ArticleScience advances2018
Blind prediction of noncanonical RNA structure at atomic accuracy.
Article in Science advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Fast activity prediction of chemically modified siRNAs via structure-based energy calculations and inference-augmented tabular deep learning.Molecular therapy. Nucleic acids · 2026Article
- Integrated NMR/MD investigation reveals differences after reweighting in conformational ensembles of the GAAG and GCAA tetraloops.RNA (New York, N.Y.) · 2026Article
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- On the Completeness of Existing RNA Fragment Structures.Genomics, proteomics & bioinformatics · 2025Article
- RNA-Puzzles Round V: blind predictions of 23 RNA structures.Nature methods · 2025Article
- FRET-guided modeling of nucleic acids.Nucleic acids research · 2024Article
- Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA.RNA (New York, N.Y.) · 2023Article
- RNA 3D Modeling with FARFAR2, Online.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Computationally-guided design and selection of high performing ribosomal active site mutants.Nucleic acids research · 2022Article
- Ribosome-mediated biosynthesis of pyridazinone oligomers in vitro.Nature communications · 2022Article
- Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.Nature communications · 2021Article
- Progress toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure.Non-coding RNA · 2021Article
- Modeling Noncanonical RNA Base Pairs by a Coarse-Grained IsRNA2 Model.The journal of physical chemistry. B · 2021Article
- RNA Engineering for Public Health: Innovations in RNA-Based Diagnostics and Therapeutics.Annual review of chemical and biomolecular engineering · 2021Article
- Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement.Nature communications · 2021Article
- IsRNA1:Journal of chemical theory and computation · 2021Article
- In vitro selected GUAA tetraloop-binding receptors with structural plasticity and evolvability towards natural RNA structural modules.Nucleic acids research · 2021Article
- Prediction of the RNA Tertiary Structure Based on a Random Sampling Strategy and Parallel Mechanism.Frontiers in genetics · 2021Article
- FARFAR2: Improved De Novo Rosetta Prediction of Complex Global RNA Folds.Structure (London, England : 1993) · 2020Article
- Macromolecular modeling and design in Rosetta: recent methods and frameworks.Nature methods · 2020Review
Corrections and comments
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6 authors.
Funding
Abstract
Prediction of RNA structure from nucleotide sequence remains an unsolved grand challenge of biochemistry and requires distinct concepts from protein structure prediction. Despite extensive algorithmic development in recent years, modeling of noncanonical base pairs of new RNA structural motifs has not been achieved in blind challenges. We report a stepwise Monte Carlo (SWM) method with a unique add-and-delete move set that enables predictions of noncanonical base pairs of complex RNA structures. A benchmark of 82 diverse motifs establishes the method's general ability to recover noncanonical pairs ab initio, including multistrand motifs that have been refractory to prior approaches. In a blind challenge, SWM models predicted nucleotide-resolution chemical mapping and compensatory mutagenesis experiments for three in vitro selected tetraloop/receptors with previously unsolved structures (C7.2, C7.10, and R1). As a final test, SWM blindly and correctly predicted all noncanonical pairs of a Zika virus double pseudoknot during a recent community-wide RNA-Puzzle. Stepwise structure formation, as encoded in the SWM method, enables modeling of noncanonical RNA structure in a variety of previously intractable problems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.