CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins
Author:
Del Conte Alessio1ORCID, Bouhraoua Adel1, Mehdiabadi Mahta1, Clementel Damiano1, Monzon Alexander Miguel2ORCID, Holehouse Alex S, Griffith Daniel, Emenecker Ryan J, Patil Ashwini, Sharma Ronesh, Tsunoda Tatsuhiko, Sharma Alok, Tang Yi Jun, Liu Bin, Mirabello Claudio, Wallner Björn, Rost Burkhard, Ilzhöfer Dagmar, Littmann Maria, Heinzinger Michael, Krautheimer Lea I M, Bernhofer Michael, McGuffin Liam J, Callebaut Isabelle, Feildel Tristan Bitard, Liu Jian, Cheng Jianlin, Guo Zhiye, Xu Jinbo, Wang Sheng, Malhis Nawar, Gsponer Jörg, Kim Chol-Song, Han Kun-Sop, Ma Myong-Chol, Kurgan Lukasz, Ghadermarzi Sina, Katuwawala Akila, Zhao Bi, Peng Zhenling, Wu Zhonghua, Hu Gang, Wang Kui, Hoque Md Tamjidul, Kabir Md Wasi Ul, Vendruscolo Michele, Sormanni Pietro, Li Min, Zhang Fuhao, Jia Pengzhen, Wang Yida, Lobanov Michail Yu, Galzitskaya Oxana V, Vranken Wim, Díaz Adrián, Litfin Thomas, Zhou Yaoqi, Hanson Jack, Paliwal Kuldip, Dosztányi Zsuzsanna, Erdős Gábor, Tosatto Silvio C E1, Piovesan Damiano1ORCID,
Affiliation:
1. Department of Biomedical Sciences, University of Padova , via Ugo Bassi 58b , 35121 Padova , Italy 2. Department of Information Engineering, University of Padova , via Giovanni Gradenigo 6/B , 35131 Padova , Italy
Abstract
Abstract
Intrinsic disorder (ID) in proteins is well-established in structural biology, with increasing evidence for its involvement in essential biological processes. As measuring dynamic ID behavior experimentally on a large scale remains difficult, scores of published ID predictors have tried to fill this gap. Unfortunately, their heterogeneity makes it difficult to compare performance, confounding biologists wanting to make an informed choice. To address this issue, the Critical Assessment of protein Intrinsic Disorder (CAID) benchmarks predictors for ID and binding regions as a community blind-test in a standardized computing environment. Here we present the CAID Prediction Portal, a web server executing all CAID methods on user-defined sequences. The server generates standardized output and facilitates comparison between methods, producing a consensus prediction highlighting high-confidence ID regions. The website contains extensive documentation explaining the meaning of different CAID statistics and providing a brief description of all methods. Predictor output is visualized in an interactive feature viewer and made available for download in a single table, with the option to recover previous sessions via a private dashboard. The CAID Prediction Portal is a valuable resource for researchers interested in studying ID in proteins. The server is available at the URL: https://caid.idpcentral.org.
Funder
MSCA-RISE ELIXIR, the research infrastructure for life-science data; COST Action ML4NGP European Cooperation in Science and Technology MIUR University of Padova
Publisher
Oxford University Press (OUP)
Cited by
15 articles.
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