The effects of molecular crowding on the kinetics and small molecule inhibition of alkaline phosphatase
Bibliographic record
Abstract
Enzymes have adapted to function in complex environments crowded with many other solutes. To get a better understanding of in vivo crowding, we used polyethylene glycol (MW 8000) and dextran (MW 6000) as in vitro crowding agents and observed their effects both the kinetics of alkaline phosphatase-catalyzed para-nitrophenyl phosphate hydrolysis and the inhibition of this reaction by competitive and uncompetitive inhibitors. Reaction kinetics were followed using UV-visible spectrometry and the initial rate was analyzed using Michaelis-Menten kinetics to arrive at an apparent Vmax and Km for each reaction condition. We observed that polyethylene glycol increased Vmax while a similar amount of dextran strongly reduced Vmax. Crowding by these agents also significantly altered the effectiveness of small-molecule inhibitors and suggests that the action of drugs can be different going from “bench” research to “bedside” application. *Indicates presenters
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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 | 0.001 |
| 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) | 0.000 | 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 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".