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Critical assessment of protein intrinsic disorder prediction.

Published version
Peer-reviewed

Type

Article

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Authors

CAID Predictors 
DisProt Curators 

Abstract

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.

Description

Keywords

Amino Acid Sequence, Computational Biology, Databases, Protein, Intrinsically Disordered Proteins, Protein Binding, Protein Conformation, Protein Folding, Software

Journal Title

Nat Methods

Conference Name

Journal ISSN

1548-7091
1548-7105

Volume Title

18

Publisher

Springer Science and Business Media LLC