MDPath: Unraveling Allosteric Communication Paths of Drug Targets through Molecular Dynamics Simulations.

IF 5.3 2区化学 Q1 CHEMISTRY, MEDICINAL

Journal of Chemical Information and Modeling Pub Date : 2025-10-01 DOI:10.1021/acs.jcim.5c01590

Niklas Piet Doering, Marvin Taterra, Marcel Bermúdez, Gerhard Wolber

引用次数: 0

Abstract

Understanding allosteric communication in proteins remains a critical challenge for structure-based, rational drug design. We present MDPath, a Python toolkit for analyzing allosteric communication paths in molecular dynamics simulations using NMI-based analysis. We demonstrate MDPath's ability to identify both established and novel GPCR allosteric mechanisms using the β₂-adrenoceptor, adenosine A_2A receptor, and μ-opioid receptor as model systems. The toolkit reveals ligand-specific allosteric effects in β₂-adrenoceptor and MOR, illustrating how protein-ligand interactions drive conformational changes. Analysis of ABL1 kinase in complex with allosteric and orthosteric inhibitors demonstrates the broader applicability of the approach. Ultimately, MDPath provides an open-source framework for mapping allosteric communication within proteins, advancing structure-based drug design (https://github.com/wolberlab/mdpath).

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MDPath：通过分子动力学模拟揭示药物靶点的变构通信路径。

理解蛋白质中的变构通信仍然是基于结构的合理药物设计的关键挑战。我们提出MDPath，一个Python工具包，用于使用基于nmi的分析来分析分子动力学模拟中的变构通信路径。我们利用β2-肾上腺素受体、腺苷A2A受体和μ-阿片受体作为模型系统，证明MDPath能够识别已建立的和新的GPCR变构机制。该工具包揭示了β2-肾上腺素受体和MOR中的配体特异性变构效应，说明了蛋白质-配体相互作用如何驱动构象变化。对ABL1激酶与变构和正构抑制剂复合物的分析表明，该方法具有更广泛的适用性。最终，MDPath为绘制蛋白质内的变构通信提供了一个开源框架，推进了基于结构的药物设计（https://github.com/wolberlab/mdpath）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Chemical Information and Modeling 化学-化学综合

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.