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  4. A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments
 
research article

A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments

Abriata, Luciano A.
•
Tamo, Giorgio E.
•
Dal Peraro, Matteo  
August 7, 2019
Proteins-Structure Function And Bioinformatics

We present our assessment of tertiary structure predictions for hard targets in Critical Assessment of Structure Prediction round 13 (CASP13). The analysis includes (a) assignment and discussion of best models through scores-aided visual inspection of models for each evaluation unit (EU); (b) ranking of predictors resulting from this evaluation and from global scores; and (c) evaluation of progress, state of the art, and current limitations of protein structure prediction. We witness a sizable improvement in tertiary structure prediction building on the progress observed from CASP11 to CASP12, with (a) top models reaching backbone RMSD <3 a for several EUs of size <150 residues, contributed by many groups; (b) at least one model that roughly captures global topology for all EUs, probably unprecedented in this track of CASP; and (c) even quite good models for full, unsplit targets. Better structure predictions are brought about mainly by improved residue-residue contact predictions, and since this CASP also by distance predictions, achieved through state-of-the-art machine learning methods which also progressed to work with slightly shallower alignments compared to CASP12. As we reach a new realm of tertiary structure prediction quality, new directions are proposed and explored for future CASPs: (a) dropping splitting into EUs, (b) rethinking difficulty metrics probably in terms of contact and distance predictions, (c) assessing also side chains for models of high backbone accuracy, and (d) assessing residue-wise and possibly residue-residue quality estimates.

  • Details
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Type
research article
DOI
10.1002/prot.25787
Web of Science ID

WOS:000480323900001

Author(s)
Abriata, Luciano A.
Tamo, Giorgio E.
Dal Peraro, Matteo  
Date Issued

2019-08-07

Publisher

WILEY

Published in
Proteins-Structure Function And Bioinformatics
Volume

87

Issue

12

Start page

1100

End page

1112

Subjects

Biochemistry & Molecular Biology

•

Biophysics

•

contact prediction

•

critical assessment of structure prediction

•

distance prediction

•

homology modeling

•

machine learning

•

molecular modeling

•

residue coevolution

•

sequence alignment

•

structural bioinformatics

•

structure prediction

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
UPDALPE  
Available on Infoscience
August 28, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/160666
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