Critical assessment of protein intrinsic disorder prediction
Creators: name: Necci, Marco
name: Piovesan, Damiano
name: Tosatto, Silvio C. E.
name: Hoque, Md Tamjidul
name: Walsh, Ian
name: Iqbal, Sumaiya
name: Vendruscolo, Michele
name: Sormanni, Pietro
name: Wang, Chen
name: Raimondi, Daniele
name: Sharma, Ronesh
name: Zhou, Yaoqi
name: Litfin, Thomas
name: Galzitskaya, Oxana Valerianovna
name: Lobanov, Michail Yu.
name: Vranken, Wim
name: Wallner, Björn
name: Mirabello, Claudio
name: Malhis, Nawar
name: Dosztányi, Zsuzsanna
name: Erdős, Gábor
name: Mészáros, Bálint
name: Gao, Jianzhao
name: Wang, Kui
name: Hu, Gang
name: Wu, Zhonghua
name: Sharma, Alok
name: Hanson, Jack
name: Paliwal, Kuldip
name: Callebaut, Isabelle
name: Bitard-Feildel, Tristan
name: Orlando, Gabriele
name: Peng, Zhenling
name: Xu, Jinbo
name: Wang, Sheng
name: Jones, David T.
name: Cozzetto, Domenico
name: Meng, Fanchi
name: Yan, Jing
name: Gsponer, Jörg
name: Cheng, Jianlin
name: Wu, Tianqi
name: Kurgan, Lukasz
name: Promponas, Vasilis J.
name: Tamana, Stella
name: Marino-Buslje, Cristina
name: Martínez-Pérez, Elizabeth
name: Chasapi, Anastasia
name: Ouzounis, Christos
name: Dunker, A. Keith
name: Kajava, Andrey V.
name: Leclercq, Jeremy Y.
name: Aykac-Fas, Burcu
name: Lambrughi, Matteo
name: Maiani, Emiliano
name: Papaleo, Elena
name: Chemes, Lucia Beatriz
name: Álvarez, Lucía
name: González-Foutel, Nicolás S.
name: Iglesias, Valentin
name: Pujols, Jordi
name: Ventura, Salvador
name: Palopoli, Nicolás
name: Benítez, Guillermo Ignacio
name: Parisi, Gustavo
name: Bassot, Claudio
name: Elofsson, Arne
name: Govindarajan, Sudha
name: Lamb, John
name: Salvatore, Marco
name: Hatos, András
name: Monzon, Alexander Miguel
name: Bevilacqua, Martina
name: Mičetić, Ivan
name: Minervini, Giovanni
name: Paladin, Lisanna
name: Quaglia, Federica
name: Leonardi, Emanuela
name: Davey, Norman
name: Horvath, Tamas
name: Kovacs, Orsolya Panna
name: Murvai, Nikoletta
name: Pancsa, Rita
name: Schad, Eva
name: Szabo, Beata
name: Tantos, Agnes
name: Macedo-Ribeiro, Sandra
name: Manso, Jose Antonio
name: Pereira, Pedro José Barbosa
name: Davidović, Radoslav
name: Veljkovic, Nevena
name: Hajdu-Soltész, Borbála
name: Pajkos, Mátyás
name: Szaniszló, Tamás
name: Guharoy, Mainak
name: Lazar, Tamas
name: Macossay-Castillo, Mauricio
name: Tompa, Peter
Publisher: name: Apollo - University of Cambridge Repository
Year: 2021
Subjects: Analysis
/631/114/2398
/631/114/794
/631/45/612
/631/114/2411
/631/114/1305
analysis

description: 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.