Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14).
Proteins
; 89(12): 1618-1632, 2021 12.
Article
in En
| MEDLINE
| ID: mdl-34350630
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).
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Protein Conformation
/
Proteins
/
Models, Molecular
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
Proteins
Journal subject:
BIOQUIMICA
Year:
2021
Type:
Article
Affiliation country:
United States