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

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

Volume: 12 Issue: 2

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

Affiliation:

• Department of Pharmaceutical Sciences, Dr. Hari Singh Gour University, Sagar, MP 470003,India

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

Abstract: 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.

Cite this article as:

Verma Ekta, Agarwal Shivangi , Patil Shailendra , Kashaw K. Sushil and Gajbhiye Asmita *, Mechanistic Approach to Explore Isoniazid Derivatives as Antitubercular Agents Using KNN-MF Based-QSAR Analysis, Pharmacophore Modeling and Molecular Docking, Current Drug Therapy 2017; 12 (2) . https://dx.doi.org/10.2174/1574885512666170323124245