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.

Why Do Empirical Valence Bond Simulations Yield Accurate Arrhenius Plots?

Computer simulations of the temperature dependence of enzyme reactions using the empirical valence bond (EVB) method have proven to give very accurate results in terms of the thermodynamic activation parameters. Here, we analyze the reasons for why such simulations are able to correctly capture activation enthalpies and entropies and how sensitive these quantities are to parametrization of the reactive potential energy function. We examine first the solution reference reaction for the enzyme ketosteroid isomerase, which corresponds to the acetate catalyzed deprotonation of the steroid in water. The experimentally determined activation parameters for this reaction turn out to be remarkably well reproduced by the calculations. By modifying the EVB potential so that the activation and reaction free energies become significantly shifted, we show that the activation entropy is basically invariant to such changes and that ΔS⧧ is instead determined by the specific mixture of the underlying force fields in the transition state region. The coefficients of this mixture do not change appreciably when the EVB potential is modified within reasonable limits, and hence, the estimate of ΔS⧧ becomes very robust. This is further verified by examining a more complex concerted hydride and proton transfer reaction in the enzyme hydroxybutyrate dehydrogenase.

Accurate Computation of Thermodynamic Activation Parameters in the Chorismate Mutase Reaction from Empirical Valence Bond Simulations.

Chorismate mutase (CM) enzymes have long served as model systems for benchmarking new methods and tools in computational chemistry. Despite the enzymes' prominence in the literature, the extent of the roles that activation enthalpy and entropy play in catalyzing the conversion of chorismate to prephenate is still subject to debate. Knowledge of these parameters is a key piece in fully understanding the mechanism of chorismate mutases. Within this study, we utilize EVB/MD free energy perturbation calculations at a range of temperatures, allowing us to extract activation enthalpies and entropies from an Arrhenius plot of activation free energies of the reaction catalyzed by a monofunctional Bacillus subtilis CM and the promiscuous enzyme isochorismate pyruvate lyase of Pseudomonas aeruginosa. In comparison to the uncatalyzed reaction, our results show that both enzyme-catalyzed reactions exhibit a substantial reduction in activation enthalpy, while the effect on activation entropy is relatively minor, demonstrating that enzyme-catalyzed CM reactions are enthalpically driven. Furthermore, we observe that the monofunctional CM from B. subtilis more efficiently catalyzes this reaction than its promiscuous counterpart. This is supported by a structural analysis of the reaction pathway at the transition state, from which we identified key residues explaining the enthalpically driven nature of the reactions and also the difference in efficiencies between the two enzymes.

Efficient Empirical Valence Bond Simulations with GROMACS.

We describe a protocol to perform empirical valence bond (EVB) simulations using GROMACS software. EVB is a fast and reliable method that allows one to determine the reaction free-energy profiles in complex systems, such as enzymes, by employing classical force fields to represent a chemical reaction. Therefore, running EVB simulations is basically as fast as any classical molecular dynamics simulation, and the method uses standard free-energy calculations to map the free-energy change along a given reaction path. To exemplify and validate our EVB implementation, we replicated two cases of our earlier enzyme simulations. One of these addresses the decomposition of the activation free energy into its enthalpic and entropic components, and the other is focused on calculating the overall catalytic effect of the enzyme compared to the same reaction in water. These two examples give virtually identical results to those obtained with programs that were specifically designed for EVB simulations and show that the GROMACS implementation is robust and can be used for very large systems.

Computational design of the temperature optimum of an enzyme reaction.

Cold-adapted enzymes are characterized both by a higher catalytic activity at low temperatures and by having their temperature optimum down-shifted, compared to mesophilic orthologs. In several cases, the optimum does not coincide with the onset of protein melting but reflects some other type of inactivation. In the psychrophilic α-amylase from an Antarctic bacterium, the inactivation is thought to originate from a specific enzyme-substrate interaction that breaks around room temperature. Here, we report a computational redesign of this enzyme aimed at shifting its temperature optimum upward. A set of mutations designed to stabilize the enzyme-substrate interaction were predicted by computer simulations of the catalytic reaction at different temperatures. The predictions were verified by kinetic experiments and crystal structures of the redesigned α-amylase, showing that the temperature optimum is indeed markedly shifted upward and that the critical surface loop controlling the temperature dependence approaches the target conformation observed in a mesophilic ortholog.

