References
-
Panda, S., Mohakud, N. K., Pena, L. & Kumar, S. Human metapneumovirus: review of an important respiratory pathogen. Int. J. Infect. Dis. 25, 45–52 (2014).
-
Piñana, M. et al. The emergence, impact, and evolution of human metapneumovirus variants from 2014 to 2021 in Spain. J. Infect. 87 (2), 103–110. https://doi.org/10.1016/j.jinf.2023.05.004 (2023).
-
Samuel, S., Nanjappa, S., Cooper, C. D. & Greene, J. N. Human metapneumovirus infection in immunocompromised patients. Cancer Control. 23 (4), 442–445 (2016).
-
Devanathan, N. et al. Emerging lineages A2.2.1 and A2.2.2 of human metapneumovirus (hMPV) in pediatric respiratory infections: insights from India. IJID Reg. 14, 100486. https://doi.org/10.1016/j.ijregi.2024.100486 (2025).
-
Costa-Filho, R. C., Saddy, F., Costa, J. L. F., Tavares, L. R. & Castro Faria Neto, H. C. The silent threat of human metapneumovirus: clinical challenges and diagnostic insights from a severe pneumonia case. Microorganisms 13 (1), 73 (2025).
-
Biacchesi, S. et al. Recombinant human metapneumovirus lacking the small hydrophobic SH and/or attachment G glycoprotein: deletion of G yields a promising vaccine candidate. J. Virol. 78 (23), 12877–12887 (2004).
-
Van den Hoogen, B. G. et al. A newly discovered human Pneumovirus isolated from young children with respiratory tract disease. Nat. Med. 7 (6), 719–724 (2001).
-
Wang, X. et al. Global burden of acute lower respiratory infection associated with human metapneumovirus in children under 5 years in 2018: a systematic review and modelling study. Lancet Global Health. 9 (1), e33–e43 (2021).
-
Dubois, J. et al. Strain-dependent impact of G and SH deletions provide new insights for live-attenuated HMPV vaccine development. Vaccines 7 (4), 164 (2019).
-
Hsieh, C. L. et al. Structure-based design of prefusion-stabilized human metapneumovirus fusion proteins. Nat. Commun. 13 (1), 1299 (2022).
-
Bakkers, M. J. et al. Efficacious human metapneumovirus vaccine based on AI-guided engineering of a closed prefusion trimer. Nat. Commun. 15 (1), 6270 (2024).
-
Shahda, S., Carlos, W., Kiel, P., Khan, B. & Hage, C. The human metapneumovirus: a case series and review of the literature. Transpl. Infect. Disease. 13 (3), 324–328 (2011).
-
van den Hoogen, B. G., Bestebroer, T. M., Osterhaus, A. D. & Fouchier, R. A. Analysis of the genomic sequence of a human metapneumovirus. Virology 295 (1), 119–132 (2002).
-
Piyaratna, R., Tollefson, S. J. & Williams, J. V. Genomic analysis of four human metapneumovirus prototypes. Virus Res. 160 (1–2), 200–205 (2011).
-
Andrade, C. A. et al. Innate immune components that regulate the pathogenesis and resolution of hRSV and hMPV infections. Viruses 12 (6), 637 (2020).
-
Wilson, R. L. et al. Function of small hydrophobic proteins of paramyxovirus. J. Virol. 80 (4), 1700–1709 (2006).
-
Huang, J., Miller, R. J. & Mousa, J. J. A Pan-Pneumovirus vaccine based on immunodominant epitopes of the fusion protein. Front. Immunol. 13, 941865 (2022).
-
Herfst, S. & Fouchier, R. A. Vaccination approaches to combat human metapneumovirus lower respiratory tract infections. J. Clin. Virol. 41 (1), 49–52 (2008).
-
Liu, L. Molecular biology of human metapneumovirus (HMPV) attachment protein. (2008).
-
Pardi, N., Hogan, M. J., Porter, F. W. & Weissman, D. mRNA vaccines—a new era in vaccinology. Nat. Rev. Drug Discovery. 17 (4), 261–279 (2018).
-
Adam, K. M. Immunoinformatics approach for multi-epitope vaccine design against structural proteins and ORF1a polyprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Trop. Dis. Travel Med. Vaccines. 7, 1–13 (2021).
