通过马尔可夫状态建模对 MD 中 T4 L99A 的离散结合构象进行基于动力学的状态定义

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-12-09 Epub Date: 2024-11-26 DOI:10.1021/acs.jcim.4c01364
Chris Zhang, Meghan Osato, David L Mobley
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引用次数: 0

摘要

作为一个模型系统,T4 溶菌酶 L99A 突变体的结合口袋一直是许多计算自由能研究的主题。然而,以前的研究未能充分采样和解释 T4 L99A 结合同源配体系列时结合口袋中观察到的变化,从而限制了结果的准确性。在这项研究中,我们在 MD 中解析了之前实验中报道的 T4 L99A 的封闭、中间和开放状态,并根据系统的动力学建立了这些状态的定义。通过分析,我们得出两个主要结论。首先,不应简单地根据晶体结构的 RMSD 将模拟轨迹分配为离散状态,因为这可能导致状态分配错误。其次,这里研究的不同可转移构象需要仔细对待,因为我们估计构象相互转换的时间尺度在 102 至 103 ns 之间--远远长于典型结合计算的时间尺度。最后,我们讨论了开发增强型采样方法的必要性,以便对相对较小的配体扰动引起的蛋白质构象的显著变化进行总体解释。
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Kinetics-Based State Definitions for Discrete Binding Conformations of T4 L99A in MD via Markov State Modeling.

As a model system, the binding pocket of the L99A mutant of T4 lysozyme has been the subject of numerous computational free energy studies. However, previous studies have failed to fully sample and account for the observed changes in the binding pocket of T4 L99A upon binding of a congeneric ligand series, limiting the accuracy of results. In this work, we resolve the closed, intermediate, and open states for T4 L99A previously reported in experiment in MD and establish definitions for these states based on the dynamics of the system. From this analysis, we arrive at two primary conclusions. First, assignment of simulation trajectories into discrete states should not be done simply based on RMSD to crystal structures as this can result in misassignment of states. Second, the different metastable conformations studied here need to be carefully treated, as we estimate the time scales for conformational interconversion to be on the order of 102 to 103 ns─far longer than time scales for typical binding calculations. We conclude with a discussion on the need to develop enhanced sampling methods to generally account for significant changes in protein conformation due to relatively small ligand perturbations.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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