Principles of Cold Adaptation of Fish Lactate Dehydrogenases Revealed by Computer Simulations of the Catalytic Reaction.

Cold-adapted enzymes from psychrophilic and psychrotolerant species are characterized by a higher catalytic activity at low temperature than their mesophilic orthologs and are also usually found to be more thermolabile. Computer simulations of the catalytic reactions have been shown to be a very powerful tool for analyzing the structural and energetic origins of these effects. Here, we examine the cold adaptation of lactate dehydrogenases from two Antarctic and sub-Antarctic fish species using this approach and compare our results with those obtained for the orthologous dogfish enzyme. Direct calculations of thermodynamic activation parameters show that the cold-adapted fish enzymes are characterized by a lower activation enthalpy and a more negative entropy term. This appears to be a universal feature of psychrophilic enzymes, and it is found to originate from a higher flexibility of certain parts of the protein surface. We also carry out free energy simulations that address the differences in thermal stability and substrate binding affinity between the two cold-adapted enzymes, which only differ by a single mutation. These calculations capture the effects previously seen in in vitro studies and provide straightforward explanations of these experimental results.

Calculation of Heat Capacity Changes in Enzyme Catalysis and Ligand Binding.

It has been suggested that heat capacity changes in enzyme catalysis may be the underlying reason for temperature optima that are not related to unfolding of the enzyme. If this were to be a common phenomenon, it would have major implications for our interpretation of enzyme kinetics. In most cases, the support for the possible existence of a nonzero (negative) activation heat capacity, however, only relies on fitting such a kinetic model to experimental data. It is therefore of fundamental interest to try to use computer simulations to address this issue. One way is simply to calculate the temperature dependence of the activation free energy and determine whether the relationship is linear or not. An alternative approach is to calculate the absolute heat capacities of the reactant and transition states from plain molecular dynamics simulations using either the temperature derivative or fluctuation formula for the enthalpy. Here, we examine these different approaches for a designer enzyme with a temperature optimum that is not caused by unfolding. Benchmark calculations for the heat capacity of liquid water are first carried out using different thermostats. It is shown that the derivative formula for the heat capacity is generally the most robust and insensitive to the thermostat used and its parameters. The enzyme calculations using this method give results in agreement with direct calculations of activation free energies and show no sign of a negative activation heat capacity. We also provide a simple scheme for the calculation of binding heat capacity changes, which is of clear interest in ligand design, and demonstrate it for substrate binding to the designer enzyme. Neither in that case do the simulations predict any negative heat capacity change.

Structure and Mechanism of a Cold-Adapted Bacterial Lipase.

The structural origin of enzyme cold-adaptation has been the subject of considerable research efforts in recent years. Comparative studies of orthologous mesophilic-psychrophilic enzyme pairs found in nature are an obvious strategy for solving this problem, but they often suffer from relatively low sequence identity of the enzyme pairs. Small bacterial lipases adapted to distinctly different temperatures appear to provide an excellent model system for these types of studies, as they may show a very high degree of sequence conservation. Here, we report the first crystal structures of lipase A from the psychrophilic bacterium Bacillus pumilus, which confirm the high structural similarity to the mesophilic Bacillus subtilis enzyme, as indicated by their 81% sequence identity. We further employ extensive QM/MM calculations to delineate the catalytic reaction path and its energetics. The computational prediction of a rate-limiting deacylation step of the enzymatic ester hydrolysis reaction is verified by stopped-flow experiments, and steady-state kinetics confirms the psychrophilic nature of the B. pumilus enzyme. These results provide a useful benchmark for examining the structural basis of cold-adaptation and should now make it possible to disentangle the effects of the 34 mutations between the two enzymes on catalytic properties and thermal stability.

The Activation Parameters of a Cold-Adapted Short Chain Dehydrogenase Are Insensitive to Enzyme Oligomerization.

