ATP Binding Residues of Sarcoplasmic Reticulum Ca<sup>2+</sup>‐ATPase
Bibliographic record
Abstract
ATP-binding residues in the N and P domains of sarcoplasmic reticulum Ca-ATPase have been investigated using mutagenesis in combination with a binding assay based on the photolabeling of Lys(492) with [g-(32)P] 2',3'-O-(2,4,6 trinitrophenyl)-8-azido-ATP and competition with nucleotide. In the N domain, mutations to several residues in conserved motifs, (438)GEATE, (487)FSRDRK, (515)KGAPE, and (560)RCLALA produce nucleotide-binding defects. Key residues include Thr(441), Glu(442), Phe(487), Arg(489), Lys(492), Lys(515), Arg(560), and Leu(562). In the absence of Mg(2+), Arg(489), Lys(492), and Arg(560) are most important, whereas in its presence Thr(441) and Glu(442) also play a crucial role. In the P domain, Asp(351) is striking for its strong electrostatic repulsion of the gamma-phosphate, especially in the presence of Mg(2+). Lys(352) is a key residue, and Asp(627) and Lys(684) must come close to the nucleotide. Thr(353), Asn(359), Asp(601), and Asp(703) interact only in the presence of Mg(2+). Asn(706) and Asp(707) are unimportant for nucleotide binding. The results identify several ATP binding residues in the N and P domains and suggest that Mg(2+) changes the nucleotide/protein interaction in both. Models of bound ATP and MgATP are presented.
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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".