SH2db, an information system for the SH2 domain
Bibliographic record
Abstract
SH2 domains are key mediators of phosphotyrosine-based signalling, and therapeutic targets for diverse, mostly oncological, disease indications. They have a highly conserved structure with a central beta sheet that divides the binding surface of the protein into two main pockets, responsible for phosphotyrosine binding (pY pocket) and substrate specificity (pY + 3 pocket). In recent years, structural databases have proven to be invaluable resources for the drug discovery community, as they contain highly relevant and up-to-date information on important protein classes. Here, we present SH2db, a comprehensive structural database and webserver for SH2 domain structures. To organize these protein structures efficiently, we introduce (i) a generic residue numbering scheme to enhance the comparability of different SH2 domains, (ii) a structure-based multiple sequence alignment of all 120 human wild-type SH2 domain sequences and their PDB and AlphaFold structures. The aligned sequences and structures can be searched, browsed and downloaded from the online interface of SH2db (http://sh2db.ttk.hu), with functions to conveniently prepare multiple structures into a Pymol session, and to export simple charts on the contents of the database. Our hope is that SH2db can assist researchers in their day-to-day work by becoming a one-stop shop for SH2 domain related research.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.042 |
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".