CASP PREDICTION CENTER INFRASTRUCTURE AND EVALUATION MEASURES IN CASP10 AND CASP ROLL

By Andriy Kryshtafovych, Bohdan Monastyrskyy, Krzysztof Fidelis. 2013

98 citations recorded by the source corpus.

The Protein Structure Prediction Center at the University of California, Davis, supports the CASP experiments by identifying prediction targets, accepting predictions, performing standard evaluations, assisting independent CASP assessors, presenting and archiving results, and facilitating information exchange relating to CASP and structure prediction in general. We provide an overview of the CASP infrastructure implemented at the Center, and summarize standard measures used for evaluating predictions in the latest round of CASP. Several components were introduced or significantly redesigned for CASP10, in particular an improved assessors' common web‐workspace; a Sphere Grinder visualization tool for analyzing local accuracy of predictions; brand new blocks for evaluation contact prediction and contact‐assisted structure prediction; expanded evaluation and visualization tools for tertiary structure, refinement and quality assessment. Technical aspects of conducting the CASP10 and CASP ROLL experiments and relevant statistics are also provided. Proteins 2014; 82(Suppl 2):7–13. © 2013 Wiley Periodicals, Inc.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests (2013, methodology): “Also, the SphereGrinder score (Kryshtafovych et al., 2013) was used for the assessment of local accuracy of refinement targets in CASP9 (MacCallum et al., 2011).”
High‐accuracy protein structure prediction in CASP14 (2021, background): “…the model 17 ; (3) CADaa, which compares residues' contact surface areas 18 ; (4) Sphere-Grinder (SG), a measure of local environment conservation 19 ; and (5) ASE, the accuracy self-estimate measure that assesses how well the coordinate error estimates provided by the predictors in the model…”
Assessment of model accuracy estimations in CASP12 (2017, methodology): “Figure 4B shows that top three places in the summary Cumulative ranking of the groups based on the differences between their success and failure rates calculated with GDT_TS, LDDT, CADaa, and SphereGrinder measures.”
Evaluation of free modeling targets in CASP11 and ROLL (2016, methodology): “11 Given the new CASP initiative to address the biological relevance of structure models in assessments, lDDT is well suited to compare functionally relevant regions of structure models.”
CASP11 Statistics and the Prediction Center Evaluation System (2016, methodology): “2,24–26 For CASP11, we extended the infrastructure to include additional evaluation measures, additional prediction categories, and interactive cumulative score tables for regular targets, refinement targets, as well as contact-assisted and residue–residue contact targets.”
Evaluation of residue-residue contact prediction in CASP10 (2013, methodology): “For CASP10, we developed an infrastructure for an automatic evaluation of the RR predictions and visual analysis of the results 44 .”
Evaluation of template-based modeling in CASP13 (2019, background): “Sphere-Grinder (SG) measures how well local environment is conserved between the model and target.(25) Finally, the accuracy self-estimate measure, ASE, evaluates the degree to which the coordinate error estimates predict positional differences from the target.”
Assessment of template based protein structure predictions in CASP10 (2014, methodology): “19,20 The Prediction Center also provided large-scale calculations of LDDT,1 RPF, Sphere Grinder,19 Mol-Probity,13,21,22 and Prosa23 scores.”
Assessment of Protein Model Structure Accuracy Estimation in CASP14: Old and New Challenges (2021, methodology): “The model accuracy measures used in previous CASP assessments include GDT-TS, 12 LDDT, 13 CAD, 14,15 and SphereGrinder.”
Cryo-EM targets in CASP13: overview and evaluation of results (2019, methodology): “CASP has been using a wide suite of numerical measures to assess the similarity of models to native structures.(4,5) Below we describe the measures that were chosen for the evaluation of cryo-EM targets.”
Assessment of the model refinement category in CASP12 (2017, methodology): “…based our analysis on the following metrics: the Root Mean Square Deviation of the C a atoms (RMSD), the Global Distance Test 33,35 (GDT_TS and GDT_HA), SphereGrinder 36 (SphGr), the Local Distance Difference Test (LDDT), 37 and the MolProbity score (MolPrb) 38 to assess the model stereochemistry.”