An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis

Abstract Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of dr...

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Autor principal:	Aqel Albutti
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f8a547ac993e41ceaa7fcb592694d476
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spelling	oai:doaj.org-article:f8a547ac993e41ceaa7fcb592694d4762021-11-14T12:19:31ZAn integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis10.1038/s41598-021-01283-62045-2322https://doaj.org/article/f8a547ac993e41ceaa7fcb592694d4762021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-01283-6https://doaj.org/toc/2045-2322Abstract Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of drug resistant strains. Bacillus Calmette–Guerin (BCG) is the only licensed attenuated vaccine available for use in humans however, many countries have stopped its use as it fails to confer protective immunity. Therefore, urgent efforts are required to identify new and safe vaccine candidates that are not only provide high immune protection but also have broad spectrum applicability. Considering this, herein, I performed an extensive computational vaccine analysis to investigate 200 complete sequenced genomes of M. tuberculosis to identify core vaccine candidates that harbor safe, antigenic, non-toxic, and non-allergic epitopes. To overcome literature reported limitations of epitope-based vaccines, I carried out additional analysis by designing a multi-epitopes vaccine to achieve maximum protective immunity as well as to make experimental follow up studies easy by selecting a vaccine that can be easily analyzed because of its favorable physiochemical profile. Based on these analyses, I identified two potential vaccine proteins that fulfill all required vaccine properties. These two vaccine proteins are diacylglycerol acyltransferase and ESAT-6-like protein. Epitopes: DSGGYNANS from diacylglycerol acyltransferase and AGVQYSRAD, ADEEQQQAL, and VSRADEEQQ from ESAT-6-like protein were found to cover all necessary parameters and thus used in a multi-epitope vaccine construct. The designed vaccine is depicting a high binding affinity for different immune receptors and shows stable dynamics and rigorous van der Waals and electrostatic binding energies. The vaccine also simulates profound primary, secondary, tertiary immunoglobulin production as well as high interleukins and interferons count. In summary, the designed vaccine is ideal to be evaluated experimentally to decipher its real biological efficacy in controlling drug resistant infections of M. tuberculosis.Aqel AlbuttiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Aqel Albutti An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
description	Abstract Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of drug resistant strains. Bacillus Calmette–Guerin (BCG) is the only licensed attenuated vaccine available for use in humans however, many countries have stopped its use as it fails to confer protective immunity. Therefore, urgent efforts are required to identify new and safe vaccine candidates that are not only provide high immune protection but also have broad spectrum applicability. Considering this, herein, I performed an extensive computational vaccine analysis to investigate 200 complete sequenced genomes of M. tuberculosis to identify core vaccine candidates that harbor safe, antigenic, non-toxic, and non-allergic epitopes. To overcome literature reported limitations of epitope-based vaccines, I carried out additional analysis by designing a multi-epitopes vaccine to achieve maximum protective immunity as well as to make experimental follow up studies easy by selecting a vaccine that can be easily analyzed because of its favorable physiochemical profile. Based on these analyses, I identified two potential vaccine proteins that fulfill all required vaccine properties. These two vaccine proteins are diacylglycerol acyltransferase and ESAT-6-like protein. Epitopes: DSGGYNANS from diacylglycerol acyltransferase and AGVQYSRAD, ADEEQQQAL, and VSRADEEQQ from ESAT-6-like protein were found to cover all necessary parameters and thus used in a multi-epitope vaccine construct. The designed vaccine is depicting a high binding affinity for different immune receptors and shows stable dynamics and rigorous van der Waals and electrostatic binding energies. The vaccine also simulates profound primary, secondary, tertiary immunoglobulin production as well as high interleukins and interferons count. In summary, the designed vaccine is ideal to be evaluated experimentally to decipher its real biological efficacy in controlling drug resistant infections of M. tuberculosis.
format	article
author	Aqel Albutti
author_facet	Aqel Albutti
author_sort	Aqel Albutti
title	An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
title_short	An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
title_full	An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
title_fullStr	An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
title_full_unstemmed	An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis
title_sort	integrated computational framework to design a multi-epitopes vaccine against mycobacterium tuberculosis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f8a547ac993e41ceaa7fcb592694d476
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An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis

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