Peptide Mimics of the M13 Coat Protein Transmembrane Segment
Bibliographic record
Abstract
Sequence-specific noncovalent helix-helix interactions between transmembrane (TM) segments in proteins are investigated by incorporating selected TM sequences into synthetic peptides using the construct CKKK-TM-KKK. The peptides are of suitable hydrophobicity for spontaneous membrane insertion, whereas formation of an N-terminal S-S bond can bring pairs of TM helices into proximity and promote their parallel orientation. Using the propensity of the protein to undergo thermally induced alpha-helix --> beta-sheet transitions as a parameter for helix stability, we compared the wild type and mutant (V29A and V31A) bacteriophage M13 coat proteins with their corresponding TM peptide constructs (M13 residues 24-42). Our results demonstrated that the relevant helix-helix tertiary contacts found in the intact proteins persist in the peptide mimics. Molecular dynamics simulations support the tight "two in-two out" dimerization motif for V31A consistent with mutagenesis data. The overall results reinforce the notion of TM segments as autonomous folding domains and suggest that the generic peptide construct provides a viable reductionist system for membrane protein structural and computational analysis.
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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) | 0.001 | 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".