Functional Relevance of <scp>CASP16</scp> Nucleic Acid Predictions as Evaluated by Structure Providers

Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Authors

Institutions

Publication Details

Journal
Proteins Structure Function and Bioinformatics
Published
2025-09-04
DOI
https://doi.org/10.1002/prot.70043
Citations
8
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
6.45

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

Heewhan Shin, Eric Largy, Cameron D. Mackereth, Jiahao Xie et al.
8 citations
Proteins Structure Function and Bioinformatics
RNA and protein synthesis mechanisms
6.45
article

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

Heewhan Shin, Eric Largy, Cameron D. Mackereth, Jiahao Xie, Emil L. Kristoffersen, Yoshita Srivastava, John Moult, Anna Lewicka, Michela Nigro, Claudia Höbartner, Phoebe A. Rice, Anna‐Lena Steckelberg, Manju Ojha, Andriy Kryshtafovych, Wah Chiu, Rachael C. Kretsch, Ebbe Sloth Andersen, Hsuan‐Ai Chen, Jeanine Gezelle, Marcus D. Hartmann, Deepak Koirala, Marco Marcia, Shekhar Jadhav, Rhiju Das, Philip E. Johnson, Zhaoming Su, Joseph A. Piccirilli, Liu Wang, Yimin Hu, Christopher P. Jones, Yuan Wu, Reinhard Albrecht, Nikolaj H. Zwergius
article en
8 citations

Abstract

Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Proteins Structure Function and BioinformaticsVol. 94(1)
Uppsala University (SE), Centre National de la Recherche Scientifique (FR), Howard Hughes Medical Institute (US), Université de Bordeaux (FR), Inserm (FR), York University (CA), Aarhus University (DK), Chengdu Medical College (CN), Sichuan University (CN), University of Würzburg (DE), Science for Life Laboratory (SE), SLAC National Accelerator Laboratory (US), Italian Institute of Technology (IT), University of Chicago (US), West China Hospital of Sichuan University (CN), Bordeaux Population Health (FR), National Heart, Lung, and Blood Institute (US), European Molecular Biology Laboratory (FR), National Clinical Research (US), Stomatology Hospital (CN), Research Institute for Bioscience and Biotechnology (NP), Advanced Bioscience Laboratories (United States) (US), Max Planck Institute for Biology (DE), Acides nucléiques: Régulations naturelles et artificielles (FR), Institute for Bioscience and Biotechnology Research, Columbia University (US), University of Maryland, Baltimore County (US), University of Tübingen (DE), University of California, Davis (US), University of Bologna (IT), Stanford University (US)
National Science Foundation, Howard Hughes Medical Institute, U.S. Department of Energy, Aarhus Universitet, Villum Fonden, European Commission, Deutsche Forschungsgemeinschaft, National Natural Science Foundation of China, Gottfried Wilhelm Leibniz Universität Hannover, Novo Nordisk, Novo Nordisk Fonden, National Institutes of Health, Office of Science, Stanford Bio-X, Natural Sciences and Engineering Research Council of Canada, Leibniz-Gemeinschaft, National Key Research and Development Program of China, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, Office of Research Infrastructure Programs, National Institutes of Health, Argonne National Laboratory, Common Fund
Openalex Percentile: Top 3%
RNA and protein synthesis mechanisms
6.45
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.