Development of pan-specific antibody against trimethyllysine for protein research
Bibliographic record
Abstract
BACKGROUND: Trimethylation of the Nepsilon-lysine residues in a protein is one of the most important events of posttranslational modifications. Simple methods for rapid detection and isolation of the Nepsilon-trimethylated protein species are needed. This report introduces a novel method to prepare the affinity purified antibody specific for the Nepsilon-trimethylated lysine (tMeK). The applications of the purified antibody are also reported in this paper. METHODS: We generated the methylated keyhole limpet heomocyanin (KLH) under controlled chemical methylation reaction using CH3I and used it as an immunogen to raise anti-methylated lysine antibodies. The tMeK specific antibody was selectively isolated using a two-step affinity chromatography in which the mMeK/dMeK specific antibodies were removed and the tMeK specific antibody was captured. Finally, the eluted anti-tMeK antibody was characterized. RESULTS: The ELISA results indicated that the antibody reacted only to tMeK but not to mono- and dimethyllysine. Western-blot results showed that the Nepsilon-trimethylated proteins were detected in both animal tissue and cultured cells and that the antibody signal could be competitively inhibited with free tMeK. CONCLUSION: The specific tMeK antibody we developed is useful for one-step isolation of proteins with Nepsilon-trimethyllysine residues and also for the detection, identification and localization of proteins with trimethyllysine residues in the cells.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".