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...
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| Format: | Article |
| Language: | English |
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Frontiers Media
2022
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| Online Access: | https://doi.org/10.3389/fmolb.2021.643849 http://hdl.handle.net/11408/4679 |
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| author | Mugumbate, Grace Nyathi, Brilliant Zindoga, Albert Munyuki, Gadzikano |
| author_facet | Mugumbate, Grace Nyathi, Brilliant Zindoga, Albert Munyuki, Gadzikano |
| author_sort | Mugumbate, Grace |
| collection | DSpace |
| 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. |
| format | Article |
| id | ir-11408-4679 |
| institution | My University |
| language | English |
| publishDate | 2022 |
| publisher | Frontiers Media |
| record_format | dspace |
| spelling | ir-11408-46792022-06-27T13:49:06Z Application of computational methods in understanding mutations in mycobacterium tuberculosis drug resistance Mugumbate, Grace Nyathi, Brilliant Zindoga, Albert Munyuki, Gadzikano Drug-resistant Mycobacterium tuberculosis Computational techniques 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. 2022-03-11T11:03:42Z 2022-03-11T11:03:42Z 2021 Article 2296-889X https://doi.org/10.3389/fmolb.2021.643849 http://hdl.handle.net/11408/4679 en Frontiers in Molecular Biosciences;Vol. 8 open Frontiers Media |
| spellingShingle | Drug-resistant Mycobacterium tuberculosis Computational techniques Mugumbate, Grace Nyathi, Brilliant Zindoga, Albert Munyuki, Gadzikano Application of computational methods in understanding mutations in mycobacterium tuberculosis drug resistance |
| 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 | Drug-resistant Mycobacterium tuberculosis Computational techniques |
| url | https://doi.org/10.3389/fmolb.2021.643849 http://hdl.handle.net/11408/4679 |
| work_keys_str_mv | AT mugumbategrace applicationofcomputationalmethodsinunderstandingmutationsinmycobacteriumtuberculosisdrugresistance AT nyathibrilliant applicationofcomputationalmethodsinunderstandingmutationsinmycobacteriumtuberculosisdrugresistance AT zindogaalbert applicationofcomputationalmethodsinunderstandingmutationsinmycobacteriumtuberculosisdrugresistance AT munyukigadzikano applicationofcomputationalmethodsinunderstandingmutationsinmycobacteriumtuberculosisdrugresistance |