Preventing <i>N</i>‐ and <i>O</i>‐formylation of proteins when incubated in concentrated formic acid
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
Concentrated formic acid is among the most effective solvents for protein solubilization. Unfortunately, this acid also presents a risk of inducing chemical modifications thereby limiting its use in proteomics. Previous reports have supported the esterification of serine and threonine residues (O-formylation) for peptides incubated in formic acid. However as shown here, exposure of histone H4 to 80% formic (1 h, 20(o) C) induces N-formylation of two independent lysine residues. Furthermore, incubating a mixture of Escherichia coli proteins in formic acid demonstrates a clear preference toward lysine modification over reactions at serine/threonine. N-formylation accounts for 84% of the 225 uniquely identified formylation sites. To prevent formylation, we provide a detailed investigation of reaction conditions (temperature, time, acid concentration) that define the parameters permitting the use of concentrated formic acid in a proteomics workflow for MS characterization. Proteins can be maintained in 80% formic acid for extended periods (24 h) without inducing modification, so long as the temperature is maintained at or below -20(o) C.
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 | 0.000 | 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 it