The Extended Cleavage Specificity of Human Thrombin

Thrombin is one of the most extensively studied of all proteases. Its central role in the coagulation cascade as well as several other areas has been thoroughly documented. Despite this, its consensus cleavage site has never been determined in detail. Here we have determined its extended substrate recognition profile using phage-display technology. The consensus recognition sequence was identified as, P2-Pro, P1-Arg, P1′-Ser/Ala/Gly/Thr, P2′-not acidic and P3′-Arg. Our analysis also identifies an important role for a P3′-arginine in thrombin substrates lacking a P2-proline. In order to study kinetics of this cooperative or additive effect we developed a system for insertion of various pre-selected cleavable sequences in a linker region between two thioredoxin molecules. Using this system we show that mutations of P2-Pro and P3′-Arg lead to an approximate 20-fold and 14-fold reduction, respectively in the rate of cleavage. Mutating both Pro and Arg results in a drop in cleavage of 200–400 times, which highlights the importance of these two positions for maximal substrate cleavage. Interestingly, no natural substrates display the obtained consensus sequence but represent sequences that show only 1–30% of the optimal cleavage rate for thrombin. This clearly indicates that maximal cleavage, excluding the help of exosite interactions, is not always desired, which may instead cause problems with dysregulated coagulation. It is likely exosite cooperativity has a central role in determining the specificity and rate of cleavage of many of these in vivo substrates. Major effects on cleavage efficiency were also observed for residues as far away as 4 amino acids from the cleavage site. Insertion of an aspartic acid in position P4 resulted in a drop in cleavage by a factor of almost 20 times

Implantation Serine Proteinase 1 Exhibits Mixed Substrate Specificity that Silences Signaling via Proteinase-Activated Receptors

Implantation S1 family serine proteinases (ISPs) are tryptases involved in embryo hatching and uterine implantation in the mouse. The two different ISP proteins (ISP1 and ISP2) have been detected in both pre- and post-implantation embryo tissue. To date, native ISP obtained from uterus and blastocyst tissues has been isolated only as an active hetero-dimer that exhibits trypsin-like substrate specificity. We hypothesised that in isolation, ISP1 might have a unique substrate specificity that could relate to its role when expressed alone in individual tissues. Thus, we isolated recombinant ISP1 expressed in Pichia pastoris and evaluated its substrate specificity. Using several chromogenic substrates and serine proteinase inhibitors, we demonstrate that ISP1 exhibits trypsin-like substrate specificity, having a preference for lysine over arginine at the P1 position. Phage display peptide mimetics revealed an expanded but mixed substrate specificity of ISP1, including chymotryptic and elastase activity. Based upon targets observed using phage display, we hypothesised that ISP1 might signal to cells by cleaving and activating proteinase-activated receptors (PARs) and therefore assessed PARs 1, 2 and 4 as potential ISP1 targets. We observed that ISP1 silenced enzyme-triggered PAR signaling by receptor-disarming. This PAR-disarming action of ISP1 may be important for embryo development and implantation

A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department

BACKGROUND: Several models for prediction of acute coronary syndrome (ACS) among chest pain patients in the emergency department (ED) have been presented, but many models predict only the likelihood of acute myocardial infarction, or include a large number of variables, which make them less than optimal for implementation at a busy ED. We report here a simple statistical model for ACS prediction that could be used in routine care at a busy ED. METHODS: Multivariable analysis and logistic regression were used on data from 634 ED visits for chest pain. Only data immediately available at patient presentation were used. To make ACS prediction stable and the model useful for personnel inexperienced in electrocardiogram (ECG) reading, simple ECG data suitable for computerized reading were included. RESULTS: Besides ECG, eight variables were found to be important for ACS prediction, and included in the model: age, chest discomfort at presentation, symptom duration and previous hypertension, angina pectoris, AMI, congestive heart failure or PCI/CABG. At an ACS prevalence of 21% and a set sensitivity of 95%, the negative predictive value of the model was 96%. CONCLUSION: The present prediction model, combined with the clinical judgment of ED personnel, could be useful for the early discharge of chest pain patients in populations with a low prevalence of ACS