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Record W3086609578 · doi:10.1039/d0sc04401f

Glycoside hydrolase stabilization of transition state charge: new directions for inhibitor design

2020· article· en· W3086609578 on OpenAlexafffund
Weiwu Ren, Marco Farren‐Dai, Natalia Sannikova, Katarzyna Świderek, Yang Wang, Oluwafemi Akintola, Robert Britton, Vicent Moliner, Andrew J. Bennet

Bibliographic record

VenueChemical Science · 2020
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsBurnaby HospitalSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaGeneralitat ValencianaMichael Smith Health Research BCMinisterio de Ciencia, Innovación y UniversidadesUniversitat Jaume IWestern Canada Research GridMinisterio de Economía y CompetitividadCompute Canada
KeywordsAllylic rearrangementCharge (physics)Transition (genetics)Transition state analogState (computer science)ChemistryCatalysisStereochemistryChemical physicsTransition stateCombinatorial chemistryComputational chemistryCrystallographyPhysicsActive siteOrganic chemistryComputer scienceBiochemistryQuantum mechanics

Abstract

fetched live from OpenAlex

2 transition state with no discrete enzyme-bound cationic intermediate. We conclude that, in complement to what we know about the TS structures of enzyme-natural substrate complexes, knowledge of the TS structures of enzymes reacting with non-natural carbasugar substrates shows that GHs can stabilize a wider range of positively charged TS structures than previously thought. Furthermore, this enhanced understanding will enable the design of new carbasugar GH transition state analogues to be used as, for example, chemical biology tools and pharmaceutical lead compounds.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.031
GPT teacher head0.241
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2020
Admission routes2
Has abstractyes

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