ArticleNucleic acids research2021
Characteristic chemical probing patterns of loop motifs improve prediction accuracy of RNA secondary structures.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Markov models of SHAPE data improve secondary structure prediction.bioRxiv : the preprint server for biology · 2026Article
- Consistent features observed in structural probing data of eukaryotic RNAs.NAR genomics and bioinformatics · 2025Article
- 2'-OH as a universal handle for studying intracellular RNAs.Cell chemical biology · 2024Review
- Molecular Dynamics Simulations with Grand-Canonical Reweighting Suggest Cooperativity Effects in RNA Structure Probing Experiments.Journal of chemical theory and computation · 2023Article
- Diverse Reagent Scaffolds Provide Differential Selectivity of 2'-OH Acylation in RNA.Journal of the American Chemical Society · 2023Article
- Acylation probing of "generic" RNA libraries reveals critical influence of loop constraints on reactivity.Cell chemical biology · 2022Article
- Conjugation of RNAChemical communications (Cambridge, England) · 2022Article
- Accurate detection of RNA stem-loops in structurome data reveals widespread association with protein binding sites.RNA biology · 2021Article
- Potential Achilles heels of SARS-CoV-2 are best displayed by the base order-dependent component of RNA folding energy.Computational biology and chemistry · 2021Article
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2 authors.
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Abstract
RNA structures play a fundamental role in nearly every aspect of cellular physiology and pathology. Gaining insights into the functions of RNA molecules requires accurate predictions of RNA secondary structures. However, the existing thermodynamic folding models remain less accurate than desired, even when chemical probing data, such as selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) reactivities, are used as restraints. Unlike most SHAPE-directed algorithms that only consider SHAPE restraints for base pairing, we extract two-dimensional structural features encoded in SHAPE data and establish robust relationships between characteristic SHAPE patterns and loop motifs of various types (hairpin, internal, and bulge) and lengths (2-11 nucleotides). Such characteristic SHAPE patterns are closely related to the sugar pucker conformations of loop residues. Based on these patterns, we propose a computational method, SHAPELoop, which refines the predicted results of the existing methods, thereby further improving their prediction accuracy. In addition, SHAPELoop can provide information about local or global structural rearrangements (including pseudoknots) and help researchers to easily test their hypothesized secondary structures.
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