Hinge bending within the cytokine receptor superfamily revealed by the 2.4 A crystal structure of the extracellular domain of rabbit tissue factor

Conformational Changes of Congenital FVII Variants with Defective Binding to Tissue Factor ARG304GLN (FVII Padua), ARG 304TRP (FVII Nagoya) and ARG79GLN (FVII Shinjo or Tondabayashi)

BACKGROUND

The relation between Factor VII (FVII) and tissue thromboplastin is not completely clarified, yet. Three FVII abnormalities, FVII Padua (Arg304Gln), FVII Nagoya (Arg304Trp) and FVII Shinjo or Tondabayshi (Arg79Gln) show different FVII activity according to the tissue Tissue Factor (TF) used in the assay system (rabbit brain, human placenta or human recombinant and ox brain).

OBJECTIVES

To investigate the possible existence of common conformational changes with regard to different tissue factors in these three FVII variants.

MATERIAL AND METHODS

Crystal structure analysis and "visual inspection" of FVII were deeply performed to select a crystallographic template for the in silico mutagenesis procedure of FVII Arg79Gln, Arg304Gln and Arg304Trp.100ns 300K NVT large-scale molecular dynamics simulation on GPU were applied to the models of FVII. The aims of this run was to describe at molecular level the influence of the mutation on the protein structure and function.

RESULTS

The molecular modelling of those three variants has shown common features in spite of the different location of the mutation involved (the first epidermal growth factor for the Arg79Gln and the catalytic region for the Arg304Gln or Arg304Trp). Molecular dynamics studies have shown in fact that the mutant FVII, shows a decreased flexibility or freezing of the protein conformation of FVIIa with regard to TF. This results in the formation of a defective FVIIa-TF complex that justifies the different clotting results observed in these variants according to the TF used.

CONCLUSIONS

The conformational studies may supply useful information on the structure- function relation of clotting factors.

The role of dynamic conformational ensembles in biomolecular recognition

Molecular recognition is central to all biological processes. For the past 50 years, Koshland's 'induced fit' hypothesis has been the textbook explanation for molecular recognition events. However, recent experimental evidence supports an alternative mechanism. 'Conformational selection' postulates that all protein conformations pre-exist, and the ligand selects the most favored conformation. Following binding the ensemble undergoes a population shift, redistributing the conformational states. Both conformational selection and induced fit appear to play roles. Following binding by a primary conformational selection event, optimization of side chain and backbone interactions is likely to proceed by an induced fit mechanism. Conformational selection has been observed for protein-ligand, protein-protein, protein-DNA, protein-RNA and RNA-ligand interactions. These data support a new molecular recognition paradigm for processes as diverse as signaling, catalysis, gene regulation and protein aggregation in disease, which has the potential to significantly impact our views and strategies in drug design, biomolecular engineering and molecular evolution.

FlexProt: alignment of flexible protein structures without a predefinition of hinge regions

FlexProt is a novel technique for the alignment of flexible proteins. Unlike all previous algorithms designed to solve the problem of structural comparisons allowing hinge-bending motions, FlexProt does not require an a priori knowledge of the location of the hinge(s). FlexProt carries out the flexible alignment, superimposing the matching rigid subpart pairs, and detects the flexible hinge regions simultaneously. A large number of methods are available to handle rigid structural alignment. However, proteins are flexible molecules, which may appear in different conformations. Hence, protein structural analysis requires algorithms that can deal with molecular flexibility. Here, we present a method addressing specifically a flexible protein alignment task. First, the method efficiently detects maximal congruent rigid fragments in both molecules. Transforming the task into a graph theoretic problem, our method proceeds to calculate the optimal arrangement of previously detected maximal congruent rigid fragments. The fragment arrangement does not violate the protein sequence order. A clustering procedure is performed on fragment-pairs which have the same 3-D rigid transformation regardless of insertions and deletions (such as loops and turns) which separate them. Although the theoretical worst case complexity of the algorithm is O(n(6)), in practice FlexProt is highly efficient. It performs a structural comparison of a pair of proteins 300 amino acids long in about seven seconds on a standard desktop PC (400 MHz Pentium II processor with 256MB internal memory). We have performed extensive experiments with the algorithm. An assortment of these results is presented here. FlexProt can be accessed via WWW at bioinfo3d.cs.tau.ac.il/FlexProt/.

