PhaSePred: A Meta-predictor For Phase-Separating Proteins

Liquid-liquid phase separation (LLPS) mediates the compartmentalization of proteins and nucleic acids in cell. This process is driven by multivalent weak interactions mediated by intrinsically disordered regions (IDRs) or multiple modular domains. A difference between these two interactions is that a single species can undergo IDR-mediated phase separation, while phase separation mediated by multiple interacting domains often involves two or more different protein species. Herein, we characterize proteins that can self-assemble to form condensates as self-assembling phase-separating proteins (LLPS-Self), and we define proteins whose phase separation behaviors are regulated by partner components as partner-dependent phase-separating proteins (LLPS-Part).
PhaSePred is a centralized resource that provides self-assembling and partner-dependent phase-separating protein prediction and integrates scores from several LLPS-related predicting tools.


Examples: P35637, FUS,

2021-08-31: 116,806 sequences from 18 species were available.

Zhaoming Chen, Chao Hou, Liang Wang, Chunyu Yu, Taoyu Chen, Boyan Shen, Pilong Li, and Tingting Li. Screening Membraneless Organelle Participants with Machine Learning Models that Integrate Multimodal Features.

Integrated Resources
catGRANULE PLAAC Pscore Espritz localCIDRE DeepCoil SEG PhosphoSitePlus DeepPhase