Abstract
In the present study, 3D-QSAR analysis was performed on a set of 37 TGF-β inhibitors utilizing pharmacophore based alignment to uncover the essential structural and steric features of these newly discovered b-annulated 1,4- dihydropyridine (1,4-DHP) molecules to get better antagonism of the TGF-β receptor. The best 3D-QSAR model identified with PLS factor 4 that had the highest values of external predictability parameters exhibited Q2 (0.8972), and R2 (0.9826) and displayed high values of F (281.9) and low SD (0.0785). This selected model was validated statistically by determining Pearson-r (0.9718) for test set molecules. Contours thus obtained from different properties generated using our QSAR model explained the variation in the activity of dataset with respect to different attachments in the core structure. This would help to make suitable structural modifications in 1, 4-DHP molecules so as to make a better complementary fit to the active site of TGF-β receptor, which in turn would improve the potency of newly designed molecules.
Keywords: Atom based QSAR, Pharmacophore, TGFβ signalling, Cardiogenesis.
Letters in Drug Design & Discovery
Title:Pharmacophore and 3D QSAR Study of TGFβ Inhibitors
Volume: 11 Issue: 3
Author(s): Mohamed Asraf Vazhapully, D. Vinod and N.H. Zeinul Hukuman
Affiliation:
Keywords: Atom based QSAR, Pharmacophore, TGFβ signalling, Cardiogenesis.
Abstract: In the present study, 3D-QSAR analysis was performed on a set of 37 TGF-β inhibitors utilizing pharmacophore based alignment to uncover the essential structural and steric features of these newly discovered b-annulated 1,4- dihydropyridine (1,4-DHP) molecules to get better antagonism of the TGF-β receptor. The best 3D-QSAR model identified with PLS factor 4 that had the highest values of external predictability parameters exhibited Q2 (0.8972), and R2 (0.9826) and displayed high values of F (281.9) and low SD (0.0785). This selected model was validated statistically by determining Pearson-r (0.9718) for test set molecules. Contours thus obtained from different properties generated using our QSAR model explained the variation in the activity of dataset with respect to different attachments in the core structure. This would help to make suitable structural modifications in 1, 4-DHP molecules so as to make a better complementary fit to the active site of TGF-β receptor, which in turn would improve the potency of newly designed molecules.
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Cite this article as:
Vazhapully Asraf Mohamed, Vinod D. and Hukuman Zeinul N.H., Pharmacophore and 3D QSAR Study of TGFβ Inhibitors, Letters in Drug Design & Discovery 2014; 11 (3) . https://dx.doi.org/10.2174/157018081131000071
DOI https://dx.doi.org/10.2174/157018081131000071 |
Print ISSN 1570-1808 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-628X |
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