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Signaling of the tissue factor-FVIIa complex regulates angiogenesis, tumor growth, and inflammation. TF-FVIIa triggers cell signaling events by cleavage of protease activated receptor (PAR2) at the Arg36-Ser37 scissile bond. The recognition of PAR2 by the FVIIa protease domain is poorly understood. We perform molecular modeling and dynamics simulations to derive the PAR2-FVIIa interactions. Docking of the PAR2 Arg36-Ser37 scissile bond to the S1 site and subsequent molecular dynamics leads to interactions of the PAR2 ectodomain with P and P' sites of the FVIIa catalytic cleft as well as to electrostatic interactions between a stably folded region of PAR2 and a cluster of basic residues remote from the catalytic cleft of FVIIa. To address the functional significance of this interaction for PAR2 cleavage, we employed two antibodies with epitopes previously mapped to this cluster of basic residues. Although these antibodies do not block the catalytic cleft, both antibodies completely abrogated PAR2 activation by TF-FVIIa. Our simulations indicate a conformation of the PAR2 ectodomain that limits the cleavage site to no more than 33 A from its membrane proximal residue. Since the active site of FVIIa in the TF-FVIIa complex is approximately 75 A above the membrane, cleavage of the folded conformation of PAR2 would require tilting of the TF-FVIIa complex toward the membrane, indicating that additional cellular factors may be required to properly align the scissile bond of PAR2 with TF-FVIIa., (2009 Wiley-Liss, Inc.)

Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations. Despite the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multiresolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a nonredundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work, we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed "blobbyness." Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation. The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness = -0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness = -0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking.

We present a method, termed AutoLigand, for the prediction of ligand-binding sites in proteins of known structure. The method searches the space surrounding the protein and finds the contiguous envelope with the specified volume of atoms, which has the largest possible interaction energy with the protein. It uses a full atomic representation, with atom types for carbon, hydrogen, oxygen, nitrogen and sulfur (and others, if desired), and is designed to minimize the need for artificial geometry. Testing on a set of 187 diverse protein-ligand complexes has shown that the method is successful in predicting the location and approximate volume of the binding site in 73% of cases. Additional testing was performed on a set of 96 protein-ligand complexes with crystallographic structures of apo and holo forms, and AutoLigand was able to predict the binding site in 80% of the apo structures., (2007 Wiley-Liss, Inc.)

Factor X is activated to factor Xa (fXa) in the extrinsic coagulation pathway by the tissue factor (TF)/factor VIIa (fVIIa) complex. Upon activation, the fXa molecule remains associated with the TF/fVIIa complex, and this ternary complex is known to activate protease-activated receptors (PARs) 1 and 2. Activation of fVII in the TF complex by fXa is also seen at physiologic concentrations. The ternary complexes TF/fVII/fXa, TF/fVIIa/fX, and TF/fVIIa/fXa are therefore all physiologically relevant and of interest as targets for inhibition of both coagulation and cell-signaling pathways that are important in cardiovascular disease and inflammation. We therefore present a model of the TF/fVIIa/fXa complex, built with the use of the available structures of the TF/fVIIa complex and fXa by protein-protein docking calculations with the program Surfdock. The fXa model has an extended conformation, similar to that of fVIIa in the TF/fVIIa complex, with extensive interactions with TF and the protease domain of fVIIa. All four domains of fXa are involved in the interaction. The gamma-carboxyglutamate (Gla) and epithelial growth factor (EGF1 and EGF2) domains of fVIIa are not significantly involved in the interaction. Docking of the Gla domain of fXa to TF/fVIIa has been reported previously. The docking results identify potential interface residues, allowing rational selection of target residues for site-directed mutagenesis. This combination of docking and mutagenesis confirms that residues Glu51 and Asn57 in the EGF1 domain, Asp92 and Asp95 in the EGF2 domain, and Asp 185a, Lys 186, and Lys134 in the protease domain of factor Xa are involved in the interaction with TF/fVIIa. Other fX protease domain residues predicted to be involved in the interaction come from the 160s loop and the N-terminus of the fX protease domain, which is oriented in such a way that activation of both fVII by fXa, and the reciprocal fX activation by fVIIa, is possible., (Copyright 2003 Wiley-Liss, Inc.)

