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Publication Detail
Critical assessment of protein intrinsic disorder prediction
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Necci M, Piovesan D, Hoque MT, Walsh I, Iqbal S, Vendruscolo M, Sormanni P, Wang C, Raimondi D, Sharma R, Zhou Y, Litfin T, Galzitskaya OV, Lobanov MY, Vranken W, Wallner B, Mirabello C, Malhis N, Dosztányi Z, Erdős G, Mészáros B, Gao J, Wang K, Hu G, Wu Z, Sharma A, Hanson J, Paliwal K, Callebaut I, Bitard-Feildel T, Orlando G, Peng Z, Xu J, Wang S, Jones DT, Cozzetto D, Meng F, Yan J, Gsponer J, Cheng J, Wu T, Kurgan L, Promponas VJ, Tamana S, Marino-Buslje C, Martínez-Pérez E, Chasapi A, Ouzounis C, Dunker AK, Kajava AV, Leclercq JY, Aykac-Fas B, Lambrughi M, Maiani E, Papaleo E, Chemes LB, Álvarez L, González-Foutel NS, Iglesias V, Pujols J, Ventura S, Palopoli N, Benítez GI, Parisi G, Bassot C, Elofsson A, Govindarajan S, Lamb J, Salvatore M, Hatos A, Monzon AM, Bevilacqua M, Mičetić I, Minervini G, Paladin L, Quaglia F, Leonardi E, Davey N, Horvath T, Kovacs OP, Murvai N, Pancsa R, Schad E, Szabo B, Tantos A, Macedo-Ribeiro S, Manso JA, Pereira PJB, Davidović R, Veljkovic N, Hajdu-Soltész B, Pajkos M, Szaniszló T, Guharoy M, Lazar T, Macossay-Castillo M, Tompa P, Tosatto SCE
  • Publication date:
    01/05/2021
  • Pagination:
    472, 481
  • Journal:
    Nature Methods
  • Volume:
    18
  • Status:
    Published
  • Print ISSN:
    1548-7091
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 F = 0.483 on the full dataset and F = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude. max max max
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