通过分子动力学模拟中的构象动力学捕获和水基口袋表征鉴定蛋白质隐位

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL
Tianming Qu, Steven L. Austin, Lianqing Zheng, James Zhang and Wei Yang*, 
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引用次数: 0

摘要

利用分子动力学(MD)模拟研究新的蛋白质隐位点的形成已经引起了药物发现领域越来越多的兴趣。该领域的一个具体挑战是找到一种可行的方法来准确识别和表征MD模拟结果中的隐位点转变,同时最大限度地减少对大量人力投入的需求。由于隐位点的形成通常涉及蛋白质结构的重大构象变化,因此能够精确捕获和描述这些动态口袋转变的方法是必不可少的。在本文中,我们提出了一个新的程序,构象动力学捕获和水基表征(CDC-WBC)。该程序通过跟踪在分子动力学(MD)模拟中观察到的蛋白质构象变化来动态识别隐位点区域。该程序还包含水密度信息,以增强跨帧的隐位点的表征。我们通过应用CDC-WBC程序来表征TEM1 β-内酰胺酶中两个已被充分研究的隐位点的开放过程来评估它。结果表明,CDC-WBC方法准确地捕获了两个隐位点的开闭转变。为了比较,我们采用三种常用的蛋白空腔检测方法,即POVME2、Epock和MDpocket,对TEM1 β-内酰胺酶中的“CBT”隐匿位点进行鉴定。结果表明,CDC-WBC方法在表征“CBT”隐位点转变方面优于这些方法。此外,使用来自CryptoSite数据集的84个蛋白质系统(93个隐泡)的基准集,CDC-WBC在区分隐泡位点的开放和封闭状态方面始终表现出更好的性能,进一步突出了其精确表征动态隐泡位点转变的能力。CDC-WBC程序的详细实现和演示数据集上传到GitHub: https://github.com/TianmingQu/CDC-WBC.git
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Employing molecular dynamics (MD) simulation to study the formation of novel protein cryptic sites has attracted increasing interest in the field of drug discovery. One specific challenge in this area is finding a viable method to accurately identify and characterize cryptic site transitions from MD simulation results while minimizing the need for extensive human input. Since the formation of cryptic sites often involves significant conformational changes in the protein structure, a method capable of capturing and describing these dynamic pocket transitions with precision is essential. In this paper, we present a new procedure, Conformational Dynamics Capturing and Water-Based Characterization (CDC-WBC). This procedure dynamically identifies the cryptic site region by tracking protein conformational changes observed during molecular dynamics (MD) simulations. The procedure also incorporates water density information to enhance the characterization of cryptic sites across frames. We evaluate the CDC-WBC procedure by applying it to characterize the opening process of the two well-studied cryptic sites in TEM1 β-lactamase. The results demonstrate that the CDC-WBC method accurately captures the open-closed transitions of the two cryptic sites. For comparison, three commonly used protein cavity detection methods in cryptic sites studies, POVME2, Epock, and MDpocket, are applied to identify the “CBT” cryptic site in TEM1 β-lactamase. The results show that the CDC-WBC method outperforms these methods in characterizing the transitions of the “CBT” cryptic site. Additionally, using a benchmark set of 84 protein systems (93 cryptic pockets) from the CryptoSite data set, CDC-WBC consistently shows better performance in distinguishing between the open and closed states of cryptic sites, further highlighting its capability for precise characterization of dynamic cryptic site transitions. The detailed implementation of the CDC-WBC procedure and demo data sets are uploaded to GitHub: https://github.com/TianmingQu/CDC-WBC.git

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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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