Preparation, characterization, and the crystal structure of the inhibitor ZK-807834 (CI-1031) complexed with factor Xa

Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART)

Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflows make use of only water-soluble fragments, as hydrophobic fragments would cause lipophilic aggregation. To date the two approaches that allow usage of hydrophobic cosolvent molecules are to use a low (0.2 M) concentration of hydrophobic probes, with the disadvantage of a lower sampling speed, or to use force field modifications, with the disadvantage of a difficult and inflexible setup procedure. Here we present a third alternative, that does not suffer from low sampling speed nor from cumbersome preparation procedures. We have built an easy-to-use open source command line tool PART (Plumed Automatic Restraining Tool) to generate a PLUMED file handling all intermolecular restraints to prevent lipophilic aggregation. We have compared restrained and unrestrained cosolvent MD simulations, showing that restraints are necessary to prevent lipophilic aggregation at hydrophobic probe concentrations of 0.5 M. Furthermore, we benchmarked PART generated restraints on a test set of four proteins (Factor-Xa, HIV protease, P38 MAP kinase and RNase A), showing that cosolvent MD with PART generated restraints qualitatively reproduces binding features of cocrystallised ligands.

Impact of electronic polarizability on protein-functional group interactions

Interactions of proteins with functional groups are key to their biological functions, making it essential that they be accurately modeled. To investigate the impact of the inclusion of explicit treatment of electronic polarizability in force fields on protein-functional group interactions, the additive CHARMM and Drude polarizable force field are compared in the context of the Site-Identification by Ligand Competitive Saturation (SILCS) simulation methodology from which functional group interaction patterns with five proteins for which experimental binding affinities of multiple ligands are available, were obtained. The explicit treatment of polarizability produces significant differences in the functional group interactions in the ligand binding sites including overall enhanced binding of functional groups to the proteins. This is associated with variations of the dipole moments of solutes representative of functional groups in the binding sites relative to aqueous solution with higher dipole moments systematically occurring in the latter, though exceptions occur with positively charged methylammonium. Such variation indicates the complex, heterogeneous nature of the electronic environments of ligand binding sites and emphasizes the inherent limitation of fixed charged, additive force fields for modeling ligand-protein interactions. These effects yield more defined orientation of the functional groups in the binding pockets and a small, but systematic improvement in the ability of the SILCS method to predict the binding orientation and relative affinities of ligands to their target proteins. Overall, these results indicate that the physical model associated with the explicit treatment of polarizability along with the presence of lone pairs in a force field leads to changes in the nature of the interactions of functional groups with proteins versus that occurring with additive force fields, suggesting the utility of polarizable force fields in obtaining a more realistic understanding of protein-ligand interactions.

Effective Estimation of Ligand-Binding Affinity Using Biased Sampling Method

The binding between two biomolecules is one of the most critical factors controlling many bioprocesses. Therefore, it is of great interest to derive a reliable method to calculate the free binding energy between two biomolecules. In this work, we have demonstrated that the binding affinity of ligands to proteins can be determined through biased sampling simulations. The umbrella sampling (US) method was applied on 20 protein-ligand complexes, including the cathepsin K (CTSK), type II dehydroquinase (DHQase), heat shock protein 90 (HSP90), and factor Xa (FXa) systems. The ligand-binding affinity was evaluated as the difference between the largest and smallest values of the free-energy curve, which was obtained via a potential of mean force analysis. The calculated affinities differ sizably from the previously reported experimental values, with an average difference of ∼3.14 kcal/mol. However, the calculated results are in good correlation with the experimental data, with correlation coefficients of 0.76, 0.87, 0.96, and 0.97 for CTSK, DHQase, HSP90, and FXa, respectively. Thus, the binding free energy of a new ligand can be reliably estimated using our US approach. Furthermore, the root-mean-square errors (RMSEs) of binding affinity of these systems are 1.13, 0.90, 0.37, and 0.25 kcal/mol, for CTSK, DHQase, HSP90, and FXa, respectively. The small RMSE values indicate the good precision of the biased sampling method that can distinguish the ligands exhibiting similar binding affinities.

