Systems-wide Identification of cis-Regulatory Elements in Proteins
Bibliographic record
Abstract
Protein interactions in cis that can activate or autoinhibit protein function play an important role in the fine-tuning of regulatory and signaling processes in the cell, but thus far cis-regulatory elements (CREs) in proteins have not been systematically identified and studied. Here, we introduce a computational tool that identifies intrinsically disordered protein segments that contribute to protein function regulation via interactions in cis. We apply this tool to estimate the prevalence of CREs in the human proteome and reveal that cis regulation is enriched in several signaling pathways, including the MAP kinase pathway, for which we provide a detailed map of its "cis regulome." We also show that disease-causing mutations are highly enriched in CREs, but not in motifs that classically mediate protein-protein interactions of disordered protein segments. Our approach should facilitate the discovery and characterization of CREs in proteins and the identification of disease-causing mutations that disrupt protein regulation in cis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".