Missense mutations could affect the Liquid-Liquid Phase Separation (LLPS) propensity of proteins and lead to aberrant phase-separating behaviours, which are recently found to be associated with many diseases including Alzheimer's and cancer. However, the regulatory role of mutations in LLPS remains unclear due to challenges in accurately characterizing the LLPS ability of mutants, including the high similarity in features, lack of labeled data, and vast amounts of data involved. To bridge this gap and facilitate the discovery of therapeutic strategies, we propose the first machine learning-based guider for protein phase-separating behaviour alteration, PScalpel. PScalpel leverages both structural information and an auxiliary tasks-based graph contrastive learning framework to distinguish the mutants’ LLPS ability, and incorporates a genetic algorithms-based recommendation method to identify mutants with desired LLPS properties. Comprehensive computational and biological experiments validate the effectiveness of PScalpel as a versatile tool for guiding alterations in protein phase separation behavior.

We introduce a unified system for SCHOLAT to import information into Encyclopedia, called Semi-automatic Scholar Encyclopedia Generating System, which consists of four modules: website display page, backstage administration module, version comparison and website security module. Scholar Encyclopedia is implemented as a subsystem of Semi-automatic Scholar Encyclopedia Generating System. Scholar Encyclopedia is a scholar information website that has been independently compiled by the scholars and filled in by personal information. Scholar Encyclopedia Import Model consists of three modules: user evaluation, information import and manual review. At present, Semi-automatic Scholar Encyclopedia Generating System has been used, and the beta version of Scholar Encyclopedia has been deployed in our school network center. The online application shows that Scholar Encyclopedia Import Model has good accuracy and practicability.