Are there dynamical effects in enzyme catalysis? Some thoughts concerning the enzymatic chemical step

A role for conformational changes in enzyme catalysis

The role played by conformational changes in enzyme catalysis is controversial. In addition to examining specific enzymes, studying formal models can help identify the conditions under which conformational changes promote catalysis. Here, we present a model demonstrating how conformational changes can break a generic trade-off due to the conflicting requirements of successive steps in catalytic cycles, namely high specificity for the transition state to accelerate the chemical transformation and low affinity for the products to favor their release. The mechanism by which the trade-off is broken is a transition between conformations with different affinities for the substrate. The role of the effector that induces the transition is played by a substrate "handle," a part of the substrate that is not chemically transformed but whose interaction with the enzyme is nevertheless essential to rapidly complete the catalytic cycle. A key element of the model is the formalization of the constraints causing the trade-off that the presence of multiple states breaks, which we attribute to the strong chemical similarity between successive reaction states-substrates, transition states, and products. For the sake of clarity, we present our model for irreversible one-step unimolecular reactions. In this context, we demonstrate how the different forms that chemical similarities between reaction states can take impose limits on the overall catalytic turnover. We first analyze catalysts without internal degrees of freedom and then show how two-state catalysts can overcome their limitations. Our results recapitulate previous proposals concerning the role of conformational changes and substrate handles in a formalism that makes explicit the constraints that elicit these features. In addition, our approach establishes links with studies in the field of heterogeneous catalysis, where the same trade-offs are observed and where overcoming them is a well-recognized challenge.

Learning QM/MM potential using equivariant multiscale model

The machine learning (ML) method emerges as an efficient and precise surrogate model for high-level electronic structure theory. Its application has been limited to closed chemical systems without considering external potentials from the surrounding environment. To address this limitation and incorporate the influence of external potentials, polarization effects, and long-range interactions between a chemical system and its environment, the first two terms of the Taylor expansion of an electrostatic operator have been used as extra input to the existing ML model to represent the electrostatic environments. However, high-order electrostatic interaction is often essential to account for external potentials from the environment. The existing models based only on invariant features cannot capture significant distribution patterns of the external potentials. Here, we propose a novel ML model that includes high-order terms of the Taylor expansion of an electrostatic operator and uses an equivariant model, which can generate a high-order tensor covariant with rotations as a base model. Therefore, we can use the multipole-expansion equation to derive a useful representation by accounting for polarization and intermolecular interaction. Moreover, to deal with long-range interactions, we follow the same strategy adopted to derive long-range interactions between a target system and its environment media. Our model achieves higher prediction accuracy and transferability among various environment media with these modifications.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Anisotropic dynamics of an interfacial enzyme active site observed using tethered substrate analogs and ultrafast 2D IR spectroscopy

Enzymes accelerate the rates of biomolecular reactions by many orders of magnitude compared to bulk solution, and it is widely understood that this catalytic effect arises from a combination of polar pre-organization and electrostatic transition state stabilization. A number of recent reports have also implicated ultrafast (femtosecond-picosecond) timescale motions in enzymatic activity. However, complications arising from spatially-distributed disorder, the occurrence of multiple substrate binding modes, and the influence of hydration dynamics on solvent-exposed active sites still confound many experimental studies. Here we use ultrafast two-dimensional infrared (2D IR) spectroscopy and covalently-tethered substrate analogs to examine dynamical properties of the promiscuous Pyrococcus horikoshii ene-reductase (PhENR) active site in two binding configurations mimicking proposed "inactive" and "reactive" Michaelis complexes. Spectral diffusion measurements of aryl-nitrile substrate analogs reveal an end-to-end tradeoff between fast (sub-ps) and slow (>5 ps) motions. Fermi resonant aryl-azide analogs that sense interactions of coupled oscillators are described. Lineshape and quantum beat analyses of these probes reveal characteristics that correlate with aryl-nitrile frequency fluctuation correlation functions parameters, demonstrating that this anisotropy is an intrinsic property of the water-exposed active site, where countervailing gradients of fast dynamics and disorder in the reactant ground state are maintained near the hydration interface. Our results suggest several plausible factors leading to state-selective rate enhancement and promiscuity in PhENR. This study also highlights a strategy to detect perturbations to vibrational modes outside the transparent window of the mid-IR spectrum, which may be extended to other macromolecular systems.