3D proteochemometrics: using three-dimensional information of proteins and ligands to address aspects of the selectivity of serine proteases

The high similarity between certain sub-pockets of serine proteases may lead to low selectivity of protease inhibitors. Therefore the application of proteochemometrics (PCM), which quantifies the relationship between protein/ligand descriptors and affinity for multiple ligands and targets simultaneously, is useful to understand and improve the selectivity profiles of potential inhibitors. In this study, protein field-based PCM that uses knowledge-based and WaterMap derived fields to describe proteins in combination with 2D (RDKit and MOE fingerprints) and 3D (4 point pharmacophoric fingerprints and GRIND) ligand descriptors was used to model the bioactivities of 24 homologous serine proteases and 5863 inhibitors in an integrated fashion. Of the multiple field-based PCM models generated based on different ligand descriptors, RDKit fingerprints showed the best performance in terms of external prediction with Rtest2 of 0.72 and RMSEP of 0.81. Further, visual interpretation of the models highlights sub-pocket specific regions that influence affinity and selectivity of serine protease inhibitors.

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.

Enthalpic Breakdown of Water Structure on Protein Active-Site Surfaces

The principles underlying water reorganization around simple nonpolar solutes are well understood and provide the framework for the classical hydrophobic effect, whereby water molecules structure themselves around solutes so that they maintain favorable energetic contacts with both the solute and the other water molecules. However, for certain solute surface topographies, water molecules, due to their geometry and size, are unable to simultaneously maintain favorable energetic contacts with both the surface and neighboring water molecules. In this study, we analyze the solvation of ligand-binding sites for six structurally diverse proteins using hydration site analysis and measures of local water structure, in order to identify surfaces at which water molecules are unable to structure themselves in a way that maintains favorable enthalpy relative to bulk water. These surfaces are characterized by a high degree of enclosure, weak solute-water interactions, and surface constraints that induce unfavorable pair interactions between neighboring water molecules. Additionally, we find that the solvation of charged side chains in an active site generally results in favorable enthalpy but can also lead to pair interactions between neighboring water molecules that are significantly unfavorable relative to bulk water. We find that frustrated local structure can occur not only in apolar and weakly polar pockets, where overall enthalpy tends to be unfavorable, but also in charged pockets, where overall water enthalpy tends to be favorable. The characterization of local water structure in these terms may prove useful for evaluating the displacement of water from diverse protein active-site environments.

Theoretical Study of Molecular Structure and Physicochemical Properties of Novel Factor Xa Inhibitors and Dual Factor Xa and Factor IIa Inhibitors

The geometries and energies of factor Xa inhibitors edoxaban, eribaxaban, fidexaban, darexaban, letaxaban, and the dual factor Xa and thrombin inhibitors tanogitran and SAR107375 in both the gas-phase and aqueous solution were studied using the Becke3LYP/6-31++G(d,p) or Grimme’s B97D/6-31++G(d,p) method. The fully optimized conformers of these anticoagulants show a characteristic l-shape structure, and the water had a remarkable effect on the equilibrium geometry. According to the calculated pKa values eribaxaban and letaxaban are in neutral undissociated form at pH 7.4, while fidexaban and tanogitran exist as zwitterionic structures. The lipophilicity of the inhibitors studied lies within a large range of log P between 1 and 4. The dual inhibitor SAR107375 represents an improvement in structural, physicochemical and pharmacokinetic characteristics over tanogitran. At blood pH, SAR107375 predominantly exists in neutral form. In contrast with tanogitran, it is better absorbed and more lipophilic and active after oral application.

Spatial Decomposition of Translational Water-Water Correlation Entropy in Binding Pockets

A number of computational tools available today compute the thermodynamic properties of water at surfaces and in binding pockets by using inhomogeneous solvation theory (IST) to analyze explicit-solvent simulations. Such methods enable qualitative spatial mappings of both energy and entropy around a solute of interest and can also be applied quantitatively. However, the entropy estimates of existing methods have, to date, been almost entirely limited to the first-order terms in the IST’s entropy expansion. These first-order terms account for localization and orientation of water molecules in the field of the solute but not for the modification of water–water correlations by the solute. Here, we present an extension of the Grid Inhomogeneous Solvation Theory (GIST) approach which accounts for water–water translational correlations. The method involves rewriting the two-point density of water in terms of a conditional density and utilizes the efficient nearest-neighbor entropy estimation approach. Spatial maps of this second order term, for water in and around the synthetic host cucurbit[7]uril and in the binding pocket of the enzyme Factor Xa, reveal mainly negative contributions, indicating solute-induced water–water correlations relative to bulk water; particularly strong signals are obtained for sites at the entrances of cavities or pockets. This second-order term thus enters with the same, negative, sign as the first order translational and orientational terms. Numerical and convergence properties of the methodology are examined.

