Terminal Residue Hydrophobicity Modulates Transmembrane Helix–Helix Interactions
Bibliographic record
Abstract
Central to the formation of tertiary structure in membrane protein folding is the presence of amino acid sequence motifs (such as "small-XXX-small" segments) in the TM segments that promote interaction-compatible surfaces through which the TM α-helices interact. Here, we sought to elucidate additional factors that may work in tandem to dictate the ultimate interaction fate of TM-embedded segments. In this context, we used proteolipid protein (PLP), the major protein from central nervous system myelin for which mutant-dependent non-native oligomerization has been implicated in neurological disorders, to explore the specific effects of TM boundary residues (the membrane entry and exit points), keying on the secondary structure and self-association of peptides corresponding to the PLP TM2 α-helix (wild-type sequence ⁶⁶AFQYVIYGTASFFFLYGALLLAEGF⁹⁰). Using gel electrophoresis, circular dichroism, and Förster resonance energy transfer in the membrane-mimetic detergent sodium dodecyl sulfate (SDS), we found that mutation of F90 to residues such as A, I, L, or V maintains the onset of TM2-TM2 dimerization, whereas mutation to E, G, Q, N, S, or T abrogates dimer formation. We attribute this sensitivity to changes in local hydrophobicity, viz., a decrease in hydrophobicity reduces local lipid-peptide interactions, which in turn disrupts peptide α-helicity and hence the effectiveness of an incipient interaction-compatible surface. Our results show that the secondary structure and oligomeric state of PLP TM2 Lys-tagged peptides are significantly modulated by the specific nature of their C-terminal boundary residue, thus providing insight as to how point mutations, particularly where they produce disease states, can compromise the folding process.
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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".