药物发现
数量结构-活动关系
计算机科学
药品
计算生物学
医学
机器学习
数据科学
药理学
生物
生物信息学
作者
Riccardo Zanni,María Gálvez-Llompart,Jorge Gálvez,Ramón García‐Domenech
出处
期刊:Current Computer - Aided Drug Design
[Bentham Science Publishers]
日期:2014-07-15
卷期号:10 (2): 129-136
被引量:30
标识
DOI:10.2174/157340991002140708105124
摘要
The main purpose of the present review is to summarize the most significant works up to date in the field of multi-target QSAR (mt-QSAR), in order to emphasize the importance that this technique has acquired over the last decade. Unlike traditional QSAR techniques, mt-QSAR permits to calculate the probability of activity of a given compound against different biological or pharmacological targets. In simple terms, a single equation for multiple outputs. To emphasize more the importance of the mt-QSAR in the field of drug discovery, we also present a novel mt-QSAR model, made on purpose by our research group, for the prediction of the susceptibility of Gram + and Gram – anaerobic bacteria. Keywords: Anaerobic bacteria, molecular topology, multi-target QSAR.
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