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Content loaded within last 14 days Peptide Aptamer of Complementarity-determining Region to Detect Avian Influenza Virus

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Despite significant progress in the development of diagnostic methods for influenza, avian influenza (AI) infection continues to represent a substantial threat to human health. Among the subtypes of AI, H5 influenza is highly infectious to animals and humans; however, there are no reliable H5 subtype-specific diagnostic systems owing to a scarcity of H5 subtype-specific detection elements. In this study, a new peptide aptamer (P1:KASGYTFTSF) was developed to recognize the H5 viral subtype using an in silico bioinformatics approach for predicting complementarity-determining regions (CDRs), and the aptamer was evaluated by immunoassays. The three-dimensional structure of influenza hemagglutinin (HA) and the peptide were used in a molecular docking study, and the peptide was compared to the epitope-derived peptide aptamer (H5-P2:KPNGAINF). Interactions between the peptides and the virus were then assessed by fluorescence-linked sandwich immunosorbent assay (FLISA), immunofluorescence staining assay (IFA), and rapid fluorescent immunochromatographic assay (FICT). P1 and H5-P2 both significantly detected H5N3 at 15.6 HAU/mL (P < 0.05), and P1 detected the virus more effectively (P < 0.05), consistent with the docking result. An optical image of the peptide recognizing an H5N3-infected cell was acquired by IFA, and was consistent with the antibody-linked IFA result. FICT employing the peptide showed the ability for H5 subtype-specific diagnosis, with 2-fold higher performance than that of a conventional, antibody-linked rapid test. This work shows the potential of a CDR-predicted peptide aptamer as a probe for immunological assays that can specifically recognize AI virus.
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Keywords: AVIAN INFLUENZA; IMMUNOASSAY; IN SILICO BIOINFORMATICS; PEPTIDE APTAMER; PREDICTION OF COMPLEMENTARITY-DETERMINING REGION

Document Type: Research Article

Publication date: June 1, 2019

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  • Journal of Biomedical Nanotechnology (JBN) is a peer-reviewed multidisciplinary journal providing broad coverage in all research areas focused on the applications of nanotechnology in medicine, drug delivery systems, infectious disease, biomedical sciences, biotechnology, and all other related fields of life sciences.
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