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Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents

Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. T...

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Autores principales: Adeniji, Shola Elijah, Adamu Shallangwa, Gideon, Ebuka Arthur, David, Abdullahi, Mustapha, Mahmoud, A.Y., Haruna, Abdurrashid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7114754/
https://www.ncbi.nlm.nih.gov/pubmed/32258484
http://dx.doi.org/10.1016/j.heliyon.2020.e03639
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author Adeniji, Shola Elijah
Adamu Shallangwa, Gideon
Ebuka Arthur, David
Abdullahi, Mustapha
Mahmoud, A.Y.
Haruna, Abdurrashid
author_facet Adeniji, Shola Elijah
Adamu Shallangwa, Gideon
Ebuka Arthur, David
Abdullahi, Mustapha
Mahmoud, A.Y.
Haruna, Abdurrashid
author_sort Adeniji, Shola Elijah
collection PubMed
description Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. Time expended and costs in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis (TB). Meanwhile, to solve the problem stated, a new approach i.e. QSAR which establish connection between novel drugs with a better biological against M. tuberculosis is adopted. The anti-tubercular model established in this study to forecast the biological activities of some anti-tubercular compounds selected and to design new hypothetical drugs is subjective to the molecular descriptors; AATS7s, VE2_Dzi, SpMin7-Bhe and RDF110i. The significant of the model were observed with R(2) of 0.8738, R(2) adj of 0.8351 Q_cvˆ2 of 0.7127 which served as criteria to substantiate the QSAR model. More also, the model significant with the QSAR external validation criterial ‘‘(R(2)test) of 0.7532. Ligand-receptor interactions between quinoline derivatives and the receptor (DNA gyrase) was carried out using molecular docking technique by employing the PyRx virtual screening software and discovery studio visualizer software. Furthermore, docking study indicates that compounds 10 of the derivatives with promising biological activity have the utmost binding energy of -18.8 kcal/mol. Meanwhile, the interaction of the standard drug; isoniazid with the target enzyme was observed with the binding energy -14.6 kcal/mol which was significantly lesser than the binding energy of the ligand (compound 10). This implies that ligand 10 could be used as a structural template to design better hypothetical anti-tubercular drugs with more efficient activities. The presumption of this research aid the medicinal chemists and pharmacist to design and synthesis a novel drug candidate against the tuberculosis. Moreover, in-vitro and in-vivo test could be carried out to validate the computational results.
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spelling pubmed-71147542020-04-06 Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents Adeniji, Shola Elijah Adamu Shallangwa, Gideon Ebuka Arthur, David Abdullahi, Mustapha Mahmoud, A.Y. Haruna, Abdurrashid Heliyon Article Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. Time expended and costs in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis (TB). Meanwhile, to solve the problem stated, a new approach i.e. QSAR which establish connection between novel drugs with a better biological against M. tuberculosis is adopted. The anti-tubercular model established in this study to forecast the biological activities of some anti-tubercular compounds selected and to design new hypothetical drugs is subjective to the molecular descriptors; AATS7s, VE2_Dzi, SpMin7-Bhe and RDF110i. The significant of the model were observed with R(2) of 0.8738, R(2) adj of 0.8351 Q_cvˆ2 of 0.7127 which served as criteria to substantiate the QSAR model. More also, the model significant with the QSAR external validation criterial ‘‘(R(2)test) of 0.7532. Ligand-receptor interactions between quinoline derivatives and the receptor (DNA gyrase) was carried out using molecular docking technique by employing the PyRx virtual screening software and discovery studio visualizer software. Furthermore, docking study indicates that compounds 10 of the derivatives with promising biological activity have the utmost binding energy of -18.8 kcal/mol. Meanwhile, the interaction of the standard drug; isoniazid with the target enzyme was observed with the binding energy -14.6 kcal/mol which was significantly lesser than the binding energy of the ligand (compound 10). This implies that ligand 10 could be used as a structural template to design better hypothetical anti-tubercular drugs with more efficient activities. The presumption of this research aid the medicinal chemists and pharmacist to design and synthesis a novel drug candidate against the tuberculosis. Moreover, in-vitro and in-vivo test could be carried out to validate the computational results. Elsevier 2020-03-31 /pmc/articles/PMC7114754/ /pubmed/32258484 http://dx.doi.org/10.1016/j.heliyon.2020.e03639 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Adeniji, Shola Elijah
Adamu Shallangwa, Gideon
Ebuka Arthur, David
Abdullahi, Mustapha
Mahmoud, A.Y.
Haruna, Abdurrashid
Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title_full Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title_fullStr Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title_full_unstemmed Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title_short Quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
title_sort quantum modelling and molecular docking evaluation of some selected quinoline derivatives as anti-tubercular agents
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7114754/
https://www.ncbi.nlm.nih.gov/pubmed/32258484
http://dx.doi.org/10.1016/j.heliyon.2020.e03639
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