Biophysical characterization of a series of novel non‐RAFT copolymers with improved buffer behavior
Bibliographic record
Abstract
Synthetic amphipathic polymers present an invaluable tool for excision and liberation of superstructures of membrane proteins (MPs) and their surrounding annular membrane bilayer in donut‐shaped nanoparticles or discs. Styrene‐ co ‐maleic acid polymers (SMAs) have demonstrated most efficiency for the structural characterization of membrane proteins. However, some drawbacks such as sensitivity to acidic pH and high concentration of divalent cations, interference with the spectroscopic profiles of proteins, high polydispersity index (PDI) and nonspecific interaction with protein surface have hindered the ultimate optimal utilization of SMA polymers for functional characterization of MPs in lipid bilayer and hence for drug discovery purposes. We have developed multiple series of novel non‐RAFT amphipathic polymers that demonstrate improved behaviors in acidic pH and high concentration of calcium. Some of these unique amphipathic polymers display exemplary polydispersity (PDI ~1), strict alternation (a well‐defined sequence of comonomers) and distinct spectrophotometric profiles. We further characterized the application of these novel polymeric detergents for purification of a model integral beta‐barrel MP, PagP, from the outer membrane of E. coli .
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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".