Systematic design of unimolecular star copolymer micelles using molecular dynamics simulations
Bibliographic record
Abstract
Star copolymers (SCPs) have recently attracted considerable attention due to their unique applicability in a wide range of biomedical fields. With the intention of rationally designing a stable unimolecular SCP, atomistic molecular dynamics simulations of thirteen SCPs are conducted. The SCPs each have six identical arms of methoxypoly(ethylene glycol)-b-polycaprolactone (MePEGx-b-PCLy) and systematically vary in terms of total molecular weight and ratio of hydrophobic to hydrophilic block length. For all hydrated SCPs, the simulations predict a densely packed hydrophobic PCL core that excludes water and is phase separated from a highly mobile hydrophilic PEG corona. The radii of the hydrophobic PCL core and the PEG blocks are independent of each other and can be predicted over a broad molecular weight range. A linear relationship between the hydration and the molecular weight of the PEG blocks is observed with the average number of water molecules bound per PEG repeat unit within the range of that determined experimentally. As well, a quantitative relationship relates the water accessed surface area of the hydrophobic PCL core to the molecular weights of PCL and PEG moieties. We postulate that the propensity for aggregation of SCPs into multimolecular micelles is correlated with the partial hydration of the hydrophobic core of unimers. Our results suggest that SCPs with a hydrophobic PCL core ≤2 kDa per arm are fully protected from water when the hydrophilic PEG blocks approach 14.6 kDa per arm. We therefore predict that SCPs of this composition yield unimolecular micelles that are thermodynamically stable at low concentrations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".