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药物类药性工具包有助于药物发现中的 ADMET 研究。

A drug-likeness toolbox facilitates ADMET study in drug discovery.

机构信息

Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, PR China.

Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, PR China; International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan, 430079, PR China; State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Research and Development Center for Fine Chemicals, Guizhou University, Guiyang 550025, PR China.

出版信息

Drug Discov Today. 2020 Jan;25(1):248-258. doi: 10.1016/j.drudis.2019.10.014. Epub 2019 Nov 6.

DOI:10.1016/j.drudis.2019.10.014
PMID:31705979
Abstract

Undesirable pharmacokinetic (PK) properties or unacceptable toxicity are the main causes of the failure of drug candidates at the clinical trial stage. Since the concept of drug-likeness was first proposed, it has become an important consideration in the selection of compounds with desirable bioavailability during the early phases of drug discovery. Over the past decade, online resources have effectively facilitated drug-likeness studies in an economical and time-efficient manner. Here, we provide a comprehensive summary and comparison of current accessible online resources, in terms of their key features, application fields, and performance for in silico drug-likeness studies. We hope that the assembled toolbox will provide useful guidance to facilitate future in silico drug-likeness research.

摘要

不理想的药代动力学(PK)性质或不可接受的毒性是候选药物在临床试验阶段失败的主要原因。自从药物类似性的概念首次提出以来,它已成为在药物发现的早期阶段选择具有理想生物利用度的化合物的重要考虑因素。在过去的十年中,在线资源有效地以经济高效的方式促进了药物类似性研究。在这里,我们全面总结和比较了当前可访问的在线资源,从其关键特性、应用领域和用于计算机药物类似性研究的性能方面进行了比较。我们希望这个工具包能为未来的计算机药物类似性研究提供有用的指导。

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