Stephen J. Everse

Crystal structures of fragment D from human fibrinogen and its crosslinked counterpart from fibrin.

In blood coagulation, units of the protein fibrinogen pack together to form a fibrin clot, but a crystal structure for fibrinogen is needed to understand how this is achieved. The structure of a core fragment (fragment D) from human fibrinogen has now been determined to 2.9 Å resolution. The 86K three-chained structure consists of a coiled-coil region and two homologous globular entities oriented at approximately 130 degrees to each other. Additionally, the covalently bound dimer of fragment D, known as ‘double-D’, was isolated from human fibrin, crystallized in the presence of a Gly-Pro-Arg-Pro-amide peptide ligand, which simulates the donor polymerization site, and its structure solved by molecular replacement with the model of fragment D.

The Crystal Structure of Iron-free Human Serum Transferrin Provides Insight into Inter-lobe Communication and Receptor Binding

Serum transferrin reversibly binds iron in each of two lobes and delivers it to cells by a receptor-mediated, pH-dependent process. The binding and release of iron result in a large conformational change in which two subdomains in each lobe close or open with a rigid twisting motion around a hinge. We report the structure of human serum transferrin (hTF) lacking iron (apo-hTF), which was independently determined by two methods: 1) the crystal structure of recombinant non-glycosylated apo-hTF was solved at 2.7-Å resolution using a multiple wavelength anomalous dispersion phasing strategy, by substituting the nine methionines in hTF with selenomethionine and 2) the structure of glycosylated apo-hTF (isolated from serum) was determined to a resolution of 2.7Å by molecular replacement using the human apo-N-lobe and the rabbit holo-C1-subdomain as search models. These two crystal structures are essentially identical. They represent the first published model for full-length human transferrin and reveal that, in contrast to family members (human lactoferrin and hen ovotransferrin), both lobes are almost equally open: 59.4° and 49.5° rotations are required to open the N- and C-lobes, respectively (compared with closed pig TF). Availability of this structure is critical to a complete understanding of the metal binding properties of each lobe of hTF; the apo-hTF structure suggests that differences in the hinge regions of the N- and C-lobes may influence the rates of iron binding and release. In addition, we evaluate potential interactions between apo-hTF and the human transferrin receptor.

How the binding of human transferrin primes the transferrin receptor potentiating iron release at endosomal pH

Delivery of iron to cells requires binding of two iron-containing human transferrin (hTF) molecules to the specific homodimeric transferrin receptor (TFR) on the cell surface. Through receptor-mediated endocytosis involving lower pH, salt, and an unidentified chelator, iron is rapidly released from hTF within the endosome. The crystal structure of a monoferric N-lobe hTF/TFR complex (3.22-Å resolution) features two binding motifs in the N lobe and one in the C lobe of hTF. Binding of FeNhTF induces global and site-specific conformational changes within the TFR ectodomain. Specifically, movements at the TFR dimer interface appear to prime the TFR to undergo pH-induced movements that alter the hTF/TFR interaction. Iron release from each lobe then occurs by distinctly different mechanisms: Binding of His349 to the TFR (strengthened by protonation at low pH) controls iron release from the C lobe, whereas displacement of one N-lobe binding motif, in concert with the action of the dilysine trigger, elicits iron release from the N lobe. One binding motif in each lobe remains attached to the same α-helix in the TFR throughout the endocytic cycle. Collectively, the structure elucidates how the TFR accelerates iron release from the C lobe, slows it from the N lobe, and stabilizes binding of apohTF for return to the cell surface. Importantly, this structure provides new targets for mutagenesis studies to further understand and define this system.

The impact of uncertainty in a blood coagulation model

Deterministic mathematical models of biochemical processes operate as if the empirically derived rate constants governing the dynamics are known with certainty. Our objective in this study was to explore the sensitivity of a deterministic model of blood coagulation to variations in the values of its 44 rate constants. This was accomplished for each rate constant at a given time by defining a normalized ensemble standard deviation (w(k(i))(f)(t)) that accounted for the sensitivity of the predicted concentration of each protein species to variation in that rate constant (from 10 to 1000% of the accepted value). A mean coefficient of variation derived from (w(k(i))(f)(t)) values for all protein species was defined to quantify the overall variation introduced into the models predictive capacity at that time by the assumed uncertainty in that rate constant. A time-average value of the coefficient of variation over the 20-min simulation for each rate constant was then used to rank rate constants. The models predictive capacity is particularly sensitive (50% of the aggregate variation) to uncertainty in five rate constants involved in the regulation of the formation and function of the factor VIIa-tissue factor complex. Therefore, our analysis has identified specific rate constants to which the predictive capability of this model is most sensitive and thus where improvements in measurement accuracy will yield the greatest increase in predictive capability.

Predicting the pharmacology of thrombin inhibitors.

Summary.  Thrombotic disorders can lead to uncontrolled thrombin generation and clot formation within the circulatory system leading to vascular thrombosis. Direct inhibitors of thrombin have been developed and tested in clinical trials for the treatment of a variety of these thrombotic disorders. The bleeding complications observed during these trials have raised questions about their clinical use. The development of a computer‐based model of coagulation using the kinetic rates of individual reactions and concentrations of the constituents involved in each reaction within blood has made it possible to study coagulation pathologies in silico. We present an extension of our initial model of coagulation to include several specific thrombin inhibitors. Using this model we have studied the effect of a variety of inhibitors on thrombin generation and compared these results with the clinically observed data. The data suggest that numerical models will be useful in predicting the effectiveness of inhibitors of coagulation.