Free-Energy Landscape and Rate Estimation of the Aromatic Ring Flips in Basic Pancreatic Trypsin Inhibitors Using Metadynamics

Aromatic side chains (phenylalanine and tyrosine) of a protein flip by 180° around the Cβ-Cγ axis (χ2 dihedral of the side chain), producing two symmetry-equivalent states. The study of ring flip dynamics with nuclear magnetic resonance (NMR) experiments helps to understand local conformational fluctuations. Ring flips are categorized as slow (milliseconds and onward) or fast (nanoseconds to near milliseconds) based on timescales accessible to NMR experiments. In this study, we investigated the ability of the infrequent metadynamics approach to estimate the flip rate and discriminate between slow and fast ring flips for eight individual aromatic side chains (F4, Y10, Y21, F22, Y23, F33, Y35, and F45) of the basic pancreatic trypsin inhibitor. Well-tempered metadynamics simulations were performed to estimate the ring-flipping free-energy surfaces for all eight aromatic residues. The results indicate that χ2 as a standalone collective variable (CV) is not sufficient to obtain computationally consistent results. Inclusion of a complementary CV, such as χ1(Cα-Cβ), solved the problem for most residues and enabled us to classify fast and slow ring flips. This indicates the importance of librational motions in ring flips. Multiple pathways and mechanisms were observed for residues F4, Y10, and F22. Recrossing events were observed for residues F22 and F33, indicating a possible role of friction effects in ring flipping. The results demonstrate the successful application of infrequent metadynamics to estimate ring flip rates and identify certain limitations of the approach.

Electrostatics and Chemical Reactivity at the Air-Water Interface

It has been recently discovered that chemical reactions at aqueous interfaces can be orders of magnitude faster compared to conventional bulk phase reactions, but despite its wide-ranging implications, which extend from atmospheric to synthetic chemistry or technological applications, the phenomenon is still incompletely understood. The role of strong electric fields due to space asymmetry and the accumulation of ions at the interface has been claimed as a possible cause from some experiments, but the reorganization of the solvent around the reactive system should provide even greater additional electrostatic contributions that have not yet been analyzed. In this study, with the help of first-principles molecular dynamics simulations, we go deeper into this issue by a careful assessment of solvation electrostatics at the air-water interface. Our simulations confirm that electrostatic forces can indeed be a key factor in rate acceleration compared to bulk solution. Remarkably, the study reveals that the effect cannot simply be attributed to the magnitude of the local electric field and that the fluctuations of the full electrostatic potential resulting from unique dynamical behavior of the solvation shells at the interface must be accounted for. This finding paves the way for future applications of the phenomenon in organic synthesis, especially for charge transfer or redox reactions in thin films and microdroplets.

Hydride Transfer Mechanism of Enzymatic Sugar Nucleotide C2 Epimerization Probed with a Loose-Fit CDP-Glucose Substrate

Transient oxidation–reduction through hydride transfer with tightly bound NAD coenzyme is used by a large class of sugar nucleotide epimerases to promote configurational inversion of carbon stereocenters in carbohydrate substrates. A requirement for the epimerases to coordinate hydride abstraction and re-addition with substrate rotation in the binding pocket poses a challenge for dynamical protein conformational selection linked to enzyme catalysis. Here, we studied the thermophilic C2 epimerase from Thermodesulfatator atlanticus (TaCPa2E) in combination with a slow CDP-glucose substrate (k_cat ≈ 1.0 min^–1; 60 °C) to explore the sensitivity of the enzymatic hydride transfer toward environmental fluctuations affected by temperature (20–80 °C). We determined noncompetitive primary kinetic isotope effects (KIE) due to ²H at the glucose C2 and showed that a normal KIE on the k_cat (^Dk_cat) reflects isotope sensitivity of the hydrogen abstraction to enzyme-NAD⁺ in a rate-limiting transient oxidation. The ^Dk_cat peaked at 40 °C was 6.1 and decreased to 2.1 at low (20 °C) and 3.3 at high temperature (80 °C). The temperature profiles for k_cat with the ¹H and ²H substrate showed a decrease in the rate below a dynamically important breakpoint (∼40 °C), suggesting an equilibrium shift to an impaired conformational landscape relevant for catalysis in the low-temperature region. Full Marcus-like model fits of the rate and KIE profiles provided evidence for a high-temperature reaction via low-frequency conformational sampling associated with a broad distribution of hydride donor–acceptor distances (long-distance population centered at 3.31 ± 0.02 Å), only poorly suitable for quantum mechanical tunneling. Collectively, dynamical characteristics of TaCPa2E-catalyzed hydride transfer during transient oxidation of CDP-glucose reveal important analogies to mechanistically simpler enzymes such as alcohol dehydrogenase and dihydrofolate reductase. A loose-fit substrate (in TaCPa2E) resembles structural variants of these enzymes by extensive dynamical sampling to balance conformational flexibility and catalytic efficiency.

