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Abstract

In present study, at the beginning, the molecules whose biological properties are known are well-thought-out as a known set for regression analysis model building purpose. Using the Datawarrior software the descriptors were calculated for known set. Novel substituted 4-hydrazinylqunoline molecules were designed, improved and their descriptors were calculated. Morever, the regression analysis model was used to determine the biological activities of these new molecules. Along with this, the inhibition studies for 1QPQ and 1KNC by molecular docking method were also carried out to validate the therapeutic nature of these molecules. Accordingly, it can be concluded that these moieties on further studies may evident to be therapeutic representative against Mycobacterium tuberculosis.

Keywords

Structure activity Biological activity Docking Tuberculosis Descriptor Quinolines

Article Details

How to Cite
Bisen, C., Patle, M., & Patle, R. (2019). Regression Analysis and Docking Study of 4-Quinolylhydrazone Based Compounds as Antituberculosis Agents. Asian Journal of Organic & Medicinal Chemistry, 4(4), 248–255. https://doi.org/10.14233/ajomc.2019.AJOMC-P237
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References

  1. L.H. Hall, A Structure-Information Approach to the Prediction of Biological Activities and Properties, Chem. Biodivers., 1, 183 (2004); https://doi.org/10.1002/cbdv.200490010.
  2. P.N. Judson, QSAR and Expert Systems in the Prediction of Biological Activity, Pestic. Sci., 36, 155 (1992); https://doi.org/10.1002/ps.2780360211.
  3. A.K. Parmar and M.R. Patle, Regression Analysis and Docking Study of Hydroxyl Quinoline Based Compounds as Anti-Tuberculosis Thera-peutic Agents, Int. J. Sci. Res. Biol. Sci., 6, 177 (2019); https://doi.org/10.26438/ijsrbs/v6i1.177186.
  4. A. Tropsha, Best Practices for QSAR Model Development, Validation, and Exploitation, Mol. Inform., 29, 476 (2010); https://doi.org/10.1002/minf.201000061.
  5. L.B. Kier and L.H. Hall, Introductory Editorial, Med. Chem. Res., 7, 335 (1997).
  6. L.B. Kier and L.H. Hall, Molecular Structure Description: The Electro-topological State, Academic Press: San Diego (1999).
  7. J. Devillers and A.T. Balaban, Topological Indices and Related Descri-ptors in QSAR and QSPR, Gordon and Breach Science Publishers: Singapore (1999).
  8. G.W. Adamson and J.A. Bush, Evaluation of an Empirical Structure–Activity Relationship for Property Prediction in a Structurally Diverse Group of Local Anaesthetics, J. Chem. Soc., Perkin Transac. I, 168 (1976); https://doi.org/10.1039/P19760000168.
  9. L. Savini, L. Chiasserini, A. Gaeta and C. Pellerano, Synthesis and Anti-tubercular Evaluation of 4-Quinolylhydrazones, Bioorg. Med. Chem., 10, 2193 (2002); https://doi.org/10.1016/S0968-0896(02)00071-8.
  10. M.V.N. de Souza, K.C. Pais, C.R. Kaiser, M.A. Peralta, M. de L. Ferreira and M.C.S. Lourenço, Synthesis and in vitro Antitubercular Activity of a Series of Quinoline Derivatives, Bioorg. Med. Chem., 17, 1474 (2009); https://doi.org/10.1016/j.bmc.2009.01.013.
  11. S.N. Al-Busafi, F.E.O. Suliman and Z.R. Al-Alawi, 8-Hydroxyquinoline and its Derivatives: Synthesis and Applications, Res. Rev. J. Chem., 3, 1 (2014).
  12. E. Massarani, D. Nardi, R. Pozzi, L. Degen and M.J. Magistretti, 8-Hydroxyquinoline Derivatives. Synthesis and Biological Evaluation of Arylglyoxal N-7-Amino-5-substituted 8-Hydroxyquinoline Hemiacetals and 5-Phenylglyoxylidenamino-8-hydroxyquinolines, J. Med. Chem., 13, 380 (1970); https://doi.org/10.1021/jm00297a010.
  13. T. Sander, J. Freyss, M. von Korff and C. Rufener, DataWarrior: An Open-Source Program for Chemistry Aware Data Visualization and Analysis, J. Chem. Inf. Model., 55, 460 (2015); https://doi.org/10.1021/ci500588j.
  14. J. Huuskonen, Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology, J. Chem. Inf. Model., 40, 773 (2000); https://doi.org/10.1021/ci9901338.
  15. A. Lilienkampf, J. Mao, B. Wan, Y. Wang, S.G. Franzblau and A.P. Kozikowski, Structure-Activity Relationships for a Series of Quinoline-Based Compounds Active against Replicating and Nonreplicating Mycobacterium tuberculosis, J. Med. Chem., 52, 2109 (2009); https://doi.org/10.1021/jm900003c.
  16. SPSS version 24 for Windows. SPSS Software Packages, SPSS Inc. 444 North Michigan Avenue, Suite 3000, Chicago, Illinois 60611, USA.
  17. S. Eswaran, A.V. Adhikari, N.K. Pal and I.H. Chowdhury, Design and Synthesis of Some New Quinoline-3-carbohydrazone Derivatives as Potential Antimycobacterial Agents, Bioorg. Med. Chem. Lett., 20, 1040 (2010); https://doi.org/10.1016/j.bmcl.2009.12.045.
  18. S.H. Ganatra, M.R. Patle and G.K. Bhagat, Inhibition Studies of Pyridine Based Compounds on Quinolinic Acid Phosphoribosyl-transferase (1QPQ) Enzyme as a Potent Anti-Tuberculosis Agent, Asian J. Res. Chem., 5, 1159 (2012).
  19. J.M. Yang and C.C. Chen, GEMDOCK: A Generic Evolutionary Method for Molecular Docking, Proteins, 55, 288 (2004); https://doi.org/10.1002/prot.20035.
  20. K.C. Hsu, Y.F. Chen, S.R. Lin and J.M. Yang, iGEMDOCK: A Graphical Environment of Enhancing GEMDOCK using Pharmacological Inter-actions and Post-Screening Analysis, BMC Bioinformatics, 12(Suppl 1), S33 (2011); https://doi.org/10.1186/1471-2105-12-S1-S33.