Protein dynamics and enzyme catalysis: the ghost in the machine?

Hydrogen deuterium exchange defines catalytically linked regions of protein flexibility in the catechol O-methyltransferase reaction

Human catechol O-methyltransferase (COMT) has emerged as a model for understanding enzyme-catalyzed methyl transfer from S-adenosylmethionine (AdoMet) to small-molecule catecholate acceptors. Mutation of a single residue (tyrosine 68) behind the methyl-bearing sulfonium of AdoMet was previously shown to impair COMT activity by interfering with methyl donor-acceptor compaction within the activated ground state of the wild type enzyme [J. Zhang, H. J. Kulik, T. J. Martinez, J. P. Klinman, Proc. Natl. Acad. Sci. U.S.A. 112, 7954-7959 (2015)]. This predicts the involvement of spatially defined protein dynamical effects that further tune the donor/acceptor distance and geometry as well as the electrostatics of the reactants. Here, we present a hydrogen/deuterium exchange (HDX)-mass spectrometric study of wild type and mutant COMT, comparing temperature dependences of HDX against corresponding kinetic and cofactor binding parameters. The data show that the impaired Tyr68Ala mutant displays similar breaks in Arrhenius plots of both kinetic and HDX properties that are absent in the wild type enzyme. The spatial resolution of HDX below a break point of 15-20 °C indicates changes in flexibility across ∼40% of the protein structure that is confined primarily to the periphery of the AdoMet binding site. Above 20 °C, Tyr68Ala behaves more like WT in HDX, but its rate and enthalpic barrier remain significantly altered. The impairment of catalysis by Tyr68Ala can be understood in the context of a mutationally induced alteration in protein motions that becomes manifest along and perpendicular to the primary group transfer coordinate.

Temperature, Dynamics, and Enzyme-Catalyzed Reaction Rates

We review the adaptations of enzyme activity to different temperatures. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temperature dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity versus temperature that is not accounted for by denaturation or unfolding. This is explained by macromolecular rate theory: A negative activation heat capacity for the rate-limiting chemical step leads directly to predictions of temperature optima; both entropy and enthalpy are temperature dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining experiment with molecular simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calculate relevant thermodynamic properties (such as activation enthalpies, entropies, and heat capacities) and reveal the molecular mechanisms underlying experimentally observed behavior.

Ab Initio QM/MM Modeling of the Rate-Limiting Proton Transfer Step in the Deamination of Tryptamine by Aromatic Amine Dehydrogenase

Aromatic amine dehydrogenase (AADH) and related enzymes are at the heart of debates on the roles of quantum tunneling and protein dynamics in catalysis. The reaction of tryptamine in AADH involves significant quantum tunneling in the rate-limiting proton transfer step, shown by large H/D primary kinetic isotope effects (KIEs), with unusual temperature dependence. We apply correlated ab initio combined quantum mechanics/molecular mechanics (QM/MM) methods, at levels up to local coupled cluster theory (LCCSD(T)/(aug)-cc-pVTZ), to calculate accurate potential energy surfaces for this reaction, which are necessary for quantitative analysis of tunneling contributions and reaction dynamics. Different levels of QM/MM treatment are tested. Multiple pathways are calculated with fully flexible transition state optimization by the climbing-image nudged elastic band method at the density functional QM/MM level. The average LCCSD(T) potential energy barriers to proton transfer are 16.7 and 14.0 kcal/mol for proton transfer to the two carboxylate atoms of the catalytic base, Asp128β. The results show that two similar, but distinct pathways are energetically accessible. These two pathways have different barriers, exothermicity and curvature, and should be considered in analyses of the temperature dependence of reaction and KIEs in AADH and other enzymes. These results provide a benchmark for this prototypical enzyme reaction and will be useful for developing empirical models, and analyzing experimental data, to distinguish between different conceptual models of enzyme catalysis.

Complete sampling of an enzyme reaction pathway: a lesson from gas phase simulations

With proper sampling strategy, convergence of free energy profiles of biomolecular reactions in the gas phase can be achieved in microseconds of simulation.

Protein motions and dynamic effects in enzyme catalysis

The role of protein motions in promoting the chemical step of enzyme catalysed reactions remains a subject of considerable debate. Here, a unified view of the role of protein dynamics in dihydrofolate reductase catalysis is described. Recently the role of such motions has been investigated by characterising the biophysical properties of isotopically substituted enzymes through a combination of experimental and computational analyses. Together with previous work, these results suggest that dynamic coupling to the chemical coordinate is detrimental to catalysis and may have been selected against during DHFR evolution. The full catalytic power of Nature's catalysts appears to depend on finely tuning protein motions in each step of the catalytic cycle.

