Relative role(s) of leucine versus isoleucine in the folding of membrane proteins
Bibliographic record
Abstract
Abstract Large, hydrophobic residues (isoleucine, leucine, and valine) dominate sequences of transmembrane (TM) helices in membrane proteins (total ∼34%), but their relative roles in mediating the biologically relevant protein–lipid and protein–protein interactions have not been systematically evaluated. Here we have synthesized Leu‐containing Lys‐tagged hydrophobic peptides of identical composition, where sequences have been designed with their Leu residues either scrambled (sequence KKKLAASALAAAWLAALALSAAKKK); clustered (KKKAAASAALLLWLLAAAASAAKKK); or “lipopathic” (all Leu on one helical face) (KKKAAASLAALLWALLAAASAAKKK). These peptides were compared by several biophysical/biochemical techniques to the corresponding set of peptides where the Leu residues are replaced by the isosteric Ile residues. Circular dichroism spectra showed that all peptides were helical in POPC liposomes, as confirmed by blue shifts in Trp fluorescence spectra, notably with the Ile‐lipopathic peptide displaying increased Trp burial versus its Leu counterpart. Quenching experiments with a dibromo‐PC lipid indicated deeper membrane penetration of the Ile versus the Leu lipopathic peptide—a result supported by protease degradation assays where Ile peptides reconstituted into lipid bilayers were significantly more protected from the protease than the Leu peptides. Assessment of Trp blue shifts in the presence of lipid bilayers of varied lipid packing indicated that Leu/Ile peptide interactions are dependent on lipid composition. The overall results suggest that two main interactions tend to dominate Leu and Ile interactions within the membrane: (1) hydrophobic interactions between amino acid side chains and the surrounding lipid; and (2) degree of disruption of lipid–lipid packing. This “battle of giants” likely underlies the specific role(s) that Leu and Ile will play in the folding of a given membrane protein.
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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".