tetano
Editor, Senior Moderator
Bioinformatics
. 2021 May 27;btab406.
doi: 10.1093/bioinformatics/btab406. Online ahead of print.
Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and greater coronavirus family
Chen Wang[SUP] 1 [/SUP], Daniel M Konecki[SUP] 2 [/SUP], David C Marciano[SUP] 1 [/SUP], Harikumar Govindarajan[SUP] 1 [/SUP], Amanda M Williams[SUP] 3 [/SUP], Brigitta Wastuwidyaningtyas[SUP] 1 [/SUP], Thomas Bourquard[SUP] 1 4 [/SUP], Panagiotis Katsonis[SUP] 1 [/SUP], Olivier Lichtarge[SUP] 1 2 3 5 [/SUP]
Affiliations
Abstract
Motivation: Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family.
Results: Combining coronavirus family sequence information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally-validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent.
Availability: The results of this work are made interactively available at http://cov.lichtargelab.org.
Supplementary information: Supplementary data are available at Bioinformatics online.
. 2021 May 27;btab406.
doi: 10.1093/bioinformatics/btab406. Online ahead of print.
Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and greater coronavirus family
Chen Wang[SUP] 1 [/SUP], Daniel M Konecki[SUP] 2 [/SUP], David C Marciano[SUP] 1 [/SUP], Harikumar Govindarajan[SUP] 1 [/SUP], Amanda M Williams[SUP] 3 [/SUP], Brigitta Wastuwidyaningtyas[SUP] 1 [/SUP], Thomas Bourquard[SUP] 1 4 [/SUP], Panagiotis Katsonis[SUP] 1 [/SUP], Olivier Lichtarge[SUP] 1 2 3 5 [/SUP]
Affiliations
- PMID: 34043002
- DOI: 10.1093/bioinformatics/btab406
Abstract
Motivation: Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family.
Results: Combining coronavirus family sequence information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally-validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent.
Availability: The results of this work are made interactively available at http://cov.lichtargelab.org.
Supplementary information: Supplementary data are available at Bioinformatics online.