Disulfiram Metabolites Permanently Inactivate the Human Multidrug Resistance P-Glycoprotein
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Bibliographic record
Abstract
The human multidrug resistance P-glycoprotein (P-gp) uses ATP to transport a wide variety of structurally unrelated cytotoxic compounds out of the cell. The relatively high expression of P-gp in organs such as the intestine, kidney, blood-brain/testes barrier and in some tumor cells can compromise chemotherapy treatments for patients with cancer or AIDS/HIV. It has been difficult to inhibit P-gp during chemotherapy with noncovalent inhibitors because the relatively high levels of inhibitors have severe side effects. An alternative approach to inhibit P-gp would be to covalently modify cysteine residues within the NBDs. In this study, we tested whether metabolites of disulfiram, a drug currently used to treat chronic alcoholism, could inhibit P-gp. We show that the disulfiram metabolites, S-methyl N,N-diethylthiocarbamate sulfoxide and S-methyl N,N-diethylthiocarbamate sulfone inhibited the verapamil-stimulated ATPase activity of P-gp with IC50 values (concentrations that result in 50% inhibition of activity) of 9 and 4.8 microM, respectively. Similarly, S-methyl N,N-diethylthiocarbamate sulfoxide and S-methyl N,N-diethylthiocarbamate sulfone inhibited the activity of aldehyde dehydrogenase with IC50 values of 3.2 and 1.7 microM, respectively. Inhibition of P-gp by the metabolites was not reversed by addition of the reducing compound, dithiothreitol. We then determined which endogenous cysteine residue was responsible for inhibiting P-gp activity after exposure to the disulfiram metabolites. Treatment of P-gp mutants containing a single cysteine residue showed that inactivation was primarily due to modification of Cys1074 in NBD2. These results indicate that metabolites of disulfiram can covalently inactivate P-gp. Covalent modification of drug transporters could be a useful approach for inhibiting their activities during chemotherapy.
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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 | 0.001 |
| 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 it