Assessment of the CASP14 assembly predictions
Open accessAbstract
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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No group participating in CASP14 provided a correct model of the H1072 complex.
“No group participating in the CASP14 competition provided a correct model of the complex36.”
From AF2Complex predicts direct physical interactions in multimeric proteins with deep learning (2022) · cites this paper as [36]
Overall progress in protein complex modeling this round from the previous CASP is small.
“Although overall progress this round from the previous CASP is small3, there is excitement as to what will happen next time, for several reasons.”
From Critical assessment of methods of protein structure prediction (CASP)—Round <scp>XIV</scp> (2021) · cites this paper as [3]
Analysis by the CASP assessor Ezgi Karaca showed that at least two of the other CASP14 targets undergo substantial conformational changes on complex formation (targets T1061 and T1070).
“As noted earlier, intertwining was a problem for accurate modeling of bacterial flagellum subunit, and an analysis by the CASP assessor Ezgi Karaca3 showed that at least two of the other CASP14 targets undergo substantial conformational changes on complex formation (targets T1061 and T1070).”
From Critical assessment of methods of protein structure prediction (CASP)—Round <scp>XIV</scp> (2021) · cites this paper as [3]
Targets where homology modeling is possible continue to provide the most accurate models for protein complexes.
“As the PDB becomes more populated with large complexes, opportunities for homology modeling have steadily increased, and targets where that is possible continue to provide the most accurate models3”
From Critical assessment of methods of protein structure prediction (CASP)—Round <scp>XIV</scp> (2021) · cites this paper as [3]
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- Authors
- Ozden, B., Kryshtafovych, A., & Karaca, E.
- Affiliations
- Dokuz Eylül University (TR)
- University of California, Davis (US)
- Corresponding author
- Karaca, Ezgi
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2021-08-31
- Volume
- 89
- Issue
- 12
- Pages
- 1787-1799
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- PMC
- PMC9109697
- OpenAlex
- W3191418446
- Cited by
- 41
- References
- 55
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 9 · 2023: 16 · 2022: 5 · 2021: 7
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM100482)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- CASP14, protein-protein docking, template-based modeling, AlphaFold2, interface prediction, hydrophobic interactions
- MeSH terms
- Models, Molecular, Protein Conformation, Proteins, Software, Computational Biology, Sequence Analysis, Protein, Protein Structure, Quaternary, Databases, Protein
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