Beta-branched residues adjacent to GG4 motifs promote the efficient association of glycophorin a transmembrane helices
Bibliographic record
Abstract
Protein transmenembrane (TM) segments participating in helix-helix packing commonly contain small residue patterns (termed GG4 or "small-xxx-small" motifs) at i and i + 4 positions. Within many TM segments - such as the glycophorin A (GpA) sequence L75IxxGVxxGVxxT87- the G17y-xxx-Gly83 motif often occurs in combination with large, usually beta3-branched aliphatic residues at adjacent positions, typified here by Val30 and Val84 residues. To explore the importance of local P-branched character on GpA dimerization, we made systematic replacements to all 16 combinations of single or double Ile, Leu, and AIa residues at GpA TM Val/Val positions 80 and 84. Using the TOXCAT system to assay self-oligomerization in the Escherichia coli inner membrane--we observed that (i) combinations of Val and lie residues maintained, or improved dimerization levels; (ii) single Ala or Leu mutant combinations with Val or Ile maintained near-wild type dimerization affinities; and (iii) in the absence of beta-branching, i.e., Leu/Leu, Ala/Ala and Ala/Leu combinations, GpA dimerization was significantly diminished. An apparent capacity of lle-containing mutants to increase GpA dimerization versus WT likely arises from improved van der Waals packing (vs. Val) within the locus of helix contact, consistent with correlations we noted in lipid accessibility measurements. Examination of several synthetic peptides with sequences corresponding to selected GpA mutants (VV VI, IV II, and LL) confirmed their dimerization on sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE). The overall results reinforce the importance of a beta-branch-containing "ridge" residue to complement a "small-xxx-small groove" in promotion of TM-TM interactions.
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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".