Zhang Zhenshan, Zheng Mingyue, Du Li, Shen Jianhua, Luo Xiaomin, Zhu Weiliang, Jiang Hualiang
Center for Drug Discovery and Design, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.
J Comput Aided Mol Des. 2006 May;20(5):281-93. doi: 10.1007/s10822-006-9050-6. Epub 2006 Aug 8.
To find useful information for discovering dual functional inhibitors against both wild type (WT) and K103N mutant reverse transcriptases (RTs) of HIV-1, molecular docking and 3D-QSAR approaches were applied to a set of twenty-five 4,1-benzoxazepinone analogues of efavirenz (SUSTIVA), some of them are active against the two RTs. 3D-QSAR models were constructed, based on their binding conformations determined by molecular docking, with r(2)(cv) values ranging from 0.656 to 0.834 for CoMFA and CoMSIA, respectively. The models were then validated to be highly predictive and extrapolative by inhibitors in two test sets with different molecular skeletons. Furthermore, CoMFA models were found to be well matched with the binding sites of both WT and K103N RTs. Finally, a reasonable pharmacophore model of 4,1-benzoxazepinones were established. The application of the model not only successfully differentiated the experimentally determined inhibitors from non-inhibitors, but also discovered two potent inhibitors from the compound database SPECS. On the basis of both the 3D-QSAR and pharmacophore models, new clues for discovering and designing potent dual functional drug leads against HIV-1 were proposed: (i) adopting positively charged aliphatic group at the cis-substituent of C3; (ii) reducing the electronic density at the position of O4; (iii) positioning a small branched aliphatic group at position of C5; (iv) using the negatively charged bulky substituents at position of C7.
为了找到有助于发现针对野生型(WT)和HIV-1 K103N突变逆转录酶(RT)的双功能抑制剂的有用信息,将分子对接和3D-QSAR方法应用于一组25种依法韦仑(绥美凯)的4,1-苯并恶唑酮类似物,其中一些对这两种RT具有活性。基于通过分子对接确定的结合构象构建了3D-QSAR模型,CoMFA和CoMSIA的交叉验证相关系数(r(2)(cv))值分别在0.656至0.834之间。然后通过具有不同分子骨架的两个测试集中的抑制剂对模型进行验证,结果表明其具有高度的预测性和外推性。此外,发现CoMFA模型与WT和K103N RT的结合位点匹配良好。最后,建立了4,1-苯并恶唑酮合理的药效团模型。该模型的应用不仅成功地区分了实验确定的抑制剂和非抑制剂,还从化合物数据库SPECS中发现了两种强效抑制剂。基于3D-QSAR和药效团模型,提出了发现和设计针对HIV-1的强效双功能药物先导物的新线索:(i)在C3的顺式取代基处采用带正电荷的脂肪族基团;(ii)降低O4位置的电子密度;(iii)在C5位置定位一个小的支链脂肪族基团;(iv)在C7位置使用带负电荷的大体积取代基。