Transmembrane segment 7 of human P-glycoprotein forms part of the drug-binding pocket
Bibliographic record
Abstract
P-gp (P-glycoprotein; ABCB1) protects us by transporting a broad range of structurally unrelated compounds out of the cell. Identifying the regions of P-gp that make up the drug-binding pocket is important for understanding the mechanism of transport. The common drug-binding pocket is at the interface between the transmembrane domains of the two homologous halves of P-gp. It has been shown in a previous study [Loo, Bartlett and Clarke (2006) Biochem. J. 396, 537-545] that the first transmembrane segment (TM1) contributed to the drug-binding pocket. In the present study, we used cysteine-scanning mutagenesis, reaction with an MTS (methanethiosulfonate) thiol-reactive analogue of verapamil (termed MTS-verapamil) and cross-linking analysis to test whether the equivalent transmembrane segment (TM7) in the C-terminal-half of P-gp also contributed to drug binding. Mutation of Phe728 to cysteine caused a 4-fold decrease in apparent affinity for the drug substrate verapamil. Mutant F728C also showed elevated ATPase activity (11.5-fold higher than untreated controls) after covalent modification with MTS-verapamil. The activity returned to basal levels after treatment with dithiothreitol. The substrates, verapamil and cyclosporin A, protected the mutant from labelling with MTS-verapamil. Mutant F728C could be cross-linked with a homobifunctional thiol-reactive cross-linker to cysteines I306C(TM5) and F343C(TM6) that are predicted to line the drug-binding pocket. Disulfide cross-linking was inhibited by some drug substrates such as Rhodamine B, calcein acetoxymethyl ester, cyclosporin, verapamil and vinblastine or by vanadate trapping of nucleotides. These results indicate that TM7 forms part of the drug-binding pocket of P-gp.
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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 | 0.001 |
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".