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In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel T...

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Autores principales: Macalino, Stephani Joy Y., Billones, Junie B., Organo, Voltaire G., Carrillo, Maria Constancia O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037728/
https://www.ncbi.nlm.nih.gov/pubmed/32033144
http://dx.doi.org/10.3390/molecules25030665
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author Macalino, Stephani Joy Y.
Billones, Junie B.
Organo, Voltaire G.
Carrillo, Maria Constancia O.
author_facet Macalino, Stephani Joy Y.
Billones, Junie B.
Organo, Voltaire G.
Carrillo, Maria Constancia O.
author_sort Macalino, Stephani Joy Y.
collection PubMed
description Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.
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spelling pubmed-70377282020-03-10 In Silico Strategies in Tuberculosis Drug Discovery Macalino, Stephani Joy Y. Billones, Junie B. Organo, Voltaire G. Carrillo, Maria Constancia O. Molecules Review Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field. MDPI 2020-02-04 /pmc/articles/PMC7037728/ /pubmed/32033144 http://dx.doi.org/10.3390/molecules25030665 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Macalino, Stephani Joy Y.
Billones, Junie B.
Organo, Voltaire G.
Carrillo, Maria Constancia O.
In Silico Strategies in Tuberculosis Drug Discovery
title In Silico Strategies in Tuberculosis Drug Discovery
title_full In Silico Strategies in Tuberculosis Drug Discovery
title_fullStr In Silico Strategies in Tuberculosis Drug Discovery
title_full_unstemmed In Silico Strategies in Tuberculosis Drug Discovery
title_short In Silico Strategies in Tuberculosis Drug Discovery
title_sort in silico strategies in tuberculosis drug discovery
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037728/
https://www.ncbi.nlm.nih.gov/pubmed/32033144
http://dx.doi.org/10.3390/molecules25030665
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