ARTEMIS: a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment.

Non-coding RNAs play a major role in diverse processes in living cells with their sequence and spatial structure serving as the principal determinants of their function. Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA. To date, state-of-the-art methods for RNA 3D structure superposition rely on intricate heuristics, and the potential for topology-independent superposition has not been exhausted. Recently, we introduced the ARTEM method for unrestrained pairwise superposition of RNA 3D modules and now we developed it further to solve the global RNA 3D structure alignment problem. Our new tool ARTEMIS significantly outperforms state-of-the-art tools in both sequentially-ordered and topology-independent RNA 3D structure superposition. Using ARTEMIS we discovered a helical packing motif to be preserved within different backbone topology contexts across various non-coding RNAs, including multiple ribozymes and riboswitches. We anticipate that ARTEMIS will be essential for elucidating the landscape of RNA 3D folds and motifs featuring sequence permutations that thus far remained unexplored due to limitations in previous computational approaches.

MODOMICS: a database of RNA modifications and related information. 2023 update.

The MODOMICS database was updated with recent data and now includes new data types related to RNA modifications. Changes to the database include an expanded modification catalog, encompassing both natural and synthetic residues identified in RNA structures. This addition aids in representing RNA sequences from the RCSB PDB database more effectively. To manage the increased number of modifications, adjustments to the nomenclature system were made. Updates in the RNA sequences section include the addition of new sequences and the reintroduction of sequence alignments for tRNAs and rRNAs. The protein section was updated and connected to structures from the RCSB PDB database and predictions by AlphaFold. MODOMICS now includes a data annotation system, with 'Evidence' and 'Estimated Reliability' features, offering clarity on data support and accuracy. This system is open to all MODOMICS entries, enhancing the accuracy of RNA modification data representation. MODOMICS is available at https://iimcb.genesilico.pl/modomics/.

DEGRONOPEDIA: a web server for proteome-wide inspection of degrons.

E3 ubiquitin ligases recognize substrates through their short linear motifs termed degrons. While degron-signaling has been a subject of extensive study, resources for its systematic screening are limited. To bridge this gap, we developed DEGRONOPEDIA, a web server that searches for degrons and maps them to nearby residues that can undergo ubiquitination and disordered regions, which may act as protein unfolding seeds. Along with an evolutionary assessment of degron conservation, the server also reports on post-translational modifications and mutations that may modulate degron availability. Acknowledging the prevalence of degrons at protein termini, DEGRONOPEDIA incorporates machine learning to assess N-/C-terminal stability, supplemented by simulations of proteolysis to identify degrons in newly formed termini. An experimental validation of a predicted C-terminal destabilizing motif, coupled with the confirmation of a post-proteolytic degron in another case, exemplifies its practical application. DEGRONOPEDIA can be freely accessed at degronopedia.com.

SimRNAweb v2.0: a web server for RNA folding simulations and 3D structure modeling, with optional restraints and enhanced analysis of folding trajectories.

Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method. SimRNA employs a coarse-grained model, Monte Carlo sampling and statistical potentials to explore RNA conformational space, optionally guided by spatial restraints. Recognized for its accuracy in RNA 3D structure prediction in RNA-Puzzles and CASP competitions, SimRNA is particularly useful for incorporating restraints based on experimental data. The new server version introduces performance optimizations and extends user control over simulations and the processing of results. It allows the application of various hard and soft restraints, accommodating alternative structures involving canonical and noncanonical base pairs and unpaired residues, while also integrating data from chemical probing methods. Enhanced features include an improved analysis of folding trajectories, offering advanced clustering options and multiple analyses of the generated trajectories. These updates provide comprehensive tools for detailed RNA structure analysis. SimRNAweb v2.0 significantly broadens the scope of RNA modeling, emphasizing flexibility and user-defined parameter control. The web server is available at https://genesilico.pl/SimRNAweb.

Conserved structures and dynamics in 5'-proximal regions of Betacoronavirus RNA genomes.

Betacoronaviruses are a genus within the Coronaviridae family of RNA viruses. They are capable of infecting vertebrates and causing epidemics as well as global pandemics in humans. Mitigating the threat posed by Betacoronaviruses requires an understanding of their molecular diversity. The development of novel antivirals hinges on understanding the key regulatory elements within the viral RNA genomes, in particular the 5'-proximal region, which is pivotal for viral protein synthesis. Using a combination of cryo-electron microscopy, atomic force microscopy, chemical probing, and computational modeling, we determined the structures of 5'-proximal regions in RNA genomes of Betacoronaviruses from four subgenera: OC43-CoV, SARS-CoV-2, MERS-CoV, and Rousettus bat-CoV. We obtained cryo-electron microscopy maps and determined atomic-resolution models for the stem-loop-5 (SL5) region at the translation start site and found that despite low sequence similarity and variable length of the helical elements it exhibits a remarkable structural conservation. Atomic force microscopy imaging revealed a common domain organization and a dynamic arrangement of structural elements connected with flexible linkers across all four Betacoronavirus subgenera. Together, these results reveal common features of a critical regulatory region shared between different Betacoronavirus RNA genomes, which may allow targeting of these RNAs by broad-spectrum antiviral therapeutics.

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA.

