The proteosomal degradation of fusion proteins cannot be predicted from the proteosome susceptibility of their individual components
Bibliographic record
Abstract
It is assumed that the proteosome-processing characteristics of fusion constructs can be predicted from the sum of the proteosome sensitivity of their components. In the present study, we observed that a fusion construct consisting of proteosome-degradable proteins does not necessarily result in a proteosome-degradable chimera. Conversely, fusion of proteosome-resistant proteins may result in a proteosome-degradable composite. We previously demonstrated that conserved influenza proteins can be unified into a single fusion antigen that is protective, and that vaccination with combinations of proteosome-resistant and proteosome-degradable antigens resulted in an augmented T-cell response. In the present study we constructed proteosome-degradable mutants of conserved influenza proteins NP, M1, NS1, and M2. These were then fused into multipartite proteins in different positions. The stability and degradation profiles of these fusion constructs were demonstrated to depend on the relative position of the individual proteins within the chimeric molecule. Combining unstable sequences of either NP and M1 or NS1 and M2 resulted in either rapidly proteosome degraded or proteosome-resistant bipartite fusion mutants. However, further unification of the proteosome-degradable forms into a single four-partite fusion molecule resulted in relatively stable chimeric proteins. Conversely, the addition of proteosome-resistant wild-type M2 to proteosome-resistant NP-M1-NS1 fusion protein lead to the decreased stability of the resulting four-partite multigene products, which in one case was clearly proteosome dependent. Additionally, a highly destabilized form of M1 failed to destabilize the wild-type NP. Collectively, we did not observe any additive effect leading to proteosomal degradation/nondegradation of a multigene construct.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".