CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins

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del Conte, Alessio | Bouhraoua, Adel | Mehdiabadi, Mahta | Clementel, Damiano | Monzon, Alexander, Miguel | 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 E | Piovesan, Damiano

Edité par CCSD ; Oxford University Press -

International audience. Intrinsic disorder (ID) in proteins is well-established in structural biology, with increasing evidence for its involvement in essential biological processes. As measuring d ynamic ID beha vior e xperimentall y on a large scale remains difficult, scores of published ID predictor s ha ve tried to fill this gap. Unfortunatel y, their heterogeneity makes it difficult to compare perf ormance, conf ounding 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 priv ate dashboar d. 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 .

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