Structural Expansion of Catalytic RNA Nanostructures through Oligomerization of a Cyclic Trimer of Engineered Ribozymes.

The multimolecular assembly of three-dimensionally structured proteins forms their quaternary structures, some of which have high geometric symmetry. The size and complexity of protein quaternary structures often increase in a hierarchical manner, with simpler, smaller structures serving as units for larger quaternary structures. In this study, we exploited oligomerization of a ribozyme cyclic trimer to achieve larger ribozyme-based RNA assembly. By installing kissing loop (KL) interacting units to one-, two-, or three-unit RNA molecules in the ribozyme trimer, we constructed dimers, open-chain oligomers, and branched oligomers of ribozyme trimer units. One type of open-chain oligomer preferentially formed a closed tetramer containing 12 component RNAs to provide 12 ribozyme units. We also observed large assembly of ribozyme trimers, which reached 1000 nm in size.

Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC are mostly unknown till now. OBJECTIVE: The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. METHODS: The publicly available three independent mRNA expression profile datasets were downloaded from the NCBI-GEO database to explore common differentially expressed genes (cDEGs) between HCC and control samples using the Statistical LIMMA approach. Hub-cDEGs as drug targets highlighting their functions, pathways, and regulators were identified by using integrated bioinformatics tools and databases. Finally, Hub-cDEGs-guided top-ranked drug agents were identified by molecular docking study for HCC. RESULTS: We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs (CDKN3, TK1, NCAPG, CDCA5, RACGAP1, AURKA, PRC1, UBE2T, MELK, and ASPM) were selected as Hub-cDEGs. The GO functional and KEGG pathway enrichment analysis of Hub-cDEGs revealed some crucial cancer-stimulating biological processes, molecular functions, cellular components, and signaling pathways. The interaction network analysis identified three TF proteins and five miRNAs as the key transcriptional and post-transcriptional regulators of HubcDEGs. Then, we detected the proposed Hub-cDEGs guided top-ranked three anti-HCC drug molecules (Dactinomycin, Vincristine, Sirolimus) that were also highly supported by the already published top-ranked HCC-causing Hub-DEGs mediated receptors. CONCLUSION: The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.

Catalytic RNA Oligomers Formed by Co-Oligomerization of a Pair of Bimolecular RNase P Ribozymes.

Naturally occurring ribozymes with a modular architecture are promising platforms for construction of RNA nanostructures because modular redesign enables their oligomerization. The resulting RNA nanostructures can exhibit the catalytic function of the parent ribozyme in an assembly dependent manner. In this study, we designed and constructed open-form oligomers of a bimolecular form of an RNase P ribozyme. The ribozyme oligomers were analyzed biochemically and by atomic force microscopy (AFM).

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies.

Cervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein-protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

MicroRNAs, a Promising Target for Breast Cancer Stem Cells.

Reactivation of the stem cell programme in breast cancer is significantly associated with persistent cancer progression and therapeutic failure. Breast cancer stem cells (BCSCs) are involved in the process of breast cancer initiation, metastasis and cancer relapse. Among the various important cues found in the formation and progression of BCSCs, microRNAs (miRNAs or miRs) play a pivotal role by regulating the expression of various tumour suppressor genes or oncogenes. Accordingly, there is evidence that miRNAs are associated with BCSC self-renewal, differentiation, invasion, metastasis and therapy resistance, and therefore cancer recurrence. miRNAs execute their roles by regulating the expression of stemness markers, activation of signalling pathways or their components and regulation of transcription networks in BCSCs. Therefore, a better understanding of the association between BCSCs and miRNAs has the potential to help design more effective and safer therapeutic solutions against breast cancer. Thus, an miRNA-based therapeutic strategy may open up new horizons for the treatment of breast cancer in the future. In view of this, we present the progress to date of miRNA research associated with stemness marker expression, signalling pathways and activation of transcription networks to regulate the self-renewal, differentiation and therapy resistance properties of BCSCs.