MOTIVATION: Ribonucleic acid (RNA) function is inherently linked to its 3D structure, traditionally determined by X-ray crystallography, Nuclear Magnetic Resonance, and Cryo-EM. However, these techniques often lack atomic-level resolution, highlighting the need for accurate in silico RNA structure prediction tools. Current state-of-the-art methods, such as AlphaFold3, Boltz1, RhoFold, or trRosettaRNA, rely on deep learning models that represent residues as frames and use transformers to learn relative positions. While effective for known RNA families, their performance drops for synthetic or novel families. RESULTS: In this work, we explore the potential of graph neural networks and denoising diffusion probabilistic models for learning interatomic interactions. We model RNA as a graph in a coarse-grained, five-atom representation and evaluate our approach on a dataset of small RNA substructures, known as local RNA descriptors, which recur even in non-homologous structures. Generalization is assessed using a dataset partitioned by RNA family: the training set consists of rRNA and tRNA structures, while the test set includes descriptors from all other families. Our results demonstrate that the proposed method reliably predicts the structures of unseen descriptors and effectively adheres to user-defined constraints, such as Watson-Crick-Franklin interactions. AVAILABILITY AND IMPLEMENTATION: The GraphaRNA source code is available on GitHub (github.com/mjustynaPhD/GraphaRNA); training/test datasets and pre-trained model weights are provided on Zenodo (zenodo.org/records/13750967).

MOTIVATION: The recent progress in RNA structure determination methods has resulted in a surge of newly solved RNA 3D structures. However, there is an absence of a user-friendly browser-based tool that can facilitate the comparison and visualization of RNA motifs across multiple 3D structures. RESULTS: We introduce R3DMCS, a web server that allows users to compare selected RNA nucleotides across all 3D structures of a given molecule from a given species, or across all 3D structures mapped to a single Rfam family. Starting from one instance of the motif, R3DMCS retrieves, aligns, annotates, organizes, and displays 3D coordinates of corresponding sets of nucleotides from other 3D structures. With R3DMCS, one can explore conformational changes of motifs due to 3D structures being solved in different functional states or different experimental conditions. One can also investigate conservation of 3D structure across species, or changes in 3D structure due to changes in sequence. AVAILABILITY AND IMPLEMENTATION: R3DMCS is open-source software and freely available at https://rna.bgsu.edu/correspondence/ and https://github.com/BGSU-RNA/RNA-3D-correspondence.

MOTIVATION: Comparing 3D structures of homologous RNA molecules yields information about sequence and structural variability. To compare large RNA 3D structures, accurate automatic comparison tools are needed. In this article, we introduce a new algorithm and web server to align large homologous RNA structures nucleotide by nucleotide using local superpositions that accommodate the flexibility of RNA molecules. Local alignments are merged to form a global alignment by employing a maximum clique algorithm on a specially defined graph that we call the 'local alignment' graph. RESULTS: The algorithm is implemented in a program suite and web server called 'R3D Align'. The R3D Align alignment of homologous 3D structures of 5S, 16S and 23S rRNA was compared to a high-quality hand alignment. A full comparison of the 16S alignment with the other state-of-the-art methods is also provided. The R3D Align program suite includes new diagnostic tools for the structural evaluation of RNA alignments. The R3D Align alignments were compared to those produced by other programs and were found to be the most accurate, in comparison with a high quality hand-crafted alignment and in conjunction with a series of other diagnostics presented. The number of aligned base pairs as well as measures of geometric similarity are used to evaluate the accuracy of the alignments. AVAILABILITY: R3D Align is freely available through a web server http://rna.bgsu.edu/R3DAlign. The MATLAB source code of the program suite is also freely available for download at that location.