Colloidal Aggregation and the <i>in Vitro</i> Activity of Traditional Chinese Medicines
Bibliographic record
Abstract
Traditional Chinese Medicines (TCMs) have been the sole source of therapeutics in China for two millennia. In recent drug discovery efforts, purified components of TCM formulations have shown activity in many in vitro assays, raising concerns of promiscuity. Here, we investigated 14 bioactive small molecules isolated from TCMs for colloidal aggregation. At concentrations commonly used in cell-based or biochemical assay conditions, eight of these compounds formed particles detectable by dynamic light scattering and showed detergent-reversible inhibition against β-lactamase and malate dehydrogenase, two counter-screening enzymes. When three of these compounds were tested against their literature-reported molecular targets, they showed similar reversal of their inhibitory activity in the presence of detergent. For three of the most potent aggregators, contributions to promiscuity via oxidative cycling were investigated; addition of 1 mM DTT had no effect on their activity, which is inconsistent with an oxidative mechanism. TCMs are often active at micromolar concentrations; this study suggests that care must be taken to control for artifactual activity when seeking their primary targets. Implications for the formulation of these molecules are considered.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".