PT  - JOURNAL ARTICLE
AU  - Ryan J. Emenecker
AU  - Daniel Griffith
AU  - Alex S. Holehouse
TI  - Metapredict V2: An update to metapredict, a fast, accurate, and easy-to-use predictor of consensus disorder and structure
AID  - 10.1101/2022.06.06.494887
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.06.06.494887
4099  - http://biorxiv.org/content/early/2022/07/06/2022.06.06.494887.short
4100  - http://biorxiv.org/content/early/2022/07/06/2022.06.06.494887.full
AB  - Intrinsically disordered proteins and protein regions make up 20-40% of most eukaryotic proteomes and play essential roles in a wide gamut of cellular processes, from intracellular trafficking to epigenetic silencing. Given their importance, the ability to robustly, quickly, and easily identify IDRs within large proteins is critical. Here we present metapredict V2, an update to our deep-learning-based disorder predictor metapredict. Metapredict V2 has substantially improved accuracy, more features, and a more user-friendly interface via our web server (https://metapredict.net/), Python package, and command-line tool. To illustrate V2’s improved performance we undertake a systematic analysis of human transcription factors, as well as illustrate that metapredict V2 works well for synthetic or non-natural proteins.KEY POINTSMetapredict is a fast and easy-to-use disorder predictor released in 2021.Metapredict V2 was released in March 2022 and includes improved accuracy and new features.Metapredict V2 is now the default metapredict implementation, although the original implementation is available as ‘legacy’ metapredict.This manuscript provides a summary of how we improved the accuracy of metapredict and compares the original version (legacy) to our improved version (V2)This manuscript will not be submitted to a journal; if you use metapredict V2 please cite the original paper and make reference to the fact that V2 is being used.Competing Interest StatementA.S.H. is a scientific consultant for Dewpoint Therapeutics