Simulated Thrombin Generation in the Presence of Surface-Bound Heparin and Circulating Tissue Factor

An expanded computational model of surface induced thrombin generation was developed that includes hemodynamic effects, 22 biochemical reactions and 44 distinct chemical species. Surface binding of factors V, VIII, IX, and X was included in order to more accurately simulate the formation of the surface complexes tenase and prothrombinase. In order to model these reactions, the non-activated, activated and inactivated forms were all considered. This model was used to investigate the impact of surface bound heparin on thrombin generation with and without the additive effects of thrombomodulin (TM). In total, 104 heparin/TM pairings were evaluated (52 under venous conditions, 52 under arterial conditions), the results demonstrating the synergistic ability of heparin and TM to reduce thrombin generation. Additionally, the role of circulating tissue factor (TF[subscript p]) was investigated and compared to that of surface-bound tissue factor (TF[subscript s]). The numerical results suggest that circulating TF has the power to amplify thrombin generation once the coagulation cascade is already initiated by surface-bound TF. TF[subscript p] concentrations as low as 0.01 nM were found to have a significant impact on total thrombin generation.National Institutes of Health (U.S.) (Grants HL106018 and HL56819

Computationally Derived Points of Fragility of a Human Cascade Are Consistent with Current Therapeutic Strategies

The role that mechanistic mathematical modeling and systems biology will play in molecular medicine and clinical development remains uncertain. In this study, mathematical modeling and sensitivity analysis were used to explore the working hypothesis that mechanistic models of human cascades, despite model uncertainty, can be computationally screened for points of fragility, and that these sensitive mechanisms could serve as therapeutic targets. We tested our working hypothesis by screening a model of the well-studied coagulation cascade, developed and validated from literature. The predicted sensitive mechanisms were then compared with the treatment literature. The model, composed of 92 proteins and 148 protein–protein interactions, was validated using 21 published datasets generated from two different quiescent in vitro coagulation models. Simulated platelet activation and thrombin generation profiles in the presence and absence of natural anticoagulants were consistent with measured values, with a mean correlation of 0.87 across all trials. Overall state sensitivity coefficients, which measure the robustness or fragility of a given mechanism, were calculated using a Monte Carlo strategy. In the absence of anticoagulants, fluid and surface phase factor X/activated factor X (fX/FXa) activity and thrombin-mediated platelet activation were found to be fragile, while fIX/FIXa and fVIII/FVIIIa activation and activity were robust. Both anti-fX/FXa and direct thrombin inhibitors are important classes of anticoagulants; for example, anti-fX/FXa inhibitors have FDA approval for the prevention of venous thromboembolism following surgical intervention and as an initial treatment for deep venous thrombosis and pulmonary embolism. Both in vitro and in vivo experimental evidence is reviewed supporting the prediction that fIX/FIXa activity is robust. When taken together, these results support our working hypothesis that computationally derived points of fragility of human relevant cascades could be used as a rational basis for target selection despite model uncertainty

