Molecular Modeling and Spectroscopic Studies on the Interaction of Transresveratrol with Bovine Serum Albumin
Bibliographic record
Abstract
The interaction of transresveratrol (TRES) with bovine serum albumin (BSA) has been investigated by ultraviolet‐visible, fluorescence, Fourier transform infrared spectroscopic methods and molecular modeling techniques. The fluorescence results show that the intrinsic fluorescence of BSA is quenched by TRES through a static quenching procedure. The binding constants of TRES with BSA at 292, 297 and 302 K are calculated as 10.22 × 104, 8.71 × 104, and 7.59 × 104 L mol−1, respectively, and corresponding numbers of binding sites are approximately equal to unity. The thermodynamic parameters ΔH and ΔS are estimated to be −21.82 kJ mol−1 and +21.15 J mol−1 K−1, which indicates that the interaction of TRES with BSA is driven mainly by hydrophobic forces and there are also hydrogen bonds and electrostatic interactions. The competitive experiments suggest that the binding site of TRES to BSA is probably located on site II. The results of infrared spectra show that the binding of TRES with BSA leads to conformational changes of BSA, and the binding stabilizes the α‐helix and β‐sheet at the cost of a corresponding loss in the β‐turn structure of BSA. The results of molecular modeling calculation clarify the binding mode and the binding sites which are in good accordance with the experiment results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".