Drug transport by reconstituted P‐glycoprotein in proteoliposomes
Bibliographic record
Abstract
The P‐glycoprotein multidrug transporter (Pgp) is an active efflux pump for chemotherapeutic drugs, natural products and hydrophobic peptides. Pgp is envisaged as a ‘hydrophobic vacuum cleaner’, and drugs are believed to gain access to the substrate binding sites from within the membrane, rather than from the aqueous phase. The intimate association of both Pgp and its substrates with the membrane suggests that its function may be regulated by the biophysical properties of the lipid bilayer. Using the high affinity fluorescent substrate tetramethylrosamine (TMR), we have monitored, in real time, transport in proteoliposomes containing reconstituted Pgp. The TMR concentration gradient generated by Pgp was collapsed by the addition of either the ATPase inhibitor, vanadate, or Pgp modulators. TMR transport by Pgp obeyed Michaelis–Menten kinetics with respect to both of its substrates. The Km for ATP was 0.48 mm, close to the Km for ATP hydrolysis, and the Km for TMR was 0.3 µm. TMR transport was inhibited in a concentration‐dependent fashion by verapamil and cyclosporin A, and activated (probably by a positive allosteric effect) by the transport substrate colchicine. TMR transport by Pgp reconstituted into proteoliposomes composed of two synthetic phosphatidylcholines showed a highly unusual biphasic temperature dependence. The rate of TMR transport was relatively high in the rigid gel phase, reached a maximum at the melting temperature of the bilayer, and then decreased in the fluid liquid crystalline phase. This pattern of temperature dependence suggests that the rate of drug transport by Pgp may be dominated by partitioning of drug into the bilayer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".