Srivani P, Srinivas E, Raghu R, Sastry G Narahari
Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, India.
J Mol Graph Model. 2007 Jul;26(1):378-90. doi: 10.1016/j.jmgm.2007.01.007. Epub 2007 Jan 17.
Two- and three-dimensional quantitative structure-activity relationship (QSAR) and docking studies were carried out on a series of pyridopurinones, to model their phosphodiesterase 5 (PDE5) inhibitory activities. 2D-QSAR was performed using the heuristic and best multi linear regression (BMLR) methods in CODESSA (comprehensive descriptors for structural and statistical analysis), which had given linear models between the inhibitory activity and five descriptors of PDE5 inhibitors, with r(2)=0.987, 0.987, q(2)=0.970, 0.970, F=166.71, 166.71 and s(2)=0.0004, 0.0176, respectively. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) have provided statistically significant models with q(2) values of 0.784, 0.742 and r(2) values of 0.975, 0.972 respectively. The predictive ability of the models was validated using a set of 6 compounds that were not included in the training set and the predictive r(2) obtained for the test set was 0.901 and 0.888 respectively. Docking studies were employed to determine the probable binding conformation of these analogues in the PDE5 active site using the programs GOLD and AutoDock whose results were found complementary with 3D-QSAR maps. Since the potency towards PDE5 and the selectivity over PDE6 is important for the successful development of new PDE5 inhibitors, a PDE6 homology model was built using Insight II and Modeller with Phi-Psi BLAST alignment. The molecules were docked in the active site of PDE6 and analyzed the probable reasons for selectivity of these molecules towards PDE5 over PDE6. Mapping the 3D-QSAR models to the active site of PDE5 provides a new insight into the protein-inhibitor interactions and helpful in designing potent and selective PDE5 inhibitors for the treatment of erectile dysfunction.
对一系列吡啶并嘌呤酮进行了二维和三维定量构效关系(QSAR)及对接研究,以模拟它们的磷酸二酯酶5(PDE5)抑制活性。使用CODESSA(结构和统计分析综合描述符)中的启发式和最佳多元线性回归(BMLR)方法进行二维QSAR,该方法给出了抑制活性与PDE5抑制剂的五个描述符之间的线性模型,r(2)分别为0.987、0.987,q(2)为0.970、0.970,F为166.71、166.71,s(2)分别为0.0004、0.0176。比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)分别提供了具有统计学意义的模型,q(2)值为0.784、0.742,r(2)值为0.975、0.972。使用一组未包含在训练集中的6种化合物对模型的预测能力进行了验证,测试集获得的预测r(2)分别为0.901和0.888。采用对接研究,使用GOLD和AutoDock程序确定这些类似物在PDE5活性位点的可能结合构象,其结果与三维QSAR图谱互补。由于对PDE5的效力和对PDE6的选择性对新型PDE5抑制剂的成功开发很重要,因此使用Insight II和Modeller以及Phi-Psi BLAST比对构建了PDE6同源模型。将分子对接在PDE6的活性位点,并分析这些分子对PDE5比对PDE6具有选择性的可能原因。将三维QSAR模型映射到PDE5的活性位点,为蛋白质-抑制剂相互作用提供了新的见解,并有助于设计用于治疗勃起功能障碍的强效和选择性PDE5抑制剂。