Single-molecule spectroscopy exposes hidden states in an enzymatic electron relay

The ability to query enzyme molecules individually is transforming our view of catalytic mechanisms. Quiescin sulfhydryl oxidase (QSOX) is a multidomain catalyst of disulfide-bond formation that relays electrons from substrate cysteines through two redox-active sites to molecular oxygen. The chemical steps in electron transfer have been delineated, but the conformational changes accompanying these steps are poorly characterized. Here we use single-molecule Förster resonance energy transfer (smFRET) to probe QSOX conformation in resting and cycling enzyme populations. We report the discovery of unanticipated roles for conformational changes in QSOX beyond mediating electron transfer between redox-active sites. In particular, a state of the enzyme not previously postulated or experimentally detected is shown to gate, via a conformational transition, the entrance into a sub-cycle within an expanded QSOX kinetic scheme. By tightly constraining mechanistic models, smFRET data can reveal the coupling between conformational and chemical transitions in complex enzymatic cycles.

A major challenge in following electron transfer through dithiol/disulfide exchange is the dearth of accompanying spectroscopic effects. Here, the authors use single-molecule Förster resonance energy transfer experiments to illuminate disulfide bond rearrangements within the enzyme quiescin sulfhydryl oxidase.

Challenges in computational studies of enzyme structure, function and dynamics

In this review we give an overview of the field of Computational enzymology. We start by describing the birth of the field, with emphasis on the work of the 2013 chemistry Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by experiments, has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-molecular mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.

The dilemma of conformational dynamics in enzyme catalysis: perspectives from theory and experiment

The role of protein dynamics in catalysis is a contemporary issue that has stirred intense debate in the field. This chapter provides a brief overview of the approaches and findings of a wide range of experimental, computational and theoretical studies that have addressed this issue. We summarize the results of our recent atomistic molecular dynamic studies on cis-trans isomerase. Our results help to reconcile the disparate perspectives regarding the complex role of enzyme dynamics in the catalytic step and emphasize the major contribution of transition state stabilization in rate enhancement.

Unraveling the role of protein dynamics in dihydrofolate reductase catalysis

Protein dynamics have controversially been proposed to be at the heart of enzyme catalysis, but identification and analysis of dynamical effects in enzyme-catalyzed reactions have proved very challenging. Here, we tackle this question by comparing an enzyme with its heavy ((15)N, (13)C, (2)H substituted) counterpart, providing a subtle probe of dynamics. The crucial hydride transfer step of the reaction (the chemical step) occurs more slowly in the heavy enzyme. A combination of experimental results, quantum mechanics/molecular mechanics simulations, and theoretical analyses identify the origins of the observed differences in reactivity. The generally slightly slower reaction in the heavy enzyme reflects differences in environmental coupling to the hydride transfer step. Importantly, the barrier and contribution of quantum tunneling are not affected, indicating no significant role for "promoting motions" in driving tunneling or modulating the barrier. The chemical step is slower in the heavy enzyme because protein motions coupled to the reaction coordinate are slower. The fact that the heavy enzyme is only slightly less active than its light counterpart shows that protein dynamics have a small, but measurable, effect on the chemical reaction rate.

Measuring kinetic isotope effects in enzyme reactions using time-resolved electrospray mass spectrometry

Kinetic isotope effect (KIE) measurements are a powerful tool for studying enzyme mechanisms; they can provide insights into microscopic catalytic processes and even structural constraints for transition states. However, KIEs have not come into widespread use in enzymology, due in large part to the requirement for prohibitively cumbersome experimental procedures and daunting analytical frameworks. In this work, we introduce time-resolved electrospray ionization mass spectrometry (TRESI-MS) as a straightforward, precise, and inexpensive method for measuring KIEs. Neither radioisotopes nor large amounts of material are needed and kinetic measurements for isotopically "labeled" and "unlabeled" species are acquired simultaneously in a single "competitive" assay. The approach is demonstrated first using a relatively large isotope effect associated with yeast alcohol dehydrogenase (YADH) catalyzed oxidation of ethanol. The measured macroscopic KIE of 2.19 ± 0.05 is consistent with comparable measurements in the literature but cannot be interpreted in a way that provides insights into isotope effects in individual microscopic steps. To demonstrate the ability of TRESI-MS to directly measure intrinsic KIEs and to characterize the precision of the technique, we measure a much smaller (12)C/(13)C KIE associated specifically with presteady state acylation of chymotrypsin during hydrolysis of an ester substrate.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.