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基于混合 QM/MM 模拟的共价抑制剂的设计与 SAR 分析。

Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations.

机构信息

Drug Design and Discovery Group, Department of Food and Drug, University of Parma, Parma, Italy.

出版信息

Methods Mol Biol. 2020;2114:307-337. doi: 10.1007/978-1-0716-0282-9_19.

Abstract

Quantum mechanics/molecular mechanics (QM/MM) hybrid technique is emerging as a reliable computational method to investigate and characterize chemical reactions occurring in enzymes. From a drug discovery perspective, a thorough understanding of enzyme catalysis appears pivotal to assist the design of inhibitors able to covalently bind one of the residues belonging to the enzyme catalytic machinery. Thanks to the current advances in computer power, and the availability of more efficient algorithms for QM-based simulations, the use of QM/MM methodology is becoming a viable option in the field of covalent inhibitor design. In the present review, we summarized our experience in the field of QM/MM simulations applied to drug design problems which involved the optimization of agents working on two well-known drug targets, namely fatty acid amide hydrolase (FAAH) and epidermal growth factor receptor (EGFR). In this context, QM/MM simulations gave valuable information in terms of geometry (i.e., of transition states and metastable intermediates) and reaction energetics that allowed to correctly predict inhibitor binding orientation and substituent effect on enzyme inhibition. What is more, enzyme reaction modelling with QM/MM provided insights that were translated into the synthesis of new covalent inhibitor featured by a unique combination of intrinsic reactivity, on-target activity, and selectivity.

摘要

量子力学/分子力学 (QM/MM) 混合技术作为一种可靠的计算方法,正在被广泛应用于研究和描述酶中发生的化学反应。从药物发现的角度来看,深入了解酶催化作用似乎对于协助设计能够共价结合酶催化机制之一的残基的抑制剂至关重要。由于计算机能力的当前进展,以及基于 QM 的模拟的更有效算法的可用性,QM/MM 方法的使用在共价抑制剂设计领域正成为一种可行的选择。在本综述中,我们总结了我们在应用于涉及优化作用于两个著名药物靶点(即脂肪酸酰胺水解酶 (FAAH) 和表皮生长因子受体 (EGFR) 的药物设计问题的 QM/MM 模拟领域的经验。在这种情况下,QM/MM 模拟在几何形状(即过渡态和亚稳态中间体)和反应能方面提供了有价值的信息,这些信息允许正确预测抑制剂结合方向和取代基对酶抑制的影响。更重要的是,使用 QM/MM 进行酶反应建模提供了深入的见解,这些见解被转化为具有独特内在反应性、靶标活性和选择性的新型共价抑制剂的合成。

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