Vertika Gautam

3D-QSAR studies of 4-quinolone derivatives as high-affinity ligands at the benzodiazepine site of brain GABAA receptors

Three dimensional quantitative structure activity relationship approach using CoMFA and CoMSIA was applied to a series of 4-quinolone derivatives as high-affinity ligands at the benzodiazepine site of brain GABAA receptors. For the purpose, 27 compounds were used to develop models. 3D-QSAR models with high-squared correlation coefficient of up to 0.979 for CoMFA and 0.931 for CoMSIA were established. The robustness of the model was confirmed with the help of leave one out cross-validation method with rcv2 values of up to 0.526 and 0.546 for CoMFA and CoMSIA, respectively. Developed models highlighted the importance of shape of the molecules, i.e., steric descriptors for GABAA receptor binding.

Structure-based three-dimensional pharmacophores as an alternative to traditional methodologies

Structure-based pharmacophore approaches have become widely used in drug discovery and design. This can be attributed to the development of new tools and methods over the past decade. Various tools based on different premises have been developed, including active site information in traditional pharmacophores. These tools have been widely used in virtual screening, de novo design, and lead optimization and been proven to be highly successful. Studies based on simultaneous use of structure-based pharmacophores, ligand-based phar- macophores, and docking have also come into the picture recently. Here, the development of structure-based pharmacophores as an alternative to traditional drug discovery approaches is discussed, with emphasis on the advances and latest developments in tools and success stories

QSAR Studies on 4-Quinolone Derivatives as High-Affinity Ligands at the Benzodiazepine Site of Brain GABAA Receptors

Quantitative structure activity relationship approach using stepwise regression analysis was applied to a series of 4-quinolone derivatives as high-affinity ligands at the benzodiazepine site of brain GABA(A) receptors. For the purpose 25 compounds were used to develop models. Statistically significant equations were obtained with high squared correlation coefficient (r(2)=0.8761, 0.9295 and 0.8705) and low root mean square error (RMSE=0.4844, 0.3894 and 0.4952). The robustness of the model was confirmed with the help of leave one out cross validation method which exhibited high r(2)(cv) values (r(2)(cv)=0.7875, 0.8263 and 0.7927). A good correlation of various molecular shape parameters, like ovality, Szeged index, and energy of the molecule with the GABA(A) affinity was achieved.