An electrostatic duel: subtle differences in the catalytic performance of monoamine oxidase A and B isoenzymes elucidated at the residue level using quantum computations

The origin of the immense catalytic power of enzymes remains one of the biggest unresolved questions in biochemistry, with electrostatics being one of the main contenders. Herein, we report results that not only confirm that electrostatics is the driving force behind enzyme catalysis, but also that it is capable of tuning subtle differences in the catalytic performance between structurally similar enzymes, as demonstrated using the example of isoenzymes, monoamine oxidases A and B. Using our own computationally efficient multiscale model [A. Prah, et al., ACS Catal., 2019, 9, 1231] we analyzed the rate-limiting step of the reaction between phenylethylamine and both isoenzymes and deduced that the electrostatic environment provided by isoenzyme B has a perceivably higher catalytic influence on all the considered parameters of the reaction (energy barrier, charge transfer, dipole moment, and HOMO-LUMO gap). This is in full agreement with the available experimental kinetic data and with our own simulations of the reaction in question. In-depth analysis of individual amino acid contributions of both isoenzymes to the barrier (based on the interaction between the electric field provided by the enzyme and the dipole moment of the reacting moiety) shows that the majority of the difference between the isoenzymes can be attributed to a small number of sizable differences between the aligned amino acid pairs, whereas in most of the pairs the difference in contribution to the barrier is vanishingly small. These results suggest that electrostatics largely controls the substrate selectivity of enzymes and validates our approach as being capable of discerning fine nuances in the selectivity of structurally related isoenzymes.

Differences in thermal structural changes and melting between mesophilic and thermophilic dihydrofolate reductase enzymes

The thermal resistance of two homolog enzymes is investigated, with an emphasis on their local stability and flexibility, and on the possible implications regarding their reactivity.

Dynamic Electric Field Complicates Chemical Reactions in Solutions

Chemical reactions can be strongly influenced by an external electric field (EEF), but because the EEF is often time-dependent and in case it does not adapt quickly enough to the reaction progress, especially during fast barrier crossing processes, dynamic effects could be important. Here we find that electrostatic interactions can reduce the height of the reaction barrier for a Claissen rearrangement reaction and accelerate the key motions for bonding. Meanwhile, strong electrostatic interactions can modify the barrier into an effective potential well, confining the system into the barrier until solvents adjust themselves to provide an appropriate EEF for charge redistribution. In this case, the otherwise concerted mechanism becomes a stepwise one. Consequently, the motion of solvents modulates the reaction dynamics and leads to heterogeneous reaction paths, even in a seemingly homogeneous aqueous solution. In addition, an excessive stabilization of transition state retards the barrier crossing process, making the thermodynamically favorable pathway less favored dynamically.

Convergence of theory and experiment on the role of preorganization, quantum tunneling and enzyme motions into flavoenzyme-catalyzed hydride transfer

Hydride transfer is one of the most common reactions catalyzed by enzymatic systems and it has become an object of study due to possible significant quantum tunneling effects. In the present work, we provide a combination of theoretical QM/MM simulations and experimental measurements of the rate constants and kinetic isotopic effects (KIEs) for the hydride transfer reaction catalyzed by morphinone reductase, MR. Quantum mechanical tunneling coefficients, computed in the framework of variational transition-state theory, play a significant role in this reaction, reaching values of 23.8 ± 5.5 for the lightest isotopologue; one of the largest values reported for enzymatic systems. This prediction is supported by the agreement between the theoretically predicted rate constants and the corresponding experimental values. Simulations indicate that the role of protein motions can be satisfactorily described as equilibrium fluctuations along the reaction coordinate, in line with a high degree of preorganization displayed by this enzyme.