Interleukin-10 and related cytokines and receptors

The Class 2 alpha-helical cytokines consist of interleukin-10 (IL-10), IL-19, IL-20, IL-22, IL-24 (Mda-7), and IL-26, interferons (IFN-alpha, -beta, -epsilon, -kappa, -omega, -delta, -tau, and -gamma) and interferon-like molecules (limitin, IL-28A, IL-28B, and IL-29). The interaction of these cytokines with their specific receptor molecules initiates a broad and varied array of signals that induce cellular antiviral states, modulate inflammatory responses, inhibit or stimulate cell growth, produce or inhibit apoptosis, and affect many immune mechanisms. The information derived from crystal structures and molecular evolution has led to progress in the analysis of the molecular mechanisms initiating their biological activities. These cytokines have significant roles in a variety of pathophysiological processes as well as in regulation of the immune system. Further investigation of these critical intercellular signaling molecules will provide important information to enable these proteins to be used more extensively in therapy for a variety of diseases.

Tissue Factor: A Key Molecule in Hemostatic and Nonhemostatic Systems

Tissue factor (also known as tissue thromboplastin or CD142) is the protein that activates the blood clotting system by binding to, and activating, the plasma serine protease, factor VIIa, following vascular injury. Because of its essential role in hemostasis, tissue factor plays a role in pathology associated with hemostasis, triggering the coagulation system in many thrombotic diseases and the coagulopathies associated with sepsis and other forms of disseminated intravascular coagulation. Recent research has also implicated tissue factor in a variety of nonhemostatic roles, including cell signaling, inflammation, vasculogenesis, and tumor growth and metastasis. This review focuses on both the well-known roles of tissue factor in hemostasis and thrombosis and the newer concepts of tissue-factor biology including how it functions as a signaling receptor and the possible role of blood-borne tissue factor in thrombosis.

The human type I interferon receptor: NMR structure reveals the molecular basis of ligand binding

The potent antiviral and antiproliferative activities of human type I interferons (IFNs) are mediated by a single receptor comprising two subunits, IFNAR1 and IFNAR2. The structure of the IFNAR2 IFN binding ectodomain (IFNAR2-EC), the first helical cytokine receptor structure determined in solution, reveals the molecular basis for IFN binding. The atypical perpendicular orientation of its two fibronectin domains explains the lack of C domain involvement in ligand binding. A model of the IFNAR2-EC/IFNalpha2 complex based on double mutant cycle-derived constraints uncovers an extensive and predominantly aliphatic hydrophobic patch on the receptor that interacts with a matching hydrophobic surface of IFNalpha2. An adjacent motif of alternating charged side chains guides the two proteins into a tight complex. The binding interface may account for crossreactivity and ligand specificity of the receptor. This molecular description of IFN binding should be invaluable for study and design of IFN-based biomedical agents.

Multiple diverse ligands binding at a single protein site: a matter of pre-existing populations

Here, we comment on the steadily increasing body of data showing that proteins with specificity actually bind ligands of diverse shapes, sizes, and composition. Such a phenomenon is not surprising when one considers that binding is a dynamic process with populations in equilibrium and that the shape of the binding site is strongly influenced by the molecular partner. It derives implicitly from the concept of populations. All proteins, specific and nonspecific, exist in ensembles of substates. If the library of ligands in solution is large enough, favorably matching ligands with altered shapes and sizes can be expected to bind, with a redistribution of the protein populations. Point mutations at spatially distant sites may exert large conformational rearrangements and hinge effects, consistent with mutations away from the binding site leading to population shifts and (cross-)drug resistance. A similar effect is observed in protein superfamilies, in which different sequences with similar topologies display similar large-scale dynamic motions. The hinges are frequently at analogous sites, yet with different substrate specificity. Similar topologies yield similar conformational isomers, although with different distributions of population times, owing to the change in the conditions, that is, the change in the sequences. In turn, different distributions relate to binding of different sizes and shapes. Hence, the binding site shape and size are defined by the ligand. They are not independent entities of fixed proportions and cannot be analyzed independently of the binding partner. Such a proposition derives from viewing proteins as dynamic distributions, presenting to the incoming ligands a range of binding site shapes. It illustrates how presumably specific binding molecules can bind multiple ligands. In terms of drug design, the ability of a single receptor to recognize many dissimilar ligands shows the need to consider more diverse molecules. It provides a rationale for higher affinity inhibitors that are not derived from substrates at their transition states and indicates flexible docking schemes.

