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Beyond peptide targeting sequences: machine learning of cellular condensate localization

Jonathon A. Ditlev^1,2,3,* , Julie D. Forman-Kay^1,2,*

¹Molecular Medicine Program, Hospital for Sick Children, Toronto, ON, Canada
²Department of Biochemistry, University of Toronto, Toronto, ON, Canada
³Cell and Systems Biology Program, Hospital for Sick Children, Toronto, ON, Canada
* Correspondence: Jonathon A. Ditlev(jonathon.ditlev@sickkids.ca)Julie D. Forman-Kay(forman@sickkids.ca)

Proteins within cells must navigate complex intracellular environments to co-localize with partners and regulate functional cellular organization. In a recentScience paper, Kilgore et al. report the development of ProtGPS, a machine learning-trained predictor of protein localization within biomolecular condensates in cells that can be used to predict the ability of disease-linked mutations to dysregulate protein localization to biomolecular condensates.

https://doi.org/10.1038/s41422-025-01115-6

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