ArticleProteins2021
Assessment of the CASP14 assembly predictions.
Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Biomolecular Interaction Prediction in the Pre- and Post-AlphaFold Era: The 8th CAPRI Evaluation.Proteins · 2026Article
- Improving protein and protein interactions using pseudo-dimers derived from monomeric proteins.Nature communications · 2026Article
- Reciprocal best matching: a new pipeline for scoring models with unknown stoichiometry in CASP experiments.BMC bioinformatics · 2026Article
- A fully automated benchmarking suite to compare macromolecular complexes.Nature methods · 2026Review
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- BDM: An Assessment Metric for Protein Complex Structure Models Based on Distance Difference Matrix.Interdisciplinary sciences, computational life sciences · 2024Article
- Review and Comparative Analysis of Methods and Advancements in Predicting Protein Complex Structure.Interdisciplinary sciences, computational life sciences · 2024Review
- CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2.Nature methods · 2024Article
- Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data.Nature methods · 2024Article
- Exploring the Alternative Conformation of a Known Protein Structure Based on Contact Map Prediction.Journal of chemical information and modeling · 2024Article
- Free-Docking and Template-Based Docking: Physics Versus Knowledge-Based Docking.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The impact of AI-based modeling on the accuracy of protein assembly prediction: Insights from CASP15.Proteins · 2023Article
- CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps.Proteins · 2023Article
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- The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated bioinformatics tools.The journal of allergy and clinical immunology. Global · 2023Article
- Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies.Current atherosclerosis reports · 2023Review
- Assessment of three-dimensional RNA structure prediction in CASP15.bioRxiv : the preprint server for biology · 2023Article
- The Impact of AI-Based Modeling on the Accuracy of Protein Assembly Prediction: Insights from CASP15.bioRxiv : the preprint server for biology · 2023Article
- Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2023Article
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3 authors.
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Abstract
In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.
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