Huang Xaioqin, Xu Liaosa, Luo Xiaomin, Fan Kangnian, Ji Ruyun, Pei Gang, Chen Kaixian, Jiang Hualiang
Center for Drug Design and Discovery, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 294 Taiyuan Road, Shanghai 200031, People's Republic of China.
J Med Chem. 2002 Jan 17;45(2):333-43. doi: 10.1021/jm0102710.
The Lamarckian genetic algorithm of AutoDock 3.0 has been used to dock 27 3(S)-amino-2(S)-hydroxyl-4-phenylbutanoic acids (AHPBAs) into the active site of HIV-1 protease (HIVPR). The binding mode was demonstrated in the aspects of the inhibitor's conformation, subsite interaction, and hydrogen bonding. The data of geometrical parameters (tau(1), tau(2), and tau(3) listed in Table 2) and root mean square deviation values as compared with the known inhibitor, kni272,(28) show that both kinds of inhibitors interact with HIVPR in a very similar way. The r(2) value of 0.860 indicates that the calculated binding free energies correlate well with the inhibitory activities. The structural and energetic differences in inhibitory potencies of AHPBAs were reasonably explored. Using the binding conformations of AHPBAs, consistent and highly predictive 3D-QSAR models were developed by performing CoMFA, CoMSIA, and HQSAR analyses. The reasonable r(corss)(2) values were 0.613, 0.530, and 0.717 for CoMFA, CoMSIA, and HQSAR models, respectively. The predictive ability of these models was validated by kni272 and a set of nine compounds that were not included in the training set. Mapping these models back to the topology of the active site of HIVPR leads to a better understanding of vital AHPBA-HIVPR interactions. Structural-based investigations and the final 3D-QSAR results provide clear guidelines and accurate activity predictions for novel HIVPR inhibitors.
AutoDock 3.0的拉马克遗传算法已被用于将27种3(S)-氨基-2(S)-羟基-4-苯基丁酸(AHPBAs)对接至HIV-1蛋白酶(HIVPR)的活性位点。从抑制剂的构象、亚位点相互作用和氢键方面展示了结合模式。与已知抑制剂kni272相比的几何参数数据(表2中列出的tau(1)、tau(2)和tau(3))以及均方根偏差值表明,这两种抑制剂与HIVPR的相互作用方式非常相似。0.860的r(2)值表明计算得到的结合自由能与抑制活性具有良好的相关性。合理探讨了AHPBAs抑制效力的结构和能量差异。利用AHPBAs的结合构象,通过进行比较分子场分析(CoMFA)、比较分子相似性指数分析(CoMSIA)和高效定量构效关系(HQSAR)分析,建立了一致且具有高度预测性的三维定量构效关系(3D-QSAR)模型。CoMFA、CoMSIA和HQSAR模型的合理交叉验证r(2)值分别为0.613、0.530和0.717。这些模型的预测能力通过kni272和一组未包含在训练集中的九种化合物进行了验证。将这些模型映射回HIVPR活性位点的拓扑结构,有助于更好地理解重要的AHPBA-HIVPR相互作用。基于结构的研究和最终的3D-QSAR结果为新型HIVPR抑制剂提供了明确的指导方针和准确的活性预测。