Viral diseases cause significant harm to human health and often cause high mortality. In the past twenty years, humanity has undergone infection by SARS-CoV (severe acute respiratory syndrome), MERS-CoV (Middle East respiratory syndrome) and COVID-19 coronaviruses, which spread from animals to humans and from person to person. These diseases have led to large economic losses. To fight coronaviruses and other viruses, it is proposed to use miRNAs, which regulate protein synthesis at the translational level.MirTarget program was used to determine the following binding characteristics: the locations of miRNA binding sites in the 3'UTR, 5'UTR, and CDS; the free energy interaction ∆G between miRNA and mRNA; the ΔG/ΔGm value, where ΔGm is equal to the free energy binding of miRNA with its full complementary nucleotide sequence; and the nucleotide interaction schemes between miRNAs and mRNAs. Out of 2565 miRNAs, miR-4778-3p, miR-6864-5p and miR-5197-3p were identified as the most effectively interacting with the gRNA of SARS-CoV, MERS-CoV and COVID-19, respectively. Based on the miR-4778-3p, miR-6864-5p and miR-5197-3p sequences, complete complementary miRNA (cc-miR) binding sites in the gRNA coronaviruses were created. The detected binding sites of these cc-miRs did not form intramolecular complexes in the 2D structure of the gRNA of SARS-CoV, MERS-CoV, and COVID-19 with a value of more than 85%. Therefore, the cc-miRs will bind gRNA at these sites without competition. The cc-miRs for SARS-CoV, MERS-CoV, and COVID-19 did not have target genes among the 17508 human coding genes with a ΔG/ΔGm of more than 85%, which implies the absence of side effects of these cc-miRs on the translation of human mRNAs. cc-miRs can be used as therapeutic agents by incorporating them into exosomes or other vesicles and introducing them into the blood or lung by inhalation. The introduction of cc-miR into the blood will suppress the reproduction of the virus in the blood and in all organs into which it can enter. The proposed method of 3 inhibiting the reproduction of coronaviruses can be used for other viruses.
The development of breast cancer (BC) subtypes is controlled by distinct sets of candidate genes, and the expression of these genes is regulated by the binding of their mRNAs with miRNAs. Predicting miRNA associations and target genes is thus essential when studying breast cancer. The MirTarget program identifies the initiation of miRNA binding to mRNA, the localization of miRNA binding sites in mRNA regions, and the free energy from the binding of all miRNA nucleotides with mRNA. Candidate gene mRNAs have clusters (miRNA binding sites with overlapping nucleotide sequences). mRNAs of EPOR, MAZ and NISCH candidate genes of the HER2 subtype have clusters, and there are four clusters in mRNAs of MAZ, BRCA2 and CDK6 genes. Candidate genes of the triple-negative subtype are targets for multiple miRNAs. There are 11 sites in CBL mRNA, five sites in MMP2 mRNA, and RAB5A mRNA contains two clusters in each of the three sites. In SFN mRNA, there are two clusters in three sites, and one cluster in 21 sites. Candidate genes of luminal A and B subtypes are targets for miRNAs: there are 21 sites in FOXA1 mRNA and 15 sites in HMGA2 mRNA. There are clusters of five sites in mRNAs of ITGB1 and SOX4 genes. Clusters of eight sites and 10 sites are identified in mRNAs of SMAD3 and TGFB1 genes, respectively. Organizing miRNA binding sites into clusters reduces the proportion of nucleotide binding sites in mRNAs. This overlapping of miRNA binding sites creates a competition among miRNAs for a binding site. From 6,272 miRNAs studied, only 29 miRNAs from miRBase and 88 novel miRNAs had binding sites in clusters of target gene mRNA in breast cancer. We propose using associations of miRNAs and their target genes as markers in breast cancer subtype diagnosis.
The involvement of genes and miRNAs in the development of atherosclerosis is a challenging problem discussed in recent publications. It is necessary to establish which miRNAs affect the expression of candidate genes. We used known candidate atherosclerosis genes to predict associations. The quantitative characteristics of interactions of miRNAs with mRNA candidate genes were determined using the program, which identifies the localization of miRNA binding sites in mRNA, the free energy interaction of miRNA with mRNA. In mRNAs of GAS6 and NFE2L2 candidate genes, binding sites of 21 miRNAs and of 15 miRNAs, respectively, were identified. In IRS2 mRNA binding sites of 25 miRNAs were located in a cluster of 41 nt. In ADRB3, CD36, FASLG, FLT1, PLA2G7 , and PPARGC1A mRNAs, clusters of miR-466, ID00436.3p-miR, and ID01030.3p-miR BS were identified. The organization of overlapping miRNA binding sites in clusters led to their compaction and caused competition among the miRNAs. The binding of 53 miRNAs to the mRNAs of 14 candidate genes with free energy interactions greater than −130 kJ/mole was determined. The miR-619-5p was fully complementary to ADAM17 and CD36 mRNAs, ID01593.5p-miR to ANGPTL4 mRNA, ID01935.5p-miR to NFE2L2 , and miR-5096 to IL18 mRNA. Associations of miRNAs and candidate atherosclerosis genes are proposed for the early diagnosis of this disease.
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