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Record W1996334134 · doi:10.1074/jbc.m510677200

Structural and Kinetic Analysis of Two Covalent Sialosyl-Enzyme Intermediates on Trypanosoma rangeli Sialidase

2005· article· en· W1996334134 on OpenAlexaff
Andrew G. Watts, Pablo Oppezzo, Stephen G. Withers, Pedro M. Alzari, Alejandro Buschiazzo

Bibliographic record

VenueJournal of Biological Chemistry · 2005
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSialidaseChemistryCovalent bondSialic acidStereochemistryActive siteBiochemistryHydrolaseEnzymeGlycoside hydrolaseTransferaseNeuraminidaseOrganic chemistry

Abstract

fetched live from OpenAlex

Trypanosoma rangeli sialidase is a glycoside hydrolase (family GH33) that catalyzes the cleavage of alpha-2-->3-linked sialic acid residues from sialoglycoconjugates with overall retention of anomeric configuration. Retaining glycosidases usually operate through a ping-pong mechanism, wherein a covalent intermediate is formed between the carbohydrate and an active site carboxylic acid of the enzyme. Sialidases, instead, appear to use a tyrosine as the catalytic nucleophile, leaving the possibility of an essentially different catalytic mechanism. Indeed, a direct nucleophilic role for a tyrosine was shown for the homologous trans-sialidase from Trypanosoma cruzi, although itself not a typical sialidase. Here we present the three-dimensional structures of the covalent glycosyl-enzyme complexes formed by the T. rangeli sialidase with two different mechanism-based inactivators at 1.9 and 1.7 Angstroms resolution. To our knowledge, these are the first reported structures of enzymatically competent covalent intermediates for a strictly hydrolytic sialidase. Kinetic analyses have been carried out on the formation and turnover of both intermediates, showing that structural modifications to these inactivators can be used to modify the lifetimes of covalent intermediates. These results provide further evidence that all sialidases likely operate through a similar mechanism involving the transient formation of a covalently sialylated enzyme. Furthermore, we believe that the ability to "tune" the inactivation and reactivation rates of mechanism-based inactivators toward specific enzymes represents an important step toward developing this class of inactivators into therapeutically useful 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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.038
GPT teacher head0.335
Teacher spread0.296 · 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 teacher head, 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

Citations83
Published2005
Admission routes1
Has abstractyes

Explore more

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