Circular dichroism and fluorescence spectroscopic study on the interaction of bisdemethoxycurcumin and diacetylbisdemethoxycurcumin with human serum albumin
Bibliographic record
Abstract
The interactions of bisdemethoxycurcumin (BDMC) as a bioactive constituent of turmeric and diacetylbisdemethoxycurcumin (DABC) as a novel synthetic derivative of curcumin with human serum albumin (HSA) have been investigated by fluorescence and circular dichroism (CD) spectroscopy. The binding parameters, including the number of substantive binding sites and the binding constants, have been estimated from the analysis of fluorescence measurements. The estimated binding parameters indicated that BDMC has higher affinity than DABC to bind HSA, suggesting the essential role of the phenolic OH groups of BDMC, which are acetylated in DABC. It was found that the binding site for BDMC and DABC is located in the vicinity of Trp-214 in subdomain IIA, which is the same as binding site for curcumin (CUR). The minor changes on the far-UV circular dichroism spectra resulted in partial changes in the calculated secondary structure contents of HSA. The negligible alteration in the secondary structure of HSA indicated that ligand-induced conformational changes are localized in the binding site and do not involve considerable changes in the protein folding. The visible CD spectra indicated that the optical activity observed during the ligand binding is due to induced-protein chirality.
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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".