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运用互补原理于对接程序中:评估结合构象正确性的新方法。

Use of the Complementarity Principle in Docking Procedures: A New Approach for Evaluating the Correctness of Binding Poses.

机构信息

Department of Medicinal Chemistry, University of Zagreb Faculty of Pharmacy and Biochemistry, Ante Kovačića 1, 10000 Zagreb, Croatia.

Laboratory of Computational Modeling of Drugs, Higher Medical and Biological School, South Ural State University, Chaikovskogo 20A, Chelyabinsk 454008, Russia.

出版信息

J Chem Inf Model. 2021 Apr 26;61(4):1801-1813. doi: 10.1021/acs.jcim.0c01382. Epub 2021 Apr 2.

DOI:10.1021/acs.jcim.0c01382
PMID:33797240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8154257/
Abstract

Even though the first docking procedures were developed almost 40 years ago, they are still under intense development, alongside with their validation. In this article, we are proposing the use of the quantum free-orbital AlteQ method in evaluating the correctness of ligand binding poses and their ranking. The AlteQ method calculates the electron density in the interspace between the ligand and the receptor, and since their interactions follow the maximum complementarity principle, an equation can be obtained, which describes these interactions. In this way, the AlteQ method evaluates the quality of contacts between the ligand and the receptor, bypasses the drawbacks of using ligand RMSD as a measure of docking quality, and can be considered as an improvement of the "fraction of recovered ligand-receptor contacts" method. Free Windows and Linux versions of the AlteQ program for assessing complementarity between the ligand and the receptor are available for download at www.chemosophia.com.

摘要

尽管第一个对接程序是在近 40 年前开发的,但它们仍在与验证一起进行深入的开发。在本文中,我们提出使用量子自由轨道 AlteQ 方法来评估配体结合构象的正确性及其排序。AlteQ 方法计算配体和受体之间的间隔中的电子密度,并且由于它们的相互作用遵循最大互补原理,可以获得描述这些相互作用的方程。通过这种方式,AlteQ 方法评估配体与受体之间接触的质量,避免了使用配体 RMSD 作为对接质量的度量的缺点,并可以被认为是对“恢复的配体-受体接触分数”方法的改进。可在 www.chemosophia.com 下载用于评估配体和受体之间互补性的 AlteQ 程序的免费 Windows 和 Linux 版本。

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3
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Int J Mol Sci. 2024 Jul 28;25(15):8241. doi: 10.3390/ijms25158241.
4
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Antioxidants (Basel). 2022 Nov 7;11(11):2204. doi: 10.3390/antiox11112204.
6
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