Engineered regulation of lysozyme by the SH3-CB1 binding interaction
Bibliographic record
Abstract
The ability to design proteins with desired properties by using protein structural information will allow us to create high-value therapeutic and diagnostic products. Using the protein structures of lambda lysozyme and the SH3 domain of human Crk, we designed a synthetic protein switch that controls the activity of lysozyme by sterically hindering its active cleft through the binding of SH3 to its CB1 peptide-binding partner. First, several fusion protein designs with lysozyme and CB1 were modeled to determine the one with greatest steric effect in the presence of SH3. Next, the selected fusion protein was created and tested in vitro. In the absence of SH3, the lysozyme-CB1 fusion protein functioned normally. In the presence of SH3, the lysozyme activity was inhibited and with the addition of excess CB1 peptides to compete for SH3 binding, the lysozyme activity was restored. Lastly, this structure-based strategy can be used to engineer synthetic regulation by peptide-domain-binding interfaces into a variety of proteins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".