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Comparative Pharmacophore Modeling and QSAR Studies for Structural Requirements of some Substituted 2-Aminopyridine Derivatives as Inhibitors of Nitric Oxide Synthases

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Abstract

The present study is an attempt in this direction seeking for the development and comparison of QSAR models of substituted 2-aminopyridine derivatives as inhibitors of nitric oxide synthases by different feature selection methods. The QSAR study was carried out on V-life Molecular Design Suite software, and the derived best QSAR model was derived by partial component regression method. The statistically significant best model with high correlation coefficient (\(r^{2}=0.8408\)) was selected for further study. The model was further validated by means of crossed squared correlation coefficient (\(q^{2}=0.7270\) and \(\hbox {pred}\_r^{2}=0.7889\)) which shows model has good predictive ability. The best 3D-QSAR model showed \(q^{2}=0.8377,\,r^{2} = 0.8739\) and standard error = 0.1954. The predictive ability of the resultant model was evaluated using a test set molecules and the predicted \(r^{2}=0.8159.\) The results reveal that the acceptor, donor, aliphatic, and aromatic pharmacophore properties are favorable contour sites for both the activities. The two-dimensional and k-nearest-neighbor contour plots were required for further understanding of the relationship between structural features of substituted 2-aminopyridine derivatives and their activities which should be applicable to design newer potential inducible nitric oxide synthases.

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Acknowledgments

The author thanks Vlife Science Technologies Pvt. Ltd., for providing the software for the study.

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  1. Drug Design and Development Laboratory, School of Pharmacy, Devi Ahilya University, Takshila Campus, Khandwa Road, Indore, 452 001, India

    Mukesh C. Sharma

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Correspondence to Mukesh C. Sharma.

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Sharma, M.C. Comparative Pharmacophore Modeling and QSAR Studies for Structural Requirements of some Substituted 2-Aminopyridine Derivatives as Inhibitors of Nitric Oxide Synthases. Interdiscip Sci Comput Life Sci 7, 100–112 (2015). https://doi.org/10.1007/s12539-015-0004-3

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