Yuan Hongbin, Parrill Abby
Chemistry Department, The University of Memphis, Memphis, TN 38152, USA.
J Mol Graph Model. 2005 Jan;23(4):317-28. doi: 10.1016/j.jmgm.2004.10.003.
Three-dimensional quantitative structure-activity relationship (3D QSAR) and cluster analysis were applied to a variety of HIV-1 integrase inhibitors. One structure was chosen from each of 11 classes of inhibitors to represent the whole class in descriptor-based cluster analysis. The 11 classes of inhibitors were classified into two groups. The molecular field analysis (MFA) models for these two clusters had r2 values of 0.90 and 0.95 and q2 values of 0.85 and 0.91 that were noticeably enhanced from those of conventional QSAR models. The five test compounds, which were proposed to have a common binding site near the metal in HIV-1 integrase based on docking studies by Sotriffer et al., were utilized to compare the predictive capability of MFA and conventional QSAR models. Among these five compounds, only L-chicoric acid belongs to cluster 1 and the other four belong to cluster 2. MFA models give better overall predictions and more importantly the activity of these test compounds is better predicted by the MFA model derived from the cluster each test compound belongs to. The necessity of dividing the inhibitors into two groups to obtain predictive QSAR models supports the likelihood of two separate binding sites.
三维定量构效关系（3D QSAR）和聚类分析被应用于多种HIV-1整合酶抑制剂。在基于描述符的聚类分析中，从11类抑制剂中的每一类中选择一个结构来代表整个类别。这11类抑制剂被分为两组。这两个聚类的分子场分析（MFA）模型的r2值分别为0.90和0.95，q2值分别为0.85和0.91，与传统QSAR模型相比有显著提高。根据Sotriffer等人的对接研究，提出了5种测试化合物在HIV-1整合酶中金属附近有共同的结合位点，用于比较MFA和传统QSAR模型的预测能力。在这5种化合物中，只有L-菊苣酸属于聚类1，其他4种属于聚类2。MFA模型给出了更好的总体预测，更重要的是，这些测试化合物的活性通过源自其所属聚类的MFA模型能得到更好的预测。将抑制剂分为两组以获得预测性QSAR模型的必要性支持了存在两个独立结合位点的可能性。
