Computational Screening of Phase-separating Proteins
- Author:
Shen BOYAN
1
;
Chen ZHAOMING
;
Yu CHUNYU
;
Chen TAOYU
;
Shi MINGLEI
;
Li TINGTING
Author Information
1. Department of Biomedical Informatics,School of Basic Medical Sciences,Peking University Health Science Center,Beijing 100191,China
- Keywords:
Phase separation;
Prediction;
Protein–protein interaction;
Protein post-translational modification;
Immunofluorescence image
- From:
Genomics, Proteomics & Bioinformatics
2021;19(1):13-24
- CountryChina
- Language:Chinese
-
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:pro-tein–protein interaction (PPI) networks show multivalent interactions that underlie phase separation process; post-translational modifications (PTMs) are crucial in the regulation of phase separation behavior;spherical structures revealed in immunofluorescence (IF) images indicate condensed dro-plets formed by phase-separating proteins, distinguishing these proteins from non-phase-separating proteins. Here, we summarize the sequence-based tools for predicting phase-separating proteins and highlight the importance of incorporating PPIs, PTMs, and IF images into phase separation prediction in future studies.