The interaction of the alphaLbeta2 integrin with its cellular ligand the intercellular adhesion molecule-1 (ICAM-1) is critical for the tight binding interaction between most leukocytes and the vascular endothelium before transendothelial migration to the sites of inflammation. In this article we have modeled the alphaL subunit I-domain in its active form, which was computationally docked with the D1 domain of the ICAM-1 to probe potential protein-protein interactions. The experimentally observed key interaction between the carboxylate of Glu 34 in the ICAM-1 D1 domain and the metal ion-dependent adhesion site (MIDAS) in the open alphaL I-domain was consistently reproduced by our calculations. The calculations reveal the nature of the alphaLbeta2/ICAM-1 interaction and suggest an explanation for the increased ligand-binding affinity in the "open" versus the "closed" conformation of the alphaL I-domain. A mechanism for substrate selectivity among alphaL, alphaM, and alpha2 I-domains is suggested whereby the orientation of the loops within the I-domain is critical in mediating the interaction of the Glu 34 carboxylate of ICAM-1 D1 with the MIDAS., (Copyright 2002 Wiley-Liss, Inc.)

Drug-resistant strains are rapidly selected during AIDS therapy because of the high rate of mutation in HIV. In this report, we present an evolutionary simulation method for analysis of viral mutation and its use for optimization of HIV-1 protease drugs to improve their robustness in the face of resistance mutation. We first present an analysis of the range of resistant mutants that produce viable viruses by using a volume-based viral fitness model. Then, we analyze how this range of mutant proteases allows development of resistance to an optimal inhibitor previously designed by computational coevolution techniques. Finally, we evaluate the resistance patterns of commercially available drugs, and we discuss how resistance might be overcome by optimizing the size of specific side-chains of these inhibitors., (Copyright 2002 Wiley-Liss, Inc.)

Protein motion and heterogeneity of structural waters are approximated in ligand-docking simulations, using an ensemble of protein structures. Four methods of combining multiple target structures within a single grid-based lookup table of interaction energies are tested. The method is evaluated using complexes of 21 peptidomimetic inhibitors with human immunodeficiency virus type 1 (HIV-1) protease. Several of these structures show motion of an arginine residue, which is essential for binding of large inhibitors. A structural water is also present in 20 of the structures, but it must be absent in the remaining one for proper binding. Mean and minimum methods perform poorly, but two weighted average methods permit consistent and accurate ligand docking, using a single grid representation of the target protein structures., (Copyright 2001 Wiley-Liss, Inc.)

We compiled and analyzed a data set of paired protein structures containing proteins for which multiple high-quality uncomplexed atomic structures were available in the Protein Data Bank. Side-chain flexibility was quantified, yielding a set of residue- and environment-specific confidence levels describing the range of motion around chi1 and chi2 angles. As expected, buried residues were inflexible, adopting similar conformations in different crystal structure analyses. Ile, Thr, Asn, Asp, and the large aromatics also showed limited flexibility when exposed on the protein surface, whereas exposed Ser, Lys, Arg, Met, Gln, and Glu residues were very flexible. This information is different from and complementary to the information available from rotamer surveys. The confidence levels are useful for assessing the significance of observed side-chain motion and estimating the extent of side-chain motion in protein structure prediction. We compare the performance of a simple 40 degrees threshold with these quantitative confidence levels in a critical evaluation of side-chain prediction with the program SCWRL., (Copyright 2001 Wiley-Liss, Inc.)

Three forms of feline immunodeficiency virus protease (FIV PR), the wild type (wt) and two single point mutants, V59I and Q99V, as well as human immunodeficiency virus type 1 protease (HIV-1 PR), were cocrystallized with the C2-symmetric inhibitor, TL-3. The mutants of FIV PR were designed to replace residues involved in enzyme-ligand interactions by the corresponding HIV-1 PR residues at the structurally equivalent position. TL-3 shows decreased (improved) inhibition constants with these FIV PR mutants relative to wt FIV PR. Despite similar modes of binding of the inhibitor to all PRs (from P3 to P3'), small differences are evident in the conformation of the Phe side chains of TL-3 at the P1 and P1' positions in the complexes with the mutated FIV PRs. The differences mimick the observed binding of TL-3 in HIV-1 PR and correlate with a significant improvement in the inhibition constants of TL-3 with the two mutant FIV PRs. Large differences between the HIV-1 and FIV PR complexes are evident in the binding modes of the carboxybenzyl groups of TL-3 at P4 and P4'. In HIV-1 PR:TL-3, these groups bind over the flap region, whereas in the FIV PR complexes, the rings are located along the major axis of the active site. A significant difference in the location of the flaps in this region of the HIV-1 and FIV PRs correlates with the observed conformational changes in the binding mode of the peptidomimetic inhibitor at the P4 and P4' positions. These findings provide a structural explanation of the observed Ki values for TL-3 with the different PRs and will further assist in the development of improved inhibitors.

