Evidence map›Paper›PMID 35699952›Full record

ArticleJournal of chemical theory and computation2022

Automatic Learning of Hydrogen-Bond Fixes in the AMBER RNA Force Field.

Thorben Fröhlking, Vojtěch Mlýnský, Michal Janeček, Petra Kührová, Miroslav Krepl, Pavel Banáš, Jiří Šponer, Giovanni Bussi

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Reparameterization of the Amber RNA Force Field Non-Bonded Terms.bioRxiv : the preprint server for biology · 2026
    Article
  4. Making PLUMED Fly: A Tutorial on Optimizing Performance.The journal of physical chemistry. B · 2026
    Article
  5. Destabilization of Structured RNAs by OPC and TIP4PD Water Models.Journal of chemical theory and computation · 2026
    Article
  6. Article
  7. Article
  8. The Kink-Turn 7 Motif: An Additional Test for RNA Force Field Performance.Journal of chemical theory and computation · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

8 authors.

Thorben FröhlkingScuola Internazionale Superiore di Studi Avanzati, via Bonomea 265, Trieste 34136, Italy.
Vojtěch MlýnskýInstitute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, Brno 612 65, Czech Republic.ORCID 0000-0003-2769-1553
Michal JanečekDepartment of Physical Chemistry, Faculty of Science, Palacky University, tr. 17 listopadu 12, Olomouc 771 46, Czech Republic.ORCID 0000-0003-4599-2640
Petra KührováRegional Centre of Advanced Technologies and Materials, Czech Advanced Technology and Research Institute (CATRIN), Palacky University Olomouc, Slechtitelu 27, 779 00 Olomouc, Czech Republic.ORCID 0000-0003-1593-5282
Miroslav KreplInstitute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, Brno 612 65, Czech Republic.ORCID 0000-0002-9833-4281
Pavel BanášRegional Centre of Advanced Technologies and Materials, Czech Advanced Technology and Research Institute (CATRIN), Palacky University Olomouc, Slechtitelu 27, 779 00 Olomouc, Czech Republic.ORCID 0000-0002-7137-8225
Jiří ŠponerInstitute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, Brno 612 65, Czech Republic.ORCID 0000-0001-6558-6186
Giovanni BussiScuola Internazionale Superiore di Studi Avanzati, via Bonomea 265, Trieste 34136, Italy.ORCID 0000-0001-9216-5782

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The capability of current force fields to reproduce RNA structural dynamics is limited. Several methods have been developed to take advantage of experimental data in order to enforce agreement with experiments. Here, we extend an existing framework which allows arbitrarily chosen force-field correction terms to be fitted by quantification of the discrepancy between observables back-calculated from simulation and corresponding experiments. We apply a robust regularization protocol to avoid overfitting and additionally introduce and compare a number of different regularization strategies, namely, L1, L2, Kish size, relative Kish size, and relative entropy penalties. The training set includes a GACC tetramer as well as more challenging systems, namely, gcGAGAgc and gcUUCGgc RNA tetraloops. Specific intramolecular hydrogen bonds in the AMBER RNA force field are corrected with automatically determined parameters that we call gHBfix

Indexed as

Molecular Dynamics SimulationRNAHydrogenHydrogen BondingRNA, RibosomalHydrogenRNARNA, Ribosomal

Identifiers

PMID35699952
PMCPMC9281393

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LicenceCC BY
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Registered trials

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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.