Necci, MarcoPiovesan, DamianoCAID PredictorsDisProt CuratorsTosatto, Silvio C. E.2024-08-072024-08-072021Necci M, Piovesan D; CAID Predictors; DisProt Curators, Tosatto SCE. Critical assessment of protein intrinsic disorder prediction. Nat Methods. 2021;18(5):472-481. doi:10.1038/s41592-021-01117-3https://hdl.handle.net/1805/42691Intrinsically 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.en-USAttribution 4.0 InternationalComputational platforms and environmentsSoftwareProteinsProtein structure predictionsMachine learningArticle