In Search of Catalytic Proficiency: The Importance of Enzyme Conformational Change to Orotidine 5'-Monophosphate Decarboxylase Catalysis PDF Download
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Author: Bryant M. Wood
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Languages : en
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The focus of this research is the role of conformational flexibility in catalysis by a TIM-barrel enzyme in pyrimidine biosynthesis, orotidine 50́9-monophosphate decarboxylase (OMPDC). OMPDC catalyzes the decarboxylation of OMP to UMP; the uncatalyzed rate for this reaction has been estimated to be 2.8 x 1016 s-1 (1). The slow rate without OMPDC is attributable to the lack of internal stabilization of the negative charge which must develop in the intermediate after decarboxylation. Because OMPDC does not utilize a cofactor in its mechanism, discovering how it is able to enhance this very slow rate to near the limits of diffusion is an important problem, kcat/KM = 1.3 x 107 M-1s-1 (2). Through alanine-scanning mutagenesis, I have identified important residues in OMPDC catalysis (3, 4). The large impact of mutating residues on the periphery of the active-site has helped develop an understanding of the importance of conformational change. Residues Ser127 and Gln185 from two different loops form an interaction that helps to coordinate loop closure with substrate binding; these residues also interact with the substrate (4). Besides active-site loop closure, crystal structures reveal the TIM-barrel of OMPDC to function as two halves which move toward one another when ligand binds. Near one of the boundaries between these two domains, I identified residues remote from the active-site which form a hydrophobic cluster in the 0́−closed0́+ state of the enzyme; Val182 from the mobile active-site loop becomes anchored in this cluster upon loop closure (3). Through site-directed mutagenesis, enzyme assays, and collaboration with X-ray crystallography experts in the Almo Group at Columbia University, I was able to determine that these hydrophobic interactions were important specifically to conformational change from an 0́−open0́+ to a 0́−closed0́+ state of the enzyme and that mutations to these residues had little impact on the 0́−closed0́+ state itself (3). It is thought that this cluster helps to coordinate the movement of domains as well as stabilize loop closure when substrate binds. Additional residues at the opposite domain interface are currently being investigated. In order to determine the rate-limiting step and to gain a better picture of the energy landscape for OMPDC catalysis, I measured the dependence of the kinetic parameters for various OMPDCs on viscosity (2). This allowed me to determine to what degree chemistry was important to the measured rate because changing viscosity affects the rate of physical steps outside of the active-site while leaving unchanged the chemical steps secluded from solvent by the active-site. For kcat and kcat/KM for yeast OMPDC and kcat/KM for the archaeal M. thermautorophicus OMPDC, OMP decarboxylation was found to be only partially dependent on the rate of chemical steps in the enzyme (2). Therefore, the rate of carbon-carbon bond cleavage, which occurs ca. 2.8 x 10-16 s-1 in solution, is enhanced by OMPDC near to the rate at which substrate can diffuse into the active site. Furthermore, kcat/KM for a 0́−faster0́+ substrate, 5-fluoroOMP (FOMP), was found to be completely dependent on viscosity for the archaeal enzyme. This demonstrated that the rate of FOMP decarboxylation is limited by the rate of FOMP diffusing into the active site. This allowed for an explanation of the small difference in the kcat/KM for OMP and FOMP, 2-fold as opposed to 1000-fold as predicted. Also, evidence for slow conformational change upon substrate binding was gleaned from the inability for FOMP decarboxylation catalyzed by the yeast enzyme to reach complete dependence on solvent viscosity. In short, because the chemical rate is far too fast and because diffusive processes will exhibit linear dependence on viscosity, there must be a viscosity sensitive conformational change in the yeast enzyme. By applying the tools of enzymology learned in the Gerlt Laboratory and working successfully with numerous collaborators, I have furthered our understanding of the mechanism of one of Nature0́9s best catalysts, OMPDC. Increasingly in enzymology, the role of conformational change in enzyme catalysis has been recognized as an important one. This research has shed light on the conformational changes that take place when substrate binds OMPDC and how the two events are coordinated.
