Department of Pharmacy, Drug Discovery Laboratory, University of Naples Federico II, via D. Montesano 49, I-80131 Napoli, Italy.
Curr Med Chem. 2013;20(23):2839-60. doi: 10.2174/09298673113209990001.
Virtual screening (VS) is a powerful technique for identifying hit molecules as starting points for medicinal chemistry. The number of methods and softwares which use the ligand and target-based VS approaches is increasing at a rapid pace. What, however, are the real advantages and disadvantages of the VS technology and how applicable is it to drug discovery projects? This review provides a comprehensive appraisal of several VS approaches currently available. In the first part of this work, an overview of the recent progress and advances in both ligand-based VS (LBVS) and structure-based VS (SBVS) strategies highlighting current problems and limitations will be provided. Special emphasis will be given to in silico chemogenomics approaches which utilize annotated ligand-target as well as protein-ligand interaction databases and which could predict or reveal promiscuous binding and polypharmacology, the knowledge of which would help medicinal chemists to design more potent clinical candidates with fewer side effects. In the second part, recent case studies (all published in the last two years) will be discussed where the VS technology has been applied successfully. A critical analysis of these case studies provides a good platform in order to estimate the applicability of various VS strategies in the new lead identification and optimization.
虚拟筛选（VS）是一种强大的技术，可以识别命中分子作为药物化学的起点。使用配体和基于靶标的 VS 方法的方法和软件的数量正在迅速增加。然而，VS 技术的真正优势和劣势是什么，以及它在药物发现项目中的适用性如何？这篇综述对目前可用的几种 VS 方法进行了全面评估。在这项工作的第一部分，将提供基于配体的 VS（LBVS）和基于结构的 VS（SBVS）策略的最新进展和进展的概述，突出当前的问题和局限性。特别强调利用注释配体-靶标以及蛋白质-配体相互作用数据库的计算化学基因组学方法，这些方法可以预测或揭示混杂结合和多效性，了解这些方法将有助于药物化学家设计更有效、副作用更少的临床候选药物。在第二部分，将讨论过去两年中成功应用 VS 技术的最近案例研究。对这些案例研究的批判性分析提供了一个很好的平台，以便评估各种 VS 策略在新的先导化合物识别和优化中的适用性。
