ArticleProteins2023
Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15.
Article in Proteins, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Article
- The latest AI breakthroughs in structural biology: protein binder design and conformational state prediction.Communications biology · 2026Article
- A fully automated benchmarking suite to compare macromolecular complexes.Nature methods · 2026Review
- Updates to the CASP Infrastructure in 2024.Proteins · 2026Article
- AlphaFold3 at CASP16.Proteins · 2026Article
- Modeling Alternative Conformational States in CASP16.Proteins · 2026Article
- Predicting Pose Distribution of Protein Domains Connected by Flexible Linkers Is an Unsolved Problem.Proteins · 2026Article
- Progress and Bottlenecks for Deep Learning in Computational Structure Biology: CASP Round XVI.Proteins · 2026Article
- Article
- Blind prediction of complex water and ion ensembles around RNA in CASP16.bioRxiv : the preprint server for biology · 2025Article
- Modeling Alternative Conformational States in CASP16.bioRxiv : the preprint server for biology · 2025Article
- Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era.Briefings in bioinformatics · 2025Review
- Statistical Thermodynamics of the Protein Ensemble: Mediating Function and Evolution.Annual review of biophysics · 2025Review
- Emerging frontiers in protein structure prediction following the AlphaFold revolution.Journal of the Royal Society, Interface · 2025Review
- Tevenvirinae phages encode a family of LSm-like fold proteins.Computational and structural biotechnology journal · 2025Article
- AlphaFold2-Based Characterization of Apo and Holo Protein Structures and Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics and Ligand-Induced Conformational Changes.International journal of molecular sciences · 2024Article
- 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
- Predicting Mutation-Induced Allosteric Changes in Structures and Conformational Ensembles of the ABL Kinase Using AlphaFold2 Adaptations with Alanine Sequence Scanning.International journal of molecular sciences · 2024Article
- AlphaFold predictions of fold-switched conformations are driven by structure memorization.Nature communications · 2024Article
- AlphaFold2 has more to learn about protein energy landscapes.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
For the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community experiment included a section on computing multiple conformations for protein and RNA structures. There was full or partial success in reproducing the ensembles for four of the nine targets, an encouraging result. For protein structures, enhanced sampling with variations of the AlphaFold2 deep learning method was by far the most effective approach. One substantial conformational change caused by a single mutation across a complex interface was accurately reproduced. In two other assembly modeling cases, methods succeeded in sampling conformations near to the experimental ones even though environmental factors were not included in the calculations. An experimentally derived flexibility ensemble allowed a single accurate RNA structure model to be identified. Difficulties included how to handle sparse or low-resolution experimental data and the current lack of effective methods for modeling RNA/protein complexes. However, these and other obstacles appear addressable.
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Registered trials
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.