Modeling Ligand Binding Site Water Networks with Site Identification by Ligand Competitive Saturation: Impact on Ligand Binding Orientations and Relative Binding Affinities.

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2024-12-24 Epub Date: 2024-12-05 DOI:10.1021/acs.jctc.4c01165
Anmol Kumar, Himanshu Goel, Wenbo Yu, Mingtian Zhao, Alexander D MacKerell
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Abstract

Appropriate treatment of water contributions to protein-ligand interactions is a very challenging problem in the context of adequately determining the number of waters to investigate and undertaking conformational sampling of the ligands, the waters, and the surrounding protein. In the present study, an extension of the Site Identification by Ligand Competitive Saturation-Monte Carlo (SILCS-MC) docking approach is presented that enables the determination of the location of water molecules in the binding pocket and their impact on the predicted ligand binding orientation and affinities. The approach, termed SILCS-WATER, involves MC sampling of the ligand along with explicit water molecules in a binding site followed by selection of a subset of waters within specified energetic and distance cutoffs that contribute to ligand binding and orientation. To allow for convergence of both the water and ligand orientations, SILCS-WATER is based on just the overlap of the ligand and water with the SILCS FragMaps and the interaction energy between the waters and ligand. Results show that the SILCS-WATER methodology can capture important waters and improve ligand binding orientations. For 6 of 10 multiple ligand-protein systems, the method improved relative binding affinity prediction against experimental results, with substantial improvements in five systems, when compared to standard SILCS-MC. Improved reproduction of crystallographic ligand binding orientations is shown to be an indicator of when SILCS-WATER will yield improved binding affinity correlations. The method also identifies waters interacting with ligands that occupy unfavorable locations with respect to the protein whose displacement through the appropriate ligand modifications should improve ligand binding affinity. Results are consistent with the binding affinity being modeled as a ligand-water complex interacting with the protein. The presented approach offers new possibilities in revealing water networks and their contributions to the binding orientation and affinity of a ligand for a protein and is anticipated to be of utility for computer-aided drug design.

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通过配体竞争饱和进行位点识别的配体结合位点水网络建模:对配体结合方向和相对结合亲和力的影响。
适当处理水对蛋白质-配体相互作用的影响是一个非常具有挑战性的问题,因为要充分确定用于研究的水的数量,并对配体、水和周围蛋白质进行构象采样。在本研究中,提出了一种通过配体竞争饱和-蒙特卡罗(SILCS-MC)对接方法进行位点识别的扩展,该方法能够确定结合口袋中水分子的位置及其对预测配体结合取向和亲和力的影响。该方法被称为SILCS-WATER,包括配体的MC采样以及结合位点的明确水分子,然后在指定的能量和距离截断范围内选择一部分水,这些截断有助于配体的结合和取向。为了允许水和配体方向的收敛,SILCS- water仅基于配体和水与SILCS FragMaps的重叠以及水和配体之间的相互作用能。结果表明,SILCS-WATER方法可以捕获重要的水并改善配体的结合方向。对于10个多配体-蛋白体系中的6个,与实验结果相比,该方法改进了相对结合亲和力预测,与标准SILCS-MC相比,在5个体系中有实质性改进。晶体配体结合方向的改进再现被证明是SILCS-WATER何时产生改进的结合亲和相关性的一个指标。该方法还鉴定了与占据蛋白质不利位置的配体相互作用的水,通过适当的配体修饰其位移应提高配体结合亲和力。结果与与蛋白质相互作用的配体-水络合物的结合亲和力一致。所提出的方法为揭示水网络及其对蛋白质配体的结合取向和亲和力的贡献提供了新的可能性,并有望用于计算机辅助药物设计。
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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