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Critical assessment of protein intrinsic disorder prediction

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Tosatto, Silvio C. E.  ORCID logo
Hoque, Md Tamjidul 
Walsh, Ian 


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.



Analysis, /631/114/2398, /631/114/794, /631/45/612, /631/114/2411, /631/114/1305, analysis

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Nature Methods

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Nature Publishing Group US
EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) (778247)
Ministero dell’Istruzione, dell’Università e della Ricerca (Ministry of Education, University and Research) (2017483NH8)