Interaction between 2-(<i>p</i>-toluidino)-6-naphthalenesulfonic acid sodium salt (TNS) and β-lactoglobulin
Bibliographic record
Abstract
The major bovine milk protein β-lactoglobulin (β-LG), a member of the lipocalin superfamily, can bind a wide range of ligands and act as a transporter. In the present study, the combination of the hydrophobic molecule 2-(p-toluidino)-6-naphthalenesulfonic acid sodium salt (TNS) with β-LG was analyzed using fluorescence spectroscopy and AutoDock modeling to discern the major binding sites of the protein and to determine the capacity of other small ligands to bind with β-LG by utilizing TNS as a reference. The experimental data indicate that in a neutral pH environment, TNS is located in the hydrophobic domain of the protein, 2.5 nm away from the Trp19 residues of β-LG. The binding constant of the small molecule to β-LG is (3.30 ± 0.32) × 106 (mol L–1)−1. An interaction model between the ligand and β-LG was developed, and AutoDock modeling also demonstrates that the ligand is located in the central hydrophobic calyx of β-LG within the regions covered by the Förster radius of the Trp19–ligand pair. Although the interaction between the ligand and β-LG is affected by increasing ion strength, pH change, and heat treatment, the complex is maintained until the secondary structure of β-LG is destroyed. Additionally, the ligand binding stabilizes the folding of β-LG. The binding constants of sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS) to β-LG were obtained using competitive ligand binding measurements. With a sensitive fluorescence signal and stable complex, the ligand could be utilized as a reference to detect the binding of other small ligands to β-LG.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".