Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.11.245852v1?rss=1 Authors: Necci, M., Piovesan, D., CAID Predictors,, DisProt Curators,, Tosatto, S. C. E. Abstract: Intrinsically disordered proteins defying the traditional protein structure-function paradigm represent a challenge to study experimentally. As a large part of our knowledge rests on computational predictions, it is crucial for their accuracy to be 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 predicting intrinsically disordered regions in proteins and the subset of disordered residues involved in binding other molecules. A total of 43 methods, 32 for disorder and 11 for binding regions, were evaluated on a dataset of 646 proteins. The best methods use modern machine learning techniques and significantly outperform widely used first-generation methods across different types of targets. Disordered binding regions remain hard to predict correctly, which offers significant potential for improvement. Intriguingly, some of the top performing methods are also among the fastest. Copy rights belong to original authors. Visit the link for more info