Using Phage Display to Develop Ubiquitin Variant Modulators for E3 Ligases
Bibliographic record
Abstract
Ubiquitin is a small 8.6 kDa protein that is a core component of the ubiquitin-proteasome system. Consequently, it can bind to a diverse array of proteins with high specificity but low affinity. Through phage display, ubiquitin variants (UbVs) can be engineered such that they exhibit improved affinity over wildtype ubiquitin and maintain binding specificity to target proteins. Phage display utilizes a phagemid library, whereby the pIII coat protein of a filamentous M13 bacteriophage (chosen because it is displayed externally on the phage surface) is fused with UbVs. Specific residues of human wildtype ubiquitin are soft and randomized (i.e., there is a bias towards to native wildtype sequence) to generate UbVs so that deleterious changes in protein conformation are avoided while introducing the diversity necessary for promoting novel interactions with the target protein. During the phage display process, these UbVs are expressed and displayed on phage coat proteins and panned against a protein of interest. UbVs that exhibit favorable binding interactions with the target protein are retained, whereas poor binders are washed away and removed from the library pool. The retained UbVs, which are attached to the phage particle containing the UbV's corresponding phagemid, are eluted, amplified, and concentrated so that they can be panned against the same target protein in another round of phage display. Typically, up to five rounds of phage display are performed, during which a strong selection pressure is imposed against UbVs that bind weakly and/or promiscuously so that those with higher affinities are concentrated and enriched. Ultimately, UbVs that demonstrate higher specificity and/or affinity for the target protein than their wildtype counterparts are isolated and can be characterized through further experiments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".