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10.1155/2021/1596834 http://scihub22266oqcxt.onion/10.1155/2021/1596834 33728324!7910514!33728324     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 294.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 294.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 294.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 294.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biomed+Res+Int 2021 ; 2021 (ä): 1596834 Nephropedia Template TP {{tp|p=33728324|t=2021. Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening |pdf=|usr=}}{{33728324}} gab.com Text Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening JO: Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=33728324 #FOAvip BACKGROUND: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. METHODS: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. RESULTS: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. CONCLUSION: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2. Twit Text FOAVip Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening ????Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=33728324 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33728324 #FOAvip English Wikipedia <ref>{{Cite pmid|33728324}}</ref> Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening #MMPMID33728324 Waqas M; Haider A; Rehman A; Qasim M; Umar A; Sufyan M; Akram HN; Mir A; Razzaq R; Rasool D; Tahir RA; Sehgal SA Biomed Res Int 2021[]; 2021 (ä): 1596834 PMID33728324show ga BACKGROUND: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. METHODS: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. RESULTS: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. CONCLUSION: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2. |Amino Acid Sequence[MESH] |COVID-19 Vaccines/*immunology[MESH] |COVID-19/*immunology[MESH] |Epitopes, B-Lymphocyte/immunology[MESH] |Epitopes, T-Lymphocyte/immunology[MESH] |Humans[MESH] |Immunogenicity, Vaccine/*immunology[MESH] |Molecular Docking Simulation/methods[MESH] |SARS-CoV-2/*immunology[MESH]Immunoinformatics and Molecular Docking Studies Predicted Potential M(epmc).pdf DeepDyve Pubget Overpricing