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QSAR and pharmacophore modeling of anti-tubercular 6-Fluoroquinolone compounds utilizing calculated structural descriptors

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Abstract

Most alarming is the emergence of multidrug-resistant-tuberculosis. Multidrug-resistant-tuberculosis urgently needs to develop new second-line anti-mycobacterial chemotherapeutic including 6-fluoroquinolones. In the present study, an attempt has been made for the development of quantitative structure–activity relationship models utilizing theoretical structural descriptors calculated from the structure of 6-flouoroquinolone compounds. A number of quantitative structure–activity relationship has been generated and validated as per the statistical rules. Then the validated quantitative structure–activity relationship models have been applied for prediction of anti-mycobacterial activities for the test set of congeneric 6-FQ compounds. Further mode of binding was studied by pharmacophore modeling, which can predict the crucial features for the design of highly active congeneric ligands. It was shown that C-7 and C-8 substituent may contribute hydrophobic interaction, positive ionization of C-7 and hydrogen bonding interactions between the substituents associated to C-8 group with the DNA gyrase target may enhance the biological activities in these congeneric ligands. Basic scaffold contributes aromaticity and represents pi-stacking interaction domain. The study in this direction may focus important structural descriptors modeled in quantitative structure–activity relationship, which are crucial for the designing of new lead like active congeneric compound.

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Acknowledgements

Authors are thankful to Professor Kunal Roy, Drug Theoretics and Chemoinformatics Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India for providing “NanoBRIDGES” software. SN is sincerely thankful to National Institute of Chemistry, Ljubljana for availing DRAGON and Ligand Scout softwares used in the present work. Authors show deep gratitude to Dr. Anil Kumar Saxena, Ex-Chief Scientist and Head, Medicinal and Process Chemistry Division, CSIR Central drug Research Institute, India for the constructive predictions in 3D pharmacophoric feature based modeling.

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  1. Division of Pharmaceutical Chemistry, Global Institute of Pharmaceutical Education and Research, Uttarakhand Technical University, Kashipur, 244713, India

    Dipiksha, Mohd Salman & Sisir Nandi

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  1. Dipiksha
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  2. Mohd Salman
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  3. Sisir Nandi
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Correspondence to Sisir Nandi.

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Dipiksha, Salman, M. & Nandi, S. QSAR and pharmacophore modeling of anti-tubercular 6-Fluoroquinolone compounds utilizing calculated structural descriptors. Med Chem Res 26, 1903–1914 (2017). https://doi.org/10.1007/s00044-017-1882-1

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