In order to understand the structural basis of Factor Xa (FXa) specificity, structural complexes of FXa with its synthetic inhibitors are determined using a computational docking approach. The AutoDock suite of programs is used to determine the binding modes of the synthetic inhibitors such as 3- and 4-amidinobenzylphenyl ether (ABP), amidinophenyl pyruvic acid (APPA), diamidinobenzofuranyl ethene (DABE), and DX-9065a 2-(5'-amidino-2'-benzofuranyl)-3-(7'amidino-2'-napthyl)-propionic acid (ABAP) to FXa. The synthetic inhibitors docked in the present study are different in size, nature of linkage, and properties. Two sets of simulations were carried out for synthetic inhibitors docking to FXa. In the first set of simulations, no explicit water molecules were included. In the second set of simulations two explicit solvent molecules were considered. In all the computationally predicted synthetic inhibitor complexes of FXa, the specificity pocket residue Asp-189 is involved in hydrogen bonding with the bound inhibitor. The active site water molecule WAT522 is involved in hydrogen bonding with all the bound inhibitors. The computed energies clearly discriminate the high affinity from low affinity binders.

We present an algorithm to build self-avoiding lattice models of chain molecules with low RMS deviation from their actual 3D structures. To find the optimal coordinates for the lattice chain model, we minimize a function that consists of three terms: (1) the sum of squared deviations of link coordinates on a lattice from their off-lattice values, (2) the sum of "short-range" terms, penalizing violation of chain connectivity, and (3) the sum of "long-range" repulsive terms, penalizing chain self-intersections. We treat this function as a chain molecule "energy" and minimize it using self-consistent field (SCF) theory to represent the pairwise link repulsions as 3D fields acting on the links. The statistical mechanics of chain molecules enables computation of the chain distribution in this field on the lattice. The field is refined by iteration to become self-consistent with the chain distribution, then dynamic programming is used to find the optimal lattice model as the "lowest-energy" chain pathway in this SCF. We have tested the method on one of the coarsest (and most difficult) lattices used for model building on proteins of all structural types and show that the method is adequate for building self-avoiding models of proteins with low RMS deviations from the actual structures.

Lattice models of proteins can approximate off-lattice structure to arbitrary precision with RMS (root mean squared) deviations roughly equal to half the lattice spacing (Rykunov et al., Proteins 22:100-109, 1995; Reva et al., J. Comp. Biol., 1996). However, even small distortions in the positions of chain links lead to significant errors in lattice-based energy calculations (Reva et al., J. Comp. Chem., 1996). These errors arise mainly from rigid interactions (such as steric repulsion) which change their energies considerably at a range which is much smaller than the usual accuracy of lattice modeling (> 1.0 A). To reduce this error, we suggest a procedure of adjusting energy functions to a given lattice. The general approach is illustrated with energy calculations based on pairwise potentials by Kolinski et al. (J. Chem. Phys. 98:1-14, 1993). At all the lattice spacings, from 0.5-3.8 A, the lattice-adjusted potentials improve the accuracy of lattice-based energy calculations and increase the correlations between off-lattice and lattice energies.

Automated docking of substrates to proteins of known structure aids the process of crystallographic analysis in two ways. First, automated docking can be used to generate a small number of starting models for substrates using only protein coordinates from an early stage of refinement. Second, automated docking provides a method for exploring aspects of catalysis that are inaccessible to crystallography by postulating binding modes of catalytic intermediates. This paper describes the use of automated docking to explore the binding of substrates to aconitase. The technique starts with a substrate molecule in an arbitrary configuration and position and finds favorable docked configurations in a (static) protein active site based on a molecular mechanics type force field. Using protein coordinates from an early stage of refinement of an aconitase-isocitrate complex, we successfully predicted the binding configuration of isocitrate. Four configurations were found, the energetically most favorable of which fit the observed electron density well and was used as a starting model for further refinement. Two configurations were found in citrate docking experiments, the second of which approximates the mode of substrate binding in an aconitase-nitrocitrate complex. We were also able to propose two binding modes of the catalytic intermediate cis-aconitate. These correspond closely to the isocitrate and the citrate binding modes. The relation of these new results to the proposed reaction mechanism is discussed.

The Metropolis technique of conformation searching is combined with rapid energy evaluation using molecular affinity potentials to give an efficient procedure for docking substrates to macromolecules of known structure. The procedure works well on a number of crystallographic test systems, functionally reproducing the observed binding modes of several substrates.