Title |
In Silico Identification of Highly Conserved Epitopes of Influenza A H1N1, H2N2, H3N2, and H5N1 with Diagnostic and Vaccination Potential
|
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Published in |
BioMed Research International, August 2015
|
DOI | 10.1155/2015/813047 |
Pubmed ID | |
Authors |
José Esteban Muñoz-Medina, Carlos Javier Sánchez-Vallejo, Alfonso Méndez-Tenorio, Irma Eloísa Monroy-Muñoz, Javier Angeles-Martínez, Andrea Santos Coy-Arechavaleta, Clara Esperanza Santacruz-Tinoco, Joaquín González-Ibarra, Yu-Mei Anguiano-Hernández, César Raúl González-Bonilla, Eva Ramón-Gallegos, José Alberto Díaz-Quiñonez |
Abstract |
The unpredictable, evolutionary nature of the influenza A virus (IAV) is the primary problem when generating a vaccine and when designing diagnostic strategies; thus, it is necessary to determine the constant regions in viral proteins. In this study, we completed an in silico analysis of the reported epitopes of the 4 IAV proteins that are antigenically most significant (HA, NA, NP, and M2) in the 3 strains with the greatest world circulation in the last century (H1N1, H2N2, and H3N2) and in one of the main aviary subtypes responsible for zoonosis (H5N1). For this purpose, the HMMER program was used to align 3,016 epitopes reported in the Immune Epitope Database and Analysis Resource (IEDB) and distributed in 34,294 stored sequences in the Pfam database. Eighteen epitopes were identified: 8 in HA, 5 in NA, 3 in NP, and 2 in M2. These epitopes have remained constant since they were first identified (~91 years) and are present in strains that have circulated on 5 continents. These sites could be targets for vaccination design strategies based on epitopes and/or as markers in the implementation of diagnostic techniques. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 43 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 9 | 21% |
Student > Master | 7 | 16% |
Student > Bachelor | 6 | 14% |
Researcher | 4 | 9% |
Other | 3 | 7% |
Other | 7 | 16% |
Unknown | 7 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Immunology and Microbiology | 7 | 16% |
Medicine and Dentistry | 6 | 14% |
Biochemistry, Genetics and Molecular Biology | 6 | 14% |
Agricultural and Biological Sciences | 6 | 14% |
Veterinary Science and Veterinary Medicine | 4 | 9% |
Other | 5 | 12% |
Unknown | 9 | 21% |