Transition State P-glycoprotein Binds Drugs and Modulators with Unchanged Affinity, Suggesting a Concerted Transport Mechanism
Bibliographic record
Abstract
The P-glycoprotein multidrug transporter is a plasma membrane efflux pump for hydrophobic natural products, drugs, and peptides, driven by ATP hydrolysis. Determination of the details of the catalytic cycle of P-glycoprotein is critical if we are to understand the mechanism of drug transport and design ways to inhibit it. It has been proposed that the vanadate-trapped transition state of P-glycoprotein (Pgp x ADP x V(i) x M(2+), where M(2+) is a divalent metal ion) has a very low affinity for drugs compared to resting state protein, thus leading to binding of substrate on the cytoplasmic side of the membrane and release of substrate to the extracellular medium (or the extracellular membrane leaflet). We have used several different fluorescence spectroscopic approaches to show that isolated purified P-glycoprotein, when trapped in a stable transition state with vanadate and either Co(2+)or Mg(2+), binds drugs with high affinity. For vinblastine, colchicine, rhodamine 123, and doxorubicin, the affinity of the vanadate-trapped transition state for drugs was only very slightly (less than 2-fold) lower than the binding affinity of resting state Pgp, whereas for the modulators cyclosporin A and verapamil and the substrate Hoechst 33342, the binding affinity was very similar for the two states. The drug binding affinity of the ADP-bound form of the transporter was also comparable to that of the unoccupied transporter. These results suggest that release of drug from the transporter during the catalytic cycle precedes formation of the transition state.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".