共价抑制的动力学模型:快速波动中间态的影响。

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Kyle Ghaby,  and , Benoît Roux*, 
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引用次数: 0

摘要

人们对发现与靶标形成共价键的小分子抑制剂越来越感兴趣。然而,确定明确的合理设计原则仍然具有挑战性,因为这些分子的作用不能被理解为常见的非共价抑制。传统的动力学模型往往将共价抑制剂的结合简化为两步不可逆过程,忽略了在与靶标形成共价键之前相关的未连接抑制剂的快速复杂动力学。在本分析中,我们将中间态扩展为两种构象:反应态(E·I)和非反应态(E·I)。为了说明这种简化的结果,扩展的动力学模型可以简化为一个有效的两步方案,该方案以未连接抑制剂形成任意构象的平衡概率表示。实现了基于质量作用的数值工作流来模拟随时间变化的动力学,克服了经验模型的常见局限性。数值工作流有助于将分子动力学模拟中观察到的微观状态与宏观观察结果(如EC50和共价抑制表观速率)联系起来,显示瞬态中间体对解离速率和效价的影响。提出的框架改进了剂量-反应数据的解释,帮助药物化学家优化共价抑制剂,并提供了一个将分子构象分布与经验参数联系起来的定量平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Kinetic Modeling of Covalent Inhibition: Effects of Rapidly Fluctuating Intermediate States

Kinetic Modeling of Covalent Inhibition: Effects of Rapidly Fluctuating Intermediate States

There is increasing interest in the discovery of small-molecule inhibitors that form covalent bonds with their targets for therapeutic applications. Nevertheless, identifying clear rational design principles remains challenging because the action of these molecules cannot be understood as common noncovalent inhibition. Conventional kinetic models often reduce the binding of covalent inhibitors to a two-step irreversible process, overlooking rapid complex dynamics of the associated unlinked inhibitor before the formation of the covalent bond with its target. In the present analysis, we expand the intermediate state into two conformations: reactive (E·I) and nonreactive (E··I). To illustrate the consequences of such simplification, the expanded kinetic model can be reduced to an effective two-step scheme expressed in terms of the equilibrium probability of the unlinked inhibitor to form either conformation. A mass-action-based numerical workflow is implemented to simulate time-dependent kinetics, overcoming the common limitations of empirical models. The numerical workflow helps relate microscopic states observed in molecular dynamics simulations to macroscopic observables like EC50 and the apparent rate of covalent inhibition, showing the impact of transient intermediates on dissociation rates and potency. The proposed framework refines the interpretation of dose-response data, aiding medicinal chemists in optimizing covalent inhibitors and providing a quantitative platform that relates molecular conformational distributions to empirical parameters.

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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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