Mechanistic Approach to Explore Isoniazid Derivatives as Antitubercular Agents Using KNN-MF Based-QSAR Analysis, Pharmacophore Modeling and Molecular Docking

Author(s): Ekta Verma, Shivangi Agarwal, Shailendra Patil, Sushil K. Kashaw, Asmita Gajbhiye*

Journal Name: Current Drug Therapy

Volume 12 , Issue 2 , 2017

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Background: The resistant to current therapy against tuberculosis is tremendously increasing, novel potential anti-tubercular compounds should be developed at the urge. The presently reported analogues act by binding to the kat-G gene present in Mycobacterium tuberculosis which converts them into active form, thereby inhibiting inhA mediated mycolic acid synthesis.

Objective: To establish structure activity relationship, identify key features and find out the binding orientation of the compounds to the katG gene present in Mycobacterium tuberculosis for the treatment of tuberculosis.

Methods: In the present work, 2D Quantitative Structure Activity Relationships, 3D Quantitative Structure Activity Relationships, pharmacophore mapping and docking studies of isoniazid derivatives have been carried out with V-life Molecular Design Suite 4.2, Schrodinger and GOLD (Genetic Optimization for Ligand Docking) program. The model was developed by PLS (Partial Least Square) and kNN (k-nearest neighbour) as variable selection method.

Results: The best 2D Quantitative Structure Activity Relationships model was developed with r2 = 0.9688 and q2 = 0.8082 and correlated the effect of descriptors on the biological activity. The best 3D Quantitative Structure Activity Relationships model showed a crossvalidated correlation coefficient (q2) of 0.7332 and a predicted r2 for the external test (pred_r2) of 0.9032. The pharmacophore analysis represented that the features such as hydrogen bond acceptor, hydrogen bond donor and aromatic ring were essential for the anti-tubercular activity. When docked, the isoniazid derivatives showed good binding affinity to the receptor even in resistant cases (mutant type) and showed favourable fitness scores in-silico as compared to isoniazid.

Conclusion: The whole studies served as a basis for the development of better potential therapeutic compounds for anti-tubercular activity.

Keywords: Anti-tubercular, partial least square analysis (PLS), isoniazid derivatives, kNN analysis, KatG gene.

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Article Details

Year: 2017
Page: [97 - 114]
Pages: 18
DOI: 10.2174/1574885512666170323124245
Price: $65

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