Abstract
Three different 3D-QSAR methods namely CoMFA, CoMSIA and RSA were applied to a set of 38 angiotensin type 1 receptor (AT1) antagonists. The conformation and alignment of molecules used in each of the three QSAR methods were obtained by a novel method - Consensus Dynamics. To derive the best CoMFA model, various parameters such as partial charge formalism, grid spacing and the absolute orientation of the molecules in the grid were varied. The best CoMFA model had an r2 of 0.926 and a cross-validated correlation coefficient (q2) of 0.546, which improved with region focussing to 0.710. The best CoMSIA model for the same set had an r2 of 0.969 and a q2 of 0.524. Likewise, the best RSA model with r2 of 0.893 and q2 of 0.639 resulted from optimization of various parameters such as atomic partial charges, surface fit and the manner of representation of electrostatics on the receptor surface. The models were thoroughly validated through trials using scrambled activities and bootstrapping. The predictive power of these models was evaluated on a test set that had almost 40% representation outside the training set. The three techniques were gainfully used to identify the structural features important for biological activity in these compounds.
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