Locating the Binding Sites of Pb(II) Ion with Human and Bovine Serum Albumins
Bibliographic record
Abstract
Lead is a potent environmental toxin that has accumulated above its natural level as a result of human activity. Pb cation shows major affinity towards protein complexation and it has been used as modulator of protein-membrane interactions. We located the binding sites of Pb(II) with human serum (HSA) and bovine serum albumins (BSA) at physiological conditions, using constant protein concentration and various Pb contents. FTIR, UV-visible, CD, fluorescence and X-ray photoelectron spectroscopic (XPS) methods were used to analyse Pb binding sites, the binding constant and the effect of metal ion complexation on HSA and BSA stability and conformations. Structural analysis showed that Pb binds strongly to HSA and BSA via hydrophilic contacts with overall binding constants of K(Pb-HSA) = 8.2 (±0.8)×10(4) M(-1) and K(Pb-BSA) = 7.5 (±0.7)×10(4) M(-1). The number of bound Pb cation per protein is 0.7 per HSA and BSA complexes. XPS located the binding sites of Pb cation with protein N and O atoms. Pb complexation alters protein conformation by a major reduction of α-helix from 57% (free HSA) to 48% (metal-complex) and 63% (free BSA) to 52% (metal-complex) inducing a partial protein destabilization.
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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".