Temperature dependence of dynamic, tunnelling and kinetic isotope effects in formate dehydrogenase

The origin of the catalytic power of enzymes has been a question of debate for a long time. In this regard, the possible contribution of protein dynamics in enzymatic catalysis has become one of the most controversial topics. In the present work, the hydride transfer step in the formate dehydrogenase (FDH EC 1.2.1.2) enzyme is studied by means of molecular dynamic (MD) simulations with quantum mechanics/molecular mechanics (QM/MM) potentials in order to explore any correlation between dynamics, tunnelling effects and the rate constant. The temperature dependence of the kinetic isotope effects (KIEs), which is one of the few tests that can be studied by experiments and simulations to shed light on this debate, has been computed and the results have been compared with previous experimental data. The classical mechanical free energy barrier and the number of recrossing trajectories seem to be temperature-independent while the quantum vibrational corrections and the tunnelling effects are slightly temperature-dependent over the interval of 5-45 °C. The computed primary KIEs are in very good agreement with previous experimental data, being almost temperature-independent within the standard deviations. The modest dependence on the temperature is due to just the quantum vibrational correction contribution. These results, together with the analysis of the evolution of the collective variables such as the electrostatic potential or the electric field created by the protein on the key atoms involved in the reaction, confirm that while the protein is well preorganised, some changes take place along the reaction that favour the hydride transfer and the product release. Coordinates defining these movements are, in fact, part of the real reaction coordinate.

Molecular modeling of conformational dynamics and its role in enzyme evolution

With increasing computational power, biomolecular simulations have become an invaluable tool for understanding enzyme mechanisms and the origins of enzyme catalysis. More recently, computational studies have started to focus on understanding how enzyme activity itself evolves, both in terms of enhancing the native or new activities on existing enzyme scaffolds, or completely de novo on previously non-catalytic scaffolds. In this context, both experiment and molecular modeling provided strong evidence for an important role of conformational dynamics in the evolution of enzyme functions. This contribution will present a brief overview of the current state of the art for computationally exploring enzyme conformational dynamics in enzyme evolution, and, using several showcase studies, illustrate the ways molecular modeling can be used to shed light on how enzyme function evolves, at the most fundamental molecular level.

Conformational dynamics and enzyme evolution

Enzymes are dynamic entities, and their dynamic properties are clearly linked to their biological function. It follows that dynamics ought to play an essential role in enzyme evolution. Indeed, a link between conformational diversity and the emergence of new enzyme functionalities has been recognized for many years. However, it is only recently that state-of-the-art computational and experimental approaches are revealing the crucial molecular details of this link. Specifically, evolutionary trajectories leading to functional optimization for a given host environment or to the emergence of a new function typically involve enriching catalytically competent conformations and/or the freezing out of non-competent conformations of an enzyme. In some cases, these evolutionary changes are achieved through distant mutations that shift the protein ensemble towards productive conformations. Multifunctional intermediates in evolutionary trajectories are probably multi-conformational, i.e. able to switch between different overall conformations, each competent for a given function. Conformational diversity can assist the emergence of a completely new active site through a single mutation by facilitating transition-state binding. We propose that this mechanism may have played a role in the emergence of enzymes at the primordial, progenote stage, where it was plausibly promoted by high environmental temperatures and the possibility of additional phenotypic mutations.

Promoting Vibrations and the Function of Enzymes. Emerging Theoretical and Experimental Convergence

A complete understanding of enzyme catalysis requires knowledge of both transition state features and the detailed motions of atoms that cause reactant molecules to form and traverse the transition state. The seeming intractability of the problem arises from the femtosecond lifetime of chemical transition states, preventing most experimental access. Computational chemistry is admirably suited to short time scale analysis but can be misled by inappropriate starting points or by biased assumptions. Kinetic isotope effects provide an experimental approach to transition state structure and a method for obtaining transition state analogues but, alone, do not inform how that transition state is reached. Enzyme structures with transition state analogues provide computational starting points near the transition state geometry. These well-conditioned starting points, combined with the unbiased computational method of transition path sampling, provide realistic atomistic motions involved in transition state formation and passage. In many, but not all, enzymatic systems, femtosecond local protein motions near the catalytic site are linked to transition state formation. These motions are not inherently revealed by most approaches of transition state theory, because transition state theory replaces dynamics with the statistics of the transition state. Experimental and theoretical convergence of the link between local catalytic site vibrational modes and catalysis comes from heavy atom ("Born-Oppenheimer") enzymes. Fully labeled and catalytic site local heavy atom labels perturb the probability of finding enzymatic transition states in ways that can be analyzed and predicted by transition path sampling. Recent applications of these experimental and computational approaches reveal how subpicosecond local catalytic site protein modes play important roles in creating the transition state.