Multiple diverse ligands binding at a single protein site: a matter of pre-existing populations

Here, we comment on the steadily increasing body of data showing that proteins with specificity actually bind ligands of diverse shapes, sizes, and composition. Such a phenomenon is not surprising when one considers that binding is a dynamic process with populations in equilibrium and that the shape of the binding site is strongly influenced by the molecular partner. It derives implicitly from the concept of populations. All proteins, specific and nonspecific, exist in ensembles of substates. If the library of ligands in solution is large enough, favorably matching ligands with altered shapes and sizes can be expected to bind, with a redistribution of the protein populations. Point mutations at spatially distant sites may exert large conformational rearrangements and hinge effects, consistent with mutations away from the binding site leading to population shifts and (cross-)drug resistance. A similar effect is observed in protein superfamilies, in which different sequences with similar topologies display similar large-scale dynamic motions. The hinges are frequently at analogous sites, yet with different substrate specificity. Similar topologies yield similar conformational isomers, although with different distributions of population times, owing to the change in the conditions, that is, the change in the sequences. In turn, different distributions relate to binding of different sizes and shapes. Hence, the binding site shape and size are defined by the ligand. They are not independent entities of fixed proportions and cannot be analyzed independently of the binding partner. Such a proposition derives from viewing proteins as dynamic distributions, presenting to the incoming ligands a range of binding site shapes. It illustrates how presumably specific binding molecules can bind multiple ligands. In terms of drug design, the ability of a single receptor to recognize many dissimilar ligands shows the need to consider more diverse molecules. It provides a rationale for higher affinity inhibitors that are not derived from substrates at their transition states and indicates flexible docking schemes.

Interdomain interactions in hinge-bending transitions

BACKGROUND

The mechanisms that allow or constrain protein movement have not been understood. Here we study interdomain interactions in proteins to investigate hinge-bending motions.

RESULTS

We find a limited number of salt bridges and hydrogen bonds at the interdomain interface, in both the "closed" and the "open" conformations. Consistently, analysis of 222 salt bridges in an independently selected database indicates that most salt bridges form within rather than between independently folding hydrophobic units. Calculations show that these interdomain salt bridges either destabilize or only marginally stabilize the closed conformation in most proteins. In contrast, the nonpolar buried surface area between the moving parts can be extensive in the closed conformations. However, when the nonpolar buried surface area is large, we find that at the interdomain interface in the open conformation it may be as large or larger than in the closed conformation. Hence, the energetic penalty of opening the closed conformation is overcome. Consistently, a large nonpolar surface area buried in the closed interdomain interface accompanies limited opening of the domains, yielding a larger interface.

CONCLUSIONS

Short-range electrostatic interactions are largely absent between moving domains. Interdomain nonpolar buried surface area may be large in the closed conformation, but it is largely offset by the area buried in the open conformation. In such cases the opening of the domains appears to be relatively small. This may allow prediction of the extent of domain opening. Such predictions may have implications for the shape and size of the binding pockets in drug/protein design.

