Development of novel enzyme immobilization methods employing formaldehyde or triethoxysilylbutyraldehyde to fabricate immobilized enzyme microreactors for peptide mapping
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The digestion of proteins with proteolytic enzymes has expedited the analysis of peptide mapping. Here, we compared the digestion efficiency of soluble chymotrypsin (CT) with two immobilized CT preparations using bovine serum albumin (BSA) as the substrate. An efficient method of immobilizing chymotrypsin using formaldehyde (FA) was optimized and the conditions were applied to assess a novel immobilization reagent, triethoxysilylbutaraldehyde (TESB). Efforts to determine the best enzyme-to-substrate (E : S) ratios during digestion of denatured BSA with single-use FA-CT enzyme particles were performed by adjusting the amount of substrate used. An E : S ratio of 10 : 1 was found to be best based on the LC-MS/MS analysis data showing sequence coverage of 67%. Fabrication of immobilized enzyme microreactors (IMERs) was carried out using both (3-aminopropyl)triethoxysilane (APTES) with the idealized conditions with FA, as well as the novel procedure utilizing TESB for a proof of concept open-tubular IMER. It was found that the FA-APTES IMER had a sequence coverage of 6%, while the TESB IMER had 29% sequence coverage from MS analysis. The application of TESB in enzyme immobilization has the potential to facilitate a greater degree of enzymatic digestion with higher sequence coverage than traditional immobilization or crosslinking reagents for bottom-up proteomics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it