Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, 53113, Bonn, Germany.
Data Science Center and Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192, Japan.
J Comput Aided Mol Des. 2018 Jul;32(7):759-767. doi: 10.1007/s10822-018-0128-8. Epub 2018 Jul 2.
Shape similarity searching is a popular approach for ligand-based virtual screening on the basis of three-dimensional reference compounds. It is generally thought that well-defined experimentally determined binding modes of active reference compounds provide the best possible basis for shape searching. Herein, we show that experimental binding modes are not essential for successful shape similarity searching. Furthermore, we show that ensembles of analogs of X-ray ligands-in the absence of these ligands-further improve the search performance of single crystallographic reference compounds. This is even the case if ensembles of virtually generated analogs are used whose activity status is unknown. Taken together, the results of our study indicate that analog ensembles representing fuzzy reference states are effective starting points for shape similarity searching.
形状相似性搜索是基于三维参考化合物进行配体虚拟筛选的一种常用方法。通常认为，明确的实验确定的活性参考化合物的结合模式为形状搜索提供了最佳基础。在此，我们表明实验结合模式对于成功的形状相似性搜索并非必不可少。此外，我们还表明，即使使用虚拟生成的类似物的集合（而没有这些类似物），也可以进一步提高单晶参考化合物的搜索性能。即使使用活性状态未知的虚拟生成类似物的集合也是如此。总之，我们研究的结果表明，代表模糊参考状态的类似物集合是形状相似性搜索的有效起点。
