Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, Cambridge CB2 1EW, United Kingdom.
Department of Biomedical Sciences, University of Padova, Padova 35131, Italy.
Proc Natl Acad Sci U S A. 2023 Oct 3;120(40):e2300215120. doi: 10.1073/pnas.2300215120. Epub 2023 Sep 29.
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.
蛋白质相分离 (PPS) 现象是广泛的细胞功能的基础。相应地，PPS 过程的失调与许多人类疾病有关。为了能够基于这种关联的调节进行治疗干预，应该确定可能的靶点。为此，我们提出了一种结合多组学 PandaOmics 平台和 FuzDrop 方法来识别 PPS 倾向疾病相关蛋白的方法。使用这种方法，我们使用一种考虑与疾病机制和药物干预相关的广泛参数的分析方法，对具有高 PandaOmics 和 FuzDrop 分数的候选物进行优先级排序。我们验证了三种预测的阿尔茨海默病靶点 (MARCKS、CAMKK2 和 p62) 在两种这种疾病的细胞模型中的差异相分离行为。总的来说，我们提出的方法为与 PPS 过程失调相关的人类疾病生成了一个可能的治疗靶点列表。
