Unraveling the Impact of High-Order Silk Structures on Molecular Drug Binding and Release Behaviors
Bibliographic record
Abstract
Silk continues to amaze: over the past decade, new research threads have emerged that include the use of silk fibroin for advanced pharmaceutics, including its suitability for drug delivery. Despite this ongoing interest, the details of silk fibroin structures and their subsequent drug interactions at the molecular level remain elusive, primarily because of the difficulties encountered in modeling the silk fibroin molecule. Here, we generated an atomistic silk model containing amorphous and crystalline regions. We then exploited advanced well-tempered metadynamics simulations to generate molecular conformations that we subsequently exposed to classical molecular dynamics simulations to monitor both drug binding and release. Overall, this study demonstrated the importance of the silk fibroin primary sequence, electrostatic interactions, hydrogen bonding, and higher-order conformation in the processes of drug binding and release.
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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) | 0.000 | 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 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".