Quantifying collective interactions in biomolecular phase separation
Bibliographic record
Abstract
Biomolecular phase separation is an emerging theme for protein assembly and cellular organisation. The collective forces driving such condensation, however, remain challenging to characterise. Here we show that tracking the dilute phase concentration of only one component suffices to quantify composition and energetics of multicomponent condensates. Applying this assay to several disease- and stress-related proteins, we find that monovalent ions can either deplete from or enrich within the dense phase in a context-dependent manner. By analysing the effect of the widely used modulator 1,6-hexanediol, we find that the compound inhibits phase separation by acting as a solvation agent that expands polypeptide chains. Extending the strategy to in cellulo data, we even quantify the relative energetic contributions of individual proteins within complex condensates. Together, our approach provides a generic and broadly applicable tool for dissecting the forces governing biomolecular condensation and guiding the rational modulation of condensate behaviour.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".