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Cited by 289

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations

Open access
Chen, Alan A., García, Angel E.·2013·Proceedings of the National Academy of Sciences

Abstract

Significance: We report atomistic simulations describing the spontaneous folding of three RNA tetraloops from the unfolded state to within 1–3 Å of their experimentally determined structures. These common and highly stable motifs serve as building blocks for large structured RNA molecules. This success is caused by the reparameterization of the energy function used to describe the interatomic interactions, which was obtained by calibrating the energy function to reproduce known thermodynamic and kinetic measurements of RNA monomers and dimers. In particular, the accurate recapitulation of the characteristic loop configurations responsible for the thermodynamic hyperstability of these motifs represents a significant milestone to the accurate description of RNA tertiary structure using unbiased all-atom molecular dynamics simulations.

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Crossref · 10.1073/pnas.1309392110

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Metadata

Authors
Chen, A. A., & García, A. E.
Venue
Proceedings of the National Academy of Sciences
Published
2013-09-16
Volume
110
Issue
42
Pages
16820-16825
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2038354555
Cited by
289
References
36
FWCI
12.24
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations. https://app.cochat.ai/papers/10.1073/pnas.1309392110
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Chen, A. A., & García, A. E. (2013). High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1309392110

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.