Zeitschrift für Data Mining in Genomics & Proteomics

Abstrakt

Prediction of micro RNAs against H5N1 and H1N1 NS1 Protein: a Window to Sequence Specific Therapeutic Development

Pankaj Koparde and Shailza Singh

Motivation: Conventional Influenza drugs might result in failure of action due to highly variable nature of influenza antigenic proteins. in silico prediction of sequence specific therapeutics is less time consuming and cost effective. Most of the miRNA target prediction platforms differ in their specificity and sensitivity in prediction. Here we propose a bioinformatics approach to predict micro RNAs against non-structural protein 1 of avian influenza H5N1 virus and against segment 8 swine influenza H1N1 virus.

Results: hsa-miR-138, hsa-miR-525-5p and hsa-miR-124 were sorted out as potential sequence specific therapeutic agents against NS1 protein of H5N1 virus. Similar studies on different H1N1 segment 8 genomes resulted in the prediction of miRNAs which can be used as anti-influenza agents. The predicted micro RNAs also possess roles in regulatory processes of host cell, stress related pathways including MAPK pathway, mTOR pathway and are found to be involved in pathways related to cancer.