Locking Intracellular Helices 2 and 3 Together Inactivates Human P-glycoprotein
Bibliographic record
Abstract
The P-glycoprotein (P-gp) drug pump (ABCB1) has two transmembrane domains and two nucleotide-binding domains (NBDs). Coupling of the drug-binding sites in the transmembrane domains to the NBDs occurs through interaction of the intracellular helices (IHs) with residues in the NBDs (IH1/IH4/NBD1 and IH2/IH3/NBD2). We showed previously that cross-linking of cysteines in IH3 and IH1 with a short cross-linker mimicked drug binding as it activated P-gp ATPase activity. Here we show that residue A259C(IH2) could be directly cross-linked to W803C(IH3). Cross-linking was inhibited by the presence of ATP and adenosine 5'-(β,γ-imino)triphosphate but not by ADP. Cross-linking of mutant A259C/W803C inhibited its verapamil-stimulated ATPase activity mutant, but activity was restored after addition of dithiothreitol. Because these residues are close to the ball-and-socket joint A266C(IH2)/Phe(1086)(NBD2), we mutated the adjacent Tyr(1087)(NBD2) close to IH3. Mutants Y1087A and Y1087L, but not Y1087F, were misprocessed, and all inhibited ATPase activity. Mutation of hydrophobic residues (F793A, L797A, L814A, and L818A) flanking IH3 also inhibited maturation. The results suggest that these residues, together with Trp(803) and Phe(804), form a large hydrophobic pocket. The results show that there is an important hydrophobic network at the IH2/IH3/NBD2 transmission interface that is critical for folding and activity 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".