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10.1038/s41598-020-70864-8 http://scihub22266oqcxt.onion/10.1038/s41598-020-70864-8 32843695!7447814!32843695     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2020 ; 10 (1): 14179 Nephropedia Template TP {{tp|p=32843695|t=2020. Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome |pdf=|usr=}}{{32843695}} gab.com Text Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=32843695 #FOAvip A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development. Twit Text FOAVip Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=32843695 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32843695 #FOAvip English Wikipedia <ref>{{Cite pmid|32843695}}</ref> Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome #MMPMID32843695 Crooke SN; Ovsyannikova IG; Kennedy RB; Poland GA Sci Rep 2020[Aug]; 10 (1): 14179 PMID32843695show ga A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development. |*Computational Biology/methods[MESH] |Amino Acid Sequence[MESH] |B-Lymphocytes/immunology/metabolism[MESH] |Betacoronavirus/classification/genetics/*immunology/metabolism[MESH] |COVID-19[MESH] |Coronavirus Infections/*immunology/metabolism/*virology[MESH] |Epitopes, B-Lymphocyte/chemistry/*immunology[MESH] |Epitopes, T-Lymphocyte/chemistry/*immunology[MESH] |Genome, Viral[MESH] |Genomics/methods[MESH] |Host-Pathogen Interactions/*immunology[MESH] |Humans[MESH] |Models, Molecular[MESH] |Pandemics[MESH] |Peptides/chemistry/immunology[MESH] |Phylogeny[MESH] |Pneumonia, Viral/*immunology/metabolism/*virology[MESH] |SARS-CoV-2[MESH] |Structure-Activity Relationship[MESH] |T-Lymphocytes/immunology/metabolism[MESH] |Vaccines, Subunit/immunology[MESH] |Viral Proteins/chemistry/*immunology[MESH]Immunoinformatic identification of B cell and T cell epitopes in the S(epmc).pdf DeepDyve Pubget Overpricing