-
Lim, H. X., Lim, J., Jazayeri, S. D., Poppema, S. & Poh, C. L. Development of multi-epitope peptide-based vaccines against SARS-CoV-2. Biomedical J. 44 (1), 18–30 (2021).
-
Awasthi, A., Sharma, G. & Agrawal, P. Computational approaches for vaccine designing. In Bioinformatics; Elsevier: ; pp. 317–335. (2022).
-
Brister, J. R., Ako-adjei, D., Bao, Y. & Blinkova, O. N. C. B. I. Viral genomes resource. Nucleic Acids Res. 43 (D1), D571–D577. https://doi.org/10.1093/nar/gku1207 (2014).
-
Rencilin, C. F., Rosy, J. C., Mohan, M., Coico, R. & Sundar, K. Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19. Infect. Genet. Evol. 89, 104712. https://doi.org/10.1016/j.meegid.2021.104712 (2021).
-
Salod, Z. & Mahomed, O. Mapping potential vaccine candidates predicted by VaxiJen for different viral pathogens between 2017–2021—A scoping review. Vaccines 10 (11), 1785 (2022).
-
Huang, Y., Niu, B., Gao, Y., Fu, L. & Li, W. CD-HIT suite: a web server for clustering and comparing biological sequences. Bioinformatics 26 (5), 680–682 (2010).
-
Saha, S. & Raghava, G. P. S. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins Struct. Funct. Bioinform. 65 (1), 40–48 (2006).
-
Rouzbahani, A. K., Kheirandish, F. & Hosseini, S. Z. Design of a multi-epitope-based peptide vaccine against the S and N proteins of SARS-COV-2 using immunoinformatics approach. Egypt. J. Med. Hum. Genet. 23 (1), 16 (2022).
-
Fleri, W. et al. The immune epitope database and analysis resource in epitope discovery and synthetic vaccine design. Front. Immunol. 8, 278 (2017).
-
Kakakhel, S. et al. Annotation of potential vaccine targets and designing of mRNA-Based Multi-Epitope vaccine against lumpy skin disease virus via reverse vaccinology and Agent-Based modeling. Bioeng. (Basel). 10 (4). https://doi.org/10.3390/bioengineering10040430 (2023).
-
Khan, K., Khan, S. A., Jalal, K., Ul-Haq, Z. & Uddin, R. Immunoinformatic approach for the construction of multi-epitopes vaccine against Omicron COVID-19 variant. Virology 572, 28–43 (2022).
-
Dhanda, S. K., Vir, P. & Raghava, G. P. Designing of interferon-gamma inducing MHC class-II binders. Biol. Direct. 8, 1–15 (2013).
-
Dhanda, S. K., Gupta, S., Vir, P. & Raghava, G. P. Prediction of IL4 inducing peptides. Clin. Dev. Immunol. 2013 (263952). https://doi.org/10.1155/2013/263952 (2013).
-
Doytchinova, I. A. & Flower, D. R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 8 (4). https://doi.org/10.1186/1471-2105-8-4 (2007).
-
Elfadil, M. M. et al. Reverse vaccinology and immunoinformatics approaches for multi-epitope vaccine design against Klebsiella pneumoniae reveal a novel vaccine target protein. J. Genetic Eng. Biotechnol. 23 (3), 100510. https://doi.org/10.1016/j.jgeb.2025.100510 (2025).
-
Gupta, S. et al. In Silico approach for predicting toxicity of peptides and proteins. PloS One. 8 (9), e73957 (2013).
-
Hon, J. et al. SoluProt: prediction of soluble protein expression in Escherichia coli. Bioinformatics 37 (1), 23–28 (2021).
-
Dimitrov, I., Flower, D. R. & Doytchinova, I. AllerTOP–a server for in Silico prediction of allergens. BMC Bioinform. 14 Suppl 6 (Suppl 6), S4. https://doi.org/10.1186/1471-2105-14-s6-s4 (2013).
-
Bui, H. H. et al. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinform. 7, 1–5 (2006).
-
Fadaka, A. O. et al. Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus. Sci. Rep. 11 (1), 19707 (2021).
-
Kottarathil, A. et al. Designing multi-epitope-based vaccine targeting Immunogenic proteins of Streptococcus mutans using immunoinformatics to prevent caries. Microbe 7, 100320. https://doi.org/10.1016/j.microb.2025.100320 (2025).
