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Human Factor VIIai(K62E) Is a More Effective Inhibitor of Coagulation Than Wild-Type FVIIai.

2005· article· en· W2569973043 on OpenAlexaff
Bryan J. Clarke, Sampath Sridhara, Morris A. Blajchman

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsCanadian Blood ServicesMcMaster University
Fundersnot available
KeywordsChemistryTissue factorRecombinant DNAFactor VIIRecombinant factor VIIaAffinity chromatographyFactor XMolecular biologyMonoclonal antibodyMutantAntibodyThrombinWild typeThromboplastinBiochemistryFactor IXCoagulationEnzymePlateletBiologyImmunologyGeneMedicine

Abstract

fetched live from OpenAlex

Abstract Background: In previous work we provided evidence for a linked conformational change of the recombinant factor VII(rFVII) first epidermal growth factor-like(EGF1) domain associated with chloromethylketone(ck) covalent modification of the wild-type(WT) rFVIIa active site (J Biol Chem275:34894,2000). All naturally-occurring mutations of the human FVII gene hitherto described encode plasma FVII with both reduced activity and affinity for their cell-surface receptor tissue factor (TF). We have recently characterized a mutant rFVII protein, rFVIIa(K62E), which has both increased enzymatic activity and a 5-fold greater affinity for TF than wild-type rFVIIa (J Thromb Haemost3:1250, 2005). In the present report we provide data about the TF-binding characteristics and conformational state of rFVIIa(K62E) before and after inactivation with a variety of chloromethylketones. Methods: Purification of both the rFVIIa(K62E) mutant protein and rFVIIa(WT) and their ck-inactivated derivatives was achieved by anion-exchange chromatography. FVII antigen concentration was determined by ELISA and biological activity by modified prothrombin time (PT) assay. Affinity of inactivated rFVIIa(rFVIIai) for both TF and a FVII EGF1 domain conformation-specific monoclonal antibody(Moab 231–7) was determined by competitive ELISA (IC50). Results: The affinity of rFVIIai(K62E)DEGR and rFVIIai(K62E)FFR for TF were increased 24.4-fold and 7.7-fold respectively versus rFVIIa(WT)[shown below]. Notably, the enhanced affinity of both rFVIIai(K62E) and unmodified rFVIIa(K62E) for TF was associated with substantially increased affinity for Moab 231–7 as compared to rFVIIa(WT). The clotting time of diluted human plasma was significantly more prolonged by rFVIIai(K62E)DEGR and rFVIIai(K62E)FFR than rFVIIai(WT). Comparison of rFVIIai(K62E) and rFVIIai(WT) rFVIIa Preparation Affinity for TF(IC50) Relative Increase in TF Affinity Relative Increase in Affinity for Moab 231–7 Prolongation of Plasma Clotting time(sec) Reduction of Coagulant Activity(%) Affinity of rFVII for TF (IC50 expressed as molar excess of rFVII) was determined by competitive ELISA. Plasma clotting times were determined at 2.5-fold molar excess of each rFVIIai inhibitor. Control plasma clotting time was 81 sec. rFVIIai(K62E)DEGR 0.13 24.4 3.1 68 90 rFVIIai(K62E)FFR 0.41 7.7 4.9 57 86 rFVIIa(K62E) 0.46 6.9 4.1 ND ND rFVIIai(WT)DEGR 0.98 3.2 3.5 1 4 rFVIIai(WT)FFR 0.62 5.1 1.2 27 65 rFVIIa(WT) 3.17 1 1 ND ND Conclusions: We provide evidence that both active-site modification and the substitution K→E in human rFVIIa(K62E) causes conformational change(s) within the FVII EGF1 domain associated with a substantially increased affinity of rFVIIa(K62E) and rFVIIai(K62E) for TF. Both rFVIIai(K62E)DEGR and rFVIIai(K62E)FFR show considerable promise as more effective inhibitors of coagulation than rFVIIai(WT).

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 score0.011

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)0.0030.001

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 head0.025
GPT teacher head0.330
Teacher spread0.305 · 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".

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Citations2
Published2005
Admission routes1
Has abstractyes

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