The 1.85 A resolution crystal structures of tissue factor in complex with humanized Fab D3h44 and of free humanized Fab D3h44: revisiting the solvation of antigen combining sites

The outstanding importance of the antigen-antibody recognition process for the survival and defence strategy of higher organisms is in sharp contrast to the limited high resolution structural data available on antibody-antigen pairs with antigenic proteins. The limitation is the most severe for structural data not restricted to the antigen-antibody complex but extending to the uncomplexed antigen and antibody. We report the crystal structure of the complex between tissue factor (TF) and the humanized Fab fragment D3h44 at a resolution of 1.85 A together with the structure of uncomplexed D3h44 at the same resolution. In conjunction with the previously reported 1.7 A crystal structure of uncomplexed TF, a unique opportunity is generated to explore details of the recognition process. The TF.D3h44 interface is characterised by a high number of polar interactions, including as may as 46 solvent molecules. Conformational changes upon complex formation are very small and almost exclusively limited to the reorientation of side-chains. The binding epitope is in complete agreement with earlier mutagenesis experiments. A revaluation of two other antibody-antigen pairs reported at similar resolutions, shows that all these complexes are very similar with respect to the solvation of the interface, the number of solvent positions conserved in the uncomplexed and complexed proteins and the number of water molecules expelled from the surface and replaced by hydrophilic atoms from the binding partner upon complex formation. A strategy is proposed on how to exploit this high resolution structural data to guide the affinity maturation of humanised antibodies.

Assembly and ligand binding properties of the water-soluble extracellular domains of the glutamate receptor 1 subunit

High resolution structural studies of models of glutamate receptors (GluRs) have been limited to monomeric models of the ligand-binding site. To obtain oligomeric models of glutamate receptors that can reveal more complete structural information, we examined the assembly and ligand binding properties of two truncated versions of the GluR1 subunit. The first version, GluR1-WS, consisted of only the N-terminal extracellular segment (Ala(1)-Glu(520)) bridged by a synthetic linker to the second extracellular domain (Asn(615)-Gly(790)). The second version, GluR1-M1, consisted of the first N-terminal extracellular domain (Ala(1)-Glu(520)) bridged by a synthetic linker to a second segment containing the second extracellular domain, the third transmembrane domain, and the intracellular C-terminal domain (Asn(615)-Leu(889)). When expressed in Xenopus oocytes, GluR-WS was secreted and water-soluble; GluR1-M1 was displayed on the surface of oocytes. GluR1-WS exhibited a velocity sedimentation profile that was consistent with assembly of homooligomers and bound the glutamate receptor agonist alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid with high affinity. These findings show that the extracellular domains of GluR1 that are sufficient for ligand binding apparently are sufficient for subunit assembly and might be a suitable target for structural studies of a water-soluble GluR1 oligomer.

Folding and binding cascades: dynamic landscapes and population shifts

Whereas previously we have successfully utilized the folding funnels concept to rationalize binding mechanisms (Ma B, Kumar S, Tsai CJ, Nussinov R, 1999, Protein Eng 12:713-720) and to describe binding (Tsai CJ, Kumar S, Ma B, Nussinov R, 1999, Protein Sci 8:1181-1190), here we further extend the concept of folding funnels, illustrating its utility in explaining enzyme pathways, multimolecular associations, and allostery. This extension is based on the recognition that funnels are not stationary; rather, they are dynamic, depending on the physical or binding conditions (Tsai CJ, Ma B, Nussinov R, 1999, Proc Natl Acad Sci USA 96:9970-9972). Different binding states change the surrounding environment of proteins. The changed environment is in turn expressed in shifted energy landscapes, with different shapes and distributions of populations of conformers. Hence, the function of a protein and its properties are not only decided by the static folded three-dimensional structure; they are determined by the distribution of its conformational substates, and in particular, by the redistributions of the populations under different environments. That is, protein function derives from its dynamic energy landscape, caused by changes in its surroundings.

Dynamic character of the complex of human blood coagulation factor VIIa with the extracellular domain of human tissue factor: a normal mode analysis

As an attempt to investigate the dynamic interactions between plasma serine protease, coagulation factor VIIa (VIIa) and its cofactor, tissue factor (TF), we performed normal mode analysis (NMA) of the complex of VIIa with soluble TF (the extracellular part of TF; sTF). We compared fluctuations of Calpha atoms of VIIa or sTF derived from NMA in the VIIa-sTF complex with those of VIIa or sTF in an uncomplexed condition. The atomic fluctuations of the Calpha atoms of sTF complexed with VIIa did not significantly differ from those of sTF without VIIa. In contrast, the atomic fluctuations of VIIa complexed with sTF were much smaller than those of VIIa without sTF. These results suggest that domain motions of VIIa molecule alone are markedly dampened in the VIIa-sTF complex and that the sTF molecule is relatively more rigid than the VIIa molecule. This may indicate functions of TF as a cofactor.

