The effect of polymer end-group on the formation of styrene – maleic acid lipid particles (SMALPs)
Bibliographic record
Abstract
A series of block copolymers comprising styrene and maleic acid (SMA) has been prepared using RAFT polymerisation. RAFT often results in a large hydrophobic alkylthiocarbonylthio end group and this work examines its effect on the solution behaviour of the copolymers. SMA variants with, and without, this end group were synthesised and their behaviour compared with a commercially-available random copolymer of similar molecular weight. Dynamic light scattering and surface tension measurements found the RAFT-copolymers preferentially self-assembled into higher-order aggregates in aqueous solution. Small angle neutron scattering using deuterated styrene varients add support to the accepted model that these agreggates comprise a solvent-protected styrenic core with an acid-rich shell. Replacing the hydrophobic RAFT end group with a more hydrophilic nitrile caused differences in the resulting surface activity, attributed to the ability of the adjoining styrene homoblock to drive aggregation. Each of the copolymers formed SMALP nanodiscs with DMPC lipids, which were found to encapsulate a model membrane protein, gramicidin. However, end group variation affected solubilisition of DPPC, a lipid with a higher phase transition temperature. When using RAFT-copolymers terminated with a hydrophobic group, swelling of the bilayer and greater penetration of the homoblock into the nanodisc core occurred with increasing homoblock length. Conversely, commercial and nitrile-terminated RAFT-copolymers produced nanodisc sizes that stayed constant, instead indicating interaction at the edge of the lipid patch. The results highlight how even minor changes to the copolymer can modify the amphiphilic balance between regions, knowledge useful towards optimising copolymer structure to enhance and control nanodisc formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".