Systems Biology of Platelet Activation

Platelet intracellular calcium mobilization [Ca(t)]i is a measure of platelet activation and controls important events downstream that contribute to hemostasis such as granule release, cyclooxygenase-1 and integrin activation, and phosphatidylserine exposure. Accurate simulations of blood clotting events require prediction of platelet [Ca(t)]i in response to combinatorial agonists. Therefore, a data-driven human platelet calcium calculator was developed using neural network (NN) ensemble trained on pairwise agonist scanning (PAS) data. PAS deployed all single and pairwise combinations of six important agonists (ADP, convulxin, thrombin, U46619, iloprost and GSNO used at 0.1, 1, and 10xEC50 to stimulate platelet P2Y1/P2Y12, GPVI, PAR1/PAR4, TP, IP receptors, and guanylate cyclase, respectively, in Factor Xa-inhibited (250 nM apixaban), diluted platelet rich plasma. PAS of 10 healthy donors (5 male, 5 female) provided [Ca(t)]i data for training 10 neural networks (NN, 2-layer/12-nodes) per donor. Trinary stimulations were then conducted at all 0.1x and 1xEC50 doses (160 conditions) as was a sampling of 45 higher ordered combinations (four to six agonists). The NN-ensemble average accurately predicted [Ca (t)]i beyond the single and binary training set for trinary stimulations (R = 0.924). The 160 trinary synergy scores, a normalized metric of signaling crosstalk, were also well predicted (R = 0.850) as were the calcium dynamics (R = 0.871) and high-dimensional synergy scores (R = 0.695) for the 45 higher ordered conditions. The calculator even predicted sequential addition experiments (n = 54 conditions, R = 0.921). NN-ensemble is a fast calcium calculator that proved to be useful for multiscale clotting simulations that include spatiotemporal concentrations of ADP, collagen, thrombin, thromboxane, prostacyclin, and nitric oxide. From sequential addition experiments done in PAS, it was discovered that activating platelets with thrombin in platelet-rich plasma (PRP) caused an attenuation of convulxin-induced, GPVI platelet receptor-mediated, calcium mobilization when convulxin was added to PRP approximately six minutes later. This attenuation effect was not observed when ADP and thromboxane analog, U46619 was used in place of thrombin. When PAR-1 and PAR-4 receptor agonists (AYPGKF and SFLLRN) were used instead of thrombin for the initial dispense, the subsequent convulxin-induced calcium response was also unaffected, demonstrating thrombin’s unique role in causing attenuation of subsequent convulxin-induced calcium mobilization. Thrombin, unlike ADP, U46619 or the PAR-1 and PAR-4 receptor agonists, is able to polymerize fibrinogen into fibrin. When GPRP was added to prevent polymerization of fibrin, initial platelet activation by thrombin did not result in attenuation of convulxin- induced calcium mobilization. This experiment was repeated using a mixture of washed platelets and fibrinogen monomers instead of PRP and yielded similar results. The presence of polymerized fibrin also reduced platelet deposition in a microfluidic assay on a collagen surface. These results suggest that polymerized fibrin binds to and downregulates platelet GPVI, a platelet receptor that is important to thrombus growth and is central to mediating hemostasis

Exosite Binding in Thrombin: A Global Structural/Dynamic Overview of Complexes with Aptamers and Other Ligands

: Thrombin is the key enzyme of the entire hemostatic process since it is able to exert both procoagulant and anticoagulant functions; therefore, it represents an attractive target for the developments of biomolecules with therapeutic potential. Thrombin can perform its many functional activities because of its ability to recognize a wide variety of substrates, inhibitors, and cofactors. These molecules frequently are bound to positively charged regions on the surface of protein called exosites. In this review, we carried out extensive analyses of the structural determinants of thrombin partnerships by surveying literature data as well as the structural content of the Protein Data Bank (PDB). In particular, we used the information collected on functional, natural, and synthetic molecular ligands to define the anatomy of the exosites and to quantify the interface area between thrombin and exosite ligands. In this framework, we reviewed in detail the specificity of thrombin binding to aptamers, a class of compounds with intriguing pharmaceutical properties. Although these compounds anchor to protein using conservative patterns on its surface, the present analysis highlights some interesting peculiarities. Moreover, the impact of thrombin binding aptamers in the elucidation of the cross-talk between the two distant exosites is illustrated. Collectively, the data and the work here reviewed may provide insights into the design of novel thrombin inhibitors

