Development of indole chemistry to label tryptophan residues in protein for determination of tryptophan surface accessibility
Bibliographic record
Abstract
Solvent accessibility can be used to evaluate protein structural models, identify binding sites, and characterize protein conformational changes. The differential modification of amino acids at specific sites enables the accessible surface residues to be identified by mass spectrometry. Tryptophan residues within proteins can be differentially labeled with halocompounds by a photochemical reaction. In this study, tryptophan residues of carbonic anhydrase are reacted with chloroform, 2,2,2-trichloroethanol (TCE), 2,2,2-trichloroacetate (TCA), or 3-bromo-1-propanol (BP) under UV irradiation at 280 nm. The light-driven reactions with chloroform, TCE, TCA, and BP attach a formyl, hydroxyethanone, carboxylic acid, and propanol group, respectively, onto the indole ring of tryptophan. Trypsin and chymotrypsin digests of the modified carbonic anhydrase are used to map accessible tryptophan residues using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Tryptophan reactivity is determined by identifying peptides with tryptophan residues modified with the appropriate label. The reactivity is calculated from the frequency that the modification is identified and a semiquantitative measure of the amount of products formed. Both of these measures of tryptophan reactivity correlate significantly with the accessible surface area of tryptophan residues in carbonic anhydrase determined from the X-ray crystal structure. Therefore the photochemical reaction of halocompounds with tryptophan residues in carbonic anhydrase indicates the degree of solvent accessibility of these residues.
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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 | 0.001 |
| 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".