Spatial analysis and quantification of the thermodynamic driving forces in protein-ligand binding: binding site variability

The thermodynamic driving forces behind small molecule-protein binding are still not well-understood, including the variability of those forces associated with different types of ligands in different binding pockets. To better understand these phenomena we calculate spatially resolved thermodynamic contributions of the different molecular degrees of freedom for the binding of propane and methanol to multiple pockets on the proteins Factor Xa and p38 MAP kinase. Binding thermodynamics are computed using a statistical thermodynamics based end-point method applied on a canonical ensemble comprising the protein-ligand complexes and the corresponding free states in an explicit solvent environment. Energetic and entropic contributions of water and ligand degrees of freedom computed from the configurational ensemble provide an unprecedented level of detail into the mechanisms of binding. Direct protein-ligand interaction energies play a significant role in both nonpolar and polar binding, which is comparable to water reorganization energy. Loss of interactions with water upon binding strongly compensates these contributions leading to relatively small binding enthalpies. For both solutes, the entropy of water reorganization is found to favor binding in agreement with the classical view of the "hydrophobic effect". Depending on the specifics of the binding pocket, both energy-entropy compensation and reinforcement mechanisms are observed. It is notable to have the ability to visualize the spatial distribution of the thermodynamic contributions to binding at atomic resolution showing significant differences in the thermodynamic contributions of water to the binding of propane versus methanol.

Pharmacophore modeling using site-identification by ligand competitive saturation (SILCS) with multiple probe molecules

Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues, as SILCS naturally takes both protein flexibility and desolvation effects into account by using full molecular dynamics simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results, as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, reranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design.

Evaluation of water displacement energetics in protein binding sites with grid cell theory

The grid cell theory method was used to elucidate perturbations in water network energetics in a range of protein–ligand complexes.

Thermodynamics of Water in an Enzyme Active Site: Grid-Based Hydration Analysis of Coagulation Factor Xa

Water molecules in the active site of an enzyme occupy a complex, heterogeneous environment, and the thermodynamic properties of active-site water are functions of position. As a consequence, it is thought that an enzyme inhibitor can gain affinity by extending into a region occupied by unfavorable water or lose affinity by displacing water from a region where it was relatively stable. Recent advances in the characterization of binding-site water, based on the analysis of molecular simulations with explicit water molecules, have focused largely on simplified representations of water as occupying well-defined hydration sites. Our grid-based treatment of hydration, GIST, offers a more complete picture of the complex distributions of water properties, but it has not yet been applied to proteins. This first application of GIST to protein-ligand modeling, for the case of Coagulation Factor Xa, shows that ligand scoring functions based on GIST perform at least as well as scoring functions based on a hydration-site approach (HSA), when applied to exactly the same simulation data. Interestingly, the displacement of energetically unfavorable water emerges as the dominant factor in the fitted scoring functions, for both GIST and HSA methods, while water entropy plays a secondary role, at least in the present context.

The Influence of Bioisosteres in Drug Design: Tactical Applications to Address Developability Problems

The application of bioisosteres in drug discovery is a well-established design concept that has demonstrated utility as an approach to solving a range of problems that affect candidate optimization, progression, and durability. In this chapter, the application of isosteric substitution is explored in a fashion that focuses on the development of practical solutions to problems that are encountered in typical optimization campaigns. The role of bioisosteres to affect intrinsic potency and selectivity, influence conformation, solve problems associated with drug developability, including P-glycoprotein recognition, modulating basicity, solubility, and lipophilicity, and to address issues associated with metabolism and toxicity is used as the underlying theme to capture a spectrum of creative applications of structural emulation in the design of drug candidates.

Automating crystallographic structure solution and refinement of protein-ligand complexes

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation.

