Kinetics of human peptidylarginine deiminase 2 (hPAD2) — Reduction of Ca<sup>2+</sup> dependence by phospholipids and assessment of proposed inhibition by paclitaxel side chains
Bibliographic record
Abstract
Multiple sclerosis is a complex human neurodegenerative disease, characterized by the active destruction of the insulating myelin sheath around the axons in the central nervous system. The physical deterioration of myelin is mediated by hyperdeimination of myelin basic and other proteins, catalysed by the Ca2+ -dependent enzyme peptidylarginine deiminase 2 (PAD2). Thus, inhibition of PAD2 may be of value in treatment of this disease. Here, we have first characterized the in vitro kinetic properties of the human peptidylarginine deiminase isoform 2 (hPAD2). Phosphatidylserine and phosphatidylcholine reduced its Ca2+ dependence by almost twofold. Second, we have explored the putative inhibitory action of the methyl ester side chain of paclitaxel (TSME), which shares structural features with a synthetic PAD substrate, viz., the benzoyl-L-arginine ethyl ester (BAEE). Using the known crystallographic structure of the homologous enzyme hPAD4 and in silico molecular docking, we have shown that TSME interacted strongly with the catalytic site, albeit with a 100-fold lower affinity than BAEE. Despite paclitaxel having previously been shown to inhibit hPAD2 in vitro, the side chain of paclitaxel alone did not inhibit this enzyme's activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".