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Record W2888471281 · doi:10.1002/anie.201712611

Boronic Acids as Bioorthogonal Probes for Site‐Selective Labeling of Proteins

2018· review· en· W2888471281 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAngewandte Chemie International Edition · 2018
Typereview
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBioorthogonal chemistryBoronic acidChemistryHydroxylamineCombinatorial chemistryOrganic chemistryClick chemistry

Abstract

fetched live from OpenAlex

Over the past two decades, bioorthogonal chemistry has become a preferred tool to achieve site-selective modifications of proteins. However, there are only a handful of commonly applied bioorthogonal reactions and they display some limitations, such as slow rates, use of unstable or cytotoxic reagents, and side reactions. Hence, there is significant interest in expanding the bioorthogonal chemistry toolbox. In this regard, boronic acids have recently been introduced in bioorthogonal chemistry and are exploited in three different strategies: 1) boronic ester formation between a boronic acid and a 1,2-cis diol; 2) iminoboronate formation between 2-acetyl/formyl-arylboronic acids and hydrazine/hydroxylamine/semicarbazide derivatives; 3) use of boronic acids as transient groups in a Suzuki-Miyaura cross-coupling or other reactions that leave the boronyl group off the conjugation product. In this Review, we summarize progress made in the use of boronic acids in bioorthogonal chemistry to enable site-selective labeling of proteins and compare these methods with the most commonly utilized bioorthogonal reactions.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.344
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it