The Effects of Anions on the Solution Structure of Na,K-ATPase
Bibliographic record
Abstract
Anions interact with protein to induce structural changes at ligand binding sites. The effects of anion complexation include structural stabilization and promote cation-protein interaction. This study was designed to examine the interaction of aspirin and ascorbate anions with the Na+, K+-dependent adenosine triphosphatase (Na,K-ATPase) in H2O and D2O solutions at physiological pH, using anion concentrations of 0.1 microM to 1 mM with final protein concentration of 0.5 to 1 mg/ml. Absorption 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 anion binding mode, binding constant, and the protein secondary structure in the anion-ATPase complexes. Spectroscopic evidence showed that the anion interaction is mainly through the polypeptide C=O and C-N groups with minor perturbation of the lipid moiety. Evidence for this came from major spectral changes (intensity variations) of the protein amide I and amide II vibrations at 1651 and 1550 cm(-1). respectively. The anion-ATPase binding constants were K=6.45 x 10(3) M(-1) for aspirin and K=1.04 x 10(4) M(-1) for ascorbate complexes. The anion interaction resulted in major protein secondary structural changes from that of the alpha-helix 19.8%; beta-pleated sheet 25.6%; turn 9.1%; beta-antiparallel 7.5% and random 38% in the free Na,K-ATPase to that of the alpha-helix 24-26%; beta-pleated 17-18%; turn 8%; beta-antiparallel 5-3% and random 45.0% in the anion-ATPase complexes.
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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) | 0.000 | 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".