Author: Judith Klinman
Publisher: Springer
ISBN: 3642389627
Category : Science
Languages : en
Pages : 217
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Christopher M. Cheatum and Amnon Kohen, Relationship of Femtosecond–Picosecond Dynamics to Enzyme-Catalyzed H-Transfer. Cindy Schulenburg and Donald Hilvert, Protein Conformational Disorder and Enzyme Catalysis. A. Joshua Wand, Veronica R. Moorman and Kyle W. Harpole, A Surprising Role for Conformational Entropy in Protein Function. Travis P. Schrank, James O. Wrabl and Vincent J. Hilser, Conformational Heterogeneity Within the LID Domain Mediates Substrate Binding to Escherichia coli Adenylate Kinase: Function Follows Fluctuations. Buyong Ma and Ruth Nussinov, Structured Crowding and Its Effects on Enzyme Catalysis. Michael D. Daily, Haibo Yu, George N. Phillips Jr and Qiang Cui, Allosteric Activation Transitions in Enzymes and Biomolecular Motors: Insights from Atomistic and Coarse-Grained Simulations. Karunesh Arora and Charles L. Brooks III, Multiple Intermediates, Diverse Conformations, and Cooperative Conformational Changes Underlie the Catalytic Hydride Transfer Reaction of Dihydrofolate Reductase. Steven D. Schwartz, Protein Dynamics and the Enzymatic Reaction Coordinate.
Author: Natasha Seelam
Publisher:
ISBN:
Category :
Languages : en
Pages : 213
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Enzymes readily perform chemical reactions several orders of magnitude faster than their uncatalyzed versions in ambient conditions with high specificity, making them attractive design targets for industrial purposes. Traditionally, enzyme reactivity has been contextualized through transition-state theory (TST), in which catalytic strategies are described by their ability to minimize the activation energy to cross the reaction barrier through a combination of ground-state destabilization (GSD) and transition-state stabilization (TSS). While excellent progress has been made to rationally design enzymes, the complexity of the design space and the highly optimized nature of enzymes make general application of these approaches difficult. This thesis presents a set of computational methods and applications in order to investigate the larger perspective of enzyme-assisted kinetic processes. For the first part of the thesis, we analyzed the energetics and dynamics of proficient catalyst orotidine 5'-monophosphate decarboxylase (OMPDC), an enzyme that catalyzes decarboxylation nearly 17 orders of magnitude more proficiently than the uncatalyzed reaction in aqueous solvent. Potential-of-mean-force (PMF) calculations on wild type (WT) and two catalytically hindered mutants, S127A and V155D (representing TSS and GSD, respectively), characterized the energy barriers associated with decarboxylation as a function of two parameters: the distance between the breaking C–C bond and a proton-transfer coordinate from the nearby side chain of K72, a conserved lysine in the active site. Coupling PMF analyses with transition path sampling (TPS) approaches revealed two distinct decarboxylation strategies: a simultaneous, K72-assisted pathway and a stepwise, relatively K72-independent pathway. Both PMF and TPS rate calculations reasonably reproduced the empirical differences in relative rates between WT and mutant systems, suggesting these approaches can enable in silico inquiry into both pathway and mechanism identification in enzyme kinetics. For the second study, we investigated the electronic determinants of reactivity, using the enzyme ketol-acid reductoisomerase (KARI). KARI catalyzes first a methyl isomerization and then reduction with an active site comprised of several polar residues, two magnesium divalent cations, and NADPH. This study focused on isomerization, which is rate limiting, with two objectives: characterization of chemical mechanism in successful catalytic events (“reactive”) versus failed attempts to cross the barrier ("non-reactive"), and the interplay between atomic positions, electronic descriptors, and reactivity. Natural bonding orbital (NBO) analyses provided detailed electronic description of the dynamics through the reaction and revealed that successful catalytic events crossed the reaction barrier through a 3-center-2-electron (3C) bond, concurrent to isomerization of hydroxyl/carbonyls on the substrate. Interestingly, the non-reactive ensemble adopted a similar electronic pathway as the reactive ensemble, but its members were generally unable to form and sustain the 3C bond. Supervised machine learning classifiers then identified small subsets of geometric and electronic descriptors, “features”, that predicted reactivity; our results indicated that fewer electronic features were able to predict reactivity as effectively as a larger set of geometric features. Of these electronic features, the models selected diverse descriptors representing several facets of the chemical mechanism (charge, breaking–bond order, atomic orbital hybridization states, etc.). We then inquired how geometric features reported on electronic features with classifiers that leveraged pairs of geometric features