Hydrophobic Core Repacking in a Coiled-Coil Dimer via Phage Display: Insights into Plasticity and Specificity at a Protein−Protein Interface
Bibliographic record
Abstract
The coiled-coil, which consists of two or more interwoven amphiphilic alpha-helices, is formed by sequences that have a characteristic heptad repeat (abcdefg) where a and d are hydrophobic residues. Most efforts to elucidate the origins of coiled-coil pairing selectivity have focused on electrostatic interactions among side chains that flank the core (positions e and g) and on polar side chains that occur occasionally at core positions. We have used phage display to explore another source of coiled-coil specificity: steric matching among nonpolar side chains in the core. We introduced a destabilizing Leu-->Ala mutation into the core of one helix in a known heterodimer and then screened a phage-based library of potential partner helices in search of compensating mutations. We identified a new heterodimer pair (30 residues/helix) that is comparable in stability to the GCN4-p1 homodimer (33 residues/helix). Furthermore, the Leu-->Ala mutant shows specificity for its phage-derived partner over the original partner despite their similar sequences. These results show that a phage-based approach can provide unique insights on coiled-coil pairing preferences that should facilitate both the analysis of natural sequences and the development of specific dimerization motifs that are orthogonal to one another.
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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) | 0.000 | 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) | 0.000 | 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".