3D QSAR STUDIES ON A SERIES OF POTENT AND HIGH SELECTIVE INVERSE AGONISTS OF HUMAN CANNABINOID RECEPTOR 1

In the present study, a series of 49 5,6-diarylpyridineheterocyclic analogues exhibiting inhibitory activity against cannabinoid receptor 1 were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q 2 of  0.762, 0.767 and conventional cross-validation coefficient, r 2 of  0.954, 0.985 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r 2 pred based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel Cb1 inverse agonists prior to their synthesis.