Carbapenems and Lipid Bilayers: Localization, Partitioning, and Energetics
Bibliographic record
Abstract
Carbapenems are broad-spectrum antibiotics used today to treat otherwise antibiotic resistant bacteria. As their target transpeptidase is located within the periplasm of the Gram-negative bacteria, they can participate in nonspecific interactions between the inner leaflet of the outer membrane and the outer leaflet of the inner membrane. We, therefore, studied the interaction of the four most clinically relevant carbapenems, namely, imipenem, doripenem, ertapenem, and meropenem, with model phospholipid bilayers made of 1,2-dimyristoyl- sn-glycero-3-phosphocholine (DMPC) using molecular dynamics (MD) simulations and X-ray diffraction at low and high concentration of the drugs corresponding to 1 and 8 mol % (with respect to the number of membrane lipids). Membrane solubility was found to decrease from imipenem to doripenem, ertapenem, and finally meropenem. At low concentrations, membrane insertion was found to be a two step process, where the drugs first adsorb to the lipid head groups before inserting through a rotation of the molecule. At higher drug concentrations, the molecules were found to form aggregates in the aqueous phase before making contact with the membranes and spontaneously inserting into the bilayers. Two populations of imipenem were found: in the headgroup at ∼17 Å from the bilayer center and an inserted population at z-values of about 7 Å. Other carbapenems were found to localize in the tail groups with meropenem at ∼10 Å, doripenem at ∼8 Å, and ertapenem at ∼8 Å. The observed membrane solubility of carbapenems can potentially impact the availability of the drug to the target penicillin-binding proteins, potentially affecting their clinical efficacy.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".