School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CH-1206 Geneva, CH.
Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CH-1206 Geneva, CH.
J Phys Chem Lett. 2024 Oct 3;15(39):9871-9880. doi: 10.1021/acs.jpclett.4c02352. Epub 2024 Sep 20.
The calculation of absolute binding free energies (ABFEs) for protein-ligand systems has long been a challenge. Recently, refined force fields and algorithms have improved the quality of the ABFE calculations. However, achieving the level of accuracy required to inform drug discovery efforts remains difficult. Here, we present a transferable enhanced sampling strategy to accurately calculate absolute binding free energies using OneOPES with simple geometric collective variables. We tested the strategy on two protein targets, BRD4 and Hsp90, complexed with a total of 17 chemically diverse ligands, including both molecular fragments and drug-like molecules. Our results show that OneOPES accurately predicts protein-ligand binding affinities with a mean unsigned error within 1 kcal mol of experimentally determined free energies, without the need to tailor the collective variables to each system. Furthermore, our strategy effectively samples different ligand binding modes and consistently matches the experimentally determined structures regardless of the initial protein-ligand configuration. Our results suggest that the proposed OneOPES strategy can be used to inform lead optimization campaigns in drug discovery and to study protein-ligand binding and unbinding mechanisms.
计算蛋白质-配体体系的绝对结合自由能（ABFE）一直是一个挑战。最近，经过改进的力场和算法提高了 ABFE 计算的质量。然而，要达到为药物发现工作提供信息所需的准确性水平仍然很困难。在这里，我们提出了一种可转移的增强采样策略，使用 OneOPES 结合简单的几何集体变量来准确计算绝对结合自由能。我们在两个蛋白质靶标（BRD4 和 Hsp90）上测试了该策略，共结合了 17 种具有不同化学性质的配体，包括分子片段和类药分子。我们的结果表明，OneOPES 可以准确预测蛋白质-配体的结合亲和力，其平均无偏差误差在实验确定的自由能的 1 kcal/mol 范围内，而无需针对每个体系定制集体变量。此外，我们的策略有效地采样了不同的配体结合模式，并始终匹配实验确定的结构，而不管初始的蛋白质-配体构型如何。我们的结果表明，所提出的 OneOPES 策略可用于为药物发现中的先导优化活动提供信息，并研究蛋白质-配体结合和解离机制。
