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10.1155/2020/7079356 http://scihub22266oqcxt.onion/10.1155/2020/7079356 33299503!7686850!33299503     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       Can+J+Infect+Dis+Med+Microbiol 2020 ; 2020 (ä): 7079356 Nephropedia Template TP {{tp|p=33299503|t=2020. An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2 |pdf=|usr=}}{{33299503}} gab.com Text An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2 JO: Can J Infect Dis Med Microbiol http://www.kidney.de/pget.php?&tw=1&pmid=33299503 #FOAvip COVID-19 is a new viral emergent disease caused by a novel strain of coronavirus. This virus has caused a huge problem in the world as millions of people are affected by this disease. We aimed at designing a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system. The envelope protein sequence of SARS-CoV-2 has been retrieved from the NCBI database. The bioinformatics analysis was carried out by using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. The predicted HTL and CTL epitopes were docked with HLA alleles and binding energies were evaluated. The allergenicity of predicted epitopes was analyzed, the conservancy analysis was performed, and the population coverage was determined throughout the world. Some overlapped CTL, HTL, and B-cell epitopes were suggested to become a universal candidate for peptide-based vaccine against COVID-19. This vaccine peptide could simultaneously elicit humoral and cell-mediated immune responses. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate. Twit Text FOAVip An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2 ????Can J Infect Dis Med Microbiol http://www.kidney.de/pget.php?&tw=1&pmid=33299503 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33299503 #FOAvip English Wikipedia <ref>{{Cite pmid|33299503}}</ref> An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2 #MMPMID33299503 Jakhar R; Gakhar SK Can J Infect Dis Med Microbiol 2020[]; 2020 (ä): 7079356 PMID33299503show ga COVID-19 is a new viral emergent disease caused by a novel strain of coronavirus. This virus has caused a huge problem in the world as millions of people are affected by this disease. We aimed at designing a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system. The envelope protein sequence of SARS-CoV-2 has been retrieved from the NCBI database. The bioinformatics analysis was carried out by using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. The predicted HTL and CTL epitopes were docked with HLA alleles and binding energies were evaluated. The allergenicity of predicted epitopes was analyzed, the conservancy analysis was performed, and the population coverage was determined throughout the world. Some overlapped CTL, HTL, and B-cell epitopes were suggested to become a universal candidate for peptide-based vaccine against COVID-19. This vaccine peptide could simultaneously elicit humoral and cell-mediated immune responses. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate. äAn Immunoinformatics Study to Predict Epitopes in the Envelope Protein(epmc).pdf DeepDyve Pubget Overpricing