ArticleBiochemistry2013
Principles for understanding the accuracy of SHAPE-directed RNA structure modeling.
Article in Biochemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- De novo design of RNA pseudoknots with deep learning.bioRxiv : the preprint server for biology · 2026Article
- Exploring Secondary Structure Predictions for RNA-Targeted Drug Discovery: Power and Challenges.Journal of chemical information and modeling · 2026Article
- Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.bioRxiv : the preprint server for biology · 2023Article
- Predicting the Structure of a Viroid : Structure, Structure Distribution, Consensus Structure, and Structure Drawing.Methods in molecular biology (Clifton, N.J.) · 2022Article
- ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites.BMC bioinformatics · 2021Article
- Sieving RNA 3D Structures with SHAPE and Evaluating Mechanisms Driving Sequence-Dependent Reactivity Bias.The journal of physical chemistry. B · 2021Article
- On the Problem of Reconstructing a Mixture of RNA Structures.Bulletin of mathematical biology · 2020Article
- An RNA pseudoknot stimulates HTLV-1RNA (New York, N.Y.) · 2020Article
- Challenges and perspectives for structural biology of lncRNAs-the example of the Xist lncRNA A-repeats.Journal of molecular cell biology · 2019Article
- High-throughput determination of RNA structures.Nature reviews. Genetics · 2018Review
- Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.The journal of physical chemistry. B · 2018Article
- Synergistic SHAPE/Single-Molecule Deconvolution of RNA Conformation under Physiological Conditions.Biophysical journal · 2018Article
- Characterization and visualization of RNA secondary structure Boltzmann ensemble via information theory.BMC bioinformatics · 2018Article
- Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations.Scientific reports · 2017Article
- Direct identification of base-paired RNA nucleotides by correlated chemical probing.RNA (New York, N.Y.) · 2017Article
- Transcending the prediction paradigm: novel applications of SHAPE to RNA function and evolution.Wiley interdisciplinary reviews. RNA · 2017Review
- Evolutionary Algorithm for RNA Secondary Structure Prediction Based on Simulated SHAPE Data.PloS one · 2016Article
- The RNA Domain Vc1 Regulates Downstream Gene Expression in Response to Cyclic Diguanylate in Vibrio cholerae.PloS one · 2016Article
- Computational analysis of RNA structures with chemical probing data.Methods (San Diego, Calif.) · 2015Review
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7 authors.
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Abstract
Accurate RNA structure modeling is an important, incompletely solved, challenge. Single-nucleotide resolution SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) yields an experimental measurement of local nucleotide flexibility that can be incorporated as pseudo-free energy change constraints to direct secondary structure predictions. Prior work from our laboratory has emphasized both the overall accuracy of this approach and the need for nuanced interpretation of modeled structures. Recent studies by Das and colleagues [Kladwang, W., et al. (2011) Biochemistry 50, 8049; Nat. Chem. 3, 954], focused on analyzing six small RNAs, yielded poorer RNA secondary structure predictions than expected on the basis of prior benchmarking efforts. To understand the features that led to these divergent results, we re-examined four RNAs yielding the poorest results in this recent work: tRNA(Phe), the adenine and cyclic-di-GMP riboswitches, and 5S rRNA. Most of the errors reported by Das and colleagues reflected nonstandard experiment and data processing choices, and selective scoring rules. For two RNAs, tRNA(Phe) and the adenine riboswitch, secondary structure predictions are nearly perfect if no experimental information is included but were rendered inaccurate by the SHAPE data of Das and colleagues. When best practices were used, single-sequence SHAPE-directed secondary structure modeling recovered ~93% of individual base pairs and >90% of helices in the four RNAs, essentially indistinguishable from the results of the mutate-and-map approach with the exception of a single helix in the 5S rRNA. The field of experimentally directed RNA secondary structure prediction is entering a phase focused on the most difficult prediction challenges. We outline five constructive principles for guiding this field forward.
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