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Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants.
Campos, Daniel Melo de Oliveira; Silva, Maria Karolaynne da; Barbosa, Emmanuel Duarte; Leow, Chiuan Yee; Fulco, Umberto Laino; Oliveira, Jonas Ivan Nobre.
  • Campos DMO; Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, 59064-741, Natal/RN, Brazil. Electronic address: danielmelo.biomed@gmail.com.
  • Silva MKD; Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, 59064-741, Natal/RN, Brazil. Electronic address: mkarolaynnesilva@gmail.com.
  • Barbosa ED; Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, 59064-741, Natal/RN, Brazil. Electronic address: emmanuel.baduarte@gmail.com.
  • Leow CY; Universiti Sains Malaysia, Penang, Malaysia. Electronic address: yee.leow@usm.my.
  • Fulco UL; Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, 59064-741, Natal/RN, Brazil. Electronic address: umbertofulco@gmail.com.
  • Oliveira JIN; Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, 59064-741, Natal/RN, Brazil. Electronic address: jonasivan@gmail.com.br.
Comput Biol Chem ; 101: 107754, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2049073
ABSTRACT
The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Comput Biol Chem Journal subject: Biology / Medical Informatics / Chemistry Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Comput Biol Chem Journal subject: Biology / Medical Informatics / Chemistry Year: 2022 Document Type: Article