<i>In-vivo</i> crystals reveal protein interactions
Bibliographic record
Abstract
Abstract Crystallisation of recombinant proteins has been fundamental to our understanding of protein function, dysfunction, and molecular recognition. However, this information has often been gleaned under non-physiological extremes of protein, salt, and H + concentrations. Here, we describe the development of the robust iBox-PAK4cat system that spontaneously crystallises in several mammalian cell types. The developments described here allow the quantitation of in-vivo protein-protein interactions using a novel GFP-linked reporter system. Here, we have combined this assay with in-vitro X-ray crystallography and molecular dynamics studies characterise the molecular determinants of the interaction between NHERF1 PDZ2 and CFTR, a protein complex pertinent to the genetic disease cystic fibrosis. These studies have revealed the crystal structure of the extended PDZ domain of NHERF1, and indicated, contrary to previous reports, that residue selection at −1 and −3 PDZ-binding motif positions influence the affinity and specificity of the interaction. The results presented here demonstrate that the iBox-PAK4cat assay could easily be utilised to screen other protein-protein interactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".