tetano
Editor, Senior Moderator
PLoS One
. 2020 Dec 22;15(12):e0244176.
doi: 10.1371/journal.pone.0244176. eCollection 2020.
Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches
Muhammad Tahir Ul Qamar[SUP] 1 [/SUP], Abdur Rehman[SUP] 2 [/SUP], Kishver Tusleem[SUP] 3 [/SUP], Usman Ali Ashfaq[SUP] 2 [/SUP], Muhammad Qasim[SUP] 2 [/SUP], Xitong Zhu[SUP] 4 [/SUP], Israr Fatima[SUP] 2 [/SUP], Farah Shahid[SUP] 2 [/SUP], Ling-Ling Chen[SUP] 1 4 [/SUP]
Affiliations
Abstract
Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.
. 2020 Dec 22;15(12):e0244176.
doi: 10.1371/journal.pone.0244176. eCollection 2020.
Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches
Muhammad Tahir Ul Qamar[SUP] 1 [/SUP], Abdur Rehman[SUP] 2 [/SUP], Kishver Tusleem[SUP] 3 [/SUP], Usman Ali Ashfaq[SUP] 2 [/SUP], Muhammad Qasim[SUP] 2 [/SUP], Xitong Zhu[SUP] 4 [/SUP], Israr Fatima[SUP] 2 [/SUP], Farah Shahid[SUP] 2 [/SUP], Ling-Ling Chen[SUP] 1 4 [/SUP]
Affiliations
- PMID: 33351863
- DOI: 10.1371/journal.pone.0244176
Abstract
Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.