CASP13 target classification into tertiary structure prediction categories
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Protein target structures for the Critical Assessment of Structure Prediction round 13 (CASP13) were split into evaluation units (EUs) based on their structural domains, the domain organization of available templates, and the performance of servers on whole targets compared to split target domains. Eighty targets were split into 112 EUs. The EUs were classified into categories suitable for assessment of high accuracy modeling (or template-based modeling [TBM]) and topology (or free modeling [FM]) based on target difficulty. Assignment into assessment categories considered the following criteria: (a) the evolutionary relationship of target domains to existing fold space as defined by the Evolutionary Classification of Protein Domains (ECOD) database; (b) the clustering of target domains using eight objective sequence, structure, and performance measures; and (c) the placement of target domains in a scatter plot of target difficulty against server performance used in the previous CASP. Generally, target domains with good server predictions had close template homologs and were classified as TBM. Alternately, targets with poor server predictions represent a mixture of fast evolving homologs, structure analogs, and new folds, and were classified as FM or FM/TBM overlap.
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Most targets in the FM category at CASP do match a known fold, even though the template is not found with sequence-based searching.
“Indeed most targets in the FM category at CASP do match a known fold, even though the template is not found with sequence-based searching (44).”
From Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins (2020) · cites this paper as [44]
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Critical assessment of methods of protein structure prediction (CASP)—Round XIII
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- Authors
- Kinch, L. N., Kryshtafovych, A., Monastyrskyy, B., & Grishin, N. V.
- Affiliations
- Howard Hughes Medical Institute (US)
- University of California, Davis (US)
- Corresponding author
- Kinch, Lisa N.
- Venue
- Proteins Structure Function and Bioinformatics
- Publisher
- Wiley
- Published
- 2019-07-24
- Volume
- 87
- Issue
- 12
- Pages
- 1021-1036
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- PMC
- PMC6851465
- OpenAlex
- W2957531855
- Cited by
- 36
- References
- 39
- Citations by year
- 2025: 2 · 2024: 1 · 2023: 3 · 2022: 5 · 2021: 12 · 2020: 7 · 2019: 6
- FWCI
- 2.48
- 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 Institutes of Health (GM094575, GM100482, GM127390)
- Welch Foundation (I‐1505)
- 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
- CASP13, protein structure prediction, target classification, assessment units, template-based modeling, target difficulty, protein domains, ECOD
- MeSH terms
- Amino Acid Sequence, Models, Molecular, Protein Conformation, Proteins, Sequence Alignment, Protein Structure, Tertiary, Protein Folding, Computational Biology, Databases, Protein
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