The structural principles of enzyme cold adaptation are of fundamental interest both for understanding protein evolution and for biotechnological applications. It has become clear in recent years that structural flexibility plays a major role in tuning enzyme activity at low temperatures, which is reflected by characteristic changes in the thermodynamic activation parameters for psychrophilic enzymes, compared to those of mesophilic and thermophilic ones. Hence, increased flexibility of the enzyme surface has been shown to lead to a lower enthalpy and a more negative entropy of activation, which leads to higher activity in the cold. This immediately raises the question of how enzyme oligomerization affects the temperature dependence of catalysis. Here, we address this issue by computer simulations of the catalytic reaction of a cold-adapted bacterial short chain dehydrogenase in different oligomeric states. Reaction free energy profiles are calculated at different temperatures for the tetrameric, dimeric, and monomeric states of the enzyme, and activation parameters are obtained from the corresponding computational Arrhenius plots. The results show that the activation free energy, enthalpy, and entropy are remarkably insensitive to the oligomeric state, leading to the conclusion that assembly of the subunit interfaces does not compromise cold adaptation, even though the mobilities of interfacial residues are indeed affected.

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations.

Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.

Transition States for Psychrophilic and Mesophilic (R)-3-Hydroxybutyrate Dehydrogenase-Catalyzed Hydride Transfer at Sub-zero Temperatures.

(R)-3-Hydroxybutyrate dehydrogenase (HBDH) catalyzes the NADH-dependent reduction of 3-oxocarboxylates to (R)-3-hydroxycarboxylates. The active sites of a pair of cold- and warm-adapted HBDHs are identical except for a single residue, yet kinetics evaluated at -5, 0, and 5 °C show a much higher steady-state rate constant (kcat) for the cold-adapted than for the warm-adapted HBDH. Intriguingly, single-turnover rate constants (kSTO) are strikingly similar between the two orthologues. Psychrophilic HBDH primary deuterium kinetic isotope effects on kcat (Dkcat) and kSTO (DkSTO) decrease at lower temperatures, suggesting more efficient hydride transfer relative to other steps as the temperature decreases. However, mesophilic HBDH Dkcat and DkSTO are generally temperature-independent. The DkSTO data allowed calculation of intrinsic primary deuterium kinetic isotope effects. Intrinsic isotope effects of 4.2 and 3.9 for cold- and warm-adapted HBDH, respectively, at 5 °C, supported by quantum mechanics/molecular mechanics calculations, point to a late transition state for both orthologues. Conversely, intrinsic isotope effects of 5.7 and 3.1 for cold- and warm-adapted HBDH, respectively, at -5 °C indicate the transition state becomes nearly symmetric for the psychrophilic enzyme, but more asymmetric for the mesophilic enzyme. His-to-Asn and Asn-to-His mutations in the psychrophilic and mesophilic HBDH active sites, respectively, swap the single active-site position where these orthologues diverge. At 5 °C, the His-to-Asn mutation in psychrophilic HBDH decreases Dkcat to 3.1, suggesting a decrease in transition-state symmetry, while the His-to-Asn mutation in mesophilic HBDH increases Dkcat to 4.4, indicating an increase in transition-state symmetry. Hence, temperature adaptation and a single divergent active-site residue may influence transition-state geometry in HBDHs.

Structural Basis of Inhibition of Human Insulin-Regulated Aminopeptidase (IRAP) by Benzopyran-Based Inhibitors.

Inhibition of the insulin-regulated aminopeptidase (IRAP) improves memory and cognition in animal models. The enzyme has recently been crystallized and several series of inhibitors reported. We herein focused on one series of benzopyran-based inhibitors of IRAP known as the HFI series, with unresolved binding mode to IRAP, and developed a robust computational model to explain the structure-activity relationship (SAR) and potentially guide their further optimization. The binding model here proposed places the benzopyran ring in the catalytic binding site, coordinating the Zn2+ ion through the oxygen in position 3, in contrast to previous hypothesis. The whole series of HFI compounds was then systematically simulated, starting from this binding mode, using molecular dynamics and binding affinity estimated with the linear interaction energy (LIE) method. The agreement with experimental affinities supports the binding mode proposed, which was further challenged by rigorous free energy perturbation (FEP) calculations. Here, we found excellent correlation between experimental and calculated binding affinity differences, both between selected compound pairs and also for recently reported experimental data concerning the site directed mutagenesis of residue Phe544. The computationally derived structure-activity relationship of the HFI series and the understanding of the involvement of Phe544 in the binding of this scaffold provide valuable information for further lead optimization of novel IRAP inhibitors.

Free Energy Calculations for Protein-Ligand Binding Prediction.

