A split intein and split luciferase-coupled system for detecting protein-protein interactions
Bibliographic record
Abstract
Elucidation of protein-protein interactions (PPIs) represents one of the most important methods in biomedical research. Recently, PPIs have started to be exploited for drug discovery purposes and have thus attracted much attention from both the academic and pharmaceutical sectors. We previously developed a sensitive method, Split Intein-Mediated Protein Ligation (SIMPL), for detecting binary PPIs via irreversible splicing of the interacting proteins being investigated. Here, we incorporated tripart nanoluciferase (tNLuc) into the system, providing a luminescence signal which, in conjunction with homogenous liquid phase operation, improves the quantifiability and operability of the assay. Using a reference PPI set, we demonstrated an improvement in both sensitivity and specificity over the original SIMPL assay. Moreover, we designed the new SIMPL-tNLuc ('SIMPL2') platform with an inherent modularity allowing for flexible measurement of molecular modulators of target PPIs, including inhibitors, molecular glues and PROTACs. Our results demonstrate that SIMPL2 is a sensitive, cost- and labor-effective tool suitable for high-throughput screening (HTS) in both PPI mapping and drug discovery applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".