Structural Analysis of Human Serum Albumin Complexes with Cationic Lipids
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Bibliographic record
Abstract
Human serum albumin (HSA) is a major transporter for delivering several endogenous compounds including fatty acids in vivo. Even though HSA is the primary target of fatty acid binding, the effects of cationic lipid on protein stability and conformation have not been investigated. The aim of this study was to examine the interaction of human serum albumin (HSA) with helper lipids--cholesterol (Chol) and dioleoylphosphatidylethanolamine (DOPE)--and with cationic lipids--dioctadecyldimethylammonium bromide (DDAB) and 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), at physiological conditions, using constant protein concentration and various lipid contents. Fourier transform infrared (FTIR), circular dichroism (CD), and fluorescence spectroscopic methods were used to analyze the lipid binding mode, the binding constant, and the effects of lipid interaction on HSA stability and conformation. Structural analysis showed that cholesterol and DOPE (helper lipids) interact mainly with HSA polypeptide polar groups and via hydrophobic moieties. Hydrophobic interactions dominate the binding of cationic lipids to HSA. The number of bound lipids (n) calculated was 1.22 (cholesterol), 1.82 (DDAB), 1.76 (DOPE), and 1.56 (DOTAP). The overall binding constants estimated were KChol=2.3 (+/-0.50)x10(3) M(-1), KDDAB=8.9 (+/-0.95)x10(3) M(-1), KDOTAP=9.1 (+/-0.90)x10(3) M(-1), and KDOPE=4.7 (+/-0.70)x10(3) M(-1). HSA conformation was stabilized by cholesterol and DOPE with a slight increase of protein alpha-helical structures, while DOTAP and DDAB induced an important (alpha-->beta) transition, suggesting a partial protein unfolding.
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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 it