RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

Cuproptosis is an unusual form of cell death caused by copper accumulation in mitochondria. Cuproptosis is associated with hepatocellular carcinoma (HCC). Long noncoding RNAs (LncRNAs) have been shown to be effective prognostic biomarkers, yet the link between lncRNAs and cuproptosis remains unclear. We aimed to build a prognostic model of lncRNA risk and explore potential biomarkers of cuproptosis in HCC. Pearson correlations were used to derive lncRNAs co-expressed in cuproptosis. The model was constructed using Cox, Lasso, and multivariate Cox regressions. Kaplan–Meier survival analysis, principal components analysis, receiver operating characteristic curve, and nomogram analyses were carried out for validation. Seven lncRNAs were identified as prognostic factors. A risk model was an independent prognostic predictor. Among these seven lncRNAs, prostate cancer associated transcript 6 (PCAT6) is highly expressed in different types of cancer, activating Wnt, PI3K/Akt/mTOR, and other pathways; therefore, we performed further functional validation of PCAT6 in HCC. Reverse transcription–polymerase chain reaction results showed that PCAT6 was aberrantly highly expressed in HCC cell lines (HepG2 and Hep3B) compared to LO2 (normal hepatocytes). When its expression was knocked down, cells proliferated and migrated less. PCAT6 might be a potential biomarker for predicting prognosis in HCC.

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan–Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

We have determined the crystal structure of a pseudoknot (PK)-containing hammerhead ribozyme that closely resembles the pistol ribozyme, with essentially identical secondary structure and connectivity. The activity is more sensitive to deletion of the G8 2’OH than to the absence of magnesium ions, indicating that the catalytic mechanism is the same as the extended hammerhead, and distinct from the pistol ribozyme. Here we show that nucleophilic attack is almost perfectly in-line, and the G8 2’OH is well positioned to act as general acid, being directed towards the O5’ leaving group, and 2.9 Å away from it. Despite the similarity in overall structure to the pistol ribozyme, the local structure close to the cleavage site differs, and the PK hammerhead retains its unique mechanistic identity and demonstrates enhanced activity over other hammerhead ribozymes under standard conditions.

Cuproptosis and ferroptosis represent copper- and iron-dependent forms of cell death, respectively, and both are known to play pivotal roles in head and neck squamous cell carcinoma (HNSCC). However, few studies have explored the prognostic signatures related to cuproptosis and ferroptosis in HNSCC. Our objective was to construct a prognostic model based on genes associated with cuproptosis and ferroptosis. We randomly assigned 502 HSNCC samples from The Cancer Genome Atlas (TCGA) into training and testing sets. Pearson correlation analysis was utilized to identify cuproptosis-associated ferroptosis genes in the training set. Cox proportional hazards (COX) regression and least absolute shrinkage operator (LASSO) were employed to construct the prognostic model. The performance of the prognostic model was internally validated using single-factor COX regression, multifactor COX regression, Kaplan–Meier analysis, principal component analysis (PCA), and receiver operating curve (ROC) analysis. Additionally, we obtained 97 samples from the Gene Expression Omnibus (GEO) database for external validation. The constructed model, based on 12 cuproptosis-associated ferroptosis genes, proved to be an independent predictor of HNSCC prognosis. Among these genes, the increased expression of aurora kinase A (AURKA) has been implicated in various cancers. To further investigate, we employed small interfering RNAs (siRNAs) to knock down AURKA expression and conducted functional experiments. The results demonstrated that AURKA knockdown significantly inhibited the proliferation and migration of HNSCC cells (Cal27 and CNE2). Therefore, AURKA may serve as a potential biomarker in HNSCC.