Lead(II) Binding to the Chelating Agent <scp>d</scp>-Penicillamine in Aqueous Solution
Bibliographic record
Abstract
A spectroscopic investigation of the complexes formed between the Pb(II) ion and D-penicillamine (H2Pen), a chelating agent used in the treatment of lead poisoning, was carried out on two sets of alkaline aqueous solutions with CPb(II) ≈ 10 and 100 mM, varying the H2Pen/Pb(II) molar ratio (2.0, 3.0, 4.0, 10.0). Ultraviolet-visible (UV-vis) spectra of the 10 mM Pb(II) solutions consistently showed an absorption peak at 298 nm for S(-) → Pb(II) ligand-to-metal charge-transfer. The downfield (13)C NMR chemical shift for the penicillamine COO(-) group confirmed Pb(II) coordination. The (207)Pb NMR chemical shifts were confined to a narrow range between 1806 ppm and 1873 ppm for all Pb(II)-penicillamine solutions, indicating only small variations in the speciation, even in large penicillamine excess. Those chemical shifts are considerably deshielded, relative to the solid-state (207)Pb NMR isotropic chemical shift of 909 ppm obtained for crystalline penicillaminatolead(II) with Pb(S,N,O-Pen) coordination. The Pb LIII-edge extended X-ray absorption fine structure (EXAFS) spectra obtained for these solutions were well-modeled with two Pb-S and two Pb-(N/O) bonds with mean distances 2.64 ± 0.04 Å and 2.45 ± 0.04 Å, respectively. The combined spectroscopic results, reporting δ((207)Pb) ≈ 1870 ppm and λmax ≈ 298 nm for a Pb(II)S2NO site, are consistent with a dominating 1:2 lead(II):penicillamine complex with [Pb(S,N,O-Pen)(S-HnPen)](2-n) (n = 0-1) coordination in alkaline solutions, and provide useful structural information on how penicillamine can function as an antidote against lead toxicity in vivo.
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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) | 0.001 | 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".