Quantifying the limits of transition state theory in enzymatic catalysis

While being one of the most popular reaction rate theories, the applicability of transition state theory to the study of enzymatic reactions has been often challenged. The complex dynamic nature of the protein environment raised the question about the validity of the nonrecrossing hypothesis, a cornerstone in this theory. We present a computational strategy to quantify the error associated to transition state theory from the number of recrossings observed at the equicommittor, which is the best possible dividing surface. Application of a direct multidimensional transition state optimization to the hydride transfer step in human dihydrofolate reductase shows that both the participation of the protein degrees of freedom in the reaction coordinate and the error associated to the nonrecrossing hypothesis are small. Thus, the use of transition state theory, even with simplified reaction coordinates, provides a good theoretical framework for the study of enzymatic catalysis.

Active Site Flexibility of Mycobacterium tuberculosis Isocitrate Lyase in Dimer Form

Tuberculosis (TB) still remains a global threat due to the emergence of a drug-resistant strain. Instead of focusing on the drug target of active stage TB, we are highlighting the isocitrate lyase (ICL) at the dormant stage TB. ICL is one of the persistent factors for Mycobacterium tuberculosis (MTB) to survive during the dormant phase. In addition, the absence of ICL in human has made ICL a potential drug target for TB therapy. However, the dynamic details of ICL which could give insights to the ICL-ligand interaction have yet to be solved. Therefore, a series of ICL dimer dynamics studies through molecular dynamics simulation were performed in this work. The ICL active site entrance gate closure is contributed to by hydrogen bonding and electrostatic interactions with the C-terminal. Analysis suggested that the open-closed behavior of the ICL active site entrance depends on the type of ligand present in the active site. We also observed four residues (Ser91, Asp108, Asp153, and Cys191) which could possibly be the nucleophiles for nucleophilic attack on the cleavage of isocitrate at the C₂-C₃ bond. We hope that the elucidation of ICL dynamics can benefit future works such as lead identification or antibody design against ICL for TB therapeutics.

Coupled Valence-Bond State Molecular Dynamics Description of an Enzyme-Catalyzed Reaction in a Non-Aqueous Organic Solvent

Enzymes are widely used in nonaqueous solvents to catalyze non-natural reactions. While experimental measurements showed that the solvent nature has a strong effect on the reaction kinetics, the molecular details of the catalytic mechanism in nonaqueous solvents have remained largely elusive. Here we study the transesterification reaction catalyzed by the paradigm subtilisin Carlsberg serine protease in an organic apolar solvent. The rate-limiting acylation step involves a proton transfer between active-site residues and the nucleophilic attack of the substrate to form a tetrahedral intermediate. We design the first coupled valence-bond state model that simultaneously describes both reactions in the enzymatic active site. We develop a new systematic procedure to parametrize this model on high-level ab initio QM/MM free energy calculations that account for the molecular details of the active site and for both substrate and protein conformational fluctuations. Our calculations show that the reaction energy barrier changes dramatically with the solvent and protein conformational fluctuations. We find that the mechanism of the tetrahedral intermediate formation during the acylation step is similar to that determined under aqueous conditions, and that the proton transfer and nucleophilic attack reactions occur concertedly. We identify the reaction coordinate to be mostly due to the rearrangement of some residual water molecules close to the active site.

