Details

Autor(en) / Beteiligte

• da Silva, Maria Karolaynne
• Azevedo, Arthur Antunes Coimbra
• Campos, Daniel Melo de Oliveira
• de Souto, Janeusa Trindade
• Fulco, Umberto Laino
• Oliveira, Jonas Ivan Nobre

Titel

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Ist Teil von

• Journal of biomolecular structure & dynamics, 2023-05, Vol.41 (8), p.3321-3338

Ort / Verlag

England: Taylor & Francis

Erscheinungsjahr

2023

Quelle

Taylor & Francis Journals Auto-Holdings Collection

Beschreibungen/Notizen

• Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions. Communicated by Ramaswamy H. Sarma