Inclusion of multiple fragment types in the site identification by ligand competitive saturation (SILCS) approach

The site identification by ligand competitive saturation (SILCS) method identifies the location and approximate affinities of small molecular fragments on a target macromolecular surface by performing molecular dynamics (MD) simulations of the target in an aqueous solution of small molecules representative of different chemical functional groups. In this study, we introduce a set of small molecules to map potential interactions made by neutral hydrogen bond donors and acceptors and charged donor and acceptor fragments in addition to nonpolar fragments. The affinity pattern is obtained in the form of discretized probability or, equivalently, free energy maps, called FragMaps, which can be visualized with the target surface. We performed SILCS simulations for four proteins for which structural and thermodynamic data is available for multiple diverse ligands. Good overlap is shown between high affinity regions identified by the FragMaps and the crystallographic positions of ligand functional groups with similar chemical functionality, thus demonstrating the validity of the qualitative information obtained from the simulations. To test the ability of FragMaps in providing quantitative predictions, we calculate the previously introduced ligand grid free energy (LGFE) metric and observe its correspondence with experimentally measured binding affinity. LGFE is computed for different conformational ensembles and improvement in prediction is shown with increasing ligand conformational sampling. Ensemble generation includes a Monte Carlo sampling approach that uses the GFE FragMaps directly as the energy function. The results show that some but not all experimental trends are predicted and warrant improvements in the scoring methodology. In addition, the potential utility of atom-based free energy contributions to the LGFE scores and the use of multiple ligands in SILCS to identify displaceable water molecules during ligand design are discussed.

Intimate interactions with carbonyl groups: dipole-dipole or n→π*?

Amide carbonyl groups in proteins can engage in C═O···C═O and C-X···C═O interactions, where X is a halogen. The putative involvement of four poles suggests that these interactions are primarily dipolar. Our survey of crystal structures with a C-X···C═O contact that is short (i.e., within the sum of the X and C van der Waals radii) revealed no preferred C-X···C═O dihedral angle. Moreover, we found that structures with a short X(-)···C═O contact display the signatures of an n→π* interaction. We conclude that intimate interactions with carbonyl groups do not require a dipole.

Are homology models sufficiently good for free-energy simulations?

In this paper, I evaluate the usefulness of protein homology models in rigorous free-energy simulations to determine ligand affinities. Two templates were used to create models of the factor Xa protein and one template was used for dihydrofolate reductase from Plasmodium falciparum. Then, the relative free energies for several pairs of ligands were estimated using thermodynamic integration with the homology models as starting point of the simulation. These binding affinities were compared to affinities obtained when using published crystal structures as starting point of the simulations. Encouragingly, the differences between the affinities obtained when starting from either homology models or crystal structure were not statistical significant for a majority of the considered pairs of ligands. Differences between 1 and 2 kJ/mol were observed for the dihydrofolate reductase ligands and differences between 0 and 8 kJ/mol were observed for the factor Xa ligands. The largest difference for factor Xa was caused by an erroneous modeling of a loop region close to two of the ligands, and it was only observed when using one of the templates. Therefore, it is advisible to always use more than one template when creating homology models if they should be used in free-energy simulations.

Systematic placement of structural water molecules for improved scoring of protein-ligand interactions

Structural water molecules are found in many protein-ligand complexes. They are known to be vital in mediating hydrogen-bonding interactions and, in some cases, key for facilitating tight binding. It is thus very important to consider water molecules when attempting to model protein-ligand interactions for cognate ligand identification, virtual screening and drug design. While the rigid treatment of water molecules present in structures is feasible, the more relevant task of treating all possible positions and orientations of water molecules with each possible ligand pose is computationally daunting. Current methods in molecular docking provide partial treatment for such water molecules, with modest success. Here we describe a new method employing dead-end elimination to place water molecules within a binding site, bridging interactions between protein and ligand. Dead-end elimination permits a thorough, though still incomplete, treatment of water placement. The results show that this method is able to place water molecules correctly within known complexes and to create physically reasonable hydrogen bonds. The approach has also been incorporated within an inverse molecular design approach, to model a variety of compounds in the process of de novo ligand design. The inclusion of structural water molecules, combined with ranking based on the electrostatic contribution to binding affinity, improves a number of otherwise poor energetic predictions.