to predict the relative magnitude of each electronic feature. Our findings indicated that the geometric, pair-feature models predicted electronic structure with comparable performance as cumulative geometric models, suggesting small subsets of features were capable of reporting on electronic descriptors, and that different subsets could be leveraged to describe various aspects of a chemical mechanism. Lastly, we revisited OMPDC in order to learn the key geometric features that distinguished between the simultaneous and stepwise pathways of decarboxylation, aggregating and labeling pathways drawn from WT and mutant systems ensembles. We leveraged classifiers that predicted between reactive pathways by selecting small subsets of structural features from 620 geometric features comprised of atoms from the active site. The classifiers performed comparably, with greater than 80% testing accuracy and AUC, between times starting from in the reactant basin to 30 fs into crossing the reaction barrier. Remarkably, model-selected features reported on chemically meaningful interactions despite no explicit prior knowledge of the mechanism in training. To illustrate this, we focused analyses on two particular features shown to be predictive while in the reactant basin, prior to crossing the barrier: a potential hydrogen-bond between D75*, an aspartate in the active site, and the 2'-hydroxyl of OMP, and electrostatic repulsion through the proximity of a different aspartate, D70, to the leaving group carboxylate of OMP. Analysis between the simultaneous and stepwise ensembles demonstrated that the simultaneous ensemble adopted shorter distances for both features, generally suggesting stronger interactions. Both features were additionally shown to be associated with the ability to distort the planarity of the orotidyl ring, where shorter distances for either feature were correlated with larger degrees of distortion. Taken together, this suggested the simultaneous ensemble was more effective at distorting the ground state structure prior to crossing the reaction barrier.
Author: Alexander C. Roy
Publisher:
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Category :
Languages : en
Pages :
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Author: Sarfaraz Alam
Publisher:
ISBN: 9783736991101
Category :
Languages : en
Pages : 158
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Author: Fernanda Duarte
Publisher: John Wiley & Sons
ISBN: 1119245397
Category : Science
Languages : en
Pages : 139
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A comprehensive overview of current empirical valence bond (EVB) theory and applications, one of the most powerful tools for studying chemical processes in the condensed phase and in enzymes. Discusses the application of EVB models to a broad range of molecular systems of chemical and biological interest, including reaction dynamics, design of artificial catalysts, and the study of complex biological problems Edited by a rising star in the field of computational enzymology Foreword by Nobel laureate Arieh Warshel, who first developed the EVB approach
Author: Xiaoyu Wang
Publisher: Springer
ISBN: 3662530686
Category : Technology & Engineering
Languages : en
Pages : 134
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This book describes the fundamental concepts, the latest developments and the outlook of the field of nanozymes (i.e., the catalytic nanomaterials with enzymatic characteristics). As one of today’s most exciting fields, nanozyme research lies at the interface of chemistry, biology, materials science and nanotechnology. Each of the book’s six chapters explores advances in nanozymes. Following an introduction to the rise of nanozymes research in the course of research on natural enzymes and artificial enzymes in Chapter 1, Chapters 2 through 5 discuss different nanomaterials used to mimic various natural enzymes, from carbon-based and metal-based nanomaterials to metal oxide-based nanomaterials and other nanomaterials. In each of these chapters, the nanomaterials’ enzyme mimetic activities, catalytic mechanisms and key applications are covered. In closing, Chapter 6 addresses the current challenges and outlines further directions for nanozymes. Presenting extensive information on nanozymes and supplemented with a wealth of color illustrations and tables, the book offers an ideal guide for readers from disparate areas, including analytical chemistry, materials science, nanoscience and nanotechnology, biomedical and clinical engineering, environmental science and engineering, green chemistry, and novel catalysis.
Author: Alton Meister
Publisher: Wiley-Interscience
ISBN: 9780471127017
Category : Science
Languages : en
Pages : 0
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Enzymes a revised frequently in modifying proteins for specialized uses. These books cover the latest advances in this field and its applications in the field of molecular biology.
Author: Jeehiun K. Lee
Publisher: Springer
ISBN: 9783642058196
Category : Science
Languages : en
Pages : 0
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