Latent tuberculosis and computational biology: A less-talked affair.

Autor: Sarmah DT; Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India., Parveen R; Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India., Kundu J; Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India., Chatterjee S; Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India. Electronic address: samrat.chatterjee@thsti.res.in.
Jazyk: angličtina
Zdroj: Progress in biophysics and molecular biology [Prog Biophys Mol Biol] 2023 Mar; Vol. 178, pp. 17-31. Date of Electronic Publication: 2023 Feb 11.
DOI: 10.1016/j.pbiomolbio.2023.02.002
Abstrakt: Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.
Competing Interests: Declaration of competing interest None.
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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