Prediction of MAYV peptide antigens for immunodiagnostic tests by immunoinformatics and molecular dynamics simulations

dc.creatorRodrigues, Roger Luiz
dc.creatorMenezes, Gabriela de Lima
dc.creatorSaivish, Marielena Vogel
dc.creatorCosta, Vivaldo Gomes da
dc.creatorPereira, Maristela
dc.creatorMoreli, Marcos Lázaro
dc.creatorSilva, Roosevelt Alves da
dc.date.accessioned2025-03-06T11:46:50Z
dc.date.available2025-03-06T11:46:50Z
dc.date.issued2019
dc.description.abstractThe Mayaro virus is endemic to South America, and the possible involvement of Aedes spp. mosquitoes in its transmission is a risk factor for outbreaks of greater proportions. The virus causes a potentially disabling illness known as Mayaro fever, which is similar to that caused by the chikungunya virus. The cocirculation of both viruses, with their clinical and structural similarities, and the absence of prophylactic and therapeutic measures highlight the need for studies that seek to understand the Mayaro virus. Using approaches in silico, we identifed an antigenic and specifc epitope (p_MAYV4) in domain A of the E2 glycoprotein of the Mayaro virus. This epitope was theoretically predicted to be stable and exposed on the surface of the protein, where it showed key properties that enable its interaction with neutralizing antibodies. These characteristics make it an interesting target for the development of immunodiagnostic platforms. Molecular dynamics simulation-based structural analysis showed that the PHE95 residue in the E1 fusion loop region is conserved among Alphavirus family members. PHE95 interacts with the hydrophobic residues of the E2 glycoprotein to form a cage shaped structure that is critical to assemble and stabilize the E1/E2 heterodimer. These results provide important insights useful for the advancement of diagnostic platforms and the study of therapeutic alternatives.
dc.identifier.citationRODRIGUES, Roger Luiz et al. Prediction of MAYV peptide antigens for immunodiagnostic tests by immunoinformatics and molecular dynamics simulations. Scientific Reports, London, v. 9, n. 1, e13339, 2019. DOI: 10.1038/s41598-019-50008-3. Disponível em: https://www.nature.com/articles/s41598-019-50008-3. Acesso em: 28 fev. 2025.
dc.identifier.doi10.1038/s41598-019-50008-3
dc.identifier.issne- 2045-2322
dc.identifier.urihttp://repositorio.bc.ufg.br//handle/ri/26790
dc.language.isoeng
dc.publisher.countryGra-bretanha
dc.publisher.departmentInstituto de Ciências Biológicas - ICB (RMG)
dc.rightsAcesso Aberto
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titlePrediction of MAYV peptide antigens for immunodiagnostic tests by immunoinformatics and molecular dynamics simulations
dc.typeArtigo

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