Profiling the structural determinants for the selectivity of representative factor-Xa and thrombin inhibitors using combined ligand-based and structure-based approaches

The current study deciphers the combined ligand- and structure-based computational insights to profile structural determinants for the selectivity of representative diverse classes of FXa-selective and thrombin-selective as well as dual FXa-thrombin high affinity inhibitors. The thrombin-exclusive insertion 60-loop (D-pocket) was observed to be one of the most notable recognition sites for the known thrombin-selective inhibitors. Based on the topological comparison of four common active-site pockets (S1-S4) of FXa and thrombin, the greater structural disparity was observed in the S4-pocket, which was more symmetrical (U-shaped) in FXa as compared to thrombin mainly due to the presence of L99 and I174 residues in latter in place of Y99 and F174 respectively in former protease. The S2 pocket forming partial roof at the entry of 12 Å deep S1-pocket, with two extended β-sheets running antiparallel to each other by undergoing U-turn (∼180̊), has two conserved glycine residues forming H-bonds with the bound ligand for governing ligand binding affinity. The docking, scoring, and binding pose comparison of the representative high-affinity and selective inhibitors into the active sites of FXa and thrombin revealed critical residues (S214, Y99, W60D) mediating selectivity through direct- and long-range electrostatic interactions. Interestingly, most of the thrombin-selective inhibitors attained S-shaped conformation in thrombin, while FXa-selective inhibitors attained L-shaped conformations in FXa. The role of residue at 99th position of FXa and thrombin toward governing protease selectivity was further substantiated using molecular dynamics simulations on the wild-type and mutated Y99L FXa bound to thrombin-selective inhibitor 2. Furthermore, predictive CoMFA (FXa q² = 0.814; thrombin q² = 0.667) and CoMSIA (FXa q² = 0.807; thrombin q² = 0.624) models were developed and validated (FXa r²(test) = 0.823; thrombin r(2)(test) = 0.816) to feature molecular determinants of ligand binding affinity using the docking-based conformational alignments (DBCA) of 141 (88(train)+53(test)) and 39 (27(train)+11(test)) nonamidine class of potent FXa (0.004 ≤ K(i) (nM) ≤ 4700) and thrombin (0.001 ≤ K(i) (nM) ≤ 940) inhibitors, respectively. Interestingly, the ligand-based insights well corroborated with the structure-based insights in terms of the role of steric, electrostatic, and hydrophobic parameters for governing the selectivity for the two proteases. The new computational insights presented in this study are expected to be valuable for understanding and designing potent and selective antithrombotic agents.

The role of factor XIa (FXIa) catalytic domain exosite residues in substrate catalysis and inhibition by the Kunitz protease inhibitor domain of protease nexin 2

To select residues in coagulation factor XIa (FXIa) potentially important for substrate and inhibitor interactions, we examined the crystal structure of the complex between the catalytic domain of FXIa and the Kunitz protease inhibitor (KPI) domain of a physiologically relevant FXIa inhibitor, protease nexin 2 (PN2). Six FXIa catalytic domain residues (Glu(98), Tyr(143), Ile(151), Arg(3704), Lys(192), and Tyr(5901)) were subjected to mutational analysis to investigate the molecular interactions between FXIa and the small synthetic substrate (S-2366), the macromolecular substrate (factor IX (FIX)) and inhibitor PN2KPI. Analysis of all six Ala mutants demonstrated normal K(m) values for S-2366 hydrolysis, indicating normal substrate binding compared with plasma FXIa; however, all except E98A and K192A had impaired values of k(cat) for S-2366 hydrolysis. All six Ala mutants displayed deficient k(cat) values for FIX hydrolysis, and all were inhibited by PN2KPI with normal values of K(i) except for K192A, and Y5901A, which displayed increased values of K(i). The integrity of the S1 binding site residue, Asp(189), utilizing p-aminobenzamidine, was intact for all FXIa mutants. Thus, whereas all six residues are essential for catalysis of the macromolecular substrate (FIX), only four (Tyr(143), Ile(151), Arg(3704), and Tyr(5901)) are important for S-2366 hydrolysis; Glu(98) and Lys(192) are essential for FIX but not S-2366 hydrolysis; and Lys(192) and Tyr(5901) are required for both inhibitor and macromolecular substrate interactions.

