Assessment of template based protein structure predictions in CASP9

By Valerio Mariani, Florian Kiefer, Tobias Schmidt, J. Haas, Torsten Schwede. 2011

183 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Evaluation & Benchmarks, Computational Biology & Bioinformatics

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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): “In CASP9, the local Distance Difference Test (lDDT) score was introduced, assessing how well local atomic interactions in the reference protein structure are reproduced in the prediction (Mariani et al., 2011).”
Improved protein structure refinement guided by deep learning based accuracy estimation (2020, positive): “HHsearch (28) was used to search for templates; 50 templates with highest HHsearch probability, sequence identity of at most 40% and sequence coverage of at least 50% are selected for model generation.”
Local Error Estimates Dramatically Improve the Utility of Homology Models for Solving Crystal Structures by Molecular Replacement (2015, methodology): “It seems to be a recurring ﬁnding in CASP assessment that predictors fail to assign realistic conﬁdence estimates to their predictions, except for a very few groups (Mariani et al., 2011).”
Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XII (2017, background): “33 In round 11, CASP increased the emphasis on assembly structures by extending the targets to include heteromeric complexes and by collaborating with CAPRI to address this area.”
SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information (2014, background): “Frequently, ligand binding sites and enzyme active sites are located at protein chain interfaces, and modelling of the oligomeric structure of a protein is therefore essential to build models which are useful in biomedical applications (23).”
Template-based protein structure modeling using the RaptorX web server (2012, background): “In addition, RaptorX generated the best alignments for the 50 most difficult TBM CASP9 targets 27 , outperforming all other servers.”
CASP9 results compared to those of previous CASP experiments (2011, methodology): “First, we calculate two separate z-scores from the distributions of (1) coverage and (2) sequence identity of the best template to the corresponding target in all CASPs, then average these two scores and, finally, multiply the result by (21) so that the higher resulting score will identify the highe”
Refinement of unreliable local regions in template‐based protein models (2012, methodology): “37 In certain cases, small improvements in GDT-TS, for example those obtained by improvements in local regions of relatively small sizes, can be meaningful and may allow further practical applications to functional studies.”
IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences (2015, methodology): “The IntFOLD server has performed exceptionally well in the quality assessment category, outperforming most other servers in the QA3 self-assessment or ‘B-factor’ predictions (10,12) (http://www.”
Accurate template‐based modeling in CASP12 using the IntFOLD4‐TS, ModFOLD6, and ReFOLD methods (2018, methodology): “In CASP9, the IntFOLD-TS method(1) gained attention for its high performance in the assignment of model reliability/“B-factors”, which was first evaluated in the TBM category.(10)”
Assessment of protein assembly prediction in CASP12 (2018, background): “A first attempt was explored in CASP9, 10 as part of the template-based assessment category.”
Automatic Prediction of Protein 3D Structures by Probabilistic Multi-template Homology Modeling (2015, methodology): “Cumulative Z-score of all server predictions in the template-basedmodeling category of the CASP9 and CASP10 community-wide assessment of techniques for protein structure prediction [1, 3].”
Protein Loop Modeling Using a New Hybrid Energy Function and Its Application to Modeling in Inaccurate Structural Environments (2014, methodology): “Only those targets for which the template-based models have GDT-TS [41] between 70 and 90 were considered.”
Assessment of ligand binding site predictions in CASP10 (2014, background): “The accuracy of predictions of three-dimensional structures is assessed as part of the template-based (TBM) and free-modeling (FM) categories,13–16 which includes the accuracy of binding site coordinates.17 ,18 Function prediction (FN) was introduced as a new category in CASP6.”
Template-based structure modeling of protein-protein interactions (2013, methodology): “Many variations and advanced methods have been developed for TBM [15,16], and it has been highly successful for protein tertiary structure modeling [17].”