Thai Khac-Minh, Ngo Trieu-Du, Phan Thien-Vy, Tran Thanh-Dao, Nguyen Ngoc-Vinh, Nguyen Thien-Hai, Le Minh-Tri
Department of Medicinal Chemistry, School of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, Dist. 1, Ho Chi Minh City, Viet Nam.
Med Chem. 2015;11(2):135-55. doi: 10.2174/1573406410666140902110903.
NorA is a member of the Major Facilitator Superfamily (MFS) drug efflux pumps that have been shown to mediate antibiotic resistance in Staphylococcus aureus (SA). In this study, QSAR analysis, virtual screening and molecular docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors. Originally, a set of 47 structurally diverse compounds compiled from the literature was used to develop linear QSAR models and another set of 15 different compounds were chosen for extra validation. The final model which was estimated by statistical values for the full data set (n = 45, Q(2) = 0.80, RMSE = 0.20) and for the external test set (n = 15, R(2) = 0.60, |res|max = 0.75, |res|min = 0.02) was applied on the collection of 182 flavonoides and the traditional Chinese medicine (TCM) database to screen for novel NorA inhibitors. Finally, 33 lead compounds that met the Lipinski's rules of five/three and had good predicted pIC50 values from in silico screening process were employed to analyze the binding ability by docking studies on NorA homology model in place of its unavailable crystal structures at two active sites, the central channel and the Walker B.
NorA是主要易化子超家族（MFS）药物外排泵的成员，已证实其介导金黄色葡萄球菌（SA）的抗生素耐药性。在本研究中，开展了定量构效关系（QSAR）分析、虚拟筛选和分子对接，以发现新型SA NorA外排泵抑制剂。最初，使用从文献中收集的一组47种结构多样的化合物来建立线性QSAR模型，并选择另一组15种不同的化合物进行额外验证。通过对完整数据集（n = 45，Q(2) = 0.80，RMSE = 0.20）和外部测试集（n = 15，R(2) = 0.60，|res|max = 0.75，|res|min = 0.02）的统计值估计得到的最终模型，应用于182种黄酮类化合物和中药（TCM）数据库的集合，以筛选新型NorA抑制剂。最后，33种符合Lipinski五规则/三规则且在计算机模拟筛选过程中具有良好预测pIC50值的先导化合物，被用于通过对NorA同源模型进行对接研究来分析其结合能力，该同源模型替代了其在两个活性位点（中央通道和沃克B）无法获得的晶体结构。