Folding funnels and binding mechanisms

The long-held views on lock-and-key versus induced fit in binding arose from the notion that a protein exists in a single, most stable conformation, dictated by its sequence. However, in solution proteins exist in a range of conformations, which may be described by statistical mechanical laws and their populations follow statistical distributions. Upon binding, the equilibrium will shift in favor of the bound conformation from the ensemble of conformations around the bottom of the folding funnel. Hence here we extend the implications and the usefulness of the folding funnel concept to explain fundamental binding mechanisms.

Folding funnels, binding funnels, and protein function

Folding funnels have been the focus of considerable attention during the last few years. These have mostly been discussed in the general context of the theory of protein folding. Here we extend the utility of the concept of folding funnels, relating them to biological mechanisms and function. In particular, here we describe the shape of the funnels in light of protein synthesis and folding; flexibility, conformational diversity, and binding mechanisms; and the associated binding funnels, illustrating the multiple routes and the range of complexed conformers. Specifically, the walls of the folding funnels, their crevices, and bumps are related to the complexity of protein folding, and hence to sequential vs. nonsequential folding. Whereas the former is more frequently observed in eukaryotic proteins, where the rate of protein synthesis is slower, the latter is more frequent in prokaryotes, with faster translation rates. The bottoms of the funnels reflect the extent of the flexibility of the proteins. Rugged floors imply a range of conformational isomers, which may be close on the energy landscape. Rather than undergoing an induced fit binding mechanism, the conformational ensembles around the rugged bottoms argue that the conformers, which are most complementary to the ligand, will bind to it with the equilibrium shifting in their favor. Furthermore, depending on the extent of the ruggedness, or of the smoothness with only a few minima, we may infer nonspecific, broad range vs. specific binding. In particular, folding and binding are similar processes, with similar underlying principles. Hence, the shape of the folding funnel of the monomer enables making reasonable guesses regarding the shape of the corresponding binding funnel. Proteins having a broad range of binding, such as proteolytic enzymes or relatively nonspecific endonucleases, may be expected to have not only rugged floors in their folding funnels, but their binding funnels will also behave similarly, with a range of complexed conformations. Hence, knowledge of the shape of the folding funnels is biologically very useful. The converse also holds: If kinetic and thermodynamic data are available, hints regarding the role of the protein and its binding selectivity may be obtained. Thus, the utility of the concept of the funnel carries over to the origin of the protein and to its function.

Crystal structure of the human p58 killer cell inhibitory receptor (KIR2DL3) specific for HLA-Cw3-related MHC class I

BACKGROUND

T cells and natural killer (NK) cells perform complementary roles in the cellular immune system. T cells identify infected cells directly through recognition of antigenic peptides that are displayed at the target cell surface by the classical major histocompatibility complex (MHC) class I molecules. NK cells monitor the target cell surface for malfunction of this display system, lysing potentially infected cells that might otherwise evade recognition by the T cells. Human killer cell inhibitory receptors (KIRs) control this process by either inhibiting or activating the cytotoxic activity of NK cells via specific binding to MHC class I molecules on the target cell.

RESULTS

We report the crystal structure of the extracellular region of the human p58 KIR (KIR2DL3), which is specific for the human MHC class I molecule HLA-Cw3 and related alleles. The structure shows the predicted topology of two tandem immunoglobulin-like domains, but comparison with the previously reported structure of the related receptor KIR2DL1 reveals an unexpected change of 23 degrees in the relative orientation of these domains.

CONCLUSIONS

The altered orientation of the immunoglobulin-like domains maintains an unusually acute interdomain elbow angle, which therefore appears to be a distinctive feature of the KIRs. The putative MHC class I binding site is located on the outer surface of the elbow, spanning both domains. The unexpected observation that this binding site can be modulated by differences in the relative domain orientations has implications for the general mechanism of KIR-MHC class I complex formation.