Computational Screening of Biological Phase-separating Proteins.

Abstract Phase separation is an important mechanism that mediates the compartmentalization of proteins in cells. Proteins that can undergo phase separation in cells share certain typical sequence features, like intrinsically disordered regions (IDRs) and multiple modular domains. Sequence-based analysis tools are commonly used in the screening of these proteins. However, current phase separation predictors are mostly designed for IDR-containing proteins, thus inevitably overlook the phase-separating proteins with relatively low IDR content. Features other than amino acid sequence could provide crucial information for identifying possible phase-separating proteins: protein–protein interaction (PPI) networks imply multivalent interactions that underlines phase separation process; post-translational modifications (PTMs) are crucial in the regulation of phase separation behavior; spherical structures appearing on immunofluorescence (IF) images indicate condensed droplets formed by phase-separating proteins, distinguishing these proteins from non-phase-separating proteins. Here, we summarized the sequence-based tools for predicting phase-separating proteins and highlighted the importance of incorporating PPIs, PTMs, and IF images into phase separation prediction in future studies.