Computational prediction of protein-ligand binding involves initial determination of the binding mode and subsequent evaluation of the strength of the protein-ligand interactions, which directly correlates with ligand binding affinities. As a consequence of increasing computer power, rigorous approaches to calculate protein-ligand binding affinities, such as free energy perturbation (FEP) methods, are becoming an essential part of the toolbox of computer-aided drug design. In this chapter, we provide a general overview of these methods and introduce the QFEP modules, which are open-source API workflows based on our molecular dynamics (MD) package Q. The module QligFEP allows estimation of relative binding affinities along ligand series, while QresFEP is a module to estimate binding affinity shifts caused by single-point mutations of the protein. We herein provide guidelines for the use of each of these modules based on data extracted from ligand-design projects. While these modules are stand-alone, the combined use of the two workflows in a drug-design project yields complementary perspectives of the ligand binding problem, providing two sides of the same coin. The selected case studies illustrate how to use QFEP to approach the two key questions associated with ligand binding prediction: identifying the most favorable binding mode from different alternatives and establishing structure-affinity relationships that allow the rational optimization of hit compounds.

Structure and mechanism of a phage-encoded SAM lyase revises catalytic function of enzyme family.

The first S-adenosyl methionine (SAM) degrading enzyme (SAMase) was discovered in bacteriophage T3, as a counter-defense against the bacterial restriction-modification system, and annotated as a SAM hydrolase forming 5'-methyl-thioadenosine (MTA) and L-homoserine. From environmental phages, we recently discovered three SAMases with barely detectable sequence similarity to T3 SAMase and without homology to proteins of known structure. Here, we present the very first phage SAMase structures, in complex with a substrate analogue and the product MTA. The structure shows a trimer of alpha-beta sandwiches similar to the GlnB-like superfamily, with active sites formed at the trimer interfaces. Quantum-mechanical calculations, thin-layer chromatography, and nuclear magnetic resonance spectroscopy demonstrate that this family of enzymes are not hydrolases but lyases forming MTA and L-homoserine lactone in a unimolecular reaction mechanism. Sequence analysis and in vitro and in vivo mutagenesis support that T3 SAMase belongs to the same structural family and utilizes the same reaction mechanism.

Bacteria can be infected by viruses known as bacteriophages. These viruses inject their genetic material into bacterial cells and use the bacteria's own machinery to build the proteins they need to survive and infect other cells. To protect themselves, bacteria produce a molecule called S-adenosyl methionine, or SAM for short, which deposits marks on the bacteria's DNA. These marks help the bacteria distinguish their own genetic material from the genetic material of foreign invaders: any DNA not bearing the mark from SAM will be immediately broken down by the bacterial cell. This system helps to block many types of bacteriophage infections, but not all. Some bacteriophages carry genes that code for enzymes called SAMases, which can break down SAM, switching off the bacteria's defenses. The most well-known SAMase was first discovered in the 1960s in a bacteriophage called T3. Chemical studies of this SAMase suggested that it works as a 'hydrolase', meaning that it uses water to break SAM apart. New SAMases have since been discovered in bacteriophages from environmental water samples, which, despite being able to degrade SAM, are genetically dissimilar to one another and the SAMase in T3. This brings into question whether these enzymes all use the same mechanism to break SAM down. To gain a better understanding of how these SAMases work, Guo, Söderholm, Kanchugal, Isaksen et al. solved the crystal structure of one of the newly discovered enzymes called Svi3-3. This revealed three copies of the Svi3-3 enzyme join together to form a unit that SAM binds to at the border between two of the enzymes. Computer simulations of this structure suggested that Svi3-3 holds SAM in a position where it cannot interact with water, and that once in the grip of the SAMase, SAM instead reacts with itself and splits into two. Experiments confirmed these predictions for Svi3-3 and the other tested SAMases. Furthermore, the SAMase from bacteriophage T3 was also found to degrade SAM using the same mechanism. This shows that this group of SAMases are not hydrolases as originally thought, but in fact 'lyases': enzymes that break molecules apart without using water. These findings form a starting point for further investigations into how SAM lyases help bacteriophages evade detection. SAM has various different functions in other living organisms, and these lyases could be used to modulate the levels of SAM in future studies investigating its role.

3,4-Dihydropyrimidin-2(1H)-ones as Antagonists of the Human A2B Adenosine Receptor: Optimization, Structure-Activity Relationship Studies, and Enantiospecific Recognition.

