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Structure-Based Virtual Ligand Screening: Recent Success Stories

机译:基于结构的虚拟配体筛选:近期成功案例

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摘要

Today, computational methods are commonly used in all areas of health science research. Among these methods, virtual ligand screening has become an established technique for hit discovery and optimization. In this review, we first introduce structure-based virtual ligand screening and briefly comment on compound collections and target preparations. We also provide the readers with a list of resources, from chemoinformatics packages to compound collections, which could be helpful to implement a structure-based virtual screening platform. Then we discuss seventeen recent success stories obtained with various receptor-based in silico methods, performed on experimental structures (Xray crystallography, 12 cases) or homology models (5 cases) and concerning different target classes, from the design of catalytic site inhibitors to drug-like compounds impeding macromolecular interactions. In light of these results, some suggestions are made about areas that present opportunities for improvements.
机译:如今,计算方法已广泛用于健康科学研究的所有领域。在这些方法中,虚拟配体筛选已成为命中发现和优化的成熟技术。在这篇综述中,我们首先介绍基于结构的虚拟配体筛选,并简要评论化合物的收集和靶标的制备。我们还为读者提供了从化学信息学软件包到化合物集合的资源列表,这可能有助于实现基于结构的虚拟筛选平台。然后,我们讨论通过各种基于受体的计算机模拟方法获得的十七个最近的成功故事,这些故事是在实验结构(X射线晶体学,12例)或同源模型(5例)上进行的,涉及从催化位点抑制剂到药物设计的不同目标类别类化合物阻碍大分子相互作用。根据这些结果,对提出改进机会的领域提出了一些建议。

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