Research Center of Medical Chemistry and Chemical Biology, Chongqing Technology and Business University, Chongqing, 400067, People's Republic of China.
J Mol Model. 2010 Jul;16(7):1239-49. doi: 10.1007/s00894-009-0637-4. Epub 2010 Jan 13.
Three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were carried out to explore the binding of 73 inhibitors to dipeptidyl peptidase IV (DPP-IV), and to construct highly predictive 3D-QSAR models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The negative logarithm of IC(50) (pIC(50)) was used as the biological activity in the 3D-QSAR study. The CoMFA model was developed by steric and electrostatic field methods, and leave-one-out cross-validated partial least squares analysis yielded a cross-validated value (r(2)(cv)) of 0.759. Three CoMSIA models developed by different combinations of steric, electrostatic, hydrophobic and hydrogen-bond fields yielded significant r(2)(cv) values of 0.750, 0.708 and 0.694, respectively. The CoMFA and CoMSIA models were validated by a structurally diversified test set of 18 compounds. All of the test compounds were predicted accurately using these models. The mean and standard deviation of prediction errors were within 0.33 and 0.26 for all models. Analysis of CoMFA and CoMSIA contour maps helped identify the structural requirements of inhibitors, with implications for the design of the next generation of DPP-IV inhibitors for the treatment of type 2 diabetes.
进行了三维定量构效关系(3D-QSAR)和分子对接研究,以探索 73 种抑制剂与二肽基肽酶 IV(DPP-IV)的结合,并使用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)构建高度预测性的 3D-QSAR 模型。负对数 IC(50)(pIC(50))被用作 3D-QSAR 研究中的生物活性。CoMFA 模型通过立体和静电场方法开发,通过留一法交叉验证偏最小二乘分析得到交叉验证值(r(2)(cv))为 0.759。通过不同组合的立体、静电、疏水和氢键场开发的三个 CoMSIA 模型分别产生了显著的 r(2)(cv)值 0.750、0.708 和 0.694。通过结构多样化的 18 种化合物测试集验证了 CoMFA 和 CoMSIA 模型。使用这些模型准确地预测了所有测试化合物。所有模型的预测误差的平均值和标准差均在 0.33 和 0.26 以内。CoMFA 和 CoMSIA 等高线图的分析有助于确定抑制剂的结构要求,这对设计用于治疗 2 型糖尿病的下一代 DPP-IV 抑制剂具有启示意义。