ArticleProteins2021
Assessment of prediction methods for protein structures determined by NMR in CASP14: Impact of AlphaFold2.
Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 51 citations in OpenAlex.
- Several multiple sequence alignment-perturbing methods enhance AlphaFold3 sampling of alternative protein states.Communications chemistry · 2026Article
- Hidden structural states of proteins revealed by conformer selection.Nature communications · 2026Article
- Predicting Pose Distribution of Protein Domains Connected by Flexible Linkers Is an Unsolved Problem.Proteins · 2026Article
- From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.Current protein & peptide science · 2026Review
- Memorization bias impacts modeling of alternative conformational states of solute carrier membrane proteins with methods from deep learning.PLoS computational biology · 2025Article
- Modeling protein conformational ensembles by guiding AlphaFold2 with Double Electron Electron Resonance (DEER) distance distributions.Nature communications · 2025Article
- Memorization Bias Impacts Modeling of Alternative Conformational States of Symmetric Solute Carrier Membrane Proteins with Methods from Deep Learning.bioRxiv : the preprint server for biology · 2025Article
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- Small Disulfide Proteins with Antifungal Impact: NMR Experimental Structures as Compared to Models of Alphafold Versions.International journal of molecular sciences · 2025Article
- A Structural Model of Truncated Gaussia princeps Luciferase Elucidating the Crucial Catalytic Function of No.76 Arginine towards Coelenterazine Oxidation.PLoS computational biology · 2025Article
- Secondary Structure in Free and Assisted Modeling of Proteins with the Coarse-Grained UNRES Force Field.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Integrative Modeling of Protein-Polypeptide Complexes by Bayesian Model Selection using AlphaFold and NMR Chemical Shift Perturbation Data.bioRxiv : the preprint server for biology · 2024Article
- Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies.Structural dynamics (Melville, N.Y.) · 2024Article
- Article
- Representing structures of the multiple conformational states of proteins.Current opinion in structural biology · 2023Review
- Alanine Scanning of the Unstructured Region of Ara h 2 and of a Related Mimotope Reveals Critical Amino Acids for IgE Binding.Molecular nutrition & food research · 2023Article
- Artificial intelligence and the analysis of cryo-EM data provide structural insight into the molecular mechanisms underlying LN-lamininopathies.Scientific reports · 2023Article
- Experimental NOE, Chemical Shift, and Proline Isomerization Data Provide Detailed Insights into Amelotin Oligomerization.Journal of the American Chemical Society · 2023Article
- Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2023Article
- The opportunities and challenges posed by the new generation of deep learning-based protein structure predictors.Current opinion in structural biology · 2023Review
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Authors and funding
15 authors at 9 institutions in 4 countries.
Funding
Abstract
NMR studies can provide unique information about protein conformations in solution. In CASP14, three reference structures provided by solution NMR methods were available (T1027, T1029, and T1055), as well as a fourth data set of NMR-derived contacts for an integral membrane protein (T1088). For the three targets with NMR-based structures, the best prediction results ranged from very good (GDT_TS = 0.90, for T1055) to poor (GDT_TS = 0.47, for T1029). We explored the basis of these results by comparing all CASP14 prediction models against experimental NMR data. For T1027, NMR data reveal extensive internal dynamics, presenting a unique challenge for protein structure prediction methods. The analysis of T1029 motivated exploration of a novel method of "inverse structure determination," in which an AlphaFold2 model was used to guide NMR data analysis. NMR data provided to CASP predictor groups for target T1088, a 238-residue integral membrane porin, was also used to assess several NMR-assisted prediction methods. Most groups involved in this exercise generated similar beta-barrel models, with good agreement with the experimental data. However, as was also observed in CASP13, some pure prediction groups that did not use any NMR data generated models for T1088 that better fit the NMR data than the models generated using these experimental data. These results demonstrate the remarkable power of modern methods to predict structures of proteins with accuracies rivaling solution NMR structures, and that it is now possible to reliably use prediction models to guide and complement experimental NMR data analysis.
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