Abstract
Background: Tuberculosis is one of the main medical problems and some people are suffering still from this infectious disease. 1, 4-dihydropyridines are multi-target ligands that recently are recognized as anti-tubercular agents.
Methods: In the current research, computational studies were conducted of some synthesized 1, 4- dihydropyridine-3, 5-dicarboxamides in non-hydrolyzed and hydrolyzed forms to find the drugreceptor interactions profile.
Results: Among equations obtained for non-hydrolyzed compounds, the model with better statistical parameters such as R2= 0.9462, q2 of LOO= 0.8318 and q2 of LMO= 0.7987 was considered as the best one and EEig08d, LAI, Mor23m, GATS3e, Mor28m descriptors were identified as the most significant factors that affect the biological activity of non-hydrolyzed compounds.
Conclusion: In the hydrolyzed compounds, the model which has R2= 0.9731, q2 of LOO= 0.91154462 and q2 of LMO= 0.742 was considered as the best one and Mor27e and BEHv2 were also revealed as the most important descriptors in hydrolyzed compounds.
Keywords: Docking, quantitative structure-activity relationship, tuberculosis, 1, 4-dihydropyridine, QSAR, InhA.
Current Computer-Aided Drug Design
Title:Hybrid Docking-QSAR Studies of 1, 4-dihydropyridine-3, 5-Dicarboxamides as Potential Antitubercular Agents
Volume: 14 Issue: 1
Author(s): Yasaman Rasouli and Asghar Davood*
Affiliation:
- Faculty of Pharmacy, Department of Medicinal Chemistry, Pharmaceutical Sciences Branch, Islamic Azad University, Tehran,Iran
Keywords: Docking, quantitative structure-activity relationship, tuberculosis, 1, 4-dihydropyridine, QSAR, InhA.
Abstract: Background: Tuberculosis is one of the main medical problems and some people are suffering still from this infectious disease. 1, 4-dihydropyridines are multi-target ligands that recently are recognized as anti-tubercular agents.
Methods: In the current research, computational studies were conducted of some synthesized 1, 4- dihydropyridine-3, 5-dicarboxamides in non-hydrolyzed and hydrolyzed forms to find the drugreceptor interactions profile.
Results: Among equations obtained for non-hydrolyzed compounds, the model with better statistical parameters such as R2= 0.9462, q2 of LOO= 0.8318 and q2 of LMO= 0.7987 was considered as the best one and EEig08d, LAI, Mor23m, GATS3e, Mor28m descriptors were identified as the most significant factors that affect the biological activity of non-hydrolyzed compounds.
Conclusion: In the hydrolyzed compounds, the model which has R2= 0.9731, q2 of LOO= 0.91154462 and q2 of LMO= 0.742 was considered as the best one and Mor27e and BEHv2 were also revealed as the most important descriptors in hydrolyzed compounds.
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Cite this article as:
Rasouli Yasaman and Davood Asghar *, Hybrid Docking-QSAR Studies of 1, 4-dihydropyridine-3, 5-Dicarboxamides as Potential Antitubercular Agents, Current Computer-Aided Drug Design 2018; 14 (1) . https://dx.doi.org/10.2174/1573409913666170426154045
DOI https://dx.doi.org/10.2174/1573409913666170426154045 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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