Multiomic prediction of therapeutic targets for human diseases associated with protein phase separation


The phenomenon of protein phase separation (PPS) underlies a wide range of cellular functions. Correspondingly, the dysregulation of the PPS process has been associated with numerous human diseases. To enable therapeutic interventions based on the regulation of this association, possible targets should be identified. For this purpose, we present an approach that combines the multiomic PandaOmics platform with the FuzDrop method to identify PPS-prone disease-associated proteins. Using this approach, we prioritize candidates with high PandaOmics and FuzDrop scores using a profiling method that accounts for a wide range of parameters relevant for disease mechanism and pharmacological intervention. We validate the differential phase separation behaviors of three predicted Alzheimer's disease targets (MARCKS, CAMKK2, and p62) in two cell models of this disease. Overall, the approach that we present generates a list of possible therapeutic targets for human diseases associated with the dysregulation of the PPS process.

Authors Lim CM, González Díaz A, Fuxreiter M, Pun FW, Zhavoronkov A, Vendruscolo M
Journal Proceedings of the National Academy of Sciences of the United States of America
Publication Date 2023 Oct 3;120(40):e2300215120
PubMed 37774095
PubMed Central PMC10556643
DOI 10.1073/pnas.2300215120

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