Comparative modeling of the phosphatase and kinase domains of protein tyrosine phosphatase and insulin receptor kinase from <i>Drosophila melanogaster</i> (DPTP61fm), and a computational study of their mutual interactions
Bibliographic record
Abstract
The components and functions of the insulin receptor kinase signaling pathway have been conserved in a broad range of Metazoa ranging from mammals to insects and nematodes. There is a high degree of sequence homology and functional similarity between the human insulin receptor kinase (IRK) and the drosophila (Drosophila melanogaster) form (DIRK) of this enzyme. Similarly, a high degree of homology exists between human protein tyrosine phosphatase 1B (PTP1B) (which directly regulates IRK) and its drosophila counterpart DPTP61F (DPTP). However, genetic and biochemical studies have yet to demonstrate that DPTP61F acts in the DIRK pathway. Comparative structural modeling techniques using the known structures of human IRK and PTP1B as templates have yielded structures for the drosophila enzymes. The derived structures confirm that there is a high level of structural conservation at the tertiary level. Association of the DIRK and DPTP enzymes with each other was then investigated with a view to ascertaining whether DIRK might be a substrate of the DPTP. Evaluation of the interaction surfaces, including hydrophobic patch, shape, hydrogen bonding, and electrostatic compatibility, strongly suggested that the drosophila insulin receptor is a substrate of the DPTP. The interaction surfaces of the human and drosophila enzymes are structurally similar, although changes in critical residues modify possible electrostatic and hydrogen-bonding interactions. This suggests that in the mixed systems, DPTP-IRK or PTP1B-DIRK, the kinase domain will be a comparatively poor substrate for phosphatase activity when compared with the native systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".