Paclitaxel Is an Inhibitor and Its Boron Dipyrromethene Derivative Is a Fluorescent Recognition Agent for Botulinum Neurotoxin Subtype A
Bibliographic record
Abstract
We have successfully identified one new inhibitor and one new fluorescent recognition agent for the botulinum neurotoxin subtype A (BoNT/A) using the virtual screening protocol "protein scanning with virtual ligand screening" (PSVLS). Hit selection used an in-house developed holistic binding scoring method. Selected hits were tested experimentally for inhibitory activity using fluorescence resonance energy transfer (FRET) assays against the light chain (catalytic domain) of BoNT/A. Ligand binding was determined against the light and heavy chain BoNT/A complex through either radiolabeled ligand binding assays (nonfluorescent ligands) or fluorescence intensity assays (fluorescent ligands). These experimental assays have confirmed one compound (paclitaxel) to inhibit BoNT/A's proteolytic activity experimentally with an IC50 of 5.2 μM. A fluorescent derivative was also confirmed to bind to the toxin and therefore is a suitable candidate for the rational design of new detection agents and for the development of fluorescence-based multiprobe detection assays.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".