Large-Scale Screening of Preferred Interactions of Human Src Homology-3 (SH3) Domains Using Native Target Proteins as Affinity Ligands
Bibliographic record
Abstract
The Src Homology-3 (SH3) domains are ubiquitous protein modules that mediate important intracellular protein interactions via binding to short proline-rich consensus motifs in their target proteins. The affinity and specificity of such core SH3 - ligand contacts are typically modest, but additional binding interfaces can give rise to stronger and more specific SH3-mediated interactions. To understand how commonly such robust SH3 interactions occur in the human protein interactome, and to identify these in an unbiased manner we have expressed 324 predicted human SH3 ligands as full-length proteins in mammalian cells, and screened for their preferred SH3 partners using a phage display-based approach. This discovery platform contains an essentially complete repertoire of the ∼300 human SH3 domains, and involves an inherent binding threshold that ensures selective identification of only SH3 interactions with relatively high affinity. Such strong and selective SH3 partners could be identified for only 19 of these 324 predicted ligand proteins, suggesting that the majority of human SH3 interactions are relatively weak, and thereby have capacity for only modest inherent selectivity. The panel of exceptionally robust SH3 interactions identified here provides a rich source of leads and hypotheses for further studies. However, a truly comprehensive characterization of the human SH3 interactome will require novel high-throughput methods based on function instead of absolute binding affinity.
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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".