The structural diversity of nucleic acids extends far beyond the canonical Watson-Crick base pairing, encompassing higher-order motifs, such as triads, tetrads, pentads, hexads, heptads, and octads, which play critical roles in genome regulation and stability. Among these, tetrads - forming the core of G-quadruplexes - and their polyadic extensions have emerged as key determinants in fundamental processes ranging from replication and transcription to telomere maintenance. However, the detection and characterization of these complex motifs in experimental structures remain challenging. To address this, we present LinkTetrado, a computational tool for the automated identification and classification of polyadic motifs in nucleic acid 3D structures. Applied to a curated dataset of 529 nucleic acid structures, LinkTetrado identified 25 unique structures containing such motifs, including previously unreported pentads, hexads, heptads, and octads in both DNA and RNA. Manual validation using NMR restraints and chemical shift data confirmed the accuracy of motif assignments and underscored the importance of integrating experimental evidence for reliable detection. LinkTetrado achieves a precision of 0.87 in identifying polyads. The tool is freely available at https://github.com/michal-zurkowski/linktetrado and provides a foundation for the systematic exploration of higher-order nucleic acid motifs.

MOTIVATION: Tertiary structure alignment is one of the main challenges in the computer-aided comparative study of molecular structures. Its aim is to optimally overlay the 3D shapes of two or more molecules in space to find the correspondence between their nucleotides. Alignment is the starting point for most algorithms that assess structural similarity or find common substructures. Thus, it has applications in solving a variety of bioinformatics problems, e.g. in the search for structural patterns, structure clustering, identifying structural redundancy, and evaluating the prediction accuracy of 3D models. To date, several tools have been developed to align 3D structures of RNA. However, most of them are not applicable to arbitrarily large structures and do not allow users to parameterize the optimization algorithm. RESULTS: We present two customizable heuristics for flexible alignment of 3D RNA structures, geometric search (GEOS), and genetic algorithm (GENS). They work in sequence-dependent/independent mode and find the suboptimal alignment of expected quality (below a predefined RMSD threshold). We compare their performance with those of state-of-the-art methods for aligning RNA structures. We show the results of quantitative and qualitative tests run for all of these algorithms on benchmark sets of RNA structures. AVAILABILITY AND IMPLEMENTATION: Source codes for both heuristics are hosted at https://github.com/RNApolis/rnahugs.

MOTIVATION: Quadruplexes are specific 3D structures found in nucleic acids. Due to the exceptional properties of these motifs, their exploration with the general-purpose bioinformatics methods can be problematic or insufficient. The same applies to visualizing their structure. A hand-drawn layer diagram is the most common way to represent the quadruplex anatomy. No molecular visualization software generates such a structural model based on atomic coordinates. RESULTS: DrawTetrado is an open-source Python program for automated visualization targeting the structures of quadruplexes and G4-helices. It generates static layer diagrams that represent structural data in a pseudo-3D perspective. The possibility to set color schemes, nucleotide labels, inter-element distances or angle of view allows for easy customization of the output drawing. AVAILABILITY AND IMPLEMENTATION: The program is available under the MIT license at https://github.com/RNApolis/drawtetrado.

Motivation: Understanding the formation, architecture and roles of pseudoknots in RNA structures are one of the most difficult challenges in RNA computational biology and structural bioinformatics. Methods predicting pseudoknots typically perform this with poor accuracy, often despite experimental data incorporation. Existing bioinformatic approaches differ in terms of pseudoknots' recognition and revealing their nature. A few ways of pseudoknot classification exist, most common ones refer to a genus or order. Following the latter one, we propose new algorithms that identify pseudoknots in RNA structure provided in BPSEQ format, determine their order and encode in dot-bracket-letter notation. The proposed encoding aims to illustrate the hierarchy of RNA folding. Results: New algorithms are based on dynamic programming and hybrid (combining exhaustive search and random walk) approaches. They evolved from elementary algorithm implemented within the workflow of RNA FRABASE 1.0, our database of RNA structure fragments. They use different scoring functions to rank dissimilar dot-bracket representations of RNA structure. Computational experiments show an advantage of new methods over the others, especially for large RNA structures. Availability and implementation: Presented algorithms have been implemented as new functionality of RNApdbee webserver and are ready to use at http://rnapdbee.cs.put.poznan.pl. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.