Khan Mahmud Tareq Hassan, Sylte Ingebrigt
School of Molecular and Structural Biology, and Department of Pharmacology, Institute of Medical Biology, Faculty of Medicine, University of Tromsø, 9037 Tromsø, Norway.
Curr Drug Discov Technol. 2007 Oct;4(3):141-9. doi: 10.2174/157016307782109706.
Chemical breakthrough generates large numbers of prospective drug molecules; the use of ADMET (absorption, distribution, metabolism, excretion and toxicity) properties is flattering progressively more imperative in the drug discovery, assortment, development and promotion processes. Due to the inauspicious ADMET properties a huge amount of molecules in the development stage got failure. In the past years several authors reported that it possible to do some prediction of the ADMET properties using the structural features of the molecules, suing several approaches. One of the most important approaches is QSAR modeling of the data derived from their activity profiles and their different structural features (i.e., quantitative molecular descriptors). This review is critically assessing some of the most important issues for the effective prediction of ADMET properties of drug candidates based on QSAR modeling approaches.
化学突破产生了大量潜在的药物分子；在药物发现、筛选、开发和推广过程中，利用ADMET（吸收、分布、代谢、排泄和毒性）性质变得越来越重要。由于不良的ADMET性质，大量处于开发阶段的分子遭遇失败。在过去几年里，几位作者报告称，利用分子的结构特征，通过几种方法可以对ADMET性质进行一些预测。最重要的方法之一是对从其活性谱和不同结构特征（即定量分子描述符）获得的数据进行QSAR建模。本综述批判性地评估了基于QSAR建模方法有效预测候选药物ADMET性质的一些最重要问题。
