ArticleProceedings of the National Academy of Sciences of the United States of America2025
Prediction of phase-separation propensities of disordered proteins from sequence.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- How do low-complexity domain interactions control transcription?Biochemical Society transactions · 2026Review
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- Progress toward linking single-molecule behavior and condensate material properties.Current opinion in structural biology · 2026Review
- The evolutionary origins of streptophyte multicellularity.The New phytologist · 2026Review
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- AF-CALVADOS: AlphaFold-guided simulations of multi-domain proteins at the proteome level.Protein science : a publication of the Protein Society · 2026Article
- Bacterial Sentience Is Determined by the Stochastic, Chaotic, and Deterministic Behavior of Cytoplasmic Particles.Current issues in molecular biology · 2026Review
- Proteome-scale quantification of the interactions driving condensate formation of intrinsically disordered proteins.Nature communications · 2026Article
- AI-discovered protein fragments as generalizable regulators of biomolecular condensates.bioRxiv : the preprint server for biology · 2026Article
- Analysis and design of disordered polypeptides with optimized sequence patterning properties.PLoS computational biology · 2026Article
- Distinguishing near- versus off-critical phase behaviors of intrinsically disordered proteins.Reports on progress in physics. Physical Society (Great Britain) · 2026Article
- amyloid-predict and LLPS-predict: Predicting phase separation propensities in the intrinsically disordered proteome.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- In Search of Shape in the Unshaped: Constructing Ensembles of Intrinsically Disordered Proteins.Biophysics reviews · 2026Article
- Condensates as Conformation Editors of Disordered Client Proteins.Journal of the American Chemical Society · 2026Article
- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- A composition-matching algorithm, MatchIDR, identifies prion-like domains that localize to stress granules.Protein science : a publication of the Protein Society · 2026Article
- Engineering Design of Artificial Phase-Separating Proteins.Biotechnology journal · 2026Review
- Folded domains impose structural heterogeneity and attenuated dynamics in biomolecular condensates.Nature communications · 2026Article
- Generative design of intrinsically disordered protein regions with IDiom.bioRxiv : the preprint server for biology · 2026Article
- Investigating Phase Separation in Genome Folding via Multiscale Computational Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
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5 authors.
Funding
Abstract
Phase separation is one possible mechanism governing the selective cellular enrichment of biomolecular constituents for processes such as transcriptional activation, mRNA regulation, and immune signaling. Phase separation is mediated by multivalent interactions of macromolecules including intrinsically disordered proteins and regions (IDRs). Despite considerable advances in experiments, theory, and simulations, the prediction of the thermodynamics of IDR phase behavior remains challenging. We combined coarse-grained molecular dynamics simulations and active learning to develop a fast and accurate machine learning model to predict the free energy and saturation concentration for phase separation directly from sequence. We validate the model using computational and previously measured experimental data, as well as new experimental data for six proteins. We apply our model to all 27,663 IDRs of chain length up to 800 residues in the human proteome and find that 1,420 of these (5%) are predicted to undergo homotypic phase separation with transfer free energies < -2
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