Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance
The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resist...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-09-01
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| Series: | Frontiers in Molecular Biosciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2021.643849/full |
| _version_ | 1818438979766190080 |
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| author | Grace Mugumbate Brilliant Nyathi Albert Zindoga Gadzikano Munyuki |
| author_facet | Grace Mugumbate Brilliant Nyathi Albert Zindoga Gadzikano Munyuki |
| author_sort | Grace Mugumbate |
| collection | DOAJ |
| description | The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action. |
| first_indexed | 2024-12-14T17:49:10Z |
| format | Article |
| id | doaj.art-a4551d9909d84a74a9c907c0bcb63a1d |
| institution | Directory Open Access Journal |
| issn | 2296-889X |
| language | English |
| last_indexed | 2024-12-14T17:49:10Z |
| publishDate | 2021-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Biosciences |
| spelling | doaj.art-a4551d9909d84a74a9c907c0bcb63a1d2022-12-21T22:52:41ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2021-09-01810.3389/fmolb.2021.643849643849Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug ResistanceGrace Mugumbate0Brilliant Nyathi1Albert Zindoga2Gadzikano Munyuki3Department of Chemical Sciences, Midlands State University, Gweru, ZimbabweDepartment of Chemistry, Chinhoyi University of Technology, Chinhoyi, ZimbabweDepartment of Chemistry, Chinhoyi University of Technology, Chinhoyi, ZimbabweDepartment of Chemistry, Chinhoyi University of Technology, Chinhoyi, ZimbabweThe emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action.https://www.frontiersin.org/articles/10.3389/fmolb.2021.643849/fullmutationsdrug resistancecomputational toolsMycobacterium tuberculosismolecular modeling |
| spellingShingle | Grace Mugumbate Brilliant Nyathi Albert Zindoga Gadzikano Munyuki Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance Frontiers in Molecular Biosciences mutations drug resistance computational tools Mycobacterium tuberculosis molecular modeling |
| title | Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance |
| title_full | Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance |
| title_fullStr | Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance |
| title_full_unstemmed | Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance |
| title_short | Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance |
| title_sort | application of computational methods in understanding mutations in mycobacterium tuberculosis drug resistance |
| topic | mutations drug resistance computational tools Mycobacterium tuberculosis molecular modeling |
| url | https://www.frontiersin.org/articles/10.3389/fmolb.2021.643849/full |
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