Identification of structural-kinetic and structural-thermodynamic relationships for thrombin inhibitors

Computational Analysis of Heat Capacity Effects in Protein-Ligand Binding

Heat capacity effects in protein-ligand binding as measured by calorimetric experiments have recently attracted considerable attention, particularly in the field of enzyme inhibitor design. A significant negative heat capacity change upon ligand binding implies a marked temperature dependence of the binding enthalpy, which is of high relevance for attempts to optimize protein-ligand interactions. In this work, we address the question of how well such heat capacity changes can be predicted by computer simulations. We examine a series of human thrombin inhibitors that all bind with ΔCp values of about -0.4 kcal/mol/K and calculate heat capacity changes from plain molecular dynamics simulations of the bound and free states of the enzyme and ligand. The results show that accurate ΔCp estimates within a few tenths of a kcal/mol/K of the experimental values can be obtained with this approach. This allows us to address the structural and energetic origin of the negative heat capacity changes for the thrombin inhibitors, and it is found that conformational equilibria of the free ligands in solution make a major contribution to the observed effect.

Functional and binding studies of gallic acid showing platelet aggregation inhibitory effect as a thrombin inhibitor

Objective

This study was devoted to identifying natural thrombin inhibitors from traditional Chinese medicine (TCM) and evaluating its biological activity in vitro and binding characteristics.

Methods

A combination strategy containing molecular docking, thrombin inhibition assay, surface plasmon resonance (SPR) and molecular dynamics simulation were applied to verify the study result.

Results

Gallic acid was confirmed as a direct thrombin inhibitor with IC50 of 9.07 μmol/L and showed a significant inhibitory effect on thrombin induced platelet aggregation. SPR-based binding studies demonstrated that gallic acid interacted with thrombin with a KD value of 8.29 μmol/L. Molecular dynamics and binding free energy analysis revealed that thrombin-gallic acid system attained equilibrium rapidly with very low fluctuations, the calculated binding free energies was -14.61 kcal/mol. Ala230, Glu232, Ser235, Gly258 and Gly260 were the main amino acid residues responsible for thrombin inhibition by gallic acid, providing a mechanistic basis for further optimization.

Conclusion

This study proved that gallic acid is a direct thrombin inhibitor with platelet aggregation inhibitory effect, which could provide a basis for the follow-up research and development for novel thrombin inhibitors.

The role of temperature in the binding of the disordered epitope region of human thrombopoietin to antibody: A molecular dynamics simulations study

The N-terminal domain (163 residues) of Human thrombopoietin (hTPO) is highly conserved and responsible for the receptor-binding. The crystal structure of free hTPO is not yet available, but the crystal structure of its receptor-binding domain (hTPO₁₆₃) is available in complex with the TN1-Fab antibody. According to a thermodynamic study of hTPO₁₆₃ binding to TN1-Fab Ab, the ΔH value for binding becomes more negative with an increase in temperature from 283 K to 303 K. The objective of our study is to understand how the free hTPO₁₆₃ behaves dynamically and to study the effect of temperature on the association of hTPO₁₆₃ to TN1-Fab antibody through molecular dynamics simulations. We studied the Ag-Ab interactions at two different temperatures 298 K and 303 K. The discontinuous epitope region (residues 98-115) of free hTPO₁₆₃ displays a conformational switch and it gets stabilized upon binding to the Ab at 303 K. Based on our results, it may be surmised that the epitope region 98-115 is behaving like a disordered epitope. The disordered epitopes are known to be more efficient in binding with the antibody. We also find that, there is an increase in number of hydrogen-bonding interactions and hydrophobic contacts with an increase in the temperature from 298 K to 303 K. Thus, this observation explains a possible reason behind the more negative value of ΔH at the higher temperature 303 K as compared to 298 K.

