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Record W2791046952 · doi:10.1073/pnas.1717015115

IpdAB, a virulence factor in <i>Mycobacterium tuberculosis</i> , is a cholesterol ring-cleaving hydrolase

2018· article· en· W2791046952 on OpenAlexafffund
Adam M. Crowe, Sean D. Workman, Nobuhiko Watanabe, L.J. Worrall, N.C.J. Strynadka, Lindsay D. Eltis

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSteroid Chemistry and Biochemistry
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchGovernment of CanadaHoward Hughes Medical Institute
KeywordsVirulenceMycobacterium tuberculosisVirulence factorSteroidHydrolaseRing (chemistry)BacteriaChemistryMicrobiologyBiologyBiochemistryStereochemistryEnzymeTuberculosisGeneGeneticsMedicine

Abstract

fetched live from OpenAlex

Significance All steroid-degrading bacteria utilize IpdAB, a predicted CoA transferase (CoT) that has been implicated in the hydrolysis of a carbon–carbon bond, an unprecedented reaction in CoTs. In Mycobacterium tuberculosis , IpdAB is required for degrading host cholesterol and virulence. We used a combination of X-ray crystallographic and biochemical studies to elucidate the mechanism of IpdAB. Superposition of the IpdAB Mtb active site with those of CoTs reveals distinct architectural features which, in conjunction with the biochemical data, indicate that IpdAB catalyzes a retro-Claisen-like ring-opening reaction. This reaction is unique for a member of the CoT superfamily. This study provides insights into bacterial steroid catabolism and facilitates the development of potential antituberculosis therapeutics targeting IpdAB.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.282
Teacher spread0.262 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicSteroid Chemistry and BiochemistryFrench-language works237,207