RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.
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http://dx.doi.org/10.1371/journal.pcbi.1006222 | DOI Listing |
Unlabelled: Structural RNAs exhibit a vast array of recurrent short 3D elements involving non-Watson-Crick interactions that help arrange canonical double helices into tertiary structures. We present CaCoFold-R3D, a probabilistic grammar that predicts these RNA 3D motifs (also termed modules) jointly with RNA secondary structure over a sequence or alignment. CaCoFold-R3D uses evolutionary information present in an RNA alignment to reliably identify canonical helices (including pseudoknots) by covariation.
View Article and Find Full Text PDFExoribonuclease-resistant RNAs (xrRNAs) are viral RNA structures that block degradation by cellular 5'-3' exoribonucleases to produce subgenomic viral RNAs during infection. Initially discovered in flaviviruses, xrRNAs have since been identified in wide range of RNA viruses, including those that infect plants. High sequence variability among viral xrRNAs raises questions about the shared molecular features that characterize this functional RNA class.
View Article and Find Full Text PDFPLoS Pathog
December 2024
The Pirbright Institute, Ash Road, Pirbright, Surrey, United Kingdom.
Virus assembly is a crucial step for the completion of the viral replication cycle. In addition to ensuring efficient incorporation of viral genomes into nascent virions, high specificity is required to prevent incorporation of host nucleic acids. For picornaviruses, including FMDV, the mechanisms required to fulfil these requirements are not well understood.
View Article and Find Full Text PDFJ Comput Biol
January 2025
Laboratoire d'Informatique de Bourgogne, Université de Bourgogne, Dijon Cedex, France.
An is a subset of arcs in matchings, such that the corresponding starting points are consecutive, and the same holds for the ending points. Such patterns are in one-to-one correspondence with the permutations. We focus on the occurrence frequency of such patterns in matchings and native (real-world) RNA structures with pseudoknots.
View Article and Find Full Text PDFBioinformatics
December 2024
Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta T6G 1H9, Canada.
Motivation: Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithms that minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As the most prominent example, McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization.
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