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Jarzynski 等式在计算机辅助药物设计中的表现如何?

How Good is Jarzynski's Equality for Computer-Aided Drug Design?

机构信息

Institute for Computational Sciences and Technology, Quang Trung Software City, SBI Building, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam.

Department of Theoretical Physics, Faculty of Physics and Engineering Physics, Ho Chi Minh University of Science, Ho Chi Minh City, Vietnam.

出版信息

J Phys Chem B. 2020 Jul 2;124(26):5338-5349. doi: 10.1021/acs.jpcb.0c02009. Epub 2020 Jun 22.

Abstract

Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski's equality (JE) combined with steered molecular dynamics and the linear interaction energy (LIE) method by assessing the binding affinity of 23 small compounds to six receptors, including β-lactamase, thrombin, factor Xa, HIV-1 protease (HIV), myeloid cell leukemia-1, and cyclin-dependent kinase 2 proteins. It was shown that Jarzynski's nonequilibrium binding free energy Δ correlates with the available experimental data with the correlation levels = 0.89, 0.86, 0.83, 0.80, 0.83, and 0.81 for six data sets, while for the binding free energy Δ obtained by the LIE method, we have = 0.73, 0.80, 0.42, 0.23, 0.85, and 0.01. Therefore, JE is recommended to be used for ranking binding affinities as it provides accurate and robust results. In contrast, LIE is not as reliable as JE, and it should be used with caution, especially when it comes to new systems.

摘要

准确确定配体与受体的结合亲和力仍然是计算机辅助药物设计中的一个难题。在这里,我们通过评估 23 种小分子化合物与 6 种受体(包括β-内酰胺酶、凝血酶、因子 Xa、HIV-1 蛋白酶(HIV)、髓样细胞白血病-1 和细胞周期蛋白依赖性激酶 2 蛋白)的结合亲和力,研究并比较了雅可比等式(JE)与导向分子动力学和线性相互作用能(LIE)方法的效率。结果表明,Jarzynski 的非平衡结合自由能Δ与可用的实验数据相关,对于六个数据集,相关系数分别为 0.89、0.86、0.83、0.80、0.83 和 0.81,而通过 LIE 方法获得的结合自由能Δ,我们有 0.73、0.80、0.42、0.23、0.85 和 0.01。因此,建议使用 JE 来对结合亲和力进行排序,因为它提供了准确可靠的结果。相比之下,LIE 不如 JE 可靠,因此应该谨慎使用,特别是在涉及新系统时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6568/7590978/ebbcfce4acdf/jp0c02009_0001.jpg

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