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In SilicoIdentification of Highly Conserved Epitopes of Influenza A H1N1, H2N2, H3N2, and H5N1 with Diagnostic and Vaccination Potential

Overview of attention for article published in BioMed Research International, January 2015
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Title
In SilicoIdentification of Highly Conserved Epitopes of Influenza A H1N1, H2N2, H3N2, and H5N1 with Diagnostic and Vaccination Potential
Published in
BioMed Research International, January 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

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 20%
Student > Master 7 20%
Student > Bachelor 6 17%
Researcher 4 11%
Student > Doctoral Student 2 6%
Other 7 20%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 17%
Medicine and Dentistry 6 17%
Biochemistry, Genetics and Molecular Biology 6 17%
Immunology and Microbiology 6 17%
Veterinary Science and Veterinary Medicine 3 9%
Other 5 14%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 September 2015.
All research outputs
#13,931,808
of 15,797,113 outputs
Outputs from BioMed Research International
#5,048
of 7,056 outputs
Outputs of similar age
#198,983
of 242,849 outputs
Outputs of similar age from BioMed Research International
#121
of 176 outputs
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So far Altmetric has tracked 7,056 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 176 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.