Assessing the Role of Calmodulin's Linker Flexibility in Target Binding

Calmodulin (CaM) is a highly-expressed Ca2+ binding protein known to bind hundreds of protein targets. Its binding selectivity to many of these targets is partially attributed to the protein’s flexible alpha helical linker that connects its N- and C-domains. It is not well established how its linker mediates CaM’s binding to regulatory targets yet. Insights into this would be invaluable to understanding its regulation of diverse cellular signaling pathways. Therefore, we utilized Martini coarse-grained (CG) molecular dynamics simulations to probe CaM/target assembly for a model system: CaM binding to the calcineurin (CaN) regulatory domain. The simulations were conducted assuming a ‘wild-type’ calmodulin with normal flexibility of its linker, as well as a labile, highly-flexible linker variant to emulate structural changes that could be induced, for instance, by post-translational modifications. For the wild-type model, 98% of the 600 simulations across three ionic strengths adopted a bound complex within 2 μs of simulation time; of these, 1.7% sampled the fully-bound state observed in the experimentally-determined crystallographic structure. By calculating the mean-first-passage-time for these simulations, we estimated the association rate to be ka= 8.7 × 108 M−1 s−1, which is similar to the diffusion-limited, experimentally-determined rate of 2.2 × 108 M−1 s−1. Furthermore, our simulations recapitulated its well-known inverse relationship between the association rate and the solution ionic strength. In contrast, although over 97% of the labile linker simulations formed tightly-bound complexes, only 0.3% achieved the fully-bound configuration. This effect appears to stem from a difference in the ensembles of extended and collapsed states which are controlled by the linker flexibility. Therefore, our simulations suggest that variations in the CaM linker’s propensity for alpha helical secondary structure can modulate the kinetics of target binding.

A structure-kinetic relationship study using matched molecular pair analysis

The lifetime of a binary drug–target complex is increasingly acknowledged as an important parameter for drug efficacy and safety. With a better understanding of binding kinetics and better knowledge about kinetic parameter optimization, intentionally induced prolongation of the drug–target residence time through structural changes of the ligand could become feasible. In this study we assembled datasets from 21 publications and the K4DD (Kinetic for Drug Discovery) database to conduct large scale data analysis. This resulted in 3812 small molecules annotated to 78 different targets from five protein classes (GPCRs: 273, kinases: 3238, other enzymes: 240, HSPs: 160, ion channels: 45). Performing matched molecular pair (MMP) analysis to further investigate the structure–kinetic relationship (SKR) in this data collection allowed us to identify a fundamental contribution of a ligand's polarity to its association rate, and in selected cases, also to its dissociation rate. However, we furthermore observed that the destabilization of the transition state introduced by increased polarity is often accompanied by simultaneous destabilization of the ground state resulting in an unaffected or even worsened residence time. Supported by a set of case studies, we provide concepts on how to alter ligands in ways to trigger on-rates, off-rates, or both.

A large-scale study employing matched molecular pair (MMP) analysis to uncover the contribution of a compound's polarity to its association and dissociation rates.

Recent Progress towards Chemically-Specific Coarse-Grained Simulation Models with Consistent Dynamical Properties

Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes, bottom-up CG models are systematically constructed from a higher-resolution model to retain a high level of chemical specificity. The removal of degrees of freedom from the system modifies the relationship between the relative time scales of distinct dynamical processes through both a loss of friction and a “smoothing” of the free-energy landscape. While these effects typically result in faster dynamics, decreasing the computational expense of the model, they also obscure the connection to the true dynamics of the system. The lack of consistent dynamics is a serious limitation for CG models, which not only prevents quantitatively accurate predictions of dynamical observables but can also lead to qualitatively incorrect descriptions of the characteristic dynamical processes. With many methods available for optimizing the structural and thermodynamic properties of chemically-specific CG models, recent years have seen a stark increase in investigations addressing the accurate description of dynamical properties generated from CG simulations. In this review, we present an overview of these efforts, ranging from bottom-up parameterizations of generalized Langevin equations to refinements of the CG force field based on a Markov state modeling framework. We aim to make connections between seemingly disparate approaches, while laying out some of the major challenges as well as potential directions for future efforts.

