醛糖还原酶抑制剂通过抑制多元醇通路中醛糖的还原而有希望成为治疗慢性糖尿病的新药，这促进了新型醛糖还原酶（ALR2）抑制剂的研制.本文采用两种3D-QSAR方法，即比较分子力场分析（CoMFA）和比较相似性指数分析（CoMSIA）方法，研究2，4-噻唑烷二酮类醛糖还原酶抑制剂结构与活性之间的关系.采用原子契合（相同骨架结构）、场契合和基于分子对接3种分子叠合方式构建CoMFA和CoMSIA模型.基于原子契合方式构建的模型为最佳预测模型（CoMFA r2=0.922，q2LOO=0.707；CoMSIA r2=0.917，q2LOO=0.762）.此模型进一步通过12个化合物组成的样本外测试集进行验证，结果由CoMFA和CoMSIA模型得到的测试集外部验证系数（r2pred）分别为0.824和0.883. CoMFA和CoMSIA的力场系数等高图的分析结果与分子对接的结果一致. CoMFA和CoMSIA方法结合分子对接研究有助于揭示抑制剂与醛糖还原酶之间的相互作用以及影响醛糖还原酶抑制剂活性的化合物的结构特征，这些为新型醛糖还原酶抑制剂的理性设计提供了有益的信息.%Aldose reductase (ALR2) inhibitors are promising agents for chronic diabetic complication therapy by pre⁃venting the reduction of glucose in the polyol pathway,which promotes to develop novel ALR2 inhibitors. Two kinds of techniques ,comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA),were employed for studying a series of 5-arylidene-2,4-thiazolidinediones as aldose reductase inhibitors. With the strategies of common substructure-based alignment and field-fit alignment ,the lowest energy conforma⁃tions were used to develop the ligand-based models of three-dimensional quantitative structure-activity relationship (3D-QSAR). The bioactive conformation obtained by docking all 5-arylidene-2,4-thiazolidinediones derivatives into the active site of aldose reductase (PBD ID:1ah3) was applied for the development of receptor-based model. Statistically sig⁃nificant model of ligand-based 3D-QSAR from the common substructure-based alignment exhibited the best predictive power (CoMFA r2=0.922,q2=0.707;CoMSIA r2=0.917,q2=0.762). The model was further confirmed by analyzing 12 sets of compounds with diverse structure. The results showed high predictive r2 values of 0.824 for CoMFA and 0.883 for CoMSIA respectively. The molecular docking analysis revealed that both CoMFA and CoMSIA contour maps for steric,electrostatic,hydrophobic,and hydrogen-bonding interactions matched well. The combination of CoMFA and CoMSIA with molecular docking is helpful to understand the interaction and the structure-activity relationship between ALR2 and its inhibitor. The present results provide a valuable guidance for rationally designing ARL2 inhibitors.
展开▼
