the core molecules from 9 different [Formula: see text]-lactam classes, for which we utilized the force field Toolkit and Gaussian calculations. We focus on the parametrisation of the dihedral angles, with the goal of reproducing the optimised quantum geometry in MD simulations. Parameters taken from CGenFF turn out to be a good initial guess for the multiplicity of each dihedral angle, but the key to a successful parametrisation is found to lie in the phase shifts. Based on the optimised quantum geometry, we come up with a strategy for predicting the phase shifts prior to the dihedral potential fitting. This allows us to successfully parameterise 8 out of the 11 molecules studied here, while the remaining 3 molecules can also be parameterised with small adjustments. Our work highlights the importance of predicting the dihedral phase shifts in the ligand parametrisation protocol, and provides a simple yet valuable strategy for improving the process of parameterising force fields of drug-like molecules.
当使用分子动力学 (MD) 模拟进行计算机辅助药物设计时,所使用力场的质量非常重要。在这里,我们针对 9 种不同的 [Formula: see text]-内酰胺类核心分子的力场进行了重新参数化,我们利用力场工具包和高斯计算来实现这一点。我们专注于二面角的参数化,目标是在 MD 模拟中重现优化后的量子几何形状。从 CGenFF 中获取的参数对于每个二面角的多重性来说是一个很好的初始猜测,但成功参数化的关键在于相移。基于优化后的量子几何形状,我们提出了一种在二面角势拟合之前预测相移的策略。这使我们能够成功地对研究的 11 个分子中的 8 个进行参数化,而其余 3 个分子也可以通过微小的调整进行参数化。我们的工作强调了在配体参数化协议中预测二面角相移的重要性,并提供了一种简单而有价值的策略,用于改进药物样分子力场的参数化过程。