International Journal of Computational and Theoretical Chemistry

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QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives

Received: 08 July 2014    Accepted: 23 July 2014    Published: 30 July 2014
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Abstract

Quantitative structure-activity antimycobacterial relationships have been studied for a series of β-thia adduct of chalcone and diazachalcone derivatives by means of multiple linear regression (MLR) and artificial neural networks (ANN). The antimycobacterial activity against M. tuberculosis H37Rv of the compounds studied was well correlated with descriptors encoding the chemical structure. Using the pertinent descriptors revealed by a stepwise procedure in the multiple linear regression technique, a correlation coefficient of 0.9798 (s=0.0869) for the training set was obtained for the ANN model in a [3-3-1] configuration. The results show that the antimycobacterial activity of these compounds is strongly dependent on hydrogen-bonding donors, molecular refraction and also molecular connectivity indices for 2nd order.

DOI 10.11648/j.ijctc.20140203.11
Published in International Journal of Computational and Theoretical Chemistry (Volume 2, Issue 3, May 2014)
Page(s) 20-25
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

QSAR, MLR, ANN, Antimycobacterial, β-Thia Adduct of Chalcone, Diazachalcones

References
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[6] Cramer, R., A QSAR success story. Chemtech. 1980, 10, 744-747.
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[8] Draper, N.R.; Smith, H. In: Applied Regression Analysis, John Wiley & Sons: New York, 1981.
[9] Yap, C.W., Chen, Y.Z., Quantitative structure pharmacokinetic relationships for drug distribution properties by using general regression neural network. J. Pharm. Sci. 2005, 94, 153–168.
[10] Karelson, M., Molecular Descriptors in QSAR/QSPR; John Wiley & Sons: New York, 2000.
[11] (a) Unistat statistical package, version 4.0 for Excel. (b) Data pro Qnet 2000 for Windows V2 K build neutral network modeling. Vesta Service, Winnetka, III. (c) MMP, molecular modeling pro-Demo (TM) Revision 301 demo published by ChemSW Software (TM).
[12] Chlupačova, M., Kubanova, P., Opletalova, V., Buchta, V., The Importance of the Enone-moiety for Antimycobacterial and Antifungal Properties of Chalcones, Published in: Proceedings of the 3rd International Symposium on Natural Drugs, Naples, 2-4 October 2003. Borelli, F., Capasso, F., Milic, N., Russo, A. (Eds.). Universita degli Studi di Napoli Federico II, Naples - Indena, Milano 2003, pp. 133-135.
[13] Opletalova, V., Hartl, J., Patel, A., Palat, K., Buchta, V., Ring substituted 3-phenyl-1-(2-pyrazinyl)-2-propen-1-ones as potential photosynthesis-inhibiting, antifungal and antimycobacterial agents. Il Farmaco, 2002, 57, 135-144.
[14] Wold, S., Dunn, W. J., Multivariate quantitative structure-activity relationships (QSAR): conditions for their applicability. J. Chem. Inf. Comput. Sci., 1983, 23, 6-13.
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Author Information
  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

  • Department of Research, Faculty of Science and Technology, University Hassan II, Mohammedia, Morocco

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    Younes Abrouki, Abdelkader Anouzla, Hayat Loukili, Ahmed Rayadh, Driss Zakarya, et al. (2014). QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives. International Journal of Computational and Theoretical Chemistry, 2(3), 20-25. https://doi.org/10.11648/j.ijctc.20140203.11

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    ACS Style

    Younes Abrouki; Abdelkader Anouzla; Hayat Loukili; Ahmed Rayadh; Driss Zakarya, et al. QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives. Int. J. Comput. Theor. Chem. 2014, 2(3), 20-25. doi: 10.11648/j.ijctc.20140203.11

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    AMA Style

    Younes Abrouki, Abdelkader Anouzla, Hayat Loukili, Ahmed Rayadh, Driss Zakarya, et al. QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives. Int J Comput Theor Chem. 2014;2(3):20-25. doi: 10.11648/j.ijctc.20140203.11

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  • @article{10.11648/j.ijctc.20140203.11,
      author = {Younes Abrouki and Abdelkader Anouzla and Hayat Loukili and Ahmed Rayadh and Driss Zakarya and Mohamed Zahouily},
      title = {QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives},
      journal = {International Journal of Computational and Theoretical Chemistry},
      volume = {2},
      number = {3},
      pages = {20-25},
      doi = {10.11648/j.ijctc.20140203.11},
      url = {https://doi.org/10.11648/j.ijctc.20140203.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijctc.20140203.11},
      abstract = {Quantitative structure-activity antimycobacterial relationships have been studied for a series of β-thia adduct of chalcone and diazachalcone derivatives by means of multiple linear regression (MLR) and artificial neural networks (ANN). The antimycobacterial activity against M. tuberculosis H37Rv of the compounds studied was well correlated with descriptors encoding the chemical structure. Using the pertinent descriptors revealed by a stepwise procedure in the multiple linear regression technique, a correlation coefficient of 0.9798 (s=0.0869) for the training set was obtained for the ANN model in a [3-3-1] configuration. The results show that the antimycobacterial activity of these compounds is strongly dependent on hydrogen-bonding donors, molecular refraction and also molecular connectivity indices for 2nd order.},
     year = {2014}
    }
    

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    T1  - QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives
    AU  - Younes Abrouki
    AU  - Abdelkader Anouzla
    AU  - Hayat Loukili
    AU  - Ahmed Rayadh
    AU  - Driss Zakarya
    AU  - Mohamed Zahouily
    Y1  - 2014/07/30
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    DO  - 10.11648/j.ijctc.20140203.11
    T2  - International Journal of Computational and Theoretical Chemistry
    JF  - International Journal of Computational and Theoretical Chemistry
    JO  - International Journal of Computational and Theoretical Chemistry
    SP  - 20
    EP  - 25
    PB  - Science Publishing Group
    SN  - 2376-7308
    UR  - https://doi.org/10.11648/j.ijctc.20140203.11
    AB  - Quantitative structure-activity antimycobacterial relationships have been studied for a series of β-thia adduct of chalcone and diazachalcone derivatives by means of multiple linear regression (MLR) and artificial neural networks (ANN). The antimycobacterial activity against M. tuberculosis H37Rv of the compounds studied was well correlated with descriptors encoding the chemical structure. Using the pertinent descriptors revealed by a stepwise procedure in the multiple linear regression technique, a correlation coefficient of 0.9798 (s=0.0869) for the training set was obtained for the ANN model in a [3-3-1] configuration. The results show that the antimycobacterial activity of these compounds is strongly dependent on hydrogen-bonding donors, molecular refraction and also molecular connectivity indices for 2nd order.
    VL  - 2
    IS  - 3
    ER  - 

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