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Sharma M.C.,Devi Ahilya University | Sharma S.,Choudhary Dilip Singh Kanya Mahavidyalaya | Bhadoriya K.S.,Rc Patel Institute Of Pharmaceutical Education And Research
Journal of Saudi Chemical Society | Year: 2012

The quantitative structure-activity relationship (QSAR) analyses including 2D-QSAR, Group-based QSAR (GQSAR), 3D-QSAR using kNN-MFA methodology and pharmacophore studies were carried out for a series of tetrazole and sulfonamide analogs of imidazo[4,5-b]pyridine to find out the structural requirements of their angiotensin AT 1 receptor antagonistic activities. The multiple linear regression (MLR) and kNN-MFA methods coupled with simulated annealing (SA) feature selection method were applied to derive QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The statistically significant best 2D-QSAR model 1 having r 2 = 0.8762 and q 2 = 0.7732 with pred_r 2 = 0.7563 was developed by SA-MLR and the best Group-based QSAR (GQSAR) model having r 2 = 0.7806 and q 2 = 0.7180 with pred_r 2 = 0.7885 was developed by SA-MLR. Molecular field analysis (MFA) was used to construct the best 3D-QSAR model using SA-kNN method, showing good correlative and predictive capabilities in terms of q 2 = 0.8271 and pred_r 2 = 0.7991. Five chemical feature based several pharmacophore models were generated using VLife MDS MolSign Module and the best pharmacophore model is selected on the basis of the lowest RMSD value, containing one aromatic carbon center, one aliphatic carbon center, one hydrogen bond donor and two hydrogen bond acceptor features. These combined studies for a series of tetrazole and sulfonamide analogs of imidazo[4,5-b]pyridine provide guidance for further lead optimization and designing of novel potent antihypertensive agents. © 2012. Source


Bhadoriya K.S.,Rc Patel Institute Of Pharmaceutical Education And Research | Sharma M.C.,Devi Ahilya University | Sharma S.,Choudhary Dilip Singh Kanya Mahavidyalaya | Jain S.V.,Nirma University | Avchar M.H.,Rc Patel Institute Of Pharmaceutical Education And Research
Arabian Journal of Chemistry | Year: 2014

Alzheimer's disease (AD) is a chronic neurodegenerative disease. Current therapies of AD are only symptomatic, therefore the need for the development of new therapies to treat Alzheimer's disease effectively. To achieve this objective quantitative structure-activity relationship (QSAR) studies were carried out as it provides the rationale for the changes in the structure to have more potent Aβ42 inhibitors or anti-Alzheimer's agents. Quantitative structure-activity relationship (QSAR) studies were carried out on a series of 34 fused 5,6-bicyclic heterocycles to investigate the structural requirements of their inhibitory activity against Aβ42. The statistically significant best 3D-QSAR model having cross-validated squared correlation coefficient q2=0.8457 with external predictive ability of pred_r2=0.7556 was developed by SW-kNN. Developed kNN-MFA model highlighted the importance of shape of the molecules, i.e., hydrophobic and steric descriptors at the grid points H_83 and S_183, S_227 for γ-secretase binding interaction. This model (3D) was found to yield reliable clues for further optimization of fused 5,6-bicyclic heterocycles in the data set. The information rendered by the 3D-QSAR model may lead to a better understanding of the structural requirements of γ-secretase modulators and can also help in the design of novel potent γ-secretase modulators. © 2013. Source


Sharma M.C.,Devi Ahilya University | Sharma S.,Choudhary Dilip Singh Kanya Mahavidyalaya | Bhadoriya K.S.,Rc Patel Institute Of Pharmaceutical Education And Research
Journal of Saudi Chemical Society | Year: 2013