Contribution of explicit solvent effects to the binding affinity of small-molecule inhibitors in blood coagulation factor serine proteases

The prevention of blood coagulation is important in treating thromboembolic disorders, and several serine proteases involved in the coagulation cascade have been classified as pharmaceutically relevant. Whereas structure-based drug design has contributed to the development of some serine protease inhibitors, traditional computational methods have not been able to fully describe structure-activity relationships (SAR). Here, we study the SAR for a number of serine proteases by using a method that calculates the thermodynamic properties (enthalpy and entropy) of the water that solvates the active site. We show that the displacement of water from specific subpockets (such as S1-4 and the ester binding pocket) of the active site by the ligand can govern potency, especially for cases in which small chemical changes (i.e., a methyl group or halogen) result in a substantial increase in potency. Furthermore, we describe how relative binding free energies can be estimated by combining the water displacement energy with complementary terms from an implicit solvent molecular mechanics description binding.

Discovery of a tetrahydropyrimidin-2(1H)-one derivative (TAK-442) as a potent, selective, and orally active factor Xa inhibitor

Coagulation enzyme factor Xa (FXa) is a particularly promising target for the development of new anticoagulant agents. We previously reported the imidazo[1,5-c]imidazol-3-one derivative 1 as a potent and orally active FXa inhibitor. However, it was found that 1 predominantly undergoes hydrolysis upon incubation with human liver microsomes, and the human specific metabolic pathway made it difficult to predict the human pharmacokinetics. To address this issue, our synthetic efforts were focused on modification of the imidazo[1,5-c]imidazol-3-one moiety of the active metabolite 3a, derived from 1, which resulted in the discovery of the tetrahydropyrimidin-2(1H)-one derivative 5k as a highly potent and selective FXa inhibitor. Compound 5k showed no detectable amide bond cleavage in human liver microsomes, exhibited a good pharmacokinetic profile in monkeys, and had a potent antithrombotic efficacy in a rabbit model without prolongation of bleeding time. Compound 5k is currently under clinical development with the code name TAK-442.

Peptidase inhibitors in the MEROPS database

The MEROPS website (http://merops.sanger.ac.uk) includes information on peptidase inhibitors as well as on peptidases and their substrates. Displays have been put in place to link peptidases and inhibitors together. The classification of protein peptidase inhibitors is continually being revised, and currently inhibitors are grouped into 67 families based on comparisons of protein sequences. These families can be further grouped into 38 clans based on comparisons of tertiary structure. Small molecule inhibitors are important reagents for peptidase characterization and, with the increasing importance of peptidases as drug targets, they are also important to the pharmaceutical industry. Small molecule inhibitors are now included in MEROPS and over 160 summaries have been written.

An anticoagulant RNA aptamer that inhibits proteinase-cofactor interactions within prothrombinase

The interaction of factor Xa with factor Va on membranes to form prothrombinase profoundly increases the rate of the proteolytic conversion of prothrombin to thrombin. We present the characterization of an RNA aptamer (RNA(11F7t)) selected from a combinatorial library based on its ability to bind factor Xa. We show that RNA(11F7t) inhibits thrombin formation catalyzed by prothrombinase without obscuring the active site of Xa within the enzyme complex. Selective inhibition of protein substrate cleavage arises from the ability of the aptamer to bind to factor Xa and exclude interactions between the proteinase and cofactor within prothrombinase. Competition for enzyme complex assembly results from the binding of RNA(11F7t) to factor Xa with nanomolar affinity in a Ca(2+)-dependent interaction. RNA(11F7t) binds equivalently to the zymogen factor X as well as derivatives lacking gamma-carboxyglutamic acid residues. We suggest that the ability of RNA(11F7t) to compete for the Xa-Va interaction with surprisingly high affinity likely reflects a significant contribution from its ability to indirectly impact regions of Xa that participate in the proteinase-cofactor interaction. Thus, despite the complexity of the macromolecular interactions that underlie the assembly of prothrombinase, efficient inhibition of enzyme complex assembly and thrombin formation can be achieved by tight binding ligands that target factor Xa in a discrete manner.

