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In silico molecular modeling and prediction of activity of substituted tetrahydropyrans as COX-2 inhibitor

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Abstract

Series of mono-, di-, and triaryl substituted tetrahydropyrans were taken for quantitative structure–activity relationship (QSAR) study using density functional theory-based (DFT-based) quantum chemical and empirical descriptors. Several QSAR equations were formulated through regression analysis, which were able to explain 93–98 % of the variance in the data. The best equations were selected from the various statistically significant equations by following established statistical procedures. The model equations revealed that the presence of 4-cholorobenzene at R1 position is favorable for the activity and the presence of 4-bromo benzene at R1 position seems to be unfavorable for the activity, however, DFT-based descriptors demonstrate that the high values of HOMO and softness whereas low values of LUMO, hardness, and absence of –CH3 group at R1 position enhances the activity. The predictive ability of equations were cross validated by evaluating of the residual activity and R 2 values and also by leave one out (LOO) technique.

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Acknowledgments

The author A. K. Srivastava gratefully acknowledges the University Grants Commission New Delhi, India for the Grant, Grant No. 40-70/2011 (SR). Author A. Singh wishes to acknowledge the UGC, New Delhi, India, for Dr. D. S. Kothari postdoctoral fellowship. Author A. Dwivedi is grateful to UGC, New Delhi, for the award of Junior Research Fellowship.

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  1. QSAR Research Laboratory, Department of Chemistry, University of Allahabad, Allahabad, 211002, UP, India

    Amrita Dwivedi, A. K. Srivastava & Ajeet Singh

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  1. Amrita Dwivedi
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  2. A. K. Srivastava
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  3. Ajeet Singh
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Correspondence to A. K. Srivastava or Ajeet Singh.

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Dwivedi, A., Srivastava, A.K. & Singh, A. In silico molecular modeling and prediction of activity of substituted tetrahydropyrans as COX-2 inhibitor. Med Chem Res 24, 714–724 (2015). https://doi.org/10.1007/s00044-014-1148-0

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