Villoutreix Bruno O, Eudes Richard, Miteva Maria A
INSERM U973, University Paris 7, 75013 Paris, France.
Comb Chem High Throughput Screen. 2009 Dec;12(10):1000-16. doi: 10.2174/138620709789824682.
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 (X-ray 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.
如今，计算方法在健康科学研究的各个领域都得到了广泛应用。在这些方法中，虚拟配体筛选已成为一种成熟的命中发现和优化技术。在本综述中，我们首先介绍基于结构的虚拟配体筛选，并简要评论化合物库和靶点制备。我们还为读者提供了一份资源列表，从化学信息学软件包到化合物库，这些资源可能有助于构建基于结构的虚拟筛选平台。然后，我们讨论了十七个最近通过各种基于受体的计算机方法取得的成功案例，这些案例基于实验结构（X射线晶体学，12例）或同源模型（5例），涉及不同的靶点类别，从催化位点抑制剂的设计到阻碍大分子相互作用的类药物化合物。鉴于这些结果，我们对存在改进机会的领域提出了一些建议。