-
Tarrahimofrad, H., Rahimnahal, S., Zamani, J., Jahangirian, E. & Aminzadeh, S. Designing a multi-epitope vaccine to provoke the robust immune response against influenza A H7N9. Sci. Rep. 11 (1), 24485 (2021).
-
Khan, M. T. et al. Immunoinformatics and molecular dynamics approaches: next generation vaccine design against West nile virus. Plos One. 16 (6), e0253393 (2021).
-
Kozak, M. Point mutations define a sequence flanking the AUG initiator codon that modulates translation by eukaryotic ribosomes. Cell 44 (2), 283–292 (1986).
-
Liu, Q. Comparative analysis of base biases around the stop codons in six eukaryotes. Biosystems 81 (3), 281–289 (2005).
-
Ahammad, I. & Lira, S. S. Designing a novel mRNA vaccine against SARS-CoV-2: an immunoinformatics approach. Int. J. Biol. Macromol. 162, 820–837 (2020).
-
Kreiter, S. et al. Increased antigen presentation efficiency by coupling antigens to MHC class I trafficking signals. J. Immunol. 180 (1), 309–318 (2008).
-
Gallie, D. R. The cap and Poly (A) tail function synergistically to regulate mRNA translational efficiency. Genes Dev. 5 (11), 2108–2116 (1991).
-
Munroe, D. & Jacobson, A. mRNA Poly (A) tail, a 3′ enhancer of translational initiation. Mol. Cell. Biol. 10 (7), 3441–3455 (1990).
-
Bernstein, P. & Ross, J. Poly (A), Poly (A) binding protein and the regulation of mRNA stability. Trends Biochem. Sci. 14 (9), 373–377 (1989).
-
Zhao, Y. et al. Multiple injections of electroporated autologous T cells expressing a chimeric antigen receptor mediate regression of human disseminated tumor. Cancer Res. 70 (22), 9053–9061 (2010).
-
Holtkamp, S. et al. Modification of antigen-encoding RNA increases stability, translational efficacy, and T-cell stimulatory capacity of dendritic cells. Blood 108 (13), 4009–4017 (2006).
-
Pourseif, M. M. et al. A domain-based vaccine construct against SARS-CoV-2, the causative agent of COVID-19 pandemic: development of self-amplifying mRNA and peptide vaccines. BioImpacts: BI. 11 (1), 65 (2020).
-
Wang, Z., Day, N., Trifillis, P. & Kiledjian, M. An mRNA stability complex functions with Poly (A)-binding protein to stabilize mRNA in vitro. Mol. Cell. Biol. 19 (7), 4552–4560 (1999).
-
Priyadarsini, S. et al. In Silico structural delineation of nucleocapsid protein of SARS-CoV-2. J. Entomol. Zool. Stud. 8 (2), 06–10 (2020).
-
Buchan, D. W. & Jones, D. T. The PSIPRED protein analysis workbench: 20 years on. Nucleic Acids Res. 47 (W1), W402–W407 (2019).
-
Gruber, A. R., Lorenz, R., Bernhart, S. H., Neuböck, R. & Hofacker, I. L. The Vienna RNA websuite. Nucleic Acids Res. 36 (suppl_2), W70–W74 (2008).
-
Lorenz, R. et al. ViennaRNA package 2.0. Algorithms Mol. Biology. 6, 1–14 (2011).
-
Kim, D. E., Chivian, D. & Baker, D. Protein structure prediction and analysis using the Robetta server. Nucleic Acids Res. 32 (suppl_2), W526–W531 (2004).
-
Heo, L., Park, H., Seok, C. & GalaxyRefine Protein structure refinement driven by side-chain repacking. Nucleic Acids Res. 41 (W1), W384–W388 (2013).
-
Wiederstein, M. & Sippl, M. J. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 35 (suppl_2), W407–W410 (2007).
-
Kozakov, D. et al. The cluspro web server for protein–protein Docking. Nat. Protoc. 12 (2), 255–278 (2017).
-
Laskowski, R. A. et al. Structural summaries of PDB entries. Protein Sci. 27 (1), 129–134 (2018).