The present paper is an attempt in this direction seeking for the development and comparison of QSAR models of 4,5,6,7-Tetrabromobenzimidazole by different feature selection methods, which ultimately establishes the superiority of the simulated annealing-based models. Two Dimensional and Three Dimensional Quantitative Structure-Activity Relationship (QSAR) studies were performed for correlating the chemical composition of 4,5,6,7-Tetrabromobenzimidazole analogs and their Protein Kinase CK2 inhibitors using two widely used techniques, viz. simulated annealing (SA) and genetic algorithm (GA) that have been applied for descriptor optimization. 2D-QSAR modeling using simulated annealing (SA) and genetic algorithm (GA) based partial least square methods identified some important topological and electrostatic descriptors as important factors for activity. The validated 2D models constructed with H-count, potential surface area, SaasCE-index and SAAverage Hydrophobicity descriptors yielded the cross-validated correlation coefficient of 0.8376, shows that the models have sufficient predictive ability. The three-dimensional QSAR technique identifies a suitable model obtained by simulated annealing and genetic algorithm partial least square method leading to Protein Kinase CK2 Inhibitor prediction. The influences of steric, electrostatic and hydrophobic field effects generated by the contribution plot are analyzed and discussed. Molecular field analysis was used to construct the best 3D-QSAR model using the SA-PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7496 and pred_r2 = 0.7809. The aliphatic/aromatic of the important feature in the molecule, which is also, present sides in the molecule near to 4,5,6,7 sites. Both two- and three-dimensional QSAR analyses of such derivatives provide important structural insights for designing potent Protein Kinase CK2 drugs. © 2013. Source


Sharma M.C.,Devi Ahilya University | Sharma S.,Choudhary Dilip Singh Kanya Mahavidyalaya | Sharma P.,Devi Ahilya University | Kumar A.,Devi Ahilya University
Medicinal Chemistry Research | Year: 2014

Quantitative structure-activity relationship (QSAR) and Pharmacophore studies were performed on a series of 35 azaaurones derivatives to find out the structural requirements of their antimalarial activities. The compounds in the selected series were characterized by spatial, molecular and electrotopological descriptors using QSAR module of molecular design suite (V-Life MDSTM 3.5). Correlations between inhibitory activities and calculated predictor variables were established through partial least square regression method. The developed QSAR models were found to be statistically significant with respect to training (r 2 > 0.6), and cross-validation (q 2 > 0.6). Simulated annealing (SA) and stepwise (SW) regression are applied as variable selection methods for an effective comparison and model development. This study was performed with 35 compounds (data set) using the sphere exclusion (SE) algorithm method for the division of the data set into training and test sets. The statistically significant 2D-QSAR model having r 2 = 0.9061 and q 2 = 0.8150 with pred-r 2 = 0.8719 was developed by SW-PLS confirms a positive contribution of T-O-Cl-6, T-C-Cl-1, SsOHcount, T-C-F-2 and SsCH3E index to the anti-malarial activity and best Group-based QSAR (GQSAR) model having r 2 = 0.7624 and q 2 = 0.7341 with pred-r 2 = 0.7461 was developed by SA-PLS. The result two-dimensional QSAR and GQSAR clearly explained that substitution of topological indices, hydrophobic properties and auto-correlation descriptors of different atomic properties at R1 and R2 on aurone ring is essential for the activity. Further analysis using three-dimensional QSAR technique identifies a suitable model obtained by SA-partial least square method leading to anti-malarial activity prediction. Molecular field analysis was used to construct the best 3D-QSAR model using k-nearest neighbor method, showing good correlative and predictive capabilities in terms of q 2 = 0.6906 and pred-r 2 = 0.7454. Additionally the pharmacophore model well corroborated with k-nearest neighbor studies as the contours of later were in good agreement with the 3D orientation of the pharmacophoric features. The distances between the pharmacophore sites were measured in order to confirm their significance to the activities. The results reveal that the acceptor, donor, and aromatic/hydrophobic pharmacophore properties are favorable contours sites for the activities. The results of 2D-QSAR, GQSAR and k-nearest neighbor-based 3D-QSAR studies give detailed structural insights as well as highlights important binding features of these substituted azaaurones derivatives as anti-malarial activity, which can provide guidance for the rational design of novel potent azaaurones derivatives. © 2013 Springer Science+Business Media New York. Source

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