Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy.
Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
Nucleic Acids Res. 2022 Jul 5;50(W1):W337-W344. doi: 10.1093/nar/gkac386.
Many proteins perform their functions within membraneless organelles, where they form a liquid-like condensed state, also known as droplet state. The FuzDrop method predicts the probability of spontaneous liquid-liquid phase separation of proteins and provides a sequence-based score to identify the regions that promote this process. Furthermore, the FuzDrop method estimates the propensity of conversion of proteins to the amyloid state, and identifies aggregation hot-spots, which can drive the irreversible maturation of the liquid-like droplet state. These predictions can also identify mutations that can induce formation of amyloid aggregates, including those implicated in human diseases. To facilitate the interpretation of the predictions, the droplet-promoting and aggregation-promoting regions can be visualized on protein structures generated by AlphaFold. The FuzDrop server (https://fuzdrop.bio.unipd.it) thus offers insights into the complex behavior of proteins in their condensed states and facilitates the understanding of the functional relationships of proteins.
许多蛋白质在无膜细胞器内发挥功能,在那里它们形成类似液体的凝聚状态,也称为液滴状态。FuzDrop 方法预测蛋白质自发液-液相分离的概率,并提供基于序列的评分来识别促进这一过程的区域。此外,FuzDrop 方法估计蛋白质转化为淀粉样状态的倾向,并识别聚集热点,这些热点可能导致不可逆的液态液滴状态成熟。这些预测还可以识别可能诱导淀粉样聚集形成的突变,包括那些与人类疾病有关的突变。为了便于解释预测,液滴促进和聚集促进区域可以在由 AlphaFold 生成的蛋白质结构上可视化。因此,FuzDrop 服务器(https://fuzdrop.bio.unipd.it)提供了对蛋白质在凝聚状态下复杂行为的深入了解,并有助于理解蛋白质的功能关系。