Crystal structure correlations with the intrinsic thermodynamics of human carbonic anhydrase inhibitor binding

The structure-thermodynamics correlation analysis was performed for a series of fluorine- and chlorine-substituted benzenesulfonamide inhibitors binding to several human carbonic anhydrase (CA) isoforms. The total of 24 crystal structures of 16 inhibitors bound to isoforms CA I, CA II, CA XII, and CA XIII provided the structural information of selective recognition between a compound and CA isoform. The binding thermodynamics of all structures was determined by the analysis of binding-linked protonation events, yielding the intrinsic parameters, i.e., the enthalpy, entropy, and Gibbs energy of binding. Inhibitor binding was compared within structurally similar pairs that differ by para- or meta-substituents enabling to obtain the contributing energies of ligand fragments. The pairs were divided into two groups. First, similar binders—the pairs that keep the same orientation of the benzene ring exhibited classical hydrophobic effect, a less exothermic enthalpy and a more favorable entropy upon addition of the hydrophobic fragments. Second, dissimilar binders—the pairs of binders that demonstrated altered positions of the benzene rings exhibited the non-classical hydrophobic effect, a more favorable enthalpy and variable entropy contribution. A deeper understanding of the energies contributing to the protein-ligand recognition should lead toward the eventual goal of rational drug design where chemical structures of ligands could be designed based on the target protein structure.

Impact of assay temperature on antibody binding characteristics in living cells: A case study

Kinetic and thermodynamic studies of ligand-receptor interactions are essential for increasing the understanding of receptor activation mechanisms and drug behavior. The characterization of molecular interactions on living cells in real-time goes beyond most current binding assays, and provides valuable information about the dynamics and underlying mechanism of the molecules in a living system. The effect of temperature on interactions in cell-based assays is, however, rarely discussed. In the present study, the effect of temperature on binding of monoclonal antibodies, cetuximab and pertuzumab to specific receptors on living cancer cells was evaluated, and the affinity and kinetics of the interactions were estimated at selected key temperatures. Changes in the behavior of the interactions, particularly in the on- and off-rates were observed, leading to greatly extended time to reach the equilibrium at 21°C compared with at 37°C. However, the observed changes in kinetic characteristics were less than a factor of 10. It was concluded that it is possible to conduct real-time measurements with living cells at different temperatures, and demonstrated that influences of the ambient temperature on the interaction behavior are likely to be less than one order of magnitude.

Elucidating the Origin of Long Residence Time Binding for Inhibitors of the Metalloprotease Thermolysin

Kinetic parameters of protein-ligand interactions are progressively acknowledged as valuable information for rational drug discovery. However, a targeted optimization of binding kinetics is not easy to achieve, and further systematic studies are necessary to increase the understanding about molecular mechanisms involved. We determined association and dissociation rate constants for 17 inhibitors of the metalloprotease thermolysin by surface plasmon resonance spectroscopy and correlated kinetic data with high-resolution crystal structures in complex with the protein. From the structure-kinetics relationship, we conclude that the strength of interaction with Asn112 correlates with the rate-limiting step of dissociation. This residue is located at the beginning of a β-strand motif that lines the binding cleft and is commonly believed to align a substrate for catalysis. A reduced mobility of the Asn112 side chain owing to an enhanced engagement in charge-assisted hydrogen bonds prevents the conformational adjustment associated with ligand release and transformation of the enzyme to its open state. This hypothesis is supported by kinetic data of ZF^PLA, a known pseudopeptidic inhibitor of thermolysin, which blocks the conformational transition of Asn112. Interference with this retrograde induced-fit mechanism results in variation of the residence time of thermolysin inhibitors by a factor of 74 000. The high conservation of this structural motif within the M4 and M13 metalloprotease families underpins the importance of this feature and has significant implications for drug discovery.

Protease Inhibitors in View of Peptide Substrate Databases

Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROCS that applies the information about the specificity of the proteases to find new small-molecule inhibitors. Peptide substrate sequences for three to four substrate positions of each substrate from the MEROPS database were used to build the training set. Two-dimensional substrate sequences were converted to three-dimensional conformations through mutation of a template peptide substrate. The vROCS query was built from single amino acid queries for each substrate position considering the relative frequencies of the amino acids. The peptide-substrate-based shape-based virtual screening approach gives good performance for the four proteases thrombin, factor Xa, factor VIIa, and caspase-3 with the DUD-E data set. The results show that the method works for protease targets with different specificity profiles as well as for targets with different active-site mechanisms. As no structure of the target and no information on small-molecule inhibitors are required to use our approach, the method has significant advantages in comparison with conventional structure- and ligand-based methods.

