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Studies into the Mechanism by Which Glycosaminoglycans Potentiate Protein C Activation by Factor Xa.

2004· article· en· W2586710373 on OpenAlexaff
Simon McRae, Alan R. Stafford, James C. Fredenburgh, Jeffrey I. Weitz

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsSulfationChemistryHeparinGlycosaminoglycanChondroitin sulfateBiophysicsPhospholipidPhosphatidylcholineBiochemistryDextranBiologyMembrane

Abstract

fetched live from OpenAlex

Abstract Previous studies have demonstrated that protein C (PC) can be activated by factor Xa (fXa) in a reaction that requires Ca2+ and negatively-charged phospholipid. Sulfated polysaccharides, such as heparin or dextran sulfate, have been shown to accelerate this reaction, although their mechanism of action remains elusive. To further explore this phenomenon, we first examined the effect of glycosaminoglycans of varying degrees of sulfation on the kinetics of PC activation by fXa in the presence of Ca2+ and phosphatidylcholine-phosphatidylserine vesicles (75%/25% w/w). Heparin increased the rate PC activation in a concentration-dependent and saturable fashion producing a 4-fold increase in catalytic efficiency (kcat/Km of 105 M−1 min−1) by reducing the Km for the reaction. In contrast N-desulfated heparin had no effect on the rate of this reaction, whereas dextran sulfate, which is more sulfated than heparin, increased the catalytic efficiency 21-fold. These data suggest that the capacity of glycosaminoglycans to catalyze PC activation by fXa is dependent on their degree of sulfation. The extent of sulfation is more important than chain length because hypersulfated low-molecular-weight heparin (HSLMWH) and dextran sulfate, both of which have a mean molecular weight of 5000, increased the catalytic efficiency 16- and 21-fold respectively. In contrast, enoxaparin, which also has a mean molecular weight of about 5000, had little effect. The capacity of heparin to enhance PC activation by fXa is similar in the presence of factor Va as it is in its absence, suggesting that heparin can accelerate this reaction even when fXa is incorporated within the prothrombinase complex. To begin to explore the mechanism by which these glycosaminoglycans enhance PC activation by fXa, we measured their affinities for PC and fXa, both of which have heparin-binding domains, in the presence of Ca2+. This was performed by monitoring changes in extrinsic fluorescence of fluorescein-labeled fXa or PC after addition of glycosaminoglycan. Heparin binds PC with similar affinity in the absence or presence of negatively-charged phospholipid (Kd values of 1.9 and 1.0 mM, respectively). In contrast, heparin binds fXa with 86-fold higher affinity in the presence of phospholipid vesicles than in its absence (Kd values of.007 and 0.61 mM, respectively). These findings suggest that fXa binding to phospholipid exposes a high-affinity heparin-binding site. In the absence of phospholipid, more sulfated glycosaminoglycans (dextran sulfate and HSLMWH) bind fXa with 2- to 3-fold higher affinity than heparin. These compounds exhibit a smaller increase in affinity for PC. These observations suggest that the capacity of glycosaminoglycans to enhance PC activation is dependent on the extent of sulfation, a feature that determines their affinity for fXa. How glycosaminoglycan binding to fXa modulates this reaction is uncertain, but it is more likely to reflect conformational changes in the enzyme than bridging of the enzyme to the substrate.

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)0.000
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.276
Teacher spread0.252 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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