Binding Methylarginines and Methyllysines as Free Amino Acids: A Comparative Study of Multiple Host Classes**
Bibliographic record
Abstract
Methylated free amino acids are an important class of targets for host-guest chemistry that have recognition properties distinct from those of methylated peptides and proteins. We present comparative binding studies for three different host classes that are each studied with multiple methylated arginines and lysines to determine fundamental structure-function relationships. The hosts studied are all anionic and include three calixarenes, two acyclic cucurbiturils, and two other cleft-like hosts, a clip and a tweezer. We determined the binding association constants for a panel of methylated amino acids using indicator displacement assays. The acyclic cucurbiturils display stronger binding to the methylated amino acids, and some unique patterns of selectivity. The two other cleft-like hosts follow two different trends, shallow host (clip) following similar trends to the calixarenes, and the other more closed host (tweezer) binding certain less-methylated amino acids stronger than their methylated counterparts. Molecular modelling sheds some light on the different preferences of the various hosts. The results identify hosts with new selectivities and with affinities in a range that could be useful for biomedical applications. The overall selectivity patterns are explained by a common framework that considers the geometry, depth of binding pockets, and functional group participation across all host classes.
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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".