P-glycoprotein (ABCB1) interacts directly with lipid-based anti-cancer drugs and platelet-activating factorsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Membrane Proteins in Health and Disease.
Bibliographic record
Abstract
The P-glycoprotein multidrug transporter (Pgp; ABCB1) is an ATP-binding cassette (ABC) protein that has been implicated in the multidrug resistance of human cancers. Pgp couples ATP hydrolysis to active extrusion from the cell of a broad array of amphipathic compounds via an ill-defined mechanism. Substrates are believed to interact with Pgp within the membrane. Reconstituted Pgp functions as an ATP-dependent flippase for a variety of fluorescently labelled membrane lipids. The protein may also function as a drug 'flippase', moving its substrates from the inner to the outer leaflet of the bilayer. We show that lipid-based anti-cancer drugs, such as miltefosine, and signaling molecules, such as platelet-activating factors, bind saturably to Pgp with Kd values in the low micromolar range, and modulate its ATPase activity. These compounds also inhibit Pgp-mediated flipping of fluorescent lipids and transport of Hoechst 33342 and tetramethylrosamine, which occupy different subsites in the drug-binding pocket. Bacterial lipid A modulates Pgp ATPase activity, and glycolipid flipping is inhibited by unlabelled glucosylceramide, suggesting that these lipids also interact with the transporter. These results indicate that Pgp treats a variety of lipid-based molecules as substrates, and likely interacts with lipids and drugs in the same manner.
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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) | 0.002 | 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".