Towards understanding the unbound state of drug compounds: Implications for the intramolecular reorganization energy upon binding

There has been an explosion of structural information for pharmaceutical compounds bound to biological targets, but the conformations and dynamics of compounds free in solution are poorly characterized, if at all. Yet, knowledge of the unbound state is essential to understand the fundamentals of molecular recognition, including the much debated conformational intramolecular reorganization energy of a compound upon binding (ΔEReorg). Also, dependable observation of the unbound compounds is important for ligand-based drug discovery, e.g. with pharmacophore modelling. Here, these questions are addressed with long (⩾0.5μs) state-of-the-art molecular dynamics (MD) simulations of 26 compounds (including 7 approved drugs) unbound in explicit solvent. These compounds were selected to be chemically diverse, with a range of flexibility, and good quality bioactive X-ray structures. The MD-simulated free compounds are compared to their bioactive structure and conformers generated with ad hoc sampling in vacuo or with implicit generalized Born (GB) aqueous solvation models. The GB conformational models clearly depart from those obtained in explicit solvent, and suffer from conformational collapse almost as severe as in vacuo. Thus, the global energy minima in vacuo or with GB are not suitable representations of the unbound state, which can instead be extensively sampled by MD simulations. Many, but not all, MD-simulated compounds displayed some structural similarity to their bioactive structure, supporting the notion of conformational pre-organization for binding. The ligand-protein complexes were also simulated in explicit solvent, to estimate ΔEReorg as an enthalpic difference ΔHReorg between the intramolecular energies in the bound and unbound states. This fresh approach yielded ΔHReorg values⩽6kcal/mol for 18 out of 26 compounds. For three particularly polar compounds 15⩽ΔHReorg⩽20kcal/mol, supporting the notion that ΔHReorg can be substantial. Those large ΔHReorg values correspond to a redistribution of electrostatic interactions upon binding. Overall, the study illustrates how MD simulations offer a promising avenue to characterize the unbound state of medicinal compounds.

Direct thrombin inhibitors, but not the direct factor Xa inhibitor rivaroxaban, increase tissue factor-induced hypercoagulability in vitro and in vivo

BACKGROUND

Increased hypercoagulability has been reported with low doses of direct thrombin inhibitors but not with direct factor Xa inhibitors.

OBJECTIVES

To compare the effects of rivaroxaban with those of melagatran and dabigatran on thrombin generation (TG) and tissue factor-induced hypercoagulability and to explore the possible involvement of the thrombin-thrombomodulin/activated protein C system.

METHODS

In normal human plasma and in protein C-deficient plasma, TG was investigated in vitro in the presence and absence of recombinant human soluble thrombomodulin (rhs-TM). TG was determined by calibrated automated thrombography and an ELISA for prothrombin fragments 1+2 (F1+2 ). In an in vivo rat model, hypercoagulability was induced by tissue factor; levels of thrombin-antithrombin (TAT) and fibrinogen and the platelet count were determined.

RESULTS

Rivaroxaban inhibited TG in a concentration-dependent manner. In the absence of rhs-TM, melagatran and dabigatran also inhibited TG concentration dependently. However, in the presence of rhs-TM, lower concentrations of melagatran (119-474 nmol L(-1) ) and dabigatran (68-545 nmol L(-1) ) enhanced endogenous thrombin potential, peak TG, and F1+2 formation in normal plasma but not in protein C-deficient plasma. In vivo, rivaroxaban dose-dependently inhibited TAT generation, whereas melagatran showed a paradoxical effect, with an increase in TAT and a small decrease in fibrinogen and platelet count at lower doses.

CONCLUSION

Low concentrations of the direct thrombin inhibitors melagatran and dabigatran enhanced TG and hypercoagulability, possibly via inhibition of the protein C system. In contrast, rivaroxaban reduced TG and hypercoagulability under all conditions studied, suggesting that it does not suppress this negative-feedback system.