MDM-Pred:一个免费的网络应用程序,用于预测肠道微生物群对药物类化合物的代谢。

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY
A S Kolodnitsky, N S Ionov, A V Rudik, A A Lagunin, D A Filimonov, V V Poroikov
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引用次数: 0

摘要

人类肠道微生物群(HGM)包括一个复杂的微生物种群,它们显著影响人类健康,包括它们对外源代谢的影响。许多药物是口服的,因此会与HGM接触,HGM会代谢它们。因此,有必要评估HGM对药物在机体中的命运的影响。我们从80多份出版物中收集了600多种化合物的信息。其中至少一半(329种化合物)已知可被HGM代谢。我们利用PASS (Prediction of Activity Spectra for Substances)软件构建了三种分类SAR模型,用于hgm介导的药物代谢预测。第一个预测精度为0.85的模型估计化合物是否会被HGM代谢。第二个模型的平均预测精度为0.92,估计哪些细菌属负责药物代谢。第三个模型估计hgm介导的药物代谢过程中的生物转化反应,平均预测精度为0.92。创建的模型用于开发免费的web应用程序MDM-Pred (http://www.way2drug.com/mdm-pred/)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MDM-Pred: a freely available web application for predicting the metabolism of drug-like compounds by the gut microbiota.

The human gut microbiota (HGM) comprises a complex population of microorganisms that significantly affect human health, including their influence on xenobiotics metabolism. Many pharmaceuticals are taken orally and thus come into contact with HGM, which can metabolize them. Therefore, it is necessary to evaluate the effect of HGM on the fate of pharmaceuticals in the organism. We have collected information about over 600 compounds from more than eighty publications. At least half of them (329 compounds) are known to be metabolized by HGM. We have used PASS (Prediction of Activity Spectra for Substances) software to build three classification SAR models for HGM-mediated drug metabolism prediction. The first model with an accuracy of prediction 0.85 estimates whether compounds will be metabolized by HGM. The second model with an average accuracy of prediction 0.92 estimates which bacterial genera are responsible for the drug metabolism. The third model with an average accuracy of prediction 0.92 estimates the biotransformation reactions during HGM-mediated drug metabolism. The created models were used to develop the freely available web application MDM-Pred (http://www.way2drug.com/mdm-pred/).

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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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