PMID: 16613581Apr 15, 2006Paper

Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods

Mini Reviews in Medicinal Chemistry
C W YapY Z Chen

Abstract

Computational methods for predicting compounds of specific pharmacodynamic, pharmacokinetic, or toxicological property are useful for facilitating drug discovery and drug safety evaluation. The quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) methods are the most successfully used statistical learning methods for predicting compounds of specific property. More recently, other statistical learning methods such as neural networks and support vector machines have been explored for predicting compounds of higher structural diversity than those covered by QSAR and QSPR. These methods have shown promising potential in a number of studies. This article is intended to review the strategies, current progresses and underlying difficulties in using statistical learning methods for predicting compounds of specific property. It also evaluates algorithms commonly used for representing structural and physicochemical properties of compounds.

Citations

Feb 12, 2010·Journal of Computer-aided Molecular Design·Chin Yee LiewChun Wei Yap
Jun 26, 2013·Journal of Chemical Information and Modeling·Hongming ChenIngemar Nilsson
Jan 25, 2008·Journal of Pharmaceutical Sciences·Carlton A TaftCarlos Henrique Tomich De Paula Da Silva
Jun 7, 2011·Toxicology in Vitro : an International Journal Published in Association with BIBRA·Hui ZhangSheng-Yong Yang
Nov 7, 2008·Journal of Computational Chemistry·Xue-Gang YangYu-Zong Chen
Jan 25, 2019·Current Topics in Medicinal Chemistry·Alexander V DmitrievVladimir V Poroikov
Sep 5, 2019·SAR and QSAR in Environmental Research·A V DmitrievV V Poroikov
Mar 10, 2009·Journal of Chemical Information and Modeling·Chin Y LiewChun W Yap
Jun 10, 2010·Journal of Chemical Information and Modeling·Lisa Michielan, Stefano Moro
Jul 12, 2019·Chemical Reviews·Xin YangShengyong Yang

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