NuFold RNA Structure Database: Large-Scale RNA Tertiary Structure Prediction with Confidence Metrics

Abstract

To bridge the gap between rapid RNA sequence discovery and slow experimental characterization, we present the NuFold RNA Structure Database (https://nufold.kiharalab.org/), a resource providing large-scale, precomputed full-atom RNA tertiary structures. By removing the computational barriers associated with running the method locally, this database makes high-accuracy RNA structure models readily accessible to the biological research community for a wide range of applications. Availability and implementation: All predicted structures and corresponding data are available at https://nufold.kiharalab.org/. The source code for the NuFold program is available at https://github.com/kiharalab/NuFold. Supplementary Information: For more insight into resulting statistics gathered for this project, see https://nufold.kiharalab.org/statistics. For more insight into how to utilize the webserver itself, see https://nufold.kiharalab.org/faq and https://nufold.kiharalab.org/tutorial.

CLSP-REQA: a real-time quality-aware closed-loop seizure prediction framework with Mamba-BiLSTM and confidence-gated intervention
Mufeng Chen, Qi Wu, Bingchao Huang +4
Frontiers in neuroinformatics16 Oct 2026Peer-reviewedCC BYFull textNeuroscienceEurope PMC
TAPAS: Learned integration of AlphaFold3 confidence and geometric features for TCR-pMHC binding prediction
H. Y. Kim, H. J. Han, D. Kim
bioRxiv8 Sep 2026PreprintCC BYFull textBioinformatics & computational biologybioRxiv
Selection-aware metrics provide complementary decision-level information in plant genomic prediction
Xueyang Wang, Jun Yan
Frontiers in plant science1 Oct 2026Peer-reviewedCC BYFull textGenetics & genomicsEurope PMCCrossref
FORGE audits residue-level information encoded in RNA tertiary structure geometry
L. Gow, J. Li, X. Tan +3
bioRxiv5 Jul 2026PreprintCC BY-NCFull textBioinformatics & computational biologybioRxiv
DSSNA: An Open-Source GROMACS Module for Automated Analysis of Nucleic Acid Secondary and Tertiary Structure in Molecular Dynamics Simulations
S. Gorelov, A. Konevega, A. Shvetsov
bioRxiv25 Sep 2026PreprintCC BY-NC-NDFull textBioinformatics & computational biologybioRxiv

Cite

BibTeX RIS

BibTeX

@misc{platt2026nufold,
  title = {{NuFold RNA Structure Database: Large-Scale RNA Tertiary Structure Prediction with Confidence Metrics}},
  author = {David Platt and Yuki Kagaya and Daisuke Kihara},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.21.760778},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.21.760778v1},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - NuFold RNA Structure Database: Large-Scale RNA Tertiary Structure Prediction with Confidence Metrics
AU  - David Platt
AU  - Yuki Kagaya
AU  - Daisuke Kihara
PY  - 2026
DA  - 2026/10/21
PB  - bioRxiv
DO  - 10.64898/2026.10.21.760778
UR  - https://www.biorxiv.org/content/10.64898/2026.10.21.760778v1
AB  - To bridge the gap between rapid RNA sequence discovery and slow experimental characterization, we present the NuFold RNA Structure Database (https://nufold.kiharalab.org/), a resource providing large-scale, precomputed full-atom RNA tertiary structures. By removing the computational barriers associated with running the method locally, this database makes high-accuracy RNA structure models readily accessible to the biological research community for a wide range of applications. Availability and implementation: All predicted structures and corresponding data are available at https://nufold.kiharalab.org/. The source code for the NuFold program is available at https://github.com/kiharalab/NuFold. Supplementary Information: For more insight into resulting statistics gathered for this project, see https://nufold.kiharalab.org/statistics. For more insight into how to utilize the webserver itself, see https://nufold.kiharalab.org/faq and https://nufold.kiharalab.org/tutorial.
SN  - 2692-8205
ER  -

Abstract

Related

Cite