Barnum D, Greene J, Smellie A, Sprague P
Molecular Simulations Incorporated, Sunnyvale, California 94086, USA.
J Chem Inf Comput Sci. 1996 May-Jun;36(3):563-71. doi: 10.1021/ci950273r.
A new algorithm for identifying three-dimensional configurations of chemical features common to a set of molecules is described. The algorithm scores each configuration based both on the degree to which it is common to the input set and its estimated rarity. The algorithm can be applied to molecules with large (several hundred) conformational models. Results from the application of this algorithm to three data sets are discussed: PAF antagonists, HIV reverse transcriptase inhibitors, and HIV protease inhibitors. Of particular interest is a common configuration identified for a set of HIV reverse transcriptase inhibitors; this configuration is shared by two new, potent inhibitors that were recently described in the literature.
本文描述了一种用于识别一组分子中共有的化学特征三维构型的新算法。该算法根据构型在输入集中的常见程度及其估计的稀有程度对每个构型进行评分。该算法可应用于具有大量（数百个）构象模型的分子。讨论了将该算法应用于三个数据集的结果：血小板激活因子（PAF）拮抗剂、HIV逆转录酶抑制剂和HIV蛋白酶抑制剂。特别令人感兴趣的是为一组HIV逆转录酶抑制剂确定的一种常见构型；文献中最近描述的两种新型强效抑制剂具有这种构型。
