ArticleProteins2021
Assessing the utility of CASP14 models for molecular replacement.
Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
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Who cites it
44 citing papers in PubMed, 62 citations in OpenAlex.
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- CASP16 Protein Monomer Structure Prediction Assessment.Proteins · 2026Article
- Model Quality Assessment for CASP16.Proteins · 2026Article
- Article
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- SFCalculator: connecting deep generative models and crystallography.bioRxiv : the preprint server for biology · 2025Article
- The success rate of processed predicted models in molecular replacement: implications for experimental phasing in the AlphaFold era.Acta crystallographica. Section D, Structural biology · 2024Article
- The Nobel Prize in Chemistry: past, present, and future of AI in biology.Communications biology · 2024Article
- Utilizing anomalous signals for element identification in macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2024Article
- Artificial Intelligence Learns Protein Prediction.Cold Spring Harbor perspectives in biology · 2024Review
- AlphaFold two years on: Validation and impact.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- AlphaFold and Protein Folding: Not Dead Yet! The Frontier Is Conformational Ensembles.Annual review of biomedical data science · 2024Review
- A predicted model-aided reconstruction algorithm for X-ray free-electron laser single-particle imaging.IUCrJ · 2024Article
- Deep learning applications in protein crystallography.Acta crystallographica. Section A, Foundations and advances · 2024Review
- Tertiary structure assessment at CASP15.Proteins · 2023Article
- DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function.Bioinformatics (Oxford, England) · 2023Article
- Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15.Communications chemistry · 2023Article
- Predicted models and CCP4.Acta crystallographica. Section D, Structural biology · 2023Article
- AlphaFold and the future of structural biology.Acta crystallographica. Section F, Structural biology communications · 2023Article
- AlphaFold and the future of structural biology.IUCrJ · 2023Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 4 countries.
Funding
Abstract
The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.
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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.