Lysozyme Complexes for the Synthesis of Functionalized Biomaterials To Understand Protein–Protein Interactions and Their Biological Applications
Bibliographic record
Abstract
Interactions between the components of lysozyme/cytochrome c (lysozyme/Cyt,c) and lysozyme/zein protein mixtures were determined by following the in vitro synthesis of gold (Au) nanoparticles (NPs). Both UV–visible and fluorescence studies were employed to monitor the interactions and simultaneous synthesis of protein coated NPs. Protein coated NPs were characterized by gel electrophoresis and TEM studies. Lysozyme/Cyt,c complex coated NPs showed remarkable pH responsive behavior due to their amphiphilic nature, while lysozyme/zein complex coated NPs were not pH sensitive because of the predominantly hydrophobic nature. The results were further supported by molecular dynamics studies (MD) of protein–protein interactions and interactions of protein with the gold surface. Molecular simulations helped us to identify the amino acids that drove such interactions. Biological applications of protein coated NPs were determined from hemolytic and antimicrobial studies to demonstrate their potential in pharmaceutical and food industries. The results clearly differentiated between the greater applicability of predominantly amphiphilic lysozyme/Cyt,c complex coated NPs in comparison to predominantly hydrophobic lysozyme/zein complex coated NPs.
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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".