Retention of Native-like Oligomerization States in Transmembrane Segment Peptides: Application to the<i>Escherichia coli</i>Aspartate Receptor
Bibliographic record
Abstract
Biophysical study of the transmembrane (TM) domains of integral membrane proteins has traditionally been impeded by their hydrophobic nature. As a result, an understanding of the details of protein-protein interactions within membranes is often lacking. We have demonstrated previously that model TM segments with flanking cationic residues spontaneously fold into alpha-helices upon insertion into membrane-mimetic environments. Here, we extend these studies to investigate whether such constructs consisting of TM helices from biological systems retain their native secondary structures and oligomeric states. Single-spanning TM domains from the epidermal growth factor receptor (EGFR), glycophorin A (GPA), and the influenza A virus M2 ion channel (M2) were designed and synthesized with three to four lysine residues at both N- and C-termini. Each construct was shown to adopt an alpha-helical conformation upon insertion into sodium dodecyl sulfate micelles. Furthermore, micelle-inserted TM segments associated on SDS-PAGE gels according to their respective native-like oligomeric states: EGFR was monomeric, GPA was dimeric, and M2 was tetrameric. This approach was then used to investigate whether one or both of the TM segments (Tar-1 and Tar-2) from the Escherichia coli aspartate receptor were responsible for its homodimeric nature. Our results showed that Tar-1 formed SDS-resistant homodimers, while Tar-2 was monomeric. Furthermore, no heterooligomerization between Tar-1 and Tar-2 was detected, implicating the Tar-1 helix as the oligomeric determinant for the Tar protein. The overall results indicate that this approach can be used to elucidate the details of TM domain folding for both single-spanning and multispanning membrane proteins.
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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) | 0.000 | 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".