PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms.

ABSTRACT: Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards proteins with high structural disorder content with focus on self-phase separating (driver) proteins. Here, we present a machine learning algorithm, PICNIC (Proteins Involved in CoNdensates In Cells) to classify proteins that localize to biomolecular condensates regardless of their role in condensate formation. PICNIC successfully predicts condensate members by learning amino acid patterns in the protein sequence and structure in addition to the intrinsic disorder. Extensive experimental validation of 24 positive predictions in cellulo shows an

SUBMITTER: Hadarovich A 

PROVIDER: S-EPMC11634905 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature