Kinnings Sarah L, Jackson Richard M
Institute of Molecular and Cellular Biology and Astbury Centre for Structural Molecular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom.
J Chem Inf Model. 2009 Sep;49(9):2056-66. doi: 10.1021/ci900204y.
We have developed a new virtual screening (VS) method called LigMatch and evaluated its performance on 13 protein targets using a filtered and clustered version of the directory of useful decoys (DUD). The method uses 3D structural comparison to a crystallographically determined ligand in a bioactive 'template' conformation, using a geometric hashing method, in order to prioritize each database compound. We show that LigMatch outperforms several other widely used VS methods on the 13 DUD targets. We go on to demonstrate that improved VS performance can be gained from using multiple, structurally diverse templates rather than a single template ligand for a particular protein target. In this case, a 2D fingerprint-based method is used to select a ligand template from a set of known bioactive conformations. Furthermore, we show that LigMatch performs well even in the absence of 2D similarity to the template ligands, thereby demonstrating its robustness with respect to purely 2D methods and its potential for scaffold hopping.
我们开发了一种名为LigMatch的新型虚拟筛选(VS)方法,并使用经过筛选和聚类的有用诱饵目录(DUD)对其在13个蛋白质靶点上的性能进行了评估。该方法使用几何哈希法,将数据库中的每个化合物与处于生物活性“模板”构象的晶体学确定的配体进行三维结构比较,从而对化合物进行优先级排序。我们表明,在13个DUD靶点上,LigMatch的性能优于其他几种广泛使用的VS方法。我们进一步证明,对于特定的蛋白质靶点,使用多个结构多样的模板而非单个模板配体,可以提高VS性能。在这种情况下,使用基于二维指纹的方法从一组已知的生物活性构象中选择配体模板。此外,我们表明,即使与模板配体不存在二维相似性,LigMatch也能表现良好,从而证明了其相对于纯二维方法的稳健性及其在骨架跃迁方面的潜力。