Rapid and selective detection of fatty acylated proteins using ω-alkynyl-fatty acids and click chemistry
Bibliographic record
Abstract
Progress in understanding the biology of protein fatty acylation has been impeded by the lack of rapid direct detection and identification methods. We first report that a synthetic omega-alkynyl-palmitate analog can be readily and specifically incorporated into GAPDH or mitochondrial 3-hydroxyl-3-methylglutaryl-CoA synthase in vitro and reacted with an azido-biotin probe or the fluorogenic probe 3-azido-7-hydroxycoumarin using click chemistry for rapid detection by Western blotting or flat bed fluorescence scanning. The acylated cysteine residues were confirmed by MS. Second, omega-alkynyl-palmitate is preferentially incorporated into transiently expressed H- or N-Ras proteins (but not nonpalmitoylated K-Ras), compared with omega-alkynyl-myristate or omega-alkynyl-stearate, via an alkali sensitive thioester bond. Third, omega-alkynyl-myristate is specifically incorporated into endogenous co- and posttranslationally myristoylated proteins. The competitive inhibitors 2-bromopalmitate and 2-hydroxymyristate prevented incorporation of omega-alkynyl-palmitate and omega-alkynyl-myristate into palmitoylated and myristoylated proteins, respectively. Labeling cells with omega-alkynyl-palmitate does not affect membrane association of N-Ras. Furthermore, the palmitoylation of endogenous proteins including H- and N-Ras could be easily detected using omega-alkynyl-palmitate as label in cultured HeLa, Jurkat, and COS-7 cells, and, promisingly, in mice. The omega-alkynyl-myristate and -palmitate analogs used with click chemistry and azido-probes will be invaluable to study protein acylation in vitro, in cells, and in vivo.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".