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New 3D computational model to help fight H1N1 virus
Fri, May 22, 2009
AsiaOne

A team of scientists from A*STAR's Bioinformatics Institute (BII) are the first to demonstrate how bioinformatics and computational biology can contribute towards managing the H1N1 influenza A (1) virus.

Dr Sebastian Maurer-Stroh and his team published their complex analysis, entitled, "Mapping the sequence mutations of the 2009 H1N1 influenza A virus neuraminidase relative to drug and antibody binding sites", in Biology Direct, a peer-reviewed journal on 20 May 2009.

The team also came up with some interesting findings about the H1N1 virus:

- the neuraminidase structure of the 2009 H1N1 influenza A virus has undergone extensive surface mutations compared to closely related strains, such as the H5N1 avian flu virus or other H1N1 strains such as the 1918 Spanish flu. (Neuraminidase promotes influenza virus release from infected cells and facilitates virus spread within the respiratory tract - source: http://www.ncbi.nlm.nih.gov/pubmed/10711940)

- the 2009 H1N1 influenza A virus strain is more similar to the H5N1 avian flu than to the historic 1918 H1N1 strain (Spanish flu)

- current mutations of the virus have rendered previous flu vaccinations directed against neuraminidase less effective

- the commercial drugs, namely Tamiflu® and Relenza® , are still effective in treating the current H1N1 virus.

Dr Frank Eisenhaber, Director of BII, said: "BII's H1N1 virus sequence study marks a significant milestone in the use of computational biology methods in understanding how the mutations of the fast evolving influenza virus affect immunogenic properties or drug response. This information helps to develop a strategy for fighting the H1N1 virus and for organising an effective treatment for patients."

Besides this 3D model developed by BII, A*STAR scientists have also developed other technologies to tackle the 2009 H1N1 Influenza A virus, such as a chip that is able to quickly sequence or decode the genes in the flu virus and distinguish between the H1N1, seasonal, and mutated flu strains, a microkit to detect and identify the flu virus strain within 2 hours and a molecular diagnostic assay to distinguish between the H1N1 and seasonal flu strains.

 

 
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