ArticleProteins2021
Target classification in the 14th round of the critical assessment of protein 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 23 papers.
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Who cites it
23 citing papers in PubMed, 43 citations in OpenAlex.
- Machine Learning-Guided Engineering of Protein Phase Separation Properties in Immune Regulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- CASP16 Protein Monomer Structure Prediction Assessment.Proteins · 2026Article
- Dissecting AlphaFold2's capabilities with limited sequence information.Bioinformatics advances · 2025Article
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- The ubiquitin E3 ligase BFAR promotes degradation of PNPLA3.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Deciphering olfactory receptor binding mechanisms: a structural and dynamic perspective on olfactory receptors.Frontiers in molecular biosciences · 2024Review
- Insights into virulence: structure classification of themSystems · 2023Article
- To split or not to split: CASP15 targets and their processing into tertiary structure evaluation units.Proteins · 2023Article
- Assessment of the Performances of the Protein Modeling Techniques Participating in CASP15 Using a Structure-Based Functional Site Prediction Approach: ResiRole.Bioengineering (Basel, Switzerland) · 2023Article
- Effective Local and Secondary Protein Structure Prediction by Combining a Neural Network-Based Approach with Extensive Feature Design and Selection without Reliance on Evolutionary Information.International journal of molecular sciences · 2023Article
- More than just pattern recognition: Prediction of uncommon protein structure features by AI methods.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- AlphaFold and the future of structural biology.IUCrJ · 2023Article
- AlphaFold and the future of structural biology.Acta crystallographica. Section F, Structural biology communications · 2023Article
- DPAM: A domain parser for AlphaFold models.Protein science : a publication of the Protein Society · 2023Article
- An automated pipeline integrating AlphaFold 2 and MODELLER for protein structure prediction.Computational and structural biotechnology journal · 2023Article
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- Training undergraduate research assistants with an outcome-oriented and skill-based mentoring strategy.Acta crystallographica. Section D, Structural biology · 2022Article
- Co-component signal transduction systems: Fast-evolving virulence regulation cassettes discovered in enteric bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- A-Prot: protein structure modeling using MSA transformer.BMC bioinformatics · 2022Article
- Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
An evolutionary-based definition and classification of target evaluation units (EUs) is presented for the 14th round of the critical assessment of structure prediction (CASP14). CASP14 targets included 84 experimental models submitted by various structural groups (designated T1024-T1101). Targets were split into EUs based on the domain organization of available templates and performance of server groups. Several targets required splitting (19 out of 25 multidomain targets) due in part to observed conformation changes. All in all, 96 CASP14 EUs were defined and assigned to tertiary structure assessment categories (Topology-based FM or High Accuracy-based TBM-easy and TBM-hard) considering their evolutionary relationship to existing ECOD fold space: 24 family level, 50 distant homologs (H-group), 12 analogs (X-group), and 10 new folds. Principal component analysis and heatmap visualization of sequence and structure similarity to known templates as well as performance of servers highlighted trends in CASP14 target difficulty. The assigned evolutionary levels (i.e., H-groups) and assessment classes (i.e., FM) displayed overlapping clusters of EUs. Many viral targets diverged considerably from their template homologs and thus were more difficult for prediction than other homology-related targets. On the other hand, some targets did not have sequence-identifiable templates, but were predicted better than expected due to relatively simple arrangements of secondary structural elements. An apparent improvement in overall server performance in CASP14 further complicated traditional classification, which ultimately assigned EUs into high-accuracy modeling (27 TBM-easy and 31 TBM-hard), topology (23 FM), or both (15 FM/TBM).
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Registered trials
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