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Deoxyribozymes, DNA enzymes or simply DNAzymes are single-stranded oligo-deoxyribonucleotide molecules that, like proteins and ribozymes, possess the ability to perform catalysis. Although DNAzymes have not yet been found in living organisms, they have been isolated in the laboratory through in vitro selection. The selected DNAzyme sequences have the ability to catalyze a broad range of chemical reactions, utilizing DNA, RNA, peptides or small organic compounds as substrates. DNAmoreDB is a comprehensive database resource for DNAzymes that collects and organizes the following types of information: sequences, conditions of the selection procedure, catalyzed reactions, kinetic parameters, substrates, cofactors, structural information whenever available, and literature references. Currently, DNAmoreDB contains information about DNAzymes that catalyze 20 different reactions. We included a submission form for new data, a REST-based API system that allows users to retrieve the database contents in a machine-readable format, and keyword and BLASTN search features. The database is publicly available at https://www.genesilico.pl/DNAmoreDB/., Graphical Abstract Graphical AbstractDNAmoreDB, a comprehensive database resource for DNAzymes.

The outbreak of the COVID-19 pandemic has led to intensive studies of both the structure and replication mechanism of SARS-CoV-2. In spite of some secondary structure experiments being carried out, the 3D structure of the key function regions of the viral RNA has not yet been well understood. At the beginning of COVID-19 breakout, RNA-Puzzles community attempted to envisage the three-dimensional structure of 5′- and 3′-Un-Translated Regions (UTRs) of the SARS-CoV-2 genome. Here, we report the results of this prediction challenge, presenting the methodologies developed by six participating groups and discussing 100 RNA 3D models (60 models of 5′-UTR and 40 of 3′-UTR) predicted through applying both human experts and automated server approaches. We describe the original protocol for the reference-free comparative analysis of RNA 3D structures designed especially for this challenge. We elaborate on the deduced consensus structure and the reliability of the predicted structural motifs. All the computationally simulated models, as well as the development and the testing of computational tools dedicated to 3D structure analysis, are available for further study.

SARS-CoV-2 is a betacoronavirus with a linear single-stranded, positive-sense RNA genome, whose outbreak caused the ongoing COVID-19 pandemic. The ability of coronaviruses to rapidly evolve, adapt, and cross species barriers makes the development of effective and durable therapeutic strategies a challenging and urgent need. As for other RNA viruses, genomic RNA structures are expected to play crucial roles in several steps of the coronavirus replication cycle. Despite this, only a handful of functionally-conserved coronavirus structural RNA elements have been identified to date. Here, we performed RNA structure probing to obtain single-base resolution secondary structure maps of the full SARS-CoV-2 coronavirus genome both in vitro and in living infected cells. Probing data recapitulate the previously described coronavirus RNA elements (5′ UTR and s2m), and reveal new structures. Of these, ∼10.2% show significant covariation among SARS-CoV-2 and other coronaviruses, hinting at their functionally-conserved role. Secondary structure-restrained 3D modeling of these segments further allowed for the identification of putative druggable pockets. In addition, we identify a set of single-stranded segments in vivo, showing high sequence conservation, suitable for the development of antisense oligonucleotide therapeutics. Collectively, our work lays the foundation for the development of innovative RNA-targeted therapeutic strategies to fight SARS-related infections.

SummarySARS-CoV-2 is a betacoronavirus with a linear single-stranded, positive-sense RNA genome of ∼30 kb, whose outbreak caused the still ongoing COVID-19 pandemic. The ability of coronaviruses to rapidly evolve, adapt, and cross species barriers makes the development of effective and durable therapeutic strategies a challenging and urgent need. As for other RNA viruses, genomic RNA structures are expected to play crucial roles in several steps of the coronavirus replication cycle. Despite this, only a handful of functionally conserved structural elements within coronavirus RNA genomes have been identified to date.Here, we performed RNA structure probing by SHAPE-MaP to obtain a single-base resolution secondary structure map of the full SARS-CoV-2 coronavirus genome. The SHAPE-MaP probing data recapitulate the previously described coronavirus RNA elements (5′ UTR, ribosomal frameshifting element, and 3′ UTR), and reveal new structures. Secondary structure-restrained 3D modeling of highly-structured regions across the SARS-CoV-2 genome allowed for the identification of several putative druggable pockets. Furthermore, ∼8% of the identified structure elements show significant covariation among SARS-CoV-2 and other coronaviruses, hinting at their functionally-conserved role. In addition, we identify a set of persistently single-stranded regions having high sequence conservation, suitable for the development of antisense oligonucleotide therapeutics.Collectively, our work lays the foundation for the development of innovative RNA-targeted therapeutic strategies to fight SARS-related infections.

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.

Catalysis in biology is restricted to RNA (ribozymes) and protein enzymes, but synthetic biomolecular catalysts can also be made of DNA (deoxyribozymes)1 or synthetic genetic polymers2. In vitro selection from synthetic random DNA libraries identified DNA catalysts for various chemical reactions beyond RNA backbone cleavage3. DNA-catalysed reactions include RNA and DNA ligation in various topologies4,5, hydrolytic cleavage6,7 and photorepair of DNA8, as well as reactions of peptides9,10 and small molecules11,12. In spite of comprehensive biochemical studies of DNA catalysts for two decades, fundamental mechanistic understanding of their function is lacking in the absence of three-dimensional models at atomic resolution. Early attempts to solve the crystal structure of an RNA-cleaving deoxyribozyme resulted in a catalytically irrelevant nucleic acid fold13. Here we report the crystal structure of the RNAligating deoxyribozyme 9DB1 (ref. 14) at 2.8 Å resolution. The structure captures the ligation reaction in the post-catalytic state, revealing a compact folding unit stabilized by numerous tertiary interactions, and an unanticipated organization of the catalytic centre. Structure-guided mutagenesis provided insights into the basis for regioselectivity of the ligation reaction and allowed remarkable manipulation of substrate recognition and reaction rate. Moreover, the structure highlights how the specific properties of deoxyribose are reflected in the backbone conformation of the DNA catalyst, in support of its intricate three-dimensional organization. The structural principles underlying the catalytic ability of DNA elucidate differences and similarities in DNA versus RNA catalysts, which is relevant for comprehending the privileged position of folded RNA in the prebiotic world and in current organisms. peerReviewed

Summary SF3b is a heptameric protein complex of the U2 small nuclear ribonucleoprotein (snRNP) that is essential for pre-mRNA splicing. Mutations in the largest SF3b subunit, SF3B1/SF3b155, are linked to cancer and lead to alternative branch site (BS) selection. Here we report the crystal structure of a human SF3b core complex, revealing how the distinctive conformation of SF3b155's HEAT domain is maintained by multiple contacts with SF3b130, SF3b10, and SF3b14b. Protein-protein crosslinking enabled the localization of the BS-binding proteins p14 and U2AF65 within SF3b155's HEAT-repeat superhelix, which together with SF3b14b forms a composite RNA-binding platform. SF3b155 residues, the mutation of which leads to cancer, contribute to the tertiary structure of the HEAT superhelix and its surface properties in the proximity of p14 and U2AF65. The molecular architecture of SF3b reveals the spatial organization of cancer-related SF3b155 mutations and advances our understanding of their effects on SF3b structure and function.