The antibacterial activity of <i>p-tert</i>-butylcalix[6]arene and its effect on a membrane model: molecular dynamics and Langmuir film studies
Bibliographic record
Abstract
The antibacterial activity of a calixarene derivative, p-tert-butylcalix[6]arene (Calix6), was assessed and was shown not to inhibit the growth of E. coli, S. aureus and B. subtilis bacteria. With the aim of gaining more insights into the absence of antibacterial activity of Calix6, the interaction of this derivative with DPPG, a bacterial cell membrane lipid, was studied. Langmuir monolayers were used as the model membrane. Pure DPPG and pure Calix6 monolayers, as well as binary DPPG:Calix6 mixtures were studied using surface pressure measurements, compressional modulus, Brewster angle and fluorescence microscopies, ellipsometry, polarization-modulation infrared reflection absorption spectroscopy and molecular dynamics simulations. Thermodynamic properties of the mixed monolayers were additionally calculated using thermodynamic parameters. The analysis of isotherms showed that Calix6 significantly affects the DPPG monolayers, modifying the isotherm profile and increasing the molecular area, in agreement with the molecular dynamics simulations. The presence of Calix6 in the mixed monolayers decreased the interfacial elasticity, indicating that calixarene disrupts the strong intermolecular interactions of DPPG hindering its organization into a compact arrangement. At low molar ratios of Calix6, the DPPG:Calix6 interactions are preferentially attractive, due to the interactions between the hydrophobic tails of DPPG and the tert-butyl groups of Calix6. Increasing the proportion of calixarene generates repulsive interactions. Calix6 significantly affects the hydrophobic tail organization, which was confirmed by PM-IRRAS measurements. Calix6 appears to be expelled from the mixed films at a biologically relevant surface pressure, π = 30 mN m-1, indicating a low interaction with the cell membrane model related to the absence of antibacterial activity.
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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 | 0.000 |
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".