2D AND 3D-QSAR ANALYSIS OF AMINO (3-((3, 5-DIFLUORO -4-METHYL-6- PHENOXYPYRIDINE-2-YL) OXY) PHENYL) METHANIMINIUM DE RIVATIVES AS FACTOR XA INHIBITOR
- Vol.11(2)
- M P Innovare Academic Sciences Pvt Ltd 2019
- 104-114p.
Objective: The main objective of the present study was to evol ve a novel pharmacophore of methaniminium derivativ es as factor Xa inhibitors by developing best 2D and 3D QSAR models. The models were developed for amino (3-((3, 5-diflu oro-4-methyl-6-phenoxypyridine-2-yl) oxy) phenyl) m ethaniminium derivatives as factor Xa inhibitors. Methods: With the help of Marvin application, 2D structures of thirty compounds of methaniminium derivatives we re drawn and consequently converted to 3D structures. 2D QSAR using multiple linear regression (MLR) analysis and PLS regression method was performed with the help of molecular design suite VLife MDS 4.3.3. 3D QSAR ana lysis was carried out using k-Nearest Neighbour Mol ecular Field Analysis (k-NN-MFA). Results: The most significant 2D models of methaniminium der ivatives calculated squared correlation coefficient value 0.8002 using multiple linear regression (MLR) analysis. Partial Least Square (PL S) regression method was also employed. The results of both the methods were compared. In 2D QSAR model, T_C_O_5, T_2_O_2, s log p, T_2_O_1 and T_2_O_6 descriptors were found significant. The best 3D QSAR model with k-Nearest Neighbour Mol ecular Field Analysis have predicted q 2 value 0.8790, q2_ se value 0.0794, pred r 2 value 0.9340 and pred_r 2 se value 0.0540. The stepwise regression method was employed for anticipating the inhibitory activity of this class of compound. The 3D model demonstrated that hydrophobic, electrostatic and steric descriptors exhibit a crucial role in de termining the inhibitory activity of this class of compounds. Conclusion: The developed 2D and 3D QSAR models have shown good r 2 and q 2 values of 0.8002 and 0.8790 respectively. There is high agreement in inhibitory properties of experimental and predic ted values, which suggests that derived QSAR models have good predicting properties. The contour plots of 3D QSAR (k-NN-MFA) method furn ish additional information on the relationship betw een the structure of the compound and their inhibitory activities which can be employed t o construct newer potent factor Xa inhibitors.