Defining the boundaries of normal thrombin generation: investigations into hemostasis.

In terms of its soluble precursors, the coagulation proteome varies quantitatively among apparently healthy individuals. The significance of this variability remains obscure, in part because it is the backdrop against which the hemostatic consequences of more dramatic composition differences are studied. In this study we have defined the consequences of normal range variation of components of the coagulation proteome by using a mechanism-based computational approach that translates coagulation factor concentration data into a representation of an individuals thrombin generation potential. A novel graphical method is used to integrate standard measures that characterize thrombin generation in both empirical and computational models (e.g max rate, max level, total thrombin, time to 2 nM thrombin (“clot time”)) to visualize how normal range variation in coagulation factors results in unique thrombin generation phenotypes. Unique ensembles of the 8 coagulation factors encompassing the limits of normal range variation were used as initial conditions for the computational modeling, each ensemble representing “an individual” in a theoretical healthy population. These “individuals” with unremarkable proteome composition was then compared to actual normal and “abnormal” individuals, i.e. factor ensembles measured in apparently healthy individuals, actual coagulopathic individuals or artificially constructed factor ensembles representing individuals with specific factor deficiencies. A sensitivity analysis was performed to rank either individual factors or all possible pairs of factors in terms of their contribution to the overall distribution of thrombin generation phenotypes. Key findings of these analyses include: normal range variation of coagulation factors yields thrombin generation phenotypes indistinguishable from individuals with some, but not all, coagulopathies examined; coordinate variation of certain pairs of factors within their normal ranges disproportionately results in extreme thrombin generation phenotypes, implying that measurement of a smaller set of factors may be sufficient to identify individuals with aberrant thrombin generation potential despite normal coagulation proteome composition.

A loop in the N-lobe of human serum transferrin is critical for binding to the transferrin receptor as revealed by mutagenesis, isothermal titration calorimetry, and epitope mapping.

Transferrin (TF) is a bilobal transport protein that acquires ferric iron from the diet and holds it tightly within the cleft of each lobe (thereby preventing its hydrolysis). The iron is delivered to actively dividing cells by receptor mediated endocytosis in which diferric TF preferentially binds to TF receptors (TFRs) on the cell surface and the entire complex is taken into an acidic endosome. A combination of lower pH, a chelator, inorganic anions, and the TFR leads to the efficient release of iron from each lobe. Identification of residues/regions within both TF and TFR required for high affinity binding has been an ongoing goal in the field. In the current study, we created human TF (hTF) mutants to identify a region critical to the interaction with the TFR which also constitutes part of an overlapping epitope for two monoclonal antibodies (mAbs) to the N‐lobe, one of which was previously shown to block binding of hTF to the TFR. Four single point mutants, P142A, R143A, K144A, and P145A in the N‐lobe, were placed into diferric hTF. Isothermal titration calorimetry (ITC) revealed that three of the four residues (Pro142, Lys144, and Pro145) in this loop are essential to TFR binding. Additionally, Lys144 is common to the recognition of both mAbs which show different sensitivities to the three other residues. Taken together these studies prove that this loop is required for binding of the N‐lobe of hTF to the TFR, provide a more precise description of the role of each residue in the loop in the interaction with the TFR, and confirm that the N‐lobe is essential to high affinity binding of diferric hTF to TFR. Copyright

Proposed structural models of human factor Va and prothrombinase

Summary.  Background: The prothrombinase complex consists of factor Xa, FVa, calcium ions, and phospholipid membrane. The prothrombinase complex plays a key role in the blood coagulation process.

Modeling thrombin generation: plasma composition based approach

Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

The structure and evolution of the murine inhibitor of carbonic anhydrase: A member of the transferrin superfamily

The original signature of the transferrin (TF) family of proteins was the ability to bind ferric iron with high affinity in the cleft of each of two homologous lobes. However, in recent years, new family members that do not bind iron have been discovered. One new member is the inhibitor of carbonic anhydrase (ICA), which as its name indicates, binds to and strongly inhibits certain isoforms of carbonic anhydrase. Recently, mouse ICA has been expressed as a recombinant protein in a mammalian cell system. Here, we describe the 2.4 Å structure of mouse ICA from a pseudomerohedral twinned crystal. As predicted, the structure is bilobal, comprised of two α‐β domains per lobe typical of the other family members. As with all but insect TFs, the structure includes the unusual reverse γ‐turn in each lobe. The structure is consistent with the fact that introduction of two mutations in the N‐lobe of murine ICA (mICA) (W124R and S188Y) allowed it to bind iron with high affinity. Unexpectedly, both lobes of the mICA were found in the closed conformation usually associated with presence of iron in the cleft, and making the structure most similar to diferric pig TF. Two new ICA family members (guinea pig and horse) were identified from genomic sequences and used in evolutionary comparisons. Additionally, a comparison of selection pressure (dN/dS) on functional residues reveals some interesting insights into the evolution of the TF family including that the N‐lobe of lactoferrin may be in the process of eliminating its iron binding function.