Evidence map›Paper›PMID 31375637›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Sequence-dependent RNA helix conformational preferences predictably impact tertiary structure formation.

Joseph D Yesselman, Sarah K Denny, Namita Bisaria, Daniel Herschlag, William J Greenleaf, Rhiju Das

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Non-Enzymatic MGO-Glycation of SRSF2 Drives RNA Mis-Splicing.Journal of the American Chemical Society · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment.Journal of chemical information and modeling · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  17. Article
  18. Automated 3D Design and Evaluation of RNA Nanostructures with RNAMake.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  19. Review
  20. Measuring thermodynamic preferences to form non-native conformations in nucleic acids using ultraviolet melting.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Joseph D YesselmanDepartment of Biochemistry, Stanford University, Stanford, CA 94305.
Sarah K DennyProgram in Biophysics, Stanford University, Stanford, CA 94305.
Namita BisariaDepartment of Biochemistry, Stanford University, Stanford, CA 94305.
Daniel HerschlagDepartment of Biochemistry, Stanford University, Stanford, CA 94305; herschla@stanford.edu wjg@stanford.edu rhiju@stanford.edu.ORCID 0000-0002-4685-1973
William J GreenleafProgram in Biophysics, Stanford University, Stanford, CA 94305; herschla@stanford.edu wjg@stanford.edu rhiju@stanford.edu.ORCID 0000-0003-1409-3095
Rhiju DasDepartment of Biochemistry, Stanford University, Stanford, CA 94305; herschla@stanford.edu wjg@stanford.edu rhiju@stanford.edu.ORCID 0000-0001-7497-0972
Stanford University · USChan Zuckerberg Initiative (United States) · US

Funding

Time-resolved small angle X-ray scatteringP01GM066275 · NIGMS · STANFORD UNIVERSITY · PI HERSCHLAG, DANIEL · 2003 to 2017
$17.8M
Molecular Biophysics Training Program at StanfordT32GM008294 · NIGMS · STANFORD UNIVERSITY · PI HUANG, KERWYN C. · 1989 to 2019
$7.4M
Next-generation computational/chemical methods for complex RNA structuresR35GM122579 · NIGMS · STANFORD UNIVERSITY · PI Rhiju Das · 2017 to 2026
$7.2M
Internet-scale discovery of RNA bioengineering rulesR01GM100953 · NIGMS · STANFORD UNIVERSITY · PI DAS, RHIJU · 2012 to 2015
$1.8M
High-resolution modeling of protein-RNA interfacesR01GM121487 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BRADLEY, PHILIP · 2017 to 2020
$1.7M
Quantitative high-throughput nucleic acid assays on a sequencing chipR01GM111990 · NIGMS · STANFORD UNIVERSITY · PI GREENLEAF, WILLIAM JAMES · 2014 to 2018
$1.5M
Toward Atomic-Accuracy Design of Functional RNAsF32GM112294 · NIGMS · STANFORD UNIVERSITY · PI YESSELMAN, JOSEPH · 2015 to 2017
$113k
NIGMS NIH HHS F32 GM112294NIGMS NIH HHS P01 GM066275NIGMS NIH HHS R01 GM100953NIGMS NIH HHS R01 GM111990NIGMS NIH HHS R01 GM121487NIGMS NIH HHS R35 GM122579NIGMS NIH HHS T32 GM008294
6 · The paper itself

Abstract

Structured RNAs and RNA complexes underlie biological processes ranging from control of gene expression to protein translation. Approximately 50% of nucleotides within known structured RNAs are folded into Watson-Crick (WC) base pairs, and sequence changes that preserve these pairs are typically assumed to preserve higher-order RNA structure and binding of macromolecule partners. Here, we report that indirect effects of the helix sequence on RNA tertiary stability are, in fact, significant but are nevertheless predictable from a simple computational model called RNAMake-∆∆G. When tested through the RNA on a massively parallel array (RNA-MaP) experimental platform, blind predictions for >1500 variants of the tectoRNA heterodimer model system achieve high accuracy (rmsd 0.34 and 0.77 kcal/mol for sequence and length changes, respectively). Detailed comparison of predictions to experiments support a microscopic picture of how helix sequence changes subtly modulate conformational fluctuations at each base-pair step, which accumulate to impact RNA tertiary structure stability. Our study reveals a previously overlooked phenomenon in RNA structure formation and provides a framework of computation and experiment for understanding helix conformational preferences and their impact across biological RNA and RNA-protein assemblies.

Indexed as

Nucleic Acid ConformationBase PairingBase SequenceModels, MolecularRNARNA StabilityThermodynamicsRNAblind predictionhigh-throughput dataindirect readoutRNA energetics

Identifiers

PMID31375637
PMCPMC6708322
OpenAlexW2966848333

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.