Conformational variability of benzamidinium-based inhibitors

Determining the structure of a small molecule bound to a biological receptor (e.g., a protein implicated in a disease state) is a necessary step in structure-based drug design. The preferred conformation of a small molecule can change when bound to a protein, and a detailed knowledge of the preferred conformation(s) of a bound ligand can help in optimizing the affinity of a molecule for its receptor. However, the quality of a protein/ligand complex determined using X-ray crystallography is dependent on the size of the protein, the crystal quality, and the realized resolution. The energy restraints used in traditional X-ray refinement procedures typically use "reduced" (i.e., neglect of electrostatics and dispersion interactions) Engh and Huber force field models that, while quite suitable for modeling proteins, often are less suitable for small molecule structures due to a lack of validated parameters. Through the use of ab initio QM/MM-based X-ray refinement procedures, this shortcoming can be overcome especially in the active site or binding site of a small-molecule inhibitor. Herein, we demonstrate that ab initio QM/MM refinement of an inhibitor/protein complex provides insights into the binding of small molecules beyond what is available using more traditional refinement protocols. In particular, QM/MM refinement studies of benzamidinium derivatives show variable conformational preferences depending on the refinement protocol used and the nature of the active-site region.

Design, structure-activity relationships, X-ray crystal structure, and energetic contributions of a critical P1 pharmacophore: 3-chloroindole-7-yl-based factor Xa inhibitors

An indole-based P1 moiety was incorporated into a previously established factor Xa inhibitor series. The indole group was designed to hydrogen-bond with the carbonyl of Gly218, while its 3-methyl or 3-chloro substituent was intended to interact with Tyr228. These interactions were subsequently observed in the X-ray crystal structure of compound 18. SAR studies led to the identification of compound 20 as the most potent FXa inhibitor in this series (IC(50) = 2.4 nM, EC(2xPT) = 1.2 microM). An in-depth energetic analysis suggests that the increased binding energy of 3-chloroindole-versus 3-methylindole-containing compounds in this series is due primarily to (a) the more hydrophobic nature of chloro- versus methyl-containing compounds and (b) an increased interaction of 3-chloroindole versus 3-methylindole with Gly218 backbone. The stronger hydrophobicity of chloro- versus methyl-substituted aromatics may partly explain the general preference for chloro- versus methyl-substituted P1 groups in FXa, which extends beyond the current series.

Molecular dynamics simulations of Factor Xa: insight into conformational transition of its binding subsites

Protein flexibility and conformational diversity is well known to be a key characteristic of the function of many proteins. Human blood coagulation proteins have multiple substrates, and various protein-protein interactions are required for the smooth functioning of the coagulation cascade to maintain blood hemostasis. To address how a protein may cope with multiple interactions with its structurally diverse substrates and the accompanied structural changes that may drive these changes, we studied human Factor X. We employed 20 ns of molecular dynamics (MD) and steered molecular dynamics (SMD) simulations on two different conformational forms of Factor X, open and closed, and observed an interchangeable conformational transition from one to another. This work also demonstrates the roles of various aromatic residues involved in aromatic-aromatic interactions, which make this dynamic transition possible.

The role of autolysis loop in determining the specificity of coagulation proteases

We recently demonstrated that the substitution of the autolysis loop (residues 143 to 154 in the chymotrypsin numbering system) of activated protein C (APC) with the corresponding loop of factor Xa (fXa) renders the APC mutant (APC/fX143-154) susceptible to inhibition by antithrombin (AT) in the presence of pentasaccharide. Our recent results further indicated, that in addition to an improvement in the reactivity of APC/fX143-154 with AT, both the amidolytic and anti-factor Va activities of the mutant APC have also been significantly increased. Since the autolysis loop of APC is five residues longer than the autolysis loop of fXa, it could not be ascertained whether this loop in the mutant APC specifically interacts with the activated conformation of AT or if a shorter autolysis loop is responsible for a global improvement in the catalytic activity of the mutant protease. To answer this question, we prepared another APC mutant in which the autolysis loop of the protease was replaced with the corresponding loop of trypsin (APC/Tryp143-154). Unlike an approximately 500-fold improvement in the reactivity of APC/fX143-154 with AT in the presence of pentasaccharide, the reactivity of APC/Tryp143-154 with the serpin was improved approximately 10-fold. These results suggest that both the length and structure of residues of the autolysis loop are critical for the specificity of the coagulation protease interaction with AT. Further factor Va inactivation studies with the APC mutants revealed a similar role for the autolysis loop of APC in the interaction with its natural substrate.

