FRET Evidence that an Isoform of Caspase-7 Binds but Does Not Cleave its Substrate
Bibliographic record
Abstract
Caspase-7 is one of the executioner proteases in cellular apoptosis. Its kinetics has been monitored using biosensors based on the principle of fluorescence resonance energy transfer (FRET). Here, a caspase-7 biosensor (named vDEVDc) using fluorescent proteins as the donor and acceptor of FRET was used to study the biochemical properties of caspase-7. An active isoform of caspase-7 with the 56 N-terminal residues truncated (named 57casp7) cleaved the vDEVDc biosensor at the recognition sequence, resulting in a FRET efficiency decrease of 61%. In contrast, another caspase-7 isoform with the 23 N-terminal residues truncated (named 24casp7) bound the vDEVDc biosensor without cleaving the substrate, resulting in a FRET increase of 15%. The kinetics of the two caspase-7 isoforms were studied by monitoring the FRET change of the vDEVDc biosensor over time, which showed an exponential substrate cleavage and binding curve for the 57casp7 and 24casp7 isoform, respectively. Lastly, we modeled caspase-7 binding to the vDEVDc biosensor and estimated a FRET emission ratio increase of 16.2% after binding to caspase-7, which agrees with the 15% experimental result. We showed that two isoforms of caspase-7 with differently truncated prodomain exhibit different enzymatic properties, namely binding by the 24casp7 isoform and hydrolysis by 57casp7. We also demonstrated that our FRET biosensor (vDEVDc) can be used to detect not only the substrate cleavage event, but also the substrate binding event
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".