We present and thoroughly characterize a large collection of 3,4-dihydropyrimidin-2(1H)-ones as A2BAR antagonists, an emerging strategy in cancer (immuno) therapy. Most compounds selectively bind A2BAR, with a number of potent and selective antagonists further confirmed by functional cyclic adenosine monophosphate experiments. The series was analyzed with one of the most exhaustive free energy perturbation studies on a GPCR, obtaining an accurate model of the structure-activity relationship of this chemotype. The stereospecific binding modeled for this scaffold was confirmed by resolving the two most potent ligands [(±)-47, and (±)-38 Ki = 10.20 and 23.6 nM, respectively] into their two enantiomers, isolating the affinity on the corresponding (S)-eutomers (Ki = 6.30 and 11.10 nM, respectively). The assessment of the effect in representative cytochromes (CYP3A4 and CYP2D6) demonstrated insignificant inhibitory activity, while in vitro experiments in three prostate cancer cells demonstrated that this pair of compounds exhibits a pronounced antimetastatic effect.

Hidden Conformational States and Strange Temperature Optima in Enzyme Catalysis.

The existence of temperature optima in enzyme catalysis that occur before protein melting sets in can be described by different types of kinetic models. Such optima cause distinctly curved Arrhenius plots and have, for example, been observed in several cold-adapted enzymes from psychrophilic species. The two main explanations proposed for this behavior either invoke conformational equilibria with inactive substrate-bound states or postulate differences in heat capacity between the reactant and transition states. Herein, we analyze the implications of the different types of kinetic models in terms of apparent activation enthalpies, entropies, and heat capacities, using the catalytic reaction of a cold-adapted α-amylase as a prototypic example. We show that the behavior of these thermodynamic activation parameters is fundamentally different between equilibrium and heat capacity models, and in the α-amylase case, computer simulations have shown the former model to be correct. A few other enzyme-catalyzed reactions are also discussed in this context.

X-Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists.

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A2A adenosine receptor (AR). Eight A2A AR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A2A AR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A2A AR, an emerging target in immuno-oncology.

Computer simulations explain the anomalous temperature optimum in a cold-adapted enzyme.

Cold-adapted enzymes from psychrophilic species show the general characteristics of being more heat labile, and having a different balance between enthalpic and entropic contributions to free energy barrier of the catalyzed reaction compared to mesophilic orthologs. Among cold-adapted enzymes, there are also examples that show an enigmatic inactivation at higher temperatures before unfolding of the protein occurs. Here, we analyze these phenomena by extensive computer simulations of the catalytic reactions of psychrophilic and mesophilic α-amylases. The calculations yield temperature dependent reaction rates in good agreement with experiment, and also elicit the anomalous rate optimum for the cold-adapted enzyme, which occurs about 15 °C below the melting point. This result allows us to examine the structural basis of thermal inactivation, which turns out to be caused by breaking of a specific enzyme-substrate interaction. This type of behaviour is also likely to be relevant for other enzymes displaying such anomalous temperature optima.

Evolution of Angiotensin Peptides and Peptidomimetics as Angiotensin II Receptor Type 2 (AT2) Receptor Agonists.

Angiotensin II receptor type 1 and 2 (AT1R and AT2R) are two G-protein coupled receptors that mediate most biological functions of the octapeptide Angiotensin II (Ang II). AT2R is upregulated upon tissue damage and its activation by selective AT2R agonists has become a promising approach in the search for new classes of pharmaceutical agents. We herein analyzed the chemical evolution of AT2R agonists starting from octapeptides, through shorter peptides and peptidomimetics to the first drug-like AT2R-selective agonist, C21, which is in Phase II clinical trials and aimed for idiopathic pulmonary fibrosis. Based on the recent crystal structures of AT1R and AT2R in complex with sarile, we identified a common binding model for a series of 11 selected AT2R agonists, consisting of peptides and peptidomimetics of different length, affinity towards AT2R and selectivity versus AT1R. Subsequent molecular dynamics simulations and free energy perturbation (FEP) calculations of binding affinities allowed the identification of the bioactive conformation and common pharmacophoric points, responsible for the key interactions with the receptor, which are maintained by the drug-like agonists. The results of this study should be helpful and facilitate the search for improved and even more potent AT2R-selective drug-like agonists.

Author Correction: Inhibition of translation termination by small molecules targeting ribosomal release factors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.