Assessment of three-dimensional RNA structure prediction in CASP15.
CASP15
conformational ensembles
cryogenic electron microscopy
deep learning
molecular replacement
ribonucleic acid
structure prediction
Journal
Proteins
ISSN: 1097-0134
Titre abrégé: Proteins
Pays: United States
ID NLM: 8700181
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
revised:
21
08
2023
received:
25
04
2023
accepted:
07
09
2023
medline:
24
11
2023
pubmed:
25
10
2023
entrez:
25
10
2023
Statut:
ppublish
Résumé
The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty-two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and x-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as noncanonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.
Substances chimiques
RNA
63231-63-0
Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1747-1770Subventions
Organisme : NIH HHS
ID : R35 GM122579
Pays : United States
Organisme : NIH HHS
ID : R35 GM122579
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/S007105/1
Pays : United Kingdom
Commentaires et corrections
Type : UpdateOf
Informations de copyright
© 2023 The Authors. Proteins: Structure, Function, and Bioinformatics published by Wiley Periodicals LLC.
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