Suppr超能文献

通过马尔可夫状态模型对MD中T4 L99A离散结合构象基于动力学的状态定义

Kinetics-Based State Definitions for Discrete Binding Conformations of T4 L99A in MD via Markov State Modeling.

作者信息

Zhang Chris, Osato Meghan, Mobley David L

机构信息

Department of Chemistry, University of California, Irvine, 1120 Natural Sciences II, Irvine, California 92697, United States.

Department of Pharmaceutical Sciences, University of California, Irvine, 856 Health Sciences Road, Irvine, California 92697, United States.

出版信息

J Chem Inf Model. 2024 Dec 9;64(23):8870-8879. doi: 10.1021/acs.jcim.4c01364. Epub 2024 Nov 26.

Abstract

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 10 to 10 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.

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众多计算自由能研究的对象。然而,先前的研究未能充分采样并解释在结合同系配体系列时T4 L99A结合口袋中观察到的变化,从而限制了结果的准确性。在这项工作中,我们在分子动力学(MD)模拟中解析了先前实验报道的T4 L99A的闭合、中间和开放状态,并基于系统动力学为这些状态建立了定义。通过该分析,我们得出两个主要结论。首先,不应仅基于与晶体结构的均方根偏差(RMSD)将模拟轨迹分配到离散状态,因为这可能导致状态的错误分配。其次,这里研究的不同亚稳态构象需要仔细处理,因为我们估计构象相互转换的时间尺度在10到10纳秒量级——远比典型结合计算的时间尺度长得多。我们最后讨论了开发增强采样方法以普遍解释由于相对较小的配体扰动导致的蛋白质构象显著变化(的必要性)。

相似文献

6
Protein-ligand binding free energies from exhaustive docking.从详尽对接中获得蛋白质-配体结合自由能。
J Phys Chem B. 2012 Jun 14;116(23):6872-9. doi: 10.1021/jp212646s. Epub 2012 Apr 2.
7
Reversibly Sampling Conformations and Binding Modes Using Molecular Darting.使用分子镖射技术来可逆地采样构象和结合模式。
J Chem Theory Comput. 2021 Jan 12;17(1):302-314. doi: 10.1021/acs.jctc.0c00752. Epub 2020 Dec 8.

本文引用的文献

5
Time-Lagged Independent Component Analysis of Random Walks and Protein Dynamics.随机漫步和蛋白质动力学的时滞独立成分分析。
J Chem Theory Comput. 2021 Sep 14;17(9):5766-5776. doi: 10.1021/acs.jctc.1c00273. Epub 2021 Aug 27.
6
Enhancing Side Chain Rotamer Sampling Using Nonequilibrium Candidate Monte Carlo.利用非平衡候选蒙特卡罗方法增强侧链构象抽样。
J Chem Theory Comput. 2019 Mar 12;15(3):1848-1862. doi: 10.1021/acs.jctc.8b01018. Epub 2019 Feb 11.
10
Markov State Models: From an Art to a Science.马尔可夫状态模型:从一门艺术到一门科学。
J Am Chem Soc. 2018 Feb 21;140(7):2386-2396. doi: 10.1021/jacs.7b12191. Epub 2018 Feb 2.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验