Learning the molecular grammar of protein condensates from sequence determinants and embeddings.

ABSTRACT: Intracellular phase separation of proteins into biomolecular condensates is increasingly recognized as a process with a key role in cellular compartmentalization and regulation. Different hypotheses about the parameters that determine the tendency of proteins to form condensates have been proposed, with some of them probed experimentally through the use of constructs generated by sequence alterations. To broaden the scope of these observations, we established an in silico strategy for understanding on a global level the associations between protein sequence and phase behavior and further constructed machine-learning models for predicting protein liquid-liquid phase separation (LLPS). Our analysis highlighted that LLPS-prone proteins are more disordered, less hydrophobic, and of lower Shann

SUBMITTER: Saar KL 

PROVIDER: S-EPMC8053968 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature