Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains

Olugbenga Oluseun Oluwagbemi; Elijah Kolawole Oladipo; Emmanuel Oluwatobi Dairo; Ayodele Eugene Ayeni; Boluwatife Ayobami Irewolede; Esther Moradeyo Jimah; Moyosoluwa Precious Oyewole; Boluwatife Mary Olawale; Hadijat Motunrayo Adegoke; Adewale Joseph Ogunleye

doi:10.1016/j.imu.2022.100845

Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains

Inform Med Unlocked. 2022:28:100845. doi: 10.1016/j.imu.2022.100845. Epub 2022 Jan 15.

Authors

Olugbenga Oluseun Oluwagbemi^{1

2

3}, Elijah Kolawole Oladipo^{4

5}, Emmanuel Oluwatobi Dairo^{6

5}, Ayodele Eugene Ayeni^{5

7}, Boluwatife Ayobami Irewolede⁵, Esther Moradeyo Jimah^{8

5}, Moyosoluwa Precious Oyewole^{9

5}, Boluwatife Mary Olawale^{10

5}, Hadijat Motunrayo Adegoke⁵, Adewale Joseph Ogunleye¹¹

Affiliations

¹ Department of Computer Science and Information Technology, Sol Plaatje University, 8301, Kimberley, South Africa.
² Department of Mathematical Sciences, Stellenbosch University, 7602, Matieland, South Africa.
³ National Institute of Theoretical and Computational Sciences (NiTheCS), South Africa.
⁴ Department of Microbiology, Laboratory of Molecular Biology, Immunology and Bioinformatics, Adeleke University, Ede, Osun State, Nigeria.
⁵ Genomics Unit, Helix Biogen Institute, Ogbomoso, Oyo State, Nigeria.
⁶ Department of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
⁷ Department of Medical Microbiology and Parasitology, Faculty of Basic Medical Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria.
⁸ Department of Medical Microbiology and Parasitology, University of Ilorin, Kwara State, Nigeria.
⁹ Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria.
¹⁰ Reproduction and Bioinformatics Unit, Department of Physiology, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria.
¹¹ Moscow Institute of Physics and Technology, 141701, Dolgoprudny, Moscow Oblast, Russian Federation.

Abstract

The discovery of a new SARS-CoV-2 virus strain in South Africa presents a major public health threat, therefore contributing to increased infections and transmission rates during the second wave of the global pandemic. This study lays the groundwork for the development of a novel subunit vaccine candidate from the circulating strains of South African SARS-CoV-2 and provides an understanding of the molecular epidemiological trend of the circulating strains. A total of 475 whole-genome nucleotide sequences from South Africa submitted between December 1, 2020 and February 15, 2021 available at the GISAID database were retrieved based on its size, coverage level and hosts. To obtain the distribution of the clades and lineages of South African SARS-CoV-2 circulating strains, the metadata of the sequence retrieved were subjected to an epidemiological analysis. There was a prediction of the cytotoxic T lymphocytes (CTL), Helper T cells (HTL) and B-cell epitopes. Furthermore, there was allergenicity, antigenicity and toxicity predictions on the epitopes. The analysis of the physicochemical properties of the vaccine construct was performed; the secondary structure, tertiary structure and B-cell 3D conformational structure of the vaccine construct were predicted. Also, molecular binding simulations and dynamics simulations were adopted in the prediction of the vaccine construct's stability and binding affinity with TLRs. Result obtained from the metadata analysis indicated lineage B.1.351 to be in higher circulation among various circulating strains of SARS-CoV-2 in South Africa and GH has the highest number of circulating clades. The construct of the novel vaccine was antigenic, non-allergenic and non-toxic. The Instability index (II) score and aliphatic index were estimated as 41.74 and 78.72 respectively. The computed half-life in mammalian reticulocytes was 4.4 h in vitro, for yeast and in E. coli was >20 h and >10 h in vivo respectively. The grand average of hydropathicity (GRAVY) score is estimated to be -0.129, signifying the hydrophilic nature of the protein. The molecular docking indicates that the vaccine construct has a high binding affinity towards the TLRs with TLR 3 having the highest binding energy (-1203.2 kcal/mol) and TLR 9 with the lowest (-1559.5 kcal/mol). These results show that the vaccine construct is promising and should be evaluated using animal model.

Keywords: Bioinformatics; COVID-19; Computational construction; Control; SARS-CoV-2 virus; South Africa; Vaccine candidate.