-
Lopéz-Blanco, J. R., Garzón, J. I. & Chacón, P. iMod: multipurpose normal mode analysis in internal coordinates. Bioinformatics 27 (20), 2843–2850 (2011).
-
López-Blanco, J. R., Aliaga, J. I., Quintana-Ortí, E. S. & Chacón, P. iMODS: internal coordinates normal mode analysis server. Nucleic Acids Res. 42 (W1), W271–W276 (2014).
-
Bai, Y., Zhou, M., Wang, N., Yang, Y. & Wang, D. Designing a candidate multi-epitope vaccine against transmissible gastroenteritis virus based on immunoinformatic and molecular dynamics. Int. J. Mol. Sci. 25 (16), 8828 (2024).
-
Kaur, A. et al. Rational design and computational evaluation of a multi-epitope vaccine for Monkeypox virus: Insights into binding stability and immunological memory. Heliyon 10 (16), e36154. https://doi.org/10.1016/j.heliyon.2024.e36154 (2024).
-
Kutzner, C. et al. V. GROMACS in the cloud: A global supercomputer to speed up alchemical drug design. J. Chem. Inf. Model. 62 (7), 1691–1711 (2022).
-
Alabbas, A. B. Integrativesubtractive proteomics, immunoinformatics, docking, and simulation approaches reveal candidate vaccine against sin Nombre orthohantavirus. Front. Immunol. 13, 1022159 (2022).
-
Grote, A. et al. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Res. 33 (suppl_2), W526–W531 (2005).
-
Fu, H. et al. Codon optimization with deep learning to enhance protein expression. Sci. Rep. 10 (1), 17617 (2020).
-
Khan, N. T., Zinnia, M. A. & Islam, A. B. M. M. K. Modeling mRNA-based vaccine YFV. E1988 against yellow fever virus E-protein using immuno-informatics and reverse vaccinology approach. J. Biomol. Struct. Dynamics. 41 (5), 1617–1638 (2023).
-
Rapin, N., Lund, O., Bernaschi, M. & Castiglione, F. Computational immunology Meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system. PloS One 5(4), e9862. (2010).
-
Aziz, S. et al. Exploring whole proteome to contrive multi-epitope-based vaccine for neocov: an immunoinformtics and in-silico approach. Front. Immunol. 13, 956776 (2022).
-
Castiglione, F., Deb, D., Srivastava, A. P., Liò, P. & Liso, A. From infection to immunity: Understanding the response to SARS-CoV2 through in-silico modeling. Front. Immunol. 12, 646972 (2021).
-
Qiu, J. et al. Integrated in-silico design and in vivo validation of multi-epitope vaccines for Norovirus. Virol. J. 22 (1), 166. https://doi.org/10.1186/s12985-025-02796-6 (2025).
-
Kuang, L. et al. Changes in the epidemiological patterns of respiratory syncytial virus and human metapneumovirus infection among pediatric patients and their correlation with severe cases: a long-term retrospective study. Front. Cell. Infect. Microbiol. 14, 1435294 (2024).
-
Contentin, L., Guillon, A., Garot, D., Gaudy-Graffin, C. & Perrotin, D. Acute respiratory distress syndrome secondary to human metapneumovirus infection in a young healthy adult. Intensive Care Med. 39, 533–534 (2013).
-
Renaud, C. et al. Mortality rates of human metapneumovirus and respiratory syncytial virus lower respiratory tract infections in hematopoietic cell transplantation recipients. Biol. Blood Marrow Transpl. 19 (8), 1220–1226. https://doi.org/10.1016/j.bbmt.2013.05.005 (2013).
-
Kapandji, N. et al. Clinical significance of human metapneumovirus detection in critically ill adults with lower respiratory tract infections. Ann. Intensiv. Care. 13 (1), 21. https://doi.org/10.1186/s13613-023-01117-w (2023).
-
Saeed, M. I. & Minireview Designing next generation human metapneumovirus (HMPV) vaccine. Clin. Exp. Vaccine Res. 14 (2), 116–118. https://doi.org/10.7774/cevr.2025.14.e12 (2025).
-
Schnyder Ghamloush, S. et al. Safety and immunogenicity of an mRNA-Based hMPV/PIV3 combination vaccine in seropositive children. Pediatrics 153 (6). https://doi.org/10.1542/peds.2023-064748 (2024).