Role of the active-site solvent in the thermodynamics of factor Xa ligand binding

Understanding the underlying physics of the binding of small-molecule ligands to protein active sites is a key objective of computational chemistry and biology. It is widely believed that displacement of water molecules from the active site by the ligand is a principal (if not the dominant) source of binding free energy. Although continuum theories of hydration are routinely used to describe the contributions of the solvent to the binding affinity of the complex, it is still an unsettled question as to whether or not these continuum solvation theories describe the underlying molecular physics with sufficient accuracy to reliably rank the binding affinities of a set of ligands for a given protein. Here we develop a novel, computationally efficient descriptor of the contribution of the solvent to the binding free energy of a small molecule and its associated receptor that captures the effects of the ligand displacing the solvent from the protein active site with atomic detail. This descriptor quantitatively predicts (R(2) = 0.81) the binding free energy differences between congeneric ligand pairs for the test system factor Xa, elucidates physical properties of the active-site solvent that appear to be missing in most continuum theories of hydration, and identifies several features of the hydration of the factor Xa active site relevant to the structure-activity relationship of its inhibitors.

Isolation, cloning and structural characterisation of boophilin, a multifunctional Kunitz-type proteinase inhibitor from the cattle tick

Inhibitors of coagulation factors from blood-feeding animals display a wide variety of structural motifs and inhibition mechanisms. We have isolated a novel inhibitor from the cattle tick Boophilus microplus, one of the most widespread parasites of farm animals. The inhibitor, which we have termed boophilin, has been cloned and overexpressed in Escherichia coli. Mature boophilin is composed of two canonical Kunitz-type domains, and inhibits not only the major procoagulant enzyme, thrombin, but in addition, and by contrast to all other previously characterised natural thrombin inhibitors, significantly interferes with the proteolytic activity of other serine proteinases such as trypsin and plasmin. The crystal structure of the bovine α-thrombin·boophilin complex, refined at 2.35 Å resolution reveals a non-canonical binding mode to the proteinase. The N-terminal region of the mature inhibitor, Q16-R17-N18, binds in a parallel manner across the active site of the proteinase, with the guanidinium group of R17 anchored in the S₁ pocket, while the C-terminal Kunitz domain is negatively charged and docks into the basic exosite I of thrombin. This binding mode resembles the previously characterised thrombin inhibitor, ornithodorin which, unlike boophilin, is composed of two distorted Kunitz modules. Unexpectedly, both boophilin domains adopt markedly different orientations when compared to those of ornithodorin, in its complex with thrombin. The N-terminal boophilin domain rotates 9° and is displaced by 6 Å, while the C-terminal domain rotates almost 6° accompanied by a 3 Å displacement. The reactive-site loop of the N-terminal Kunitz domain of boophilin with its P₁ residue, K31, is fully solvent exposed and could thus bind a second trypsin-like proteinase without sterical restraints. This finding explains the formation of a ternary thrombin·boophilin·trypsin complex, and suggests a mechanism for prothrombinase inhibition in vivo.

Thiophene-anthranilamides as highly potent and orally available factor Xa inhibitors

There remains a high unmet medical need for a safe oral therapy for thrombotic disorders. The serine protease factor Xa (fXa), with its central role in the coagulation cascade, is among the more promising targets for anticoagulant therapy and has been the subject of intensive drug discovery efforts. Investigation of a hit from high-throughput screening identified a series of thiophene-substituted anthranilamides as potent nonamidine fXa inhibitors. Lead optimization by incorporation of hydrophilic groups led to the discovery of compounds with picomolar inhibitory potency and micromolar in vitro anticoagulant activity. Based on their high potency, selectivity, oral pharmacokinetics, and efficacy in a rat venous stasis model of thrombosis, compounds ZK 814048 (10b), ZK 810388 (13a), and ZK 813039 (17m) were advanced into development.

Shapelets: Possibilities and limitations of shape-based virtual screening

Complementarity of molecular surfaces is crucial for molecular recognition. A method for representation of molecular shape is presented. We decompose the molecular surface into commensurate patches with defined shape by fitting hyperbolical paraboloids onto a triangulated isosurface of the Gaussian model of a molecule. As a result of this decomposition we obtain a 3D graph representation of the molecular shape, which can be used for complete and partial shape matching and isosteric group searching. To point out the possibilities and limitations of shape-only models, we challenged our method by three scenarios in a virtual screening contest: rigid body alignment, consensus shape filtering, and target-specific screening.