The recognition and catalytic hydrolysis of ATP by protonated phenanthroline-bridged polyamine and (or) Ca(II), Mg(II), Zn(II), and La(III) ions
Bibliographic record
Abstract
The supramolecular interactions of 2,9-di(((2′-phenylamino)ethyleneamino)methyl)-1,10-phenanthroline (L) and (or) metal ions (M = Ca2+, Mg2+, Zn2+, or La3+) with nucleotides were investigated. Furthermore, the hydrolysis of ATP catalyzed by a protonated ligand and (or) a metal ion (M = Ca2+, Mg2+, Zn2+, or La3+) was studied at pH 7.6 using 31P NMR spectra. Kinetics studies show that at pH 7.6 the protonated ligand, with a rate constant of 2.9 × 104 min1, does not significantly promote ATP hydrolysis. However, in the presence of Ca2+, Mg2+, Zn2+, or La3+ ions, L can accelerate the hydrolysis of ATP, with corresponding rate constants of 5.73, 1.48, 6.76, and 31.7 × 103 min1, respectively, which are about 29-, 7.5-, 34-, and 159-fold faster than the hydrolysis rate of free ATP. By comparison with MATP (M = Ca2+, Mg2+, and La3+) systems, the rates of MLATP were also promoted. This has been achieved through the effective recognition of ATP and the availability of a good intramolecular nucleophile, i.e., a free amino nitrogen atom of L. Compared with the Zn2+ATP system, the decrease in the rate of the Zn2+LATP system at pH 7.6 may be attributed to the competition between the mixed ligands in binding Zn2+. Similar to LATP, the hydrolysis reactions in the Zn2+LATP or MLATP (M = Ca2+, Mg2+, and La3+) systems occur through an additionelimination type mechanism, in which phosphoramidate intermediates were observed at 2.88 and 4.06 parts per million (ppm) in the LATP and Mg2+LATP systems, respectively. Here, metal ions add control or regulation to the hydrolysis reaction. Key words: recognition, ATP hydrolysis, metal ions, phenanthroline-bridged polyamine.
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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".