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Title

Selection of predicted siRNA as potential antiviral therapeutic agent against influenza virus

 

Authors

Asif Raza1, Hira Shareef1, Hira Salim1, Rashid Khushal2, Habib Bokhari1*

 

Affiliation

1Department of Biosciences, COMSATS Institute of Information Technology, Chak Shazad Campus, Park Road, Islamabad, Pakistan; 2Astrazeneca, Nottingham, UK

 

Email

habib@comsats.edu.pk; *Corresponding author

 

Phone

44-07915191582

 

Fax

0092-051-4442805

 

Article Type

Hypothesis

 

Date

Received June 03, 2011; Accepted June 24, 2011; Published July 19, 2011

 

Abstract

Influenza virus A (IVA) infection is responsible for recent death worldwide. Hence, there is a need to develop therapeutic agents against the virus. We describe the prediction of short interfering RNA (siRNA) as potential therapeutic molecules for the HA (Haemagglutinin) and NA (Neuraminidase) genes. We screened 90,522 siRNA candidates for HA and 13,576 for NA and selected 1006 and 1307 candidates for HA and NA, respectively based on the proportion of viral sequences that are targeted by the corresponding siRNA, with complete matches. Further short listing to select siRNA with no off-target hits, fulfilling all the guidelines mentioned in approach, provided us 13 siRNAs for haemagglutinin and 13 siRNAs for neuraminidase. The approach of finding siRNA using multiple sequence alignments of amino acid sequences has led to the identification of five conserved amino acid sequences, three in hemagglutinin i.e. RGLFGAIAGFIE, YNAELLV and AIAGFIE and two in neuraminidase i.e. RTQSEC and EECSYP which on reveres translation provided siRNA sequences as potential therapeutic candidates. The approaches used during this study have enabled us to identify potentially therapeutic siRNAs against divergent IVA strains.

 

Keywords

Influenza virus A, Sequence analysis, siRNA, Hemagglutinin, Neuraminidase.

 

Citation

Raza et al. Bioinformation 6(9): 340-343 (2011)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.