Critical assessment of protein intrinsic disorder prediction.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 33875885.
- Also identified by DOI 10.1038/s41592-021-01117-3 and PMC identifier 8105172.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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<sub>max</sub> = 0.483 on the full dataset and F<sub>max</sub> = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F<sub>max</sub> = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.
Medical subject headings
- Computational Biology
- Intrinsically Disordered Proteins