The effect of chemical modification of amino acid side‐chains on collagen degradation by enzymes
Bibliographic record
Abstract
In this study, the effects of specific chemical modifications of amino acid side-chains on the in vitro enzyme degradation of type I collagen was studied. Two monofunctional epoxides of different size and chemistry were used to modify lysine and methylglyoxal was used to modify arginine. Lysine residues were modified using glycidol, a small hydrophilic reagent or n-butylglycidylether, a larger hydrophobic reagent. Amino acid analysis, swelling measurements, in vitro enzyme degradation analyses (using either collagenase, trypsin, acetyltrypsin, or cathepsin B), and gel chromatography were used to determine the effects of each chemical modification on purified type I collagen. Collagen solubilization by enzymes depended upon the size and chemistry of epoxides used to modify lysine residues. Modification of lysine residues by glycidol and arginine modification by methylglyoxal together significantly reduced collagen solubilization by acetyltrypsin and collagenase, whereas increased collagen solubilization was observed for all enzymes after lysine modification with n-butylglycidylether combined with arginine modification by methylglyoxal. Gel chromatographic analyses of collagen fragments solubilized by acetyltrypsin from type I collagen revealed that both the extent of solubilization and sites of cleavage were altered after lysine and arginine modification. In contrast, lysine and arginine modification only altered the amount of collagen solubilized by collagenase and had no effect on the amount collagen solubilized by cathepsin B. The ability to modulate the enzyme degradation of collagen-based materials as demonstrated in this study may facilitate the design of novel scaffolds for tissue regeneration or collagen-based drug/protein/gene delivery systems.
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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) | 0.001 | 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".