Bimolecular complementation affinity purification (BiCAP) reveals dimer-specific protein interactions for ERBB2 dimers
Bibliographic record
Abstract
The dynamic assembly of multiprotein complexes is a central mechanism of many cell signaling pathways. This process is key to maintaining the spatiotemporal specificity required for an accurate, yet adaptive, response to rapidly changing cellular conditions. We describe a technique for the specific isolation and downstream proteomic characterization of any two interacting proteins, to the exclusion of their individual moieties and competing binding partners. We termed the approach bimolecular complementation affinity purification (BiCAP) because it combines the use of conformation-specific nanobodies with a protein-fragment complementation assay with affinity purification. Using BiCAP, we characterized the specific interactome of the epidermal growth factor receptor (EGFR) family member ERBB2 when in the form of a homodimer or when in the form of a heterodimer with either EGFR or ERBB3. We identified dimer-specific interaction patterns for key adaptor proteins and identified a number of previously unknown interacting partners. Functional analysis for one of these newly identified partners revealed a noncanonical mechanism of extracellular signal-regulated kinase (ERK) activation that is specific to the ERBB2:ERBB3 heterodimer and acts through the adaptor protein FAM59A in breast cancer cells.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".