A COMPUTATIONAL BIOLOGY APPROACH TO THE ANALYSIS OF COMPLEX PHYSIOLOGY: COAGULATION, FIBRINOLYSIS, AND WOUND HEALING

The birth of complexity research derives from the logical progression of advancement in the scientific field afforded by reductionist theory. We present in silico models of two complex physiological processes, wound healing and coagulation/fibrinolysis based on two common tools in the study of complex physiology: ordinary differential equations (ODE) and Agent Based Modeling (ABM). The strengths of these two approaches are well-suited in the analysis of clinical paradigms such as wound healing and coagulation. The complex interactions that characterize acute wound healing have stymied the development of effective therapeutic modalities. The use of computational models holds the promise to improve our basic approach to understanding the process. We have modified an existing ordinary differential equation model by 1) evolving from a systemic model to a local model, 2) the incorporation of fibroblast activity, and3) including the effects of tissue oxygenation. Possible therapeutic targets, such as fibroblast death rate and rate of fibroblast recruitment have been identified by computational analysis. This model is a step toward constructing an integrative systems biology model of human wound healing. The coagulation and fibrinolytic systems are complex, inter-connected biological systems with major physiological roles. We present an Agent Based Modeling and Simulation (ABMS) approach to these complex interactions. This ABMS method successfully reproduces the initiation, propagation, and termination of blood clot formation and its lysis in vitro due to the activation of either the intrinsic or extrinsic pathways. Furthermore, the ABMS was able to simulate the pharmacological effects of two clinically used anticoagulants, warfarin and heparin, as well as the physiological effects of enzyme deficiency/dysfunction, i.e., hemophilia and antithrombin III-heparin binding impairment, on the coagulation system. The results of the model compare favorably with in vitro experimental data under both physiologic and pathophysiologic conditions. Our computational systems biology approach integrates reductionist experimental data into a cohesive model that allows rapid evaluation of the effects of multiple variables. Our ODE and AMBS models offer the ability to generate non-linear responses based on known relationships among variables and in silico modeling of mechanistic biological rules on computer software, respectively. Simulations of normal and disease states as well as effects of therapeutic intervention demonstrate the potential uses of computer simulation. Specifically, models may be applied to hypothesis generation and biological advances, discovery of new diagnostic and therapeutic options, platforms to test novel therapies, and opportunities to predict adverse events during drug development. The ultimate aim of such models is creation of bedside simulators that allow personalized, individual medicine; however, a myriad of opportunities for scientific advancement are opened through in silico experimentation

Systems Biology of Blood Coagulation and Platelet Activation

Blood clotting is a highly conserved physiological response that prevents excessive blood loss following vessel injury. It involves a sequence of plasma reactions leading to the formation of thromin (the coagulation cascade) as well as tightly controlled intracellular reactions mediating platelet activation. These two events are inextricably coupled, with the active platelet surface serving as a cofactor for coagulation factor assembly and thrombin serving as a potent platelet agonist. Using the technologies of automated liquid handling, high throughput experimental systems were developed that allowed individual exploration of these two components of the thrombotic response under diverse initial conditions. Based on this high dimensional experimental exploration, a “bottom-up” mechanism based Ordinary Differential Equation (ODE) description of thrombin generation kinetics and a “top-down” data driven Neural Network model of platelet activation were developed. In the first study, “contact activation” (and not “blood-borne TF” alone) despite the best available inhibitor to prevent it, was found build up enough autocatalytic strength to trigger coagulation in the absence of exogenous tissue factor, particularly upon activated platelets. Further, the “Platelet-Plasma model” successfully predicted the stability of blood under multiple perturbations with active enzymes at various physiologically realizable conditions. In the second study, “Pairwise Agonist Scanning” (PAS), a strategy that trains a Neural Network model based on measurements of cellular responses to individual and all pairwise combinations of input signals is described. PAS was used to predict calcium signaling responses of human platelets in EDTA-treated plasma to six different agonists (ADP, Convulxin, U46619, SFLLRN, AYPGKF and PGE2). The model predicted responses to sequentially added agonists, to ternary combinations of agonists and to 45 different combinations of four to six agonists (R=0.88). Furthermore, PAS was used to distinguish between the phenotypic responses of platelets from healthy human donors. Taken together, these two studies lay the groundwork for integration of coagulation reaction kinetics and donor specific descriptions of platelet function with models of convection and diffusion to simulate thrombosis under flow

