Partial interdigitation of lipid bilayers
Bibliographic record
Abstract
Abstract A methodology has been developed to detect partial interdigitation of lipid bilayers when a bioactive molecule is intercalated between the polar, interface, or hydrophobic segments. This methodology uses the easily accessible differential scanning calorimetry (DSC) technique as a screening one and the increase of Δ H due to the incorporated drug in lipid bilayers as a diagnostic thermodynamic parameter. The combined use of X‐ray diffraction and Raman spectroscopy complement and confirm the provided by DSC information as it is shown in three classes of molecules, namely AT 1 antagonists, vinca alkaloids, and anesthetic steroids. For the two classes of molecules, AT 1 antagonists and vinca alkaloids, their presence in lipid bilayers results in the increase of Δ H and it is accompanied by the increase of trans:gauche ratio and the decrease of d ‐spacing as depicted by Raman spectroscopy and small‐angle X‐ray diffraction correspondingly, confirming the predictive ability of DSC experiments. When an anesthetic steroid is incorporated in lipid bilayers, neither increase of Δ H nor decrease of d ‐spacing was observed, confirming again the DSC results that show the absence of partial interdigitation of this class of molecules. Molecular dynamics simulations have been carried out for a representative system [(5S)‐1‐benzylo‐5‐(1H‐benzimidazol‐1‐ylo‐methylo)‐2‐pyrrolidinone (MMK3) ligands at 1,2‐dimyristoyl‐sn‐glycero‐3‐phosphocholine (DMPC) lipid bilayer], and the results confirmed the experimental findings. The change of distance at z ‐axis of oxygen atoms at head group of lipid molecule has been measured throughout the simulations. Statistical analysis has shown ∼8.8 Å interdigitation. Derived computational results are encouraging and can be performed to another ligand/lipid system. The development of a theoretical methodology will lead to advance the field and save a valuable time and effort. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".