The effect of aspirin-HSA complexation on the protein secondary structure
Bibliographic record
Abstract
This study was designed to determine the secondary structure of human serum albumin (HSA) in the presence of aspirin in H2O and D2O solutions at physiological pH, using aspirin concentrations of 0.0001-5 mM with final protein concentration of 2% w/v. UV-vis spectra and Fourier transform infrared (FTIR) difference spectroscopy with its self-deconvolution, second derivative resolution enhancement, and curve-fitting procedures were applied to characterize the drug binding mode, the binding constant, and the protein secondary structure in the aspirin-HSA complexes. Spectroscopic evidence showed that no aspirin-protein interaction occurs at very low drug concentration (0.0001 mM), whereas at higher drug contents (0.001-0.1 mM) the aspirin anion binding (H-bonding) is mainly through the ε-amino NH3+ group with overall binding constant of K = 1.4 × 104 M-1. At high drug concentrations (1-5 mM), acetylation of Lys-199 was observed. Aspirin binding results in protein secondary structural changes from that of the α-helix 55% (free HSA) to 49%, β-sheet 22% (free HSA) to 31%, β-anti 12% (free HSA) to 4% and turn 11% (free HSA) to 16% in the aspirin-HSA complexes..Key words: aspirin, protein, drug, binding mode, binding constant secondary structure, FTIR spectroscopy.
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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".