Conformationally Constrained Sequence Designs to Bias Monomer–Dimer Equilibriums in TASP Systems
Bibliographic record
Abstract
We have designed template-assembled synthetic proteins (TASPs) with the intent of controlling their oligomeric state by stabilizing specific helical tertiary structures via histidine metal ion chelation or disulfide incorporation. In solution, cavitein Q4 was previously determined to interconvert between a four-helix bundle monomer and an eight-helix bundle dimer. In this paper, we show that judicious mutation of cavitein Q4 can stabilize either the monomeric parallel four-helix bundle or the dimeric antiparallel eight-helix bundle structure. Cavitein Q4-E3H, designed to be dimeric, is indeed biased toward dimerization as a result of incorporation of histidines. Moreover, the addition of nickel was found to further increase the association constant of dimerization. Similarly, a cavitein designed to stabilize the monomeric structure via histidine metal ion chelation (Q4-H) was found to favor a monomer in solution upon addition of nickel. Lastly, a cavitein intended to stabilize a monomeric structure via disulfide incorporation (Q4-C2) is reported. Surprisingly, this disulfide cavitein yielded two products upon oxidation suggesting disulfide formation both above the cavitand template and below may be possible. Nevertheless, the two disulfide caviteins were shown to exist as monomers as per their design.
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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 | 0.001 |
| 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 | 0.001 |
| 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".