An Insilico Methodology for Predicting Novel Micro RNAs with Therapeutic Significance

Identification of a novel method for predicting therapeutic micro RNAs (miRNAs) to treat diseases has become a challenge in the era of post genomics and the ability to apply an accurate computational approach leads to the discovery of conserved miRNAs. Initially we have identified the list of genes from Pharmacocogenomic database (PharmGKB) and then we have predicted the conserved miRNA targets from TargetScan. Finally we have found the connectivity map between the gene and validated miRNA target from miRmap and the number of binding sites were analyzed for each pair (gene-miRNA). We have applied the above mentioned approach to Psoriasis. In case of Psoriasis, 29 genes are present in PharmGKB and among them; PSORS1C2, IL6, ENOSF1, ABCC1, FCGR2A, FCGR3A, TYMS, VDR and ABCG2 contain conserved miRNAs on the basis of seed pairing in TargetScan. Number of mRNA (messenger RNA) binding sites were analyzed for the obtained miRNAs and it has been found that hsa-miR-370, hsa-miR-3074-5p and hsa-miR-4756-3p of FCGR3A and similarly hsa-miR-3163 and hsa-miR-4496 of ABCG2 contain more than 2 mRNA binding sites in their respective genes and hence there is a maximum probability for the utilization of the above mentioned miRNAs as a lead for miRNA based drug discovery. At present we have applied this model for Psoriasis and the above mentioned methodology can also be applied for other diseases in future.