Puntambekar Devendra, Giridhar Rajani, Yadav Mange Ram
Pharmacy Department, Faculty of Technology and Engineering, The M.S. University of Baroda, Vadodara 390 001, India.
Bioorg Med Chem Lett. 2006 Apr 1;16(7):1821-7. doi: 10.1016/j.bmcl.2006.01.019. Epub 2006 Feb 7.
3D-QSAR analysis has been performed on a series of previously synthesized benzonitrile derivatives, which were screened as farnesyltransferase inhibitors, using comparative molecular field analysis (CoMFA) with partial least-square fit to predict the steric and electrostatic molecular field interactions for the activity. The CoMFA study was carried out using a training set of 34 compounds. The predictive ability of the model developed was assessed using a test set of eight compounds (r(pred)(2) as high as 0.770). The analyzed 3D-QSAR CoMFA model has demonstrated a good fit, having r(2) value of 0.991 and cross-validated coefficient q(2) value as 0.619. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity.
已对一系列先前合成的苯甲腈衍生物进行了3D-QSAR分析，这些衍生物作为法尼基转移酶抑制剂进行了筛选，使用具有偏最小二乘拟合的比较分子场分析（CoMFA）来预测活性的空间和静电分子场相互作用。CoMFA研究使用了34种化合物的训练集进行。使用8种化合物的测试集评估所开发模型的预测能力（r(pred)(2)高达0.770）。分析的3D-QSAR CoMFA模型显示出良好的拟合度，r(2)值为0.991，交叉验证系数q(2)值为0.619。CoMFA等高线图的分析为分子的可能修饰以获得更好的活性提供了见解。