Evaluation of a numerical thrombosis model for a high shear rotating flow

Blood clotting, or thrombosis, is an interesting biological application for computational fluid dynamics. Existing numerical thrombosis models have previously been shown to be effective for low shear rates and simple geometries. For these models to be used in biomedical applications such as the design of rotary blood pumps, however, they must first be experimentally validated for high shear rates and complex geometries. In this study, we test the ability of a numerical thrombosis model to predict thrombosis related phenomena in a high shear flow by creating a geometry similar to that of a rotary blood pump. We have applied an existing numerical thrombosis model to an annular gap between rotating concentric cylinders, a geometry that is closely related to rotary blood pumps. Additionally, we created a physical model of the same geometry and exposed blood to a range of shear rates in both the empirical and numerical model. The empirical and numerical results are compared in order to evaluate the ability of the numerical model to predict thrombosis in similar geometries, such as high shear blood handling pumps. Fluent was used to solve the coupled convective-diffusion equations along with user defined equations that include production and consumption of 7 species critical to thrombosis. These equations, along with equations of fluid motion, were solved iteratively within the Fluent solver. All reaction constants were from previously published work. At each of the shear rates and exposure times tested, the numerical model calculated platelet deposition, platelet-platelet aggregation and the two-dimensional distribution of three primary agonists (ADP, thromboxane and thrombin) in addition to the standard fluid variables (velocity, pressure, shear rate, etc.) A physical model was designed and constructed to control the shear rate to which blood is exposed. An annular gap of 360μm was chosen in order to induce a shear rate of up to 10,000 s-1 while maintaining laminar flow. In a series of experiments, fresh, heparinized, bovine blood was exposed to a constant shear rate ranging from 1,000 to 10,000 s-1 for 120 seconds. Prothrombin time (PT) and activated partial thromboplastin time (APTT) of the blood was then measured for each stress level. While the observed changes in thromboembolitic potential (as measured by PT and APTT) of the whole blood test samples qualitatively correspond to platelet activation and agonist concentration predicted by the numerical model, further work is needed to quantitatively verify the numerical model. Thrombosis models based on coupled convective-diffusion equations show promise, but need further refinement and validation before they can be trusted to authoritatively predict thromboembolitic potential

Modeling and Analysis of Signal Transduction Networks

Biological pathways, such as signaling networks, are a key component of biological systems of each living cell. In fact, malfunctions of signaling pathways are linked to a number of diseases, and components of signaling pathways are used as potential drug targets. Elucidating the dynamic behavior of the components of pathways, and their interactions, is one of the key research areas of systems biology. Biological signaling networks are characterized by a large number of components and an even larger number of parameters describing the network. Furthermore, investigations of signaling networks are characterized by large uncertainties of the network as well as limited availability of data due to expensive and time-consuming experiments. As such, techniques derived from systems analysis, e.g., sensitivity analysis, experimental design, and parameter estimation, are important tools for elucidating the mechanisms involved in signaling networks. This Special Issue contains papers that investigate a variety of different signaling networks via established, as well as newly developed modeling and analysis techniques

Role of nitric oxide as a modulator of platelet dense granule release

Nitric oxide (NO) has been shown to suppress platelet activation, induce vasodilation, inhibit smooth muscle cell proliferation, and act against infection. Activated platelets generally have opposite effects from these. They secrete platelet-derived growth factor (PDGF), which stimulates smooth muscle growth, serotonin, which is a platelet agonist, and a number of agents that promote further platelet aggregation. However, activated platelets also produce NO through the enzymatic functions of the constitutive form of nitric oxide synthase (NOS). The primary functions of this capability are not yet completely understood. Due to its low molecular weight and high diffusivity, NO is quickly transported from its source to surrounding tissues and medium, and this characteristic may be instrumental to its function. Understanding the way in which NO interacts with platelet function could assist in the development of improved diagnostic and surgical procedures as well as biomaterials that are resistant to thrombus formation. Due to the short half-life of NO in vivo and in vitro, it was desired to use platelet-derived serotonin and an indicator for NO function. The research objectives for this project were (1) to develop mathematical models representing the diffusive transport of platelet derived agonists and inhibitors, (2) to electrochemically measure serotonin concentration during in vitro aggregation of platelets to fibrillar collagen with and without L-NMMA (a NO inhibitor), and (3) to verify platelet aggregation through histological analysis. Presence of the NOS inhibitor, L-NMMA, did not have a statistical significance when compared across experiments with fibrillar collagen, which lacked L-NMMA. It can be inferred from this analysis that a statistically significant change in serotonin concentration, resulting from platelet activation by collagen, could not be detected when compared in presence and absence of the NOS inhibitor L-NMMA. From the research conducted in this project, many questions have been postulated concerning the primary role of NO in platelet function