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bioRxiv · 10.1101/2022.06.06.494887

Metapredict V2: An update to metapredict, a fast, accurate, and easy-to-use predictor of consensus disorder and structure

Emenecker, R. J.·Griffith, D.·Holehouse, A. S.
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Abstract

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 V2s 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 POINTSO_LIMetapredict is a fast and easy-to-use disorder predictor released in 2021. C_LIO_LIMetapredict V2 was released in March 2022 and includes improved accuracy and new features. C_LIO_LIMetapredict V2 is now the default metapredict implementation, although the original implementation is available as legacy metapredict. C_LIO_LIThis manuscript provides a summary of how we improved the accuracy of metapredict and compares the original version (legacy) to our improved version (V2) C_LIO_LIThis 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. C_LI

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Emenecker, R. J., Griffith, D., Holehouse, A. S.. 2022-06-09. Metapredict V2: An update to metapredict, a fast, accurate, and easy-to-use predictor of consensus disorder and structure. https://doi.org/10.1101/2022.06.06.494887

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