Research group in Cheminformatics & Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, 43007 Tarragona, Catalonia, Spain.
EURECAT, TECNIO, CEICS, Avinguda Universitat, 1, 43204 Reus, Catalonia, Spain.
Int J Mol Sci. 2019 Mar 19;20(6):1375. doi: 10.3390/ijms20061375.
Virtual screening consists of using computational tools to predict potentially bioactive compounds from files containing large libraries of small molecules. Virtual screening is becoming increasingly popular in the field of drug discovery as in silico techniques are continuously being developed, improved, and made available. As most of these techniques are easy to use, both private and public organizations apply virtual screening methodologies to save resources in the laboratory. However, it is often the case that the techniques implemented in virtual screening workflows are restricted to those that the research team knows. Moreover, although the software is often easy to use, each methodology has a series of drawbacks that should be avoided so that false results or artifacts are not produced. Here, we review the most common methodologies used in virtual screening workflows in order to both introduce the inexperienced researcher to new methodologies and advise the experienced researcher on how to prevent common mistakes and the improper usage of virtual screening methodologies.
虚拟筛选包括使用计算工具从包含大量小分子文库的文件中预测潜在的生物活性化合物。随着计算机技术的不断发展、改进和普及,虚拟筛选在药物发现领域越来越受欢迎。由于大多数这些技术易于使用,因此私人和公共组织都应用虚拟筛选方法来节省实验室资源。然而,在虚拟筛选工作流程中实施的技术通常仅限于研究团队所知道的技术。此外,尽管该软件通常易于使用,但每种方法都有一系列需要避免的缺点,以防止产生错误结果或伪影。在这里,我们回顾了虚拟筛选工作流程中最常用的方法,以便为经验不足的研究人员介绍新的方法,并为经验丰富的研究人员提供有关如何防止常见错误和不当使用虚拟筛选方法的建议。