Molecular mechanisms of condensate modulation from energy-dominance analysis
Bibliographic record
Abstract
Biomolecular condensates in cells underpin cellular organization but have also been implicated in disease progression. As a result, modulation of condensate formation is becoming a path of interest to ameliorate biological malfunction. However, identifying the mechanism of action of a modulator is particularly challenging. This is because condensates are typically highly multicomponent, rendering it difficult to delineate which molecular interactions a modulator is influencing to drive or oppose condensate formation. Here, we extend the theoretical framework of energy dominance to include modulation effects, allowing us to uncover mechanisms of action of small molecular modulators through measuring species energetics. Using this approach, we experimentally investigate the effect of the small molecule suramin on condensates formed by the RNA-binding protein G3BP1 and RNA. We show that suramin specifically disrupts G3BP1-RNA interactions, as independently confirmed though orthogonal binding assays. Together, this work paves the way for systematic studies of condensate modulators in the future.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".