Acceleration of Semiempirical QM/MM Methods through Message Passage Interface (MPI), Hybrid MPI/Open Multiprocessing, and Self-Consistent Field Accelerator Implementations

The strategy and implementation of scalable and efficient semiempirical (SE) QM/MM methods in CHARMM are described. The serial version of the code was first profiled to identify routines that required parallelization. Afterward, the code was parallelized and accelerated with three approaches. The first approach was the parallelization of the entire QM/MM routines, including the Fock matrix diagonalization routines, using the CHARMM message passage interface (MPI) machinery. In the second approach, two different self-consistent field (SCF) energy convergence accelerators were implemented using density and Fock matrices as targets for their extrapolations in the SCF procedure. In the third approach, the entire QM/MM and MM energy routines were accelerated by implementing the hybrid MPI/open multiprocessing (OpenMP) model in which both the task- and loop-level parallelization strategies were adopted to balance loads between different OpenMP threads. The present implementation was tested on two solvated enzyme systems (including <100 QM atoms) and an S_N2 symmetric reaction in water. The MPI version exceeded existing SE QM methods in CHARMM, which include the SCC-DFTB and SQUANTUM methods, by at least 4-fold. The use of SCF convergence accelerators further accelerated the code by ∼12-35% depending on the size of the QM region and the number of CPU cores used. Although the MPI version displayed good scalability, the performance was diminished for large numbers of MPI processes due to the overhead associated with MPI communications between nodes. This issue was partially overcome by the hybrid MPI/OpenMP approach which displayed a better scalability for a larger number of CPU cores (up to 64 CPUs in the tested systems).

Perspective: Defining and quantifying the role of dynamics in enzyme catalysis

Enzymes control chemical reactions that are key to life processes, and allow them to take place on the time scale needed for synchronization between the relevant reaction cycles. In addition to general interest in their biological roles, these proteins present a fundamental scientific puzzle, since the origin of their tremendous catalytic power is still unclear. While many different hypotheses have been put forward to rationalize this, one of the proposals that has become particularly popular in recent years is the idea that dynamical effects contribute to catalysis. Here, we present a critical review of the dynamical idea, considering all reasonable definitions of what does and does not qualify as a dynamical effect. We demonstrate that no dynamical effect (according to these definitions) has ever been experimentally shown to contribute to catalysis. Furthermore, the existence of non-negligible dynamical contributions to catalysis is not supported by consistent theoretical studies. Our review is aimed, in part, at readers with a background in chemical physics and biophysics, and illustrates that despite a substantial body of experimental effort, there has not yet been any study that consistently established a connection between an enzyme's conformational dynamics and a significant increase in the catalytic contribution of the chemical step. We also make the point that the dynamical proposal is not a semantic issue but a well-defined scientific hypothesis with well-defined conclusions.

Dynamic and Electrostatic Effects on the Reaction Catalyzed by HIV-1 Protease

HIV-1 Protease (HIV-1 PR) is one of the three enzymes essential for the replication process of HIV-1 virus, which explains why it has been the main target for design of drugs against acquired immunodeficiency syndrome (AIDS). This work is focused on exploring the proteolysis reaction catalyzed by HIV-1 PR, with special attention to the dynamic and electrostatic effects governing its catalytic power. Free energy surfaces for all possible mechanisms have been computed in terms of potentials of mean force (PMFs) within hybrid QM/MM potentials, with the QM subset of atoms described at semiempirical (AM1) and DFT (M06-2X) level. The results suggest that the most favorable reaction mechanism involves formation of a gem-diol intermediate, whose decomposition into the product complex would correspond to the rate-limiting step. The agreement between the activation free energy of this step with experimental data, as well as kinetic isotope effects (KIEs), supports this prediction. The role of the protein dynamic was studied by protein isotope labeling in the framework of the Variational Transition State Theory. The predicted enzyme KIEs, also very close to the values measured experimentally, reveal a measurable but small dynamic effect. Our calculations show how the contribution of dynamic effects to the effective activation free energy appears to be below 1 kcal·mol^-1. On the contrary, the electric field created by the protein in the active site of the enzyme emerges as being critical for the electronic reorganization required during the reaction. These electrostatic properties of the active site could be used as a mold for future drug design.

