Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates
Article
Oluwagbemi, O., Oladipo, E.K., Kolawole, O.M., Oloke, J.K., Adelusi, T.I., Irewolede, B.A., Dairo, E.O, Ayeni, A.E., Kolapo, K.T., Akindiya, O.E., Oluwasegun, J.A., Oluwadara, B.F. and Fatumo, S. 2022. Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates. Computation. 10 (7). https://doi.org/10.3390/computation10070117
Type | Article |
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Title | Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates |
Authors | Oluwagbemi, O., Oladipo, E.K., Kolawole, O.M., Oloke, J.K., Adelusi, T.I., Irewolede, B.A., Dairo, E.O, Ayeni, A.E., Kolapo, K.T., Akindiya, O.E., Oluwasegun, J.A., Oluwadara, B.F. and Fatumo, S. |
Abstract | This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response. |
Keywords | bioinformatics; COVID-19; SARS-CoV-2; immunoinformatic; mRNA; vaccine; modeling; computational |
Sustainable Development Goals | 3 Good health and well-being |
Middlesex University Theme | Health & Wellbeing |
Publisher | MDPI AG |
Journal | Computation |
ISSN | |
Electronic | 2079-3197 |
Publication dates | |
Online | 08 Jul 2022 |
Jul 2022 | |
Publication process dates | |
Submitted | 04 Apr 2022 |
Accepted | 27 Jun 2022 |
Deposited | 12 Apr 2024 |
Output status | Published |
Publisher's version | License File Access Level Open |
Copyright Statement | © 2022 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 (https://creativecommons.org/licenses/by/4.0/). |
Additional information | Correction published on 2 December 2022, see Computation 2022, 10(12), 211. - https://www.mdpi.com/2079-3197/10/12/211 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/computation10070117 |
Web of Science identifier | WOS:000831560000001 |
Related Output | |
Is referenced by | https://doi.org/10.3390/computation10120211 |
Language | English |
https://repository.mdx.ac.uk/item/v2w94
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