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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".