Vibhisha Vaghasia, Kumari Snehkant Lata, Saumya Patel, Jayashankar Das
{"title":"用于鉴定针对钩端螺旋体病的潜在交叉反应肽的表位定位。","authors":"Vibhisha Vaghasia, Kumari Snehkant Lata, Saumya Patel, Jayashankar Das","doi":"10.1080/07391102.2023.2279285","DOIUrl":null,"url":null,"abstract":"<p><p><i>Leptospira</i>, the pathogenic helical spirochetes that cause leptospirosis, is an emerging zoonotic disease with effective dissemination tactics in the host and can infect humans and animals with moderate or severe illnesses. Thus, peptide-based vaccines may be the most effective strategy to manage the immune response against <i>Leptospira</i> to close these gaps. In the current investigation, highly immunogenic proteins from the proteome of <i>Leptospira interorgan</i> serogroup Icterohaemorrhagie serovar Lai strain 56601 were identified using immunoinformatic methods. It was discovered that the conserved and most immunogenic outer membrane Lepin protein was both antigenic and non-allergenic by testing 15 linear B-cells and the ten best T-cell (Helper-lymphocyte (HTL) with the most significant number of HLA-DR binding alleles and the eight cytotoxic T lymphocyte (CTL)) epitopes. Furthermore, a 3D structural model of CTL epitopes was created using the Pep-Fold3 platform. Using the Autodock 4.2 docking server, research was conducted to determine how well the top-ranked CTL peptide models attach to HLA-A*0201 (PDB ID: 4U6Y). With HLA-A*0201, the epitope SSGTGNLHV binds with a binding energy of -1.29 kcal/mol. Utilizing molecular dynamics modeling, the projected epitope-allele docked complex structure was optimized, and the stability of the complex system was assessed. Therefore, this epitope can trigger an immunological response and produce effective <i>Leptospira</i> vaccine candidates. Overall, this study offers a unique vaccination candidate and may encourage additional research into leptospirosis vaccines.Communicated by Ramaswamy H. Sarma.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":" ","pages":"20-35"},"PeriodicalIF":2.4000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Epitopes mapping for identification of potential cross-reactive peptide against leptospirosis.\",\"authors\":\"Vibhisha Vaghasia, Kumari Snehkant Lata, Saumya Patel, Jayashankar Das\",\"doi\":\"10.1080/07391102.2023.2279285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Leptospira</i>, the pathogenic helical spirochetes that cause leptospirosis, is an emerging zoonotic disease with effective dissemination tactics in the host and can infect humans and animals with moderate or severe illnesses. Thus, peptide-based vaccines may be the most effective strategy to manage the immune response against <i>Leptospira</i> to close these gaps. In the current investigation, highly immunogenic proteins from the proteome of <i>Leptospira interorgan</i> serogroup Icterohaemorrhagie serovar Lai strain 56601 were identified using immunoinformatic methods. It was discovered that the conserved and most immunogenic outer membrane Lepin protein was both antigenic and non-allergenic by testing 15 linear B-cells and the ten best T-cell (Helper-lymphocyte (HTL) with the most significant number of HLA-DR binding alleles and the eight cytotoxic T lymphocyte (CTL)) epitopes. Furthermore, a 3D structural model of CTL epitopes was created using the Pep-Fold3 platform. Using the Autodock 4.2 docking server, research was conducted to determine how well the top-ranked CTL peptide models attach to HLA-A*0201 (PDB ID: 4U6Y). With HLA-A*0201, the epitope SSGTGNLHV binds with a binding energy of -1.29 kcal/mol. Utilizing molecular dynamics modeling, the projected epitope-allele docked complex structure was optimized, and the stability of the complex system was assessed. Therefore, this epitope can trigger an immunological response and produce effective <i>Leptospira</i> vaccine candidates. Overall, this study offers a unique vaccination candidate and may encourage additional research into leptospirosis vaccines.Communicated by Ramaswamy H. 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Epitopes mapping for identification of potential cross-reactive peptide against leptospirosis.
Leptospira, the pathogenic helical spirochetes that cause leptospirosis, is an emerging zoonotic disease with effective dissemination tactics in the host and can infect humans and animals with moderate or severe illnesses. Thus, peptide-based vaccines may be the most effective strategy to manage the immune response against Leptospira to close these gaps. In the current investigation, highly immunogenic proteins from the proteome of Leptospira interorgan serogroup Icterohaemorrhagie serovar Lai strain 56601 were identified using immunoinformatic methods. It was discovered that the conserved and most immunogenic outer membrane Lepin protein was both antigenic and non-allergenic by testing 15 linear B-cells and the ten best T-cell (Helper-lymphocyte (HTL) with the most significant number of HLA-DR binding alleles and the eight cytotoxic T lymphocyte (CTL)) epitopes. Furthermore, a 3D structural model of CTL epitopes was created using the Pep-Fold3 platform. Using the Autodock 4.2 docking server, research was conducted to determine how well the top-ranked CTL peptide models attach to HLA-A*0201 (PDB ID: 4U6Y). With HLA-A*0201, the epitope SSGTGNLHV binds with a binding energy of -1.29 kcal/mol. Utilizing molecular dynamics modeling, the projected epitope-allele docked complex structure was optimized, and the stability of the complex system was assessed. Therefore, this epitope can trigger an immunological response and produce effective Leptospira vaccine candidates. Overall, this study offers a unique vaccination candidate and may encourage additional research into leptospirosis vaccines.Communicated by Ramaswamy H. Sarma.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.