Characterization of the Catalytic and Nucleotide Binding Properties of the α-Kinase Domain of Dictyostelium Myosin-II Heavy Chain Kinase A
Bibliographic record
Abstract
The α-kinases are a widely expressed family of serine/threonine protein kinases that exhibit no sequence identity with conventional eukaryotic protein kinases. In this report, we provide new information on the catalytic properties of the α-kinase domain of Dictyostelium myosin-II heavy chain kinase-A (termed A-CAT). Crystallization of A-CAT in the presence of MgATP yielded structures with AMP or adenosine in the catalytic cleft together with a phosphorylated Asp-766 residue. The results show that the β- and α-phosphoryl groups are transferred either directly or indirectly to the catalytically essential Asp-766. Biochemical assays confirmed that A-CAT hydrolyzed ATP, ADP, and AMP with kcat values of 1.9, 0.6, and 0.32 min(-1), respectively, and showed that A-CAT can use ADP to phosphorylate peptides and proteins. Binding assays using fluorescent 2'/3'-O-(N-methylanthraniloyl) analogs of ATP and ADP yielded Kd values for ATP, ADP, AMP, and adenosine of 20 ± 3, 60 ± 20, 160 ± 60, and 45 ± 15 μM, respectively. Site-directed mutagenesis showed that Glu-713, Leu-716, and Lys-645, all of which interact with the adenine base, were critical for nucleotide binding. Mutation of the highly conserved Gln-758, which chelates a nucleotide-associated Mg(2+) ion, eliminated catalytic activity, whereas loss of the highly conserved Lys-722 and Arg-592 decreased kcat values for kinase and ATPase activities by 3-6-fold. Mutation of Asp-663 impaired kinase activity to a much greater extent than ATPase, indicating a specific role in peptide substrate binding, whereas mutation of Gln-768 doubled ATPase activity, suggesting that it may act to exclude water from the active site.
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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".