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Characteristics of Influenza HA-NA Interdependence Determined Through a Graphical Technique

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Influenza viruses are characterized by two surface proteins - the hemagglutinin (HA) of which there are 16 varieties, and the neuraminidase (NA) of which there are 9, each subtype characterized by its antigenic properties. Although theoretically 16 x 9 combinations are possible, only a few like the H1N1, H3N2, etc are seen to occur more frequently. Numerous studies with select subtypes like H1N1, H5N1, etc., have explained this phenomena by indicating that viral viability necessitates functional balance between the NA and HA so that only some combinations are favored. However, the reasons for this balance or its characteristics and whether this is universal for influenza subtypes are not yet known.

Using novel graphical techniques and hypothesizing a coupling between the HA and NA, we devised a coupling factor to estimate the interdependence, if any, between HA and NA sequences covering a global sample of 10 subtypes and 164 sequences. We found that (a) the coupling we hypothesized between HAs and NAs is characteristic of each subtype, (b) within each subtype the coupling value is significantly different for human infecting strains and those that infect avians, and (c) artificial strains made up by mixing and matching HAs and NAs from different subtypes produce coupling factors that are far from the characteristic values for the parent subtype indicating possibly non-viable viruses, a result that matches with experimental evidence of Zhang et al. [1]. We also show that some natural strains that did not fit the characteristic values for its subtype could have been possible mismatches during viral packaging. Our observations have important consequences for drug and vaccine design and for monitoring of influenza virus reassortments and possible evolution of human pandemics.
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Keywords: Drug and vaccine development; HA sequence plots; HA-NA coupling characteristics; HA-NA interdependence; NA sequence plots; graphical representation; mathematical characterization; monitoring flu sequences

Document Type: Research Article

Publication date: December 1, 2014

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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