Critical assessment of protein intrinsic disorder prediction
Marco Necci(University of Padua), Damiano Piovesan(University of Padua), CAID Predictors(University of Padua), Md Tamjidul Hoque(Agency for Science, Technology and Research), Ian Walsh(Broad Institute), Sumaiya Iqbal(Broad Institute), Michele Vendruscolo(University of Cambridge), Pietro Sormanni(University of Cambridge), Chen Wang(Columbia University), Daniele Raimondi(Fiji National University), Ronesh Sharma(Griffith University), Yaoqi Zhou(Griffith University), Thomas Litfin(Griffith University), Oxana V. Galzitskaya(Institute of Theoretical and Experimental Biophysics), Michail Yu. Lobanov(Vrije Universiteit Brussel), Wim Vranken(Linköping University), Björn Wallner(Linköping University), Claudio Mirabello(Linköping University), Nawar Malhis(Eötvös Loránd University), Zsuzsanna Dosztányi(Eötvös Loránd University), Gábor Erdős(Eötvös Loránd University), Bálint Mészáros(Nankai University), Jianzhao Gao(Nankai University), Kui Wang(Nankai University), Gang Hu(Nankai University), Zhonghua Wu(Nankai University), Alok Sharma(Griffith University), Jack Hanson(Griffith University), K.K. Paliwal(Griffith University), Isabelle Callebaut(Sorbonne Université), Tristan Bitard-Feildel(Sorbonne Université), Gabriele Orlando(Tianjin University), Zhenling Peng(Toyota Technological Institute at Chicago), Jinbo Xu(Toyota Technological Institute at Chicago), Sheng Wang(Toyota Technological Institute at Chicago), David T. Jones(University College London), Domenico Cozzetto(University of Alberta), Fanchi Meng(University of Alberta), Jing Yan(University of British Columbia), Jörg Gsponer(University of British Columbia), Jianlin Cheng(University of Missouri), Tianqi Wu(Virginia Commonwealth University), Lukasz Kurgan(Virginia Commonwealth University), DisProt Curators(University of Cyprus), Vasilis J. Promponas(Fundación Instituto Leloir), Stella Tamana(Fundación Instituto Leloir), Cristina Marino‐Buslje(Fundación Instituto Leloir), Elizabeth Martínez‐Pérez(Fundación Instituto Leloir), Anastasia Chasapi(Centre for Research and Technology Hellas), Christos Ouzounis(Université de Montpellier), A. Keith Dunker(Université de Montpellier), Andrey V. Kajava(Université de Montpellier), Jérémy Leclercq(Université de Montpellier), Burcu Aykaç Fas(Danish Cancer Society), Matteo Lambrughi(Danish Cancer Society), Emiliano Maiani(Consejo Nacional de Investigaciones Científicas y Técnicas), Elena Papaleo(Consejo Nacional de Investigaciones Científicas y Técnicas), Lucía B. Chemes(Consejo Nacional de Investigaciones Científicas y Técnicas), Lucía Álvarez(Universitat Autònoma de Barcelona), Nicolás S. González Foutel(Universitat Autònoma de Barcelona), Valentín Iglesias(Universitat Autònoma de Barcelona), Jordi Pujols(Universitat Autònoma de Barcelona), Salvador Ventura(Universitat Autònoma de Barcelona), Nicolás Palópoli(National University of Quilmes), Guillermo Ignacio Benítez(National University of Quilmes), Gustavo Parisi(National University of Quilmes), Claudio Bassot(Stockholm University), Arne Elofsson(Stockholm University), Sudha Govindarajan(Stockholm University), John Lamb(University of Padua), Marco Salvatore(University of Padua), András Hatos(University of Padua), Alexander Miguel Monzón(University of Padua), Martina Bevilacqua(University of Padua), Ivan Mičetić(University of Padua), Giovanni Minervini(University of Padua), Lisanna Paladin(University of Padua), Federica Quaglia(University of Padua), Emanuela Leonardi(Institute of Molecular Life Sciences), Norman E. Davey(Institute of Cancer Research), Tamás Horváth(Institute of Molecular Life Sciences), Orsolya Panna Kovacs(Institute of Molecular Life Sciences), Nikoletta Murvai(Institute of Molecular Life Sciences), Rita Pancsa(Institute of Molecular Life Sciences), Éva Schád(Institute of Molecular Life Sciences), Beáta Szabó(Institute of Molecular Life Sciences), Ágnes Tantos(Institute of Molecular Life Sciences), Sandra Macedo‐Ribeiro(i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto), José A. Manso(University of Belgrade), Pedro José Barbosa Pereira(University of Belgrade), Radoslav Davidović(Eötvös Loránd University), Nevena Veljković(Eötvös Loránd University), Borbála Hajdu-Soltész(Eötvös Loránd University), Mátyás Pajkos(Eötvös Loránd University), Tamás Szaniszló(Eötvös Loránd University), Mainak Guharoy(Vrije Universiteit Brussel), Tamás Lázár(Vrije Universiteit Brussel), Mauricio Macossay-Castillo(Vrije Universiteit Brussel), Péter Tompa(Vrije Universiteit Brussel), Silvio C. E. Tosatto(University of Padua)
Cited by 360Open Access
Abstract
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 max = 0.483 on the full dataset and F max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.
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