-
Lee, Y. Z. et al. Rational design of uncleaved prefusion-closed trimer vaccines for human respiratory syncytial virus and metapneumovirus. Nat. Commun. 15 (1), 9939 (2024).
-
Albaqami, F. F. et al. Tahir Ul Qamar, M. Computational modeling and evaluation of potential mRNA and Peptide-Based vaccine against Marburg virus (MARV) to provide immune protection against hemorrhagic fever. Biomed. Res. Int. 2023 (1), 5560605 (2023).
-
Sahin, U. et al. COVID-19 vaccine BNT162b1 elicits human antibody and TH1 T cell responses. Nature 586 (7830), 594–599. https://doi.org/10.1038/s41586-020-2814-7 (2020).
-
Ong, E., Wong, M. U., Huffman, A. & He, Y. COVID-19 coronavirus vaccine design using reverse vaccinology and machine learning. Front. Immunol. 11, 1581 (2020).
-
Patel, R., Kaki, M., Potluri, V. S., Kahar, P. & Khanna, D. A comprehensive review of SARS-CoV-2 vaccines: Pfizer, moderna & Johnson & Johnson. Hum. Vaccin Immunother. 18 (1), 2002083. https://doi.org/10.1080/21645515.2021.2002083 (2022).
-
Melero, J. A. & Mas, V. The Pneumovirinae fusion (F) protein: A common target for vaccines and antivirals. Virus Res. 209, 128–135 (2015).
-
Ma, S. et al. Development of a novel multi-epitope mRNA vaccine candidate to combat HMPV virus. Hum. Vaccines Immunotherapeutics. 20 (1), 2293300 (2024).
-
Cheemarla, N. R. & Guerrero-Plata, A. Human metapneumovirus attachment protein contributes to neutrophil recruitment into the airways of infected mice. Viruses 9 (10), 310 (2017).
-
Aerts, L. et al. Adjuvant effect of the human metapneumovirus (HMPV) matrix protein in HMPV subunit vaccines. J. Gen. Virol. 96 (4), 767–774 (2015).
-
Zhang, Y. et al. Rational design of human metapneumovirus live attenuated vaccine candidates by inhibiting viral mRNA cap methyltransferase. J. Virol. 88 (19), 11411–11429 (2014).
-
Skiadopoulos, M. H. et al. Individual contributions of the human metapneumovirus F, G, and SH surface glycoproteins to the induction of neutralizing antibodies and protective immunity. Virology 345 (2), 492–501 (2006).
-
Khatrawi, E. M., Luqman Ali, S., Ali, S. Y., Abduldayeva, A. & Mugibel, M. A. A. Robust multiepitope vaccine from glycoproteins against human metapneumovirus genotypes A2a, A2b, and A2c by utilizing immunoinformatics and reverse vaccinology approaches. Viral Immunol. 38 (5), 157–171 (2025).
-
Rahman, M. S. et al. Epitope-based chimeric peptide vaccine design against S, M and E proteins of SARS-CoV-2, the etiologic agent of COVID-19 pandemic: an in Silico approach. PeerJ 8, e9572 (2020).
-
Aram, C., Alijanizadeh, P., Saleki, K. & Karami, L. Development of an ancestral DC and TLR4-inducing multi-epitope peptide vaccine against the Spike protein of SARS-CoV and SARS-CoV-2 using the advanced immunoinformatics approaches. Biochem. Biophys. Rep. 39, 101745 (2024).
-
Dey, J. et al. Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia. Expert Rev. Vaccines. 21 (4), 569–587 (2022).
-
Gasteiger, E. Protein identification and analysis tools on the ExPASy server. The proteomics protocols handbook/Human Press Inc. (2005).
-
Oluwagbemi, O. O. et al. Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates. Computation 10 (7), 117 (2022).
-
Kurt-Jones, E. A. et al. Pattern recognition receptors TLR4 and CD14 mediate response to respiratory syncytial virus. Nat. Immunol. 1 (5), 398–401 (2000).
-
Oladipo, E. K. et al. Exploring computational approaches to design mRNA vaccine against vaccinia and Mpox viruses. Immun. Inflamm. Dis. 12 (8), e1360 (2024).
