Evaluation of residue-residue contact prediction in CASP10

Bohdan Monastyrskyy, Daniel D'Andrea, Krzysztof Fidelis, Anna Tramontano, Andriy Kryshtafovych

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

We present the results of the assessment of the intramolecular residue-residue contact predictions from 26 prediction groups participating in the 10th round of the CASP experiment. The most recently developed direct coupling analysis methods did not take part in the experiment likely because they require a very deep sequence alignment not available for any of the 114 CASP10 targets. The performance of contact prediction methods was evaluated with the measures used in previous CASPs (i.e., prediction accuracy and the difference between the distribution of the predicted contacts and that of all pairs of residues in the target protein), as well as new measures, such as the Matthews correlation coefficient, the area under the precision-recall curve and the ranks of the first correctly and incorrectly predicted contact. We also evaluated the ability to detect interdomain contacts and tested whether the difficulty of predicting contacts depends upon the protein length and the depth of the family sequence alignment. The analyses were carried out on the target domains for which structural homologs did not exist or were difficult to identify. The evaluation was performed for all types of contacts (short, medium, and long-range), with emphasis placed on long-range contacts, i.e. those involving residues separated by at least 24 residues along the sequence. The assessment suggests that the best CASP10 contact prediction methods perform at approximately the same level, and comparably to those participating in CASP9.
Original languageEnglish (US)
Pages (from-to)138-153
Number of pages16
JournalProteins: Structure, Function, and Bioinformatics
Volume82
Issue numberSUPPL.2
DOIs
StatePublished - Aug 31 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-I1–012-43
Acknowledgements: Grant sponsor: US National Institute of General Medical Sciences (NIGMS/NIH); Grant number: R01GM100482 (to K.F.); Grant sponsor: KAUST Award; Grant number: KUK-I1–012-43 (to A.T.); Grant sponsor: EMBO.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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