Modulating Enzyme Catalysis through Mutations Designed to Alter Rapid Protein Dynamics

The relevance of sub-picosecond protein motions to the catalytic event remains a topic of debate. Heavy enzymes (isotopically substituted) provide an experimental tool for bond-vibrational links to enzyme catalysis. A recent transition path sampling study with heavy purine nucleoside phosphorylase (PNP) characterized the experimentally observed mass-dependent slowing of barrier crossing (Antoniou, D.; Ge, X.; Schramm, V. L.; Schwartz, S. D. J. Phys. Chem. Lett. 2012, 3, 3538). Here we computationally identify second-sphere amino acid residues predicted to influence the freedom of the catalytic site vibrational modes linked to heavy enzyme effects in PNP. We mutated heavy and light PNPs to increase the catalytic site vibrational freedom. Enzymatic barrier-crossing rates were converted from mass-dependent to mass-independent as a result of the mutations. The mutagenic uncoupling of femtosecond motions between catalytic site groups and reactants decreased transition state barrier crossing by 2 orders of magnitude, an indication of the femtosecond dynamic contributions to catalysis.

Phase Space Bottlenecks in Enzymatic Reactions

The definition of a transition state on an individual reactive trajectory is made via a committor analysis. In the past, the bottleneck definition has often been applied in configuration space. This is an approximation, and in order to expand this definition, we are revisiting an enzyme in which we had identified a fast subpicosecond motion that makes the reaction possible. First we used a time-series analysis method to identify the exact time when this motion initiates donor-acceptor compression. Then we modified the standard committor analysis of transition path sampling to identify events in phase space and found that there is a dividing surface in phase space significantly earlier than the configurationally defined transition-state crossing.

Statistical Evaluation of HTS Assays for Enzymatic Hydrolysis of β-Keto Esters

β-keto esters are used as precursors for the synthesis of β-amino acids, which are building blocks for some classes of pharmaceuticals. Here we describe the comparison of screening procedures for hydrolases to be used for the hydrolysis of β-keto esters, the first step in the preparation of β-amino acids. Two of the tested high throughput screening (HTS) assays depend on coupled enzymatic reactions which detect the alcohol released during ester hydrolysis by luminescence or absorption. The third assay detects the pH shift due to acid formation using an indicator dye. To choose the most efficient approach for screening, we assessed these assays with different statistical methods—namely, the classical Z’-factor, standardized mean difference (SSMD), the Kolmogorov-Smirnov-test, and t-statistics. This revealed that all three assays are suitable for HTS, the pH assay performing best. Based on our data we discuss the explanatory power of different statistical measures. Finally, we successfully employed the pH assay to identify a very fast hydrolase in an enzyme-substrate screening.

Protein electron transfer: is biology (thermo)dynamic?

Simple physical mechanisms are behind the flow of energy in all forms of life. Energy comes to living systems through electrons occupying high-energy states, either from food (respiratory chains) or from light (photosynthesis). This energy is transformed into the cross-membrane proton-motive force that eventually drives all biochemistry of the cell. Life's ability to transfer electrons over large distances with nearly zero loss of free energy is puzzling and has not been accomplished in synthetic systems. The focus of this review is on how this energetic efficiency is realized. General physical mechanisms and interactions that allow proteins to fold into compact water-soluble structures are also responsible for a rugged landscape of energy states and a broad distribution of relaxation times. Specific to a protein as a fluctuating thermal bath is the protein-water interface, which is heterogeneous both dynamically and structurally. The spectrum of interfacial fluctuations is a consequence of protein's elastic flexibility combined with a high density of surface charges polarizing water dipoles into surface nanodomains. Electrostatics is critical to the protein function and the relevant questions are: (i) What is the spectrum of interfacial electrostatic fluctuations? (ii) Does the interfacial biological water produce electrostatic signatures specific to proteins? (iii) How is protein-mediated chemistry affected by electrostatics? These questions connect the fluctuation spectrum to the dynamical control of chemical reactivity, i.e. the dependence of the activation free energy of the reaction on the dynamics of the bath. Ergodicity is often broken in protein-driven reactions and thermodynamic free energies become irrelevant. Continuous ergodicity breaking in a dense spectrum of relaxation times requires using dynamically restricted ensembles to calculate statistical averages. When applied to the calculation of the rates, this formalism leads to the nonergodic activated kinetics, which extends the transition-state theory to dynamically dispersive media. Releasing the grip of thermodynamics in kinetic calculations through nonergodicity provides the mechanism for an efficient optimization between reaction rates and the spectrum of relaxation times of the protein-water thermal bath. Bath dynamics, it appears, play as important role as the free energy in optimizing biology's performance.