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Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach
Mycobacterium tuberculosis (MTB) is becoming more and more resistant to drugs and it is a common problem, making current antimicrobials ineffective and highlighting the need for new TB drugs. One of the promising targets for treating MTB is MurB enzymes. This study aimed to identify potential inhibi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362793/ https://www.ncbi.nlm.nih.gov/pubmed/37483837 http://dx.doi.org/10.1016/j.sjbs.2023.103730 |
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author | Verma, Ankit Kumar, Vijay Naik, Bindu Masood Khan, Javed Singh, Pallavi Erik Joakim Saris, Per Gupta, Sanjay |
author_facet | Verma, Ankit Kumar, Vijay Naik, Bindu Masood Khan, Javed Singh, Pallavi Erik Joakim Saris, Per Gupta, Sanjay |
author_sort | Verma, Ankit |
collection | PubMed |
description | Mycobacterium tuberculosis (MTB) is becoming more and more resistant to drugs and it is a common problem, making current antimicrobials ineffective and highlighting the need for new TB drugs. One of the promising targets for treating MTB is MurB enzymes. This study aimed to identify potential inhibitors of MurB enzymes in M. tuberculosis, as drug resistance among MTB is a significant problem. Attempts are being made to conduct a virtual screening of 30,417 compounds, and thirty-two compounds were chosen for further analysis based on their binding conformations. The selected compounds were assessed for their drug-likeness, pharmacokinetics, and physiochemical characteristics, and seven compounds with binding energy lower than flavin (FAD) were identified. Further, molecular dynamics simulation analysis of these seven compounds found that four of them, namely DB12983, DB15688, ZINC084726167, and ZINC254071113 formed stable complexes with the MurB binding site, exhibiting promising inhibitory activity. These compounds have not been mentioned in any other study, indicating their novelty. The study suggests that these four compounds could be promising candidates for treating MTB, but their effectiveness needs to be validated through in vitro and in vivo experiments. Overall, the findings of this study provide new insight into potential drug targets and candidates for combating drug-resistant MTB. |
format | Online Article Text |
id | pubmed-10362793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103627932023-07-23 Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach Verma, Ankit Kumar, Vijay Naik, Bindu Masood Khan, Javed Singh, Pallavi Erik Joakim Saris, Per Gupta, Sanjay Saudi J Biol Sci Original Article Mycobacterium tuberculosis (MTB) is becoming more and more resistant to drugs and it is a common problem, making current antimicrobials ineffective and highlighting the need for new TB drugs. One of the promising targets for treating MTB is MurB enzymes. This study aimed to identify potential inhibitors of MurB enzymes in M. tuberculosis, as drug resistance among MTB is a significant problem. Attempts are being made to conduct a virtual screening of 30,417 compounds, and thirty-two compounds were chosen for further analysis based on their binding conformations. The selected compounds were assessed for their drug-likeness, pharmacokinetics, and physiochemical characteristics, and seven compounds with binding energy lower than flavin (FAD) were identified. Further, molecular dynamics simulation analysis of these seven compounds found that four of them, namely DB12983, DB15688, ZINC084726167, and ZINC254071113 formed stable complexes with the MurB binding site, exhibiting promising inhibitory activity. These compounds have not been mentioned in any other study, indicating their novelty. The study suggests that these four compounds could be promising candidates for treating MTB, but their effectiveness needs to be validated through in vitro and in vivo experiments. Overall, the findings of this study provide new insight into potential drug targets and candidates for combating drug-resistant MTB. Elsevier 2023-08 2023-07-04 /pmc/articles/PMC10362793/ /pubmed/37483837 http://dx.doi.org/10.1016/j.sjbs.2023.103730 Text en © 2023 The Author(s) https://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 | Original Article Verma, Ankit Kumar, Vijay Naik, Bindu Masood Khan, Javed Singh, Pallavi Erik Joakim Saris, Per Gupta, Sanjay Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title | Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title_full | Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title_fullStr | Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title_full_unstemmed | Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title_short | Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach |
title_sort | screening and molecular dynamics simulation of compounds inhibiting murb enzyme of drug-resistant mycobacterium tuberculosis: an in-silico approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362793/ https://www.ncbi.nlm.nih.gov/pubmed/37483837 http://dx.doi.org/10.1016/j.sjbs.2023.103730 |
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