Interplay Between Membrane Curvature and Conformational States in ABC Transporters
Bibliographic record
Abstract
ATP-Binding Cassette (ABC) transporters constitute one of the largest superfamily of transmembrane proteins, present in both prokaryotes and eukaryotes. ATP hydrolysis at the nucleotide binding domains (NBD) drives conformational changes in the transmembrane domains (TMD) allowing substrate translocation. During this process, the structure of the ABC transporter alternates between the inward-facing (IF) conformation and the outward-facing (OF) conformation. The most prevalent and best characterized ABC-member is the mammalian P-glycoprotein (Pgp). Pgp extrudes cytotoxic drugs out of the cell, hampering interactions with their cellular targets, and, in combination with overexpression of the transporter in cancer cells, Pgp leads to failure of cancer chemotherapy. In the IF conformation, for substrate binding, Pgp displays an inverted conical shape, while in the OF conformation, for substrate release, the protein acquires a cylinder-like shape. It has been proposed that proteins with different shapes may not only diffuse differently along the lipid bilayer but also induce different local membrane curvature. In this study, we performed coarse-grained (CG) molecular dynamics (MD) simulations of Pgp in the IF and OF conformations using the Martini force field to assess the influence of protein shape in lateral diffusion and induced membrane curvature under regimes of low and high protein density (LPD, HPD). Our 50μs long simulations reveal that in the IF form, protein diffusion is significantly diminished when in a crowded environment. In contrast, the OF form, remains unaltered. Our findings also indicate that in the IF form, protein-protein interactions are driven by a cooperative effect coupled to the membrane curvature induced by conical shape profile. Our results are aligned with previous computational and experimental reports, reinforcing the hypothesis that shape has a substantial effect in protein diffusion and deformation of the local lipid environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".