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Record W2120674430 · doi:10.1021/bi901432d

Succinylphosphonate Esters Are Competitive Inhibitors of MenD That Show Active-Site Discrimination between Homologous α-Ketoglutarate-Decarboxylating Enzymes

2010· article· en· W2120674430 on OpenAlexaff
Maohai Fang, R. Daniel Toogood, Andrea Macova, Karen Ho, Scott G. Franzblau, Michael McNeil, D.A.R. Sanders, David R. J. Palmer

Bibliographic record

VenueBiochemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical Acid Research Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsActive siteEnzymeDecarboxylationBiochemistryChemistryBiosynthesisStereochemistryNon-competitive inhibitionDehydrogenaseMycobacterium tuberculosisCatalysisTuberculosis

Abstract

fetched live from OpenAlex

MenD is a thiamin diphosphate-dependent enzyme catalyzing the first unique step in menaquinone biosynthesis in bacteria. We have synthesized acylphosphonate ester analogues of alpha-ketoglutarate, a substrate of MenD. These compounds are competitive inhibitors of MenD, with K(i) values as low as 700 nM. Observed structure-activity relationships are in notable contrast to those reported previously for succinylphosphonate inhibition of the alpha-ketoglutarate dehydrogenase complex, despite the apparent homology of these enzymes, and the identical decarboxylation reactions catalyzed. Inhibiting menaquinone biosynthesis is a proposed approach to inhibiting Mycobacterium tuberculosis growth. These inhibitors showed no significant inhibition of M. tuberculosis growth in vitro under aerobic and hypoxic conditions but give new information about the binding characteristics of the MenD active site. Site-directed mutation of Ser391 to alanine had only a minor effect on catalysis, but even the conservative mutation of Arg395 to lysine had a significant effect on the catalytic processing of isochorismate.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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

Citations43
Published2010
Admission routes1
Has abstractyes

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