Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach
Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap b...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1364129/full |
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| author | Tajul Islam Mamun Tajul Islam Mamun Md. Ahad Ali Md. Nazmul Hosen Jillur Rahman Md. Anwarul Islam Md. Golam Akib Kamruz Zaman Md. Masudur Rahman Md. Masudur Rahman Ferdaus Mohd Altaf Hossain Ferdaus Mohd Altaf Hossain Samir Ibenmoussa Mohammed Bourhia Turki M. Dawoud |
| author_facet | Tajul Islam Mamun Tajul Islam Mamun Md. Ahad Ali Md. Nazmul Hosen Jillur Rahman Md. Anwarul Islam Md. Golam Akib Kamruz Zaman Md. Masudur Rahman Md. Masudur Rahman Ferdaus Mohd Altaf Hossain Ferdaus Mohd Altaf Hossain Samir Ibenmoussa Mohammed Bourhia Turki M. Dawoud |
| author_sort | Tajul Islam Mamun |
| collection | DOAJ |
| description | Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in E. coli, with a Codon Adaptation Index of 0.99 and GC content of 54.58%. The minimum free energy of the RNA secondary structure was -494.90 kcal/mol. While our findings suggest the potential effectiveness of the designed vaccine candidate against HRV-C, further in vitro and in vivo investigations are warranted to validate its safety and efficacy. |
| format | Article |
| id | doaj-art-95a664a6ab5c4b2abc261bbd0ebefd51 |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-95a664a6ab5c4b2abc261bbd0ebefd512025-08-20T02:43:45ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-01-011510.3389/fimmu.2024.13641291364129Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approachTajul Islam Mamun0Tajul Islam Mamun1Md. Ahad Ali2Md. Nazmul Hosen3Jillur Rahman4Md. Anwarul Islam5Md. Golam Akib6Kamruz Zaman7Md. Masudur Rahman8Md. Masudur Rahman9Ferdaus Mohd Altaf Hossain10Ferdaus Mohd Altaf Hossain11Samir Ibenmoussa12Mohammed Bourhia13Turki M. Dawoud14Department of Epidemiology and Public Health, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshDepartment Of Chemistry, University of Rajshahi, Rajshahi, BangladeshDepartment of Pharmacology and Toxicology, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshDepartment of Pathology, Sylhet Agricultural University, Sylhet, BangladeshFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, BangladeshDepartment of Dairy Science, Sylhet Agricultural University, Sylhet, BangladeshLaboratory of Therapeutic and Organic Chemistry, Faculty of Pharmacy, University of Montpellier, Montpellier, FranceDepartment of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, Laayoune, MoroccoDepartment of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi ArabiaHuman rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in E. coli, with a Codon Adaptation Index of 0.99 and GC content of 54.58%. The minimum free energy of the RNA secondary structure was -494.90 kcal/mol. While our findings suggest the potential effectiveness of the designed vaccine candidate against HRV-C, further in vitro and in vivo investigations are warranted to validate its safety and efficacy.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1364129/fullhuman rhinovirus Cmulti-epitope vaccineepitope predictionreverse vaccinologyimmunoinformatics |
| spellingShingle | Tajul Islam Mamun Tajul Islam Mamun Md. Ahad Ali Md. Nazmul Hosen Jillur Rahman Md. Anwarul Islam Md. Golam Akib Kamruz Zaman Md. Masudur Rahman Md. Masudur Rahman Ferdaus Mohd Altaf Hossain Ferdaus Mohd Altaf Hossain Samir Ibenmoussa Mohammed Bourhia Turki M. Dawoud Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach Frontiers in Immunology human rhinovirus C multi-epitope vaccine epitope prediction reverse vaccinology immunoinformatics |
| title | Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach |
| title_full | Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach |
| title_fullStr | Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach |
| title_full_unstemmed | Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach |
| title_short | Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach |
| title_sort | designing a multi epitope vaccine candidate against human rhinovirus c utilizing immunoinformatics approach |
| topic | human rhinovirus C multi-epitope vaccine epitope prediction reverse vaccinology immunoinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1364129/full |
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