tetano
Editor, Senior Moderator
Infect Disord Drug Targets
. 2020 Sep 21.
doi: 10.2174/1871526520666200921154149. Online ahead of print.
Immuno-Informatics Quest against COVID-19/SARS-COV-2: Determining Putative T-Cell Epitopes for Vaccine Prediction
Nahid Akhtar[SUP] 1 [/SUP], Amit Joshi[SUP] 1 [/SUP], Bhupender Singh[SUP] 1 [/SUP], Vikas Kaushik[SUP] 1 [/SUP]
Affiliations
Abstract
Background: Since, December 2019 a novel coronavirus, SARS-CoV-2 has caused global public health issue after being reported for the first time in Wuhan province of China. So far, there have been approximately 14.8 million confirmed cases and 0.614 million deaths due to the SARS-CoV-2 infection globally, and still numbers are increasing. Although, the virus has caused a global public health concern, no effective treatment has been developed.
Objective: One of the strategies to combat the COVID-19 disease caused by SARS-CoV-2 is development of vaccines that can make humans immune to these infections. Considering this approach, in this study an attempt has been made to design epitope based vaccine for combatting COVID-19 disease by analyzing the complete proteome of the virus by using immuno-informatics tools.
Methods: The protein sequence of the SARS-CoV-2 was retrieved and the individual proteins were checked for their allergic potential. Then, from non-allergen proteins antigenic epitopes were identified that could bind with MHCII molecules. The epitopes were modeled and docked to predict the interaction with MHCII molecules. The stability of the epitopeMHCII complex was further analyzed by performing molecular dynamic simulation study. The selected vaccine candidates were also analyzed for their global population coverage and conservancy among SARS related coronavirus species.
Results: The study has predicted 5 peptide molecules that can act as potential candidate for epitope based vaccine development. Among the 5 selected epitopes, the peptide LRARSVSPK can be the most potent epitope because of its high geometric shape complementarity score, low ACE and very high response to it by the world population (81.81% global population coverage). Further, molecular dynamic simulation analysis indicated the formation of stable epitope-MHCII complex. The epitope LRARSVSPK was also found to be highly conserved among the SARS-CoV-2 isolated from different countries.
Conclusion: The study has predicted T-cell epitopes that can elicit robust immune response in global human population and act as potential vaccine candidates. However, the ability of these epitopes to act as vaccine candidate needs to be validated in wet lab studies.
Keywords: COVID-19; Coronavirus; Docking; Epitope; MHC class II; Simulation; Vaccines.
. 2020 Sep 21.
doi: 10.2174/1871526520666200921154149. Online ahead of print.
Immuno-Informatics Quest against COVID-19/SARS-COV-2: Determining Putative T-Cell Epitopes for Vaccine Prediction
Nahid Akhtar[SUP] 1 [/SUP], Amit Joshi[SUP] 1 [/SUP], Bhupender Singh[SUP] 1 [/SUP], Vikas Kaushik[SUP] 1 [/SUP]
Affiliations
- PMID: 32957905
- DOI: 10.2174/1871526520666200921154149
Abstract
Background: Since, December 2019 a novel coronavirus, SARS-CoV-2 has caused global public health issue after being reported for the first time in Wuhan province of China. So far, there have been approximately 14.8 million confirmed cases and 0.614 million deaths due to the SARS-CoV-2 infection globally, and still numbers are increasing. Although, the virus has caused a global public health concern, no effective treatment has been developed.
Objective: One of the strategies to combat the COVID-19 disease caused by SARS-CoV-2 is development of vaccines that can make humans immune to these infections. Considering this approach, in this study an attempt has been made to design epitope based vaccine for combatting COVID-19 disease by analyzing the complete proteome of the virus by using immuno-informatics tools.
Methods: The protein sequence of the SARS-CoV-2 was retrieved and the individual proteins were checked for their allergic potential. Then, from non-allergen proteins antigenic epitopes were identified that could bind with MHCII molecules. The epitopes were modeled and docked to predict the interaction with MHCII molecules. The stability of the epitopeMHCII complex was further analyzed by performing molecular dynamic simulation study. The selected vaccine candidates were also analyzed for their global population coverage and conservancy among SARS related coronavirus species.
Results: The study has predicted 5 peptide molecules that can act as potential candidate for epitope based vaccine development. Among the 5 selected epitopes, the peptide LRARSVSPK can be the most potent epitope because of its high geometric shape complementarity score, low ACE and very high response to it by the world population (81.81% global population coverage). Further, molecular dynamic simulation analysis indicated the formation of stable epitope-MHCII complex. The epitope LRARSVSPK was also found to be highly conserved among the SARS-CoV-2 isolated from different countries.
Conclusion: The study has predicted T-cell epitopes that can elicit robust immune response in global human population and act as potential vaccine candidates. However, the ability of these epitopes to act as vaccine candidate needs to be validated in wet lab studies.
Keywords: COVID-19; Coronavirus; Docking; Epitope; MHC class II; Simulation; Vaccines.