In-Silico Algorithms for the Screening of Possible microRNA Binding Sites and Their Interactions

Abstract

MicroRNAs (miRNAs) comprise a recently discovered class of small, non-coding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the transcripts of their targets i.e. protein-coding genes, leading to down-regulation or repression of the target genes. However, target gene activation has also been described. miRNAs are involved in diverse regulatory pathways, including control of developmental timing, apoptosis, cell proliferation, cell differentiation, modulation of immune response to macrophages, and organ development and are associated with many diseases, such as cancer. Computational prediction of miRNA targets is much more challenging in animals than in plants, because animal miRNAs often perform imperfect base-pairing with their target sites, unlike plant miRNAs which almost always bind their targets with near perfect complementarity. In the past years, a large number of target prediction programs and databases on experimentally validated information have been developed for animal miRNAs to fulfil the need of experimental scientists conducting miRNA research. In this review we first succinctly describe the prediction criteria (rules or principles) adapted by prediction algorithms to generate possible miRNA binding site interactions and introduce most relevant algorithms, and databases. We then summarize their applications with the help of some previously published studies. We further provide experimentally validated functional binding sites outside 3’-UTR region of target mRNAs and the resources which offer such predictions. Finally, the issue of experimental validation of miRNA binding sites will be briefly discussed.

microRNAs in viral acute respiratory infections: immune regulation, biomarkers, therapy, and vaccines

“…In the viral replication step, a dsRNA is generated that is recognized by TLR3 and RIGI [30,31]. Bioinformatic software has been useful in predicting in silico whether certain miRNAs have viral mRNAs as targets, for which the response may be in favor or against the virus Table 1 The miRNAs involved in viral acute respiratory infections (ARIs), their pathways, and the targets that they regulate [2,83] [32]. The miR-128 and miR-155 miRNAs were identified as possible regulators of the innate immune response against RV-1B [33], since they have as targets the genetic material from RV.…”

Alterations in patient plasma microRNA expression profiles following resection of metastatic melanoma

“…The cumulative weighted context++ score is a measure of the total repression expected from multiple sites of the same miR, for each predicted mRNA target . The gene targets identified by TargetScan were then assessed for overlap with the miRTarBase identified gene target lists, reducing the number of genes for analysis to 32 gene targets for miR‐150‐5p, and 120 gene targets for miR‐1260a …”

Reciprocal Alterations in Regulator of G Protein Signaling 4 and microRNA16 in Schizophrenia

“…[52][53][54][55] Moreover, as any given miR is predicted to regulate hundreds of gene products, 17 increased miR16 in the PFC almost certainly affects numerous other transcripts. Application of recently developed algorithms for the in silico prediction of miR targets 56 to specific tests of human PFC tissue will provide essential data for interpreting the functional consequences of alterations in miRs in schizophrenia.…”