Methanethiosulfonate Derivatives of Rhodamine and Verapamil Activate Human P-glycoprotein at Different Sites
Bibliographic record
Abstract
The human multidrug resistance P-glycoprotein (P-gp, ABCB1) actively extrudes a broad range of potentially cytotoxic compounds out of the cell. Key steps in understanding the transport process are binding of drug substrates in the transmembrane domains, initiation of ATPase activity, and subsequent drug efflux. We used cysteine-scanning mutagenesis of the transmembrane segment residues and reaction with the thiol-reactive drug substrate analog of rhodamine, methane-thiosulfonate-rhodamine (MTS-rhodamine), to test whether P-gp could be trapped in an activated state with high levels of ATPase activity. The presence of such an activated P-gp could be used to further investigate P-gp-drug substrate interactions. Single cysteine mutants (149) were treated with MTS-rhodamine, and ATPase activities were determined after removal of unreacted MTS-rhodamine. One mutant, F343C(TM6), showed a 5.8-fold increase in activity after reaction with MTS-rhodamine. Pre-treatment of mutant F343C with rhodamine B protected it from activation by MTS-rhodamine, indicating that residue Cys-343 contributes to the rhodamine-binding site. The ATPase activity of MTS-rhodamine-treated mutant F343C, however, was not stimulated further by colchicine or calcein-AM. By contrast, verapamil and Hoechst 33342 stimulated and inhibited, respectively, the ATPase activity of the MTS-rhodamine-treated mutant F343C. These results indicate that the MTS-rhodamine binding site overlaps that of colchicine and calcein-AM but not that of verapamil and Hoechst 33342 within the common drug-binding pocket.
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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".