In silico microrna identification and target prediction in HPV

Interference RNAs are now a day's one of the most admiring methods for gene silencing. They are of many types but among them microRNAs are very important as they can regulate gene expression by controlling the protein translation mechanism during variety of cell phenomena viz. proliferation of cancer, differentiation of stem cells and neurons etc. MicroRNAs are produced from non-coding DNA region. Since the report of the lin-4 RNA (1993) significant progress has been made in miRNA research. About 300 miRNAs have been identified in different organisms to date. Experimental identification of miRNA is a slow process as they are difficult to isolate. Thus computational identification from genomic sequence is the new approach.

MiRNA related sequences are present in most of the genomes, but this information is unexplored till now in many viral genomes and so there is a need to study it in detail. Computational and experimental microRNA prediction is a challenge for researchers. The basics of computational miRNA prediction are based on few parameters like calculation of optimum free energies (dG), Structural continuity, and number of G: C baces pairing etc. In the present work we have predicted four miRNA molecules in Human Papilloma virus (HPV) through viro-miRNA algorithm which is a computer based program. We have also predicted possible target genes which are inhibited by these predicted microRNAs.