Hydrophobic Clusters Raise the Threshold Hydrophilicity for Insertion of Transmembrane Sequences <i>in Vivo</i>
Bibliographic record
Abstract
Insertion of a nascent membrane protein segment by the translocon channel into the bilayer is naturally promoted by high segmental hydrophobicity, but its selection as a transmembrane (TM) segment is complicated by the diverse environments (aqueous vs lipidic) the protein encounters and by the fact that most TM segments contain a substantial amount (∼30%) of polar residues, as required for protein structural stabilization and/or function. To examine the contributions of these factors systematically, we designed and synthesized a peptide library consisting of pairs of compositionally identical, but sequentially different, peptides with 19-residue core sequences varying (i) in Leu positioning (with five or seven Leu residues clustered into a contiguous "block" in the middle of the segment or "scrambled" throughout the sequence) and (ii) in Ser content (0-6 residues). The library was analyzed by a combination of biophysical and biological techniques, including HPLC retention times, circular dichroism measurements of helicity in micelle and phospholipid bilayer media, and relative blue shifts in Trp fluorescence maxima, as well as by the extent of membrane insertion in a translocon-mediated assay using microsomal membranes from dog pancreas endoplasmic reticulum. We found that local blocks of high hydrophobicity heighten the translocon's propensity to insert moderately hydrophilic sequences, until a "threshold hydrophilicity" is surpassed whereby segments no longer insert even in the presence of Leu blocks. This study codifies the prerequisites of apolar/polar content and residue positioning that define nascent TM segments, illustrates the accuracy in their prediction, and highlights how a single disease-causing mutation can tip the balance toward anomalous translocation/insertion.
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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".