Giordano Deborah, Biancaniello Carmen, Argenio Maria Antonia, Facchiano Angelo
National Research Council, Institute of Food Science, Via Roma 64, 83110 Avellino, Italy.
Doctorate School in Computational and Quantitative Biology, University of Naples "Federico II", 80100 Naples, Italy.
Pharmaceuticals (Basel). 2022 May 23;15(5):646. doi: 10.3390/ph15050646.
Computer-aided drug discovery techniques reduce the time and the costs needed to develop novel drugs. Their relevance becomes more and more evident with the needs due to health emergencies as well as to the diffusion of personalized medicine. Pharmacophore approaches represent one of the most interesting tools developed, by defining the molecular functional features needed for the binding of a molecule to a given receptor, and then directing the virtual screening of large collections of compounds for the selection of optimal candidates. Computational tools to create the pharmacophore model and to perform virtual screening are available and generated successful studies. This article describes the procedure of pharmacophore modelling followed by virtual screening, the most used software, possible limitations of the approach, and some applications reported in the literature.
计算机辅助药物发现技术减少了开发新型药物所需的时间和成本。随着健康紧急情况以及个性化医疗普及所带来的需求，它们的相关性变得越来越明显。药效团方法是所开发的最有趣的工具之一，通过定义分子与给定受体结合所需的分子功能特征，然后指导对大量化合物进行虚拟筛选以选择最佳候选物。有用于创建药效团模型和进行虚拟筛选的计算工具，并且已产生了成功的研究。本文描述了药效团建模随后进行虚拟筛选的过程、最常用的软件、该方法可能存在的局限性以及文献中报道的一些应用。
