The Role of Lysine Residues 42, 43, and 44 in the Activation Peptide Region of TAFI in Its Activation by the Thrombin-Thrombomodulin Complex.
Bibliographic record
Abstract
Abstract Abstract 3187 Poster Board III-124 Thrombin-activatable fibrinolysis inhibitor (TAFI) is a 60 kDa plasma protein that is activated to the enzyme TAFIa, by a single cleavage at Arg92 by thrombin, plasmin or trypsin. TAFIa is a carboxypeptidase B-like enzyme that attenuates fibrinolysis. Thrombomodulin (TM) is a cofactor which increases the overall efficiency of thrombin-mediated TAFI activation by 1250-fold. Thus, the thrombin-TM complex is believed to be the physiological TAFI activator. The minimal structure of TM required for efficient TAFI activation contains the EGF-like domains 3 through 6. New structure models have postulated that the C-loop of TM EGF-like domain 3 has a negatively charged molecular surface that could interact with several positively charged surface patches on TAFI. One positively charged surface patch of TAFI consists of the three consecutive lysine residues at positions 42, 43, and 44, which are unique to the TAFI activation peptide as no corresponding residues exist in rattus, bovine or human tissue procarboxypeptidases A and B. More interestingly, all three lysine residues are conserved in human, rattus, murine and canine TAFI, but not for bovine TAFI which only has a single lysine residue at position 42. We previously reported that when the three lysine residues are substituted by alanine residues (K42/43/44A), compared to the wild-type, the catalytic efficiencies for TAFI activation by thrombin-TM complex decreased 8-fold. In order to identify which residue(s) are key for TAFI activation by the thrombin-TM complex, combinations of mutations of the three lysine residues were constructed and expressed. TAFI wild-type or mutants were activated by thrombin for 10 minutes in the absence or presence of TM at varying levels. At this point, the levels of TAFIa formed were measured by adding the synthetic substrate AAFR containing PPAck and measuring the absorbance change at 349nm. The rates were used to determine the kinetic parameters of TAFI activation. The non-linear regression analysis with the NONLIN module of SYSTAT returned best fit values along with their asymptotic standard errors (A.S.E) for the kinetic parameters of TAFI activation (kcat, Km, and Kd). The value of Kd (the dissociation constant for the thrombin-TM interaction) is assumed to be the same for wild-type TAFI and the mutants, because all reactions have this interaction in common. The regression analysis yielded Kd = 22.4 ± 1.3 nM for this interaction. This value agrees favourably with a value of 22 nM measured directly and reported previously. The kcat values (1/sec) ranged from 1.06 ± 0.18 (K44A) to 1.19 ± 0.18 (K43A). The value for wild-type TAFI was 1.50 ± 0.63 (1/sec). Km values ranged from 1.14 ± 0.73 μM (WT) to 3.01 ± 2.17 μM (K42A). The kcat / Km ratios (1/sec/μM), which provides the best indication of overall catalytic efficiency, ranged from 1.43 ± 0.27 (WT) to 0.43 ± 0.17 (K42A). When the three lysine residues are individually substituted by alanine residues (K42A, K43A, and K44A), compared to the wild-type, their catalytic efficiencies (kcat / Km) for TAFI activation by the thrombin-TM complex decreased 3.3-fold for K42A, 1.83-fold for K43A, and 1.96-fold for K44A. When Lys43 and Lys44 are substituted by alanine residues simultaneously (K43/44A), its catalytic efficiency decreased 3.3-fold. Together, our data show that each of these lysine residues on the activation peptide of TAFI may contribute partially to the interactions of TAFI with the thrombin-TM complex that are needed for efficient activation. In addition, the effects of the mutations may be additive. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".