Stable Colloidal Drug Aggregates Catch and Release Active Enzymes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Small molecule aggregates are considered nuisance compounds in drug discovery, but their unusual properties as colloids could be exploited to form stable vehicles to preserve protein activity. We investigated the coaggregation of seven molecules chosen because they had been previously intensely studied as colloidal aggregators, coformulating them with bis-azo dyes. The coformulation reduced colloid sizes to <100 nm and improved uniformity of the particle size distribution. The new colloid formulations are more stable than previous aggregator particles. Specifically, coaggregation of Congo Red with sorafenib, tetraiodophenolphthalein (TIPT), or vemurafenib produced particles that are stable in solutions of high ionic strength and high protein concentrations. Like traditional, single compound colloidal aggregates, the stabilized colloids adsorbed and inhibited enzymes like β-lactamase, malate dehydrogenase, and trypsin. Unlike traditional aggregates, the coformulated colloid-protein particles could be centrifuged and resuspended multiple times, and from resuspended particles, active trypsin could be released up to 72 h after adsorption. Unexpectedly, the stable colloidal formulations can sequester, stabilize, and isolate enzymes by spin-down, resuspension, and release.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it