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, whereas others, e.g. bacterial riboswitches or viral RNA motifs are considered as potential therapeutic targets. Thus, the continuous discovery of new functional RNA increases the demand for developing compounds targeting them and for methods for analyzing RNA-small molecule interactions. We recently developed fingeRNAt-a software for detecting non-covalent bonds formed within complexes of nucleic acids with different types of ligands. The program detects several non-covalent interactions and encodes them as structural interaction fingerprint (SIFt). Here, we present the application of SIFts accompanied by machine learning methods for binding prediction of small molecules to RNA. We show that SIFt-based models outperform the classic, general-purpose scoring functions in virtual screening. We also employed Explainable Artificial Intelligence (XAI)-the SHapley Additive exPlanations, Local Interpretable Model-agnostic Explanations and other methods to help understand the decision-making process behind the predictive models. We conducted a case study in which we applied XAI on a predictive model of ligand binding to human immunodeficiency virus type 1 trans-activation response element RNA to distinguish between residues and interaction types important for binding. We also used XAI to indicate whether an interaction has a positive or negative effect on binding prediction and to quantify its impact. Our results obtained using all XAI methods were consistent with the literature data, demonstrating the utility and importance of XAI in medicinal chemistry and bioinformatics.

A comprehensive survey of long-range tertiary interactions and motifs in non-coding RNA structures.

Understanding the 3D structure of RNA is key to understanding RNA function. RNA 3D structure is modular and can be seen as a composition of building blocks of various sizes called tertiary motifs. Currently, long-range motifs formed between distant loops and helical regions are largely less studied than the local motifs determined by the RNA secondary structure. We surveyed long-range tertiary interactions and motifs in a non-redundant set of non-coding RNA 3D structures. A new dataset of annotated LOng-RAnge RNA 3D modules (LORA) was built using an approach that does not rely on the automatic annotations of non-canonical interactions. An original algorithm, ARTEM, was developed for annotation-, sequence- and topology-independent superposition of two arbitrary RNA 3D modules. The proposed methods allowed us to identify and describe the most common long-range RNA tertiary motifs. Along with the prevalent canonical A-minor interactions, a large number of previously undescribed staple interactions were observed. The most frequent long-range motifs were found to belong to three main motif families: planar staples, tilted staples, and helical packing motifs.

RNA 3D structure modeling by fragment assembly with small-angle X-ray scattering restraints.

SUMMARY: Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the small-angle X-ray scattering experiments. We present RNA Masonry, a computer program and a web service for a fully automated modeling of RNA 3D structures. It assemblies RNA fragments into geometrically plausible models that meet user-provided secondary structure constraints, restraints on tertiary contacts, and small-angle X-ray scattering data. We illustrate the method description with detailed benchmarks and its application to structural studies of viral RNAs with SAXS restraints. AVAILABILITY AND IMPLEMENTATION: The program web server is available at http://iimcb.genesilico.pl/rnamasonry. The source code is available at https://gitlab.com/gchojnowski/rnamasonry.

DNAzymeBuilder, a web application for in situ generation of RNA/DNA-cleaving deoxyribozymes.

Nucleic acid cleaving DNAzymes are versatile and robust catalysts that outcompete ribozymes and protein enzymes in terms of chemical stability, affordability and ease to synthesize. In spite of their attractiveness, the choice of which DNAzyme should be used to cleave a given substrate is far from obvious, and requires expert knowledge as well as in-depth literature scrutiny. DNAzymeBuilder enables fast and automatic assembly of DNAzymes for the first time, superseding the manual design of DNAzymes. DNAzymeBuilder relies on an internal database with information on RNA and DNA cleaving DNAzymes, including the reaction conditions under which they best operate, their kinetic parameters, the type of cleavage reaction that is catalyzed, the specific sequence that is recognized by the DNAzyme, the cleavage site within this sequence, and special design features that might be necessary for optimal activity of the DNAzyme. Based on this information and the input sequence provided by the user, DNAzymeBuilder provides a list of DNAzymes to carry out the cleavage reaction and detailed information for each of them, including the expected yield, reaction products and optimal reaction conditions. DNAzymeBuilder is a resource to help researchers introduce DNAzymes in their day-to-day research, and is publicly available at https://iimcb.genesilico.pl/DNAzymeBuilder.

MODOMICS: a database of RNA modification pathways. 2021 update.

The MODOMICS database has been, since 2006, a manually curated and centralized resource, storing and distributing comprehensive information about modified ribonucleosides. Originally, it only contained data on the chemical structures of modified ribonucleosides, their biosynthetic pathways, the location of modified residues in RNA sequences, and RNA-modifying enzymes. Over the years, prompted by the accumulation of new knowledge and new types of data, it has been updated with new information and functionalities. In this new release, we have created a catalog of RNA modifications linked to human diseases, e.g., due to mutations in genes encoding modification enzymes. MODOMICS has been linked extensively to RCSB Protein Data Bank, and sequences of experimentally determined RNA structures with modified residues have been added. This expansion was accompanied by including nucleotide 5'-monophosphate residues. We redesigned the web interface and upgraded the database backend. In addition, a search engine for chemically similar modified residues has been included that can be queried by SMILES codes or by drawing chemical molecules. Finally, previously available datasets of modified residues, biosynthetic pathways, and RNA-modifying enzymes have been updated. Overall, we provide users with a new, enhanced, and restyled tool for research on RNA modification. MODOMICS is available at https://iimcb.genesilico.pl/modomics/.