-
Oladipo, E. K. et al. Utilizing immunoinformatics for mRNA vaccine design against influenza D virus. BioMedInformatics 4 (2), 1572–1588 (2024).
-
Ma, S. et al. Development of a novel multi-epitope mRNA vaccine candidate to combat HMPV virus. Hum. Vaccin Immunother. 19 (3), 2293300. https://doi.org/10.1080/21645515.2023.2293300 (2023).
-
Mohammadi, Y., Nezafat, N., Negahdaripour, M., Eskandari, S. & Zamani, M. In Silico design and evaluation of a novel mRNA vaccine against BK virus: a reverse vaccinology approach. Immunol. Res. 71 (3), 422–441 (2023).
-
Ali, A. et al. Multi-epitope-based vaccine models prioritization against astrovirus MLB1 using immunoinformatics and reverse vaccinology approaches. J. Genetic Eng. Biotechnol. 23 (1), 100451. https://doi.org/10.1016/j.jgeb.2024.100451 (2025).
-
Patel, M. C. et al. Novel drugs targeting Toll-like receptors for antiviral therapy. Future Virol. 9 (9), 811–829 (2014).
-
Ma, S. et al. Development of a novel multi-epitope subunit mRNA vaccine candidate to combat acinetobacter baumannii. Sci. Rep. 15 (1), 1410. https://doi.org/10.1038/s41598-024-84823-0 (2025).
-
Mahafujul Alam, S. S. et al. Immunoinformatics based designing of a multi-epitope cancer vaccine targeting programmed cell death ligand 1. Sci. Rep. 15 (1), 12420. https://doi.org/10.1038/s41598-025-87063-y (2025).
-
Bhattacharya, K. et al. Multi-epitope vaccine design against Monkeypox virus via reverse vaccinology method exploiting immunoinformatic and bioinformatic approaches. Vaccines 10 (12), 2010 (2022).
-
Kesavan, L. R., Kamalan, B. C. & Sivanandan, S. Targeting human inosine 5’monophosphate dehydrogenase type 2 for anti-dengue lead identification–a computational approach. J. Biomol. Struct. Dyn. 43 (14), 1–15 (2024).
-
Tahir ul Qamar, M. et al. Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: immunoinformatics and in Silico approaches. PloS One. 15 (12), e0244176 (2020).
-
Rafi, M. et al. Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods. RSC Adv. 12, 4288–4310 (2022).
-
Saleki, K. et al. Engineering a novel Immunogenic chimera protein utilizing bacterial infections associated with atherosclerosis to induce a deviation in adaptive immune responses via immunoinformatics approaches. Infect. Genet. Evol. 102, 105290. https://doi.org/10.1016/j.meegid.2022.105290 (2022).
-
Boehm, U., Klamp, T., Groot, M. & Howard, J. Cellular responses to interferon-γ. Annu. Rev. Immunol. 15 (1), 749–795 (1997).
-
Liao, W., Lin, J. X. & Leonard, W. J. IL-2 family cytokines: new insights into the complex roles of IL-2 as a broad regulator of T helper cell differentiation. Curr. Opin. Immunol. 23 (5), 598–604 (2011).
-
Sahu, L. K. & Singh, K. Cross-variant proof predictive vaccine design based on SARS-CoV-2 Spike protein using immunoinformatics approach. Beni-Suef Univ. J. Basic. Appl. Sci. 12 (1), 5 (2023).
-
Aiman, S. et al. Multi-epitope chimeric vaccine design against emerging Monkeypox virus via reverse vaccinology techniques-a bioinformatics and immunoinformatics approach. Front. Immunol. 13, 985450 (2022).
-
Rahmani, A. et al. Development of a conserved chimeric vaccine based on helper T-cell and CTL epitopes for induction of strong immune response against schistosoma mansoni using immunoinformatics approaches. Int. J. Biol. Macromol. 141, 125–136 (2019).
-
Park, J. S. et al. Comparison of nasal cytokine profiles of human metapneumovirus and respiratory syncytial virus. Asia Pac. Allergy. 7 (4), 206–212 (2017).
-
Alawadi, Z. I. et al. Designing a multiepitope mRNA-based vaccine against enterotoxigenic Escherichia coli infection in calves: immunoinformatics and molecular modeling approach. Open. Veterinary J. 14 (6), 1417 (2024).
