New approach for membrane protein reconstitution into peptidiscs and basis for their adaptability to different proteins
Bibliographic record
Abstract
Previously we introduced peptidiscs as an alternative to detergents to stabilize membrane proteins in solution (Carlson et al., 2018). Here, we present ‘on-gradient’ reconstitution, a new gentle approach for the reconstitution of labile membrane-protein complexes, and used it to reconstitute Rhodobacter sphaeroides reaction center complexes, demonstrating that peptidiscs can adapt to transmembrane domains of very different sizes and shapes. Using the conventional ‘on-bead’ approach, we reconstituted Escherichia coli proteins MsbA and MscS and find that peptidiscs stabilize them in their native conformation and allow for high-resolution structure determination by cryo-electron microscopy. The structures reveal that peptidisc peptides can arrange around transmembrane proteins differently, thus revealing the structural basis for why peptidiscs can stabilize such a large variety of membrane proteins. Together, our results establish the gentle and easy-to-use peptidiscs as a potentially universal alternative to detergents as a means to stabilize membrane proteins in solution for structural and functional studies.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".