ArticleProteins2021
Assessment of domain interactions in the fourteenth round of the Critical Assessment of Structure Prediction (CASP14).
Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- CASP16 Protein Monomer Structure Prediction Assessment.Proteins · 2026Article
- Article
- New insights into GATOR2-dependent interactions and its conformational changes in amino acid sensing.Bioscience reports · 2024Article
- The ubiquitin E3 ligase BFAR promotes degradation of PNPLA3.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target.Molecules (Basel, Switzerland) · 2022Article
- Modeling of protein conformational changes with Rosetta guided by limited experimental data.Structure (London, England : 1993) · 2022Article
- Structural validation and assessment of AlphaFold2 predictions for centrosomal and centriolar proteins and their complexes.Communications biology · 2022Article
- Article
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4 authors.
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Abstract
The high accuracy of some CASP14 models at the domain level prompted a more detailed evaluation of structure predictions on whole targets. For the first time in critical assessment of structure prediction (CASP), we evaluated accuracy of difficult domain assembly in models submitted for multidomain targets where the community predicted individual evaluation units (EUs) with greater accuracy than full-length targets. Ten proteins with domain interactions that did not show evidence of conformational change and were not involved in significant oligomeric contacts were chosen as targets for the domain interaction assessment. Groups were ranked using complementary interaction scores (F1, QS score, and Jaccard coefficient), and their predictions were evaluated for their ability to correctly model inter-domain interfaces and overall protein folds. Target performance was broadly grouped into two clusters. The first consisted primarily of targets containing two EUs wherein predictors more broadly predicted domain positioning and interfacial contacts correctly. The other consisted of complex two-EU and three-EU targets where few predictors performed well. The highest ranked predictor, AlphaFold2, produced high-accuracy models on eight out of 10 targets. Their interdomain scores on three of these targets were significantly higher than all other groups and were responsible for their overall outperformance in the category. We further highlight the performance of AlphaFold2 and the next best group, BAKER-experimental on several interesting targets.
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