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.
Published in | International Journal of Computational and Theoretical Chemistry (Volume 2, Issue 3) |
DOI | 10.11648/j.ijctc.20140203.11 |
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), 2014. Published by Science Publishing Group |
QSAR, MLR, ANN, Antimycobacterial, β-Thia Adduct of Chalcone, Diazachalcones
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APA Style
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
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
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
@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://article.sciencepublishinggroup.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} }
TY - JOUR 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 PY - 2014 N1 - https://doi.org/10.11648/j.ijctc.20140203.11 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 -