Characterizing the binding of nucleotide ATP on serum albumin by <sup>31</sup>P NMR diffusion
Bibliographic record
Abstract
The pulsed-field-gradient (PFG) 31P NMR diffusion spectra were measured under varied sample conditions to characterize the low-affinity binding of adenosine 5′-triphosphate (ATP) on human serum albumin (HSA) or bovine serum albumin (BSA). The NMR diffusion constants of ATP, ATP–HSA, or ATP–BSA were illustrated as function of ATP concentrations. The binding curves of ATP–HSA and ATP–BSA were identical but strikingly different from the ATP curve. Using a “Scatchard plot”, the apparent binding constant (K) and number of ATP binding sites (n) on serum albumin were evaluated as K = 75.25 (mol/L)–1 and n = 10, respectively. At a pH < 5.0 and a pH > 9.0 or a temperature > 45 °C, the diffusion data of ATP–HSA were found to increase remarkably, suggesting that the dissociation of ATP from HSA was largely enhanced, probably because of pH- or heat-induced protein structural change, degradation, or aggregation. In addition, our data indicated that ADP was strongly competitive with ATP for the low-affinity binding to HSA, but heptanone and Cl– were essentially noncompetitive. These results are important for further elucidating the interaction of ATP with serum albumin and its possible effect on related bioprocesses. The method can be well applied to study the binding of other nucleotides/nucleosides on proteins.
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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".