Thiols as Classical and Slow-Binding Inhibitors of IMP-1 and Other Binuclear Metallo-β-lactamases
Bibliographic record
Abstract
The inhibitory effect of a variety of thiol compounds on the function of binuclear metallo-beta-lactamases, with a particular focus on IMP-1 from Pseudomonas aeruginosa, has been investigated. Thiol inhibitors, depending on their structural features, fall into two categories, one in which inhibition at neutral pH was instantaneous and the other in which inhibition was time-dependent. While mercaptans with anionic substituents in the vicinity of their SH groups exhibited the former type of inhibition, neutral thiols appear to induce a slow, time-dependent isomerization of the initially formed EI complex to a tighter EI complex. Kinetic parameters describing the latter process were obtained by fitting progress curves of substrate hydrolysis using standard and numerical procedures. The failure of charged thiols to exhibit slow binding is suggested to be due to a rapid isomerization of the initial EI complex. Slow binding in the case of neutral thiols was observed only below pH 8. Studies on the pH dependence of catalysis by IMP-1 revealed that (i) enzyme inactivation at low pH is a slow process with presumably two groups with a pK(a) of approximately 5.2 in the protein being responsible for the loss of activity, (ii) inhibition by thiols is independent of pH between pH 5 and 9, and (iii) an apparent enhancement of the catalytic activity of IMP-1 by thiols occurs at pH <5. The last mentioned phenomenon is explained by a model in which mercaptans retard the proton-dependent isomerization of the enzyme. Studies on the thiol-mediated inhibition of the binuclear forms of Bacteroides fragilis (CcrA) and Bacillus cereus (BcII strain 5/B/6) metallo-beta-lactamase have revealed that while CcrA was instantaneously albeit moderately inhibited by mercaptans, BcII mimicked IMP-1 in its interaction with thiols. These differences are proposed to be due partly to the structural divergence of these proteins in the vicinity of Zn2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".