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基于 2D SMARTCyp 的主要药物代谢细胞色素 P450 酶的代谢部位预测反应性。

2D SMARTCyp reactivity-based site of metabolism prediction for major drug-metabolizing cytochrome P450 enzymes.

机构信息

DoD Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Material Command, Fort Detrick, Maryland 21702, USA.

出版信息

J Chem Inf Model. 2012 Jun 25;52(6):1698-712. doi: 10.1021/ci3001524. Epub 2012 Jun 4.

Abstract

Cytochrome P450 (CYP) 3A4, 2D6, 2C9, 2C19, and 1A2 are the most important drug-metabolizing enzymes in the human liver. Knowledge of which parts of a drug molecule are subject to metabolic reactions catalyzed by these enzymes is crucial for rational drug design to mitigate ADME/toxicity issues. SMARTCyp, a recently developed 2D ligand structure-based method, is able to predict site-specific metabolic reactivity of CYP3A4 and CYP2D6 substrates with an accuracy that rivals the best and more computationally demanding 3D structure-based methods. In this article, the SMARTCyp approach was extended to predict the metabolic hotspots for CYP2C9, CYP2C19, and CYP1A2 substrates. This was accomplished by taking into account the impact of a key substrate-receptor recognition feature of each enzyme as a correction term to the SMARTCyp reactivity. The corrected reactivity was then used to rank order the likely sites of CYP-mediated metabolic reactions. For 60 CYP1A2 substrates, the observed major sites of CYP1A2 catalyzed metabolic reactions were among the top-ranked 1, 2, and 3 positions in 67%, 80%, and 83% of the cases, respectively. The results were similar to those obtained by MetaSite and the reactivity + docking approach. For 70 CYP2C9 substrates, the observed sites of CYP2C9 metabolism were among the top-ranked 1, 2, and 3 positions in 66%, 86%, and 87% of the cases, respectively. These results were better than the corresponding results of StarDrop version 5.0, which were 61%, 73%, and 77%, respectively. For 36 compounds metabolized by CYP2C19, the observed sites of metabolism were found to be among the top-ranked 1, 2, and 3 sites in 78%, 89%, and 94% of the cases, respectively. The computational procedure was implemented as an extension to the program SMARTCyp 2.0. With the extension, the program can now predict the site of metabolism for all five major drug-metabolizing enzymes with an accuracy similar to or better than that achieved by the best 3D structure-based methods. Both the Java source code and the binary executable of the program are freely available to interested users.

摘要

细胞色素 P450(CYP)3A4、2D6、2C9、2C19 和 1A2 是人类肝脏中最重要的药物代谢酶。了解药物分子的哪些部分容易受到这些酶催化的代谢反应的影响,对于合理的药物设计以减轻 ADME/毒性问题至关重要。SMARTCyp 是一种最近开发的 2D 配体结构基方法,能够以与最佳和更计算密集型 3D 结构基方法相当的准确度预测 CYP3A4 和 CYP2D6 底物的特异性代谢反应性。在本文中,SMARTCyp 方法被扩展用于预测 CYP2C9、CYP2C19 和 CYP1A2 底物的代谢热点。这是通过考虑每个酶的关键底物-受体识别特征的影响作为 SMARTCyp 反应性的校正项来实现的。然后,使用校正后的反应性对可能的 CYP 介导的代谢反应位点进行排序。对于 60 种 CYP1A2 底物,在 67%、80%和 83%的情况下,观察到的 CYP1A2 催化代谢反应的主要部位分别位于前 1、2 和 3 位。结果与 MetaSite 和反应性+对接方法获得的结果相似。对于 70 种 CYP2C9 底物,在 66%、86%和 87%的情况下,观察到的 CYP2C9 代谢部位分别位于前 1、2 和 3 位。这些结果优于 StarDrop 版本 5.0 的相应结果,分别为 61%、73%和 77%。对于 36 种由 CYP2C19 代谢的化合物,在 78%、89%和 94%的情况下,观察到的代谢部位分别位于前 1、2 和 3 位。计算过程被实现为 SMARTCyp 2.0 的扩展。通过扩展,该程序现在可以以与最佳 3D 结构基方法相当或更好的准确度预测所有五种主要药物代谢酶的代谢部位。感兴趣的用户可以免费获得该程序的 Java 源代码和二进制可执行文件。

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