Induced fit model

5 Key excerpts on "Induced fit model"

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  Understanding Enzymes

  Function, Design, Engineering, and Analysis

  • Allan Svendsen(Author)
  • 2016(Publication Date)
  • Jenny Stanford Publishing

    (Publisher)

  Understanding the origin of enzymatic rate enhancement has been a goal of biochemistry for more than half a century. Initial attempts to understand enzyme mechanisms were based on steady-state kinetics studies that provided a measure of the catalytic efficiency characterized by turnover number and the strength of substrate binding. Along with direct studies of enzymes, the combination of physical organic chemistry with protein structure fostered the hypothesis that the catalytic efficiency of enzymes was attributable to the restriction of substrate rotations and the orientation of catalytic groups within the active site. To facilitate an optimal low-energy transition state, Understanding Enzymes: Function, Design, Engineering, and Analysis Edited by Allan Svendsen Copyright c 2016 Pan Stanford Publishing Pte. Ltd. ISBN 978-981-4669-32-0 (Hardcover), 978-981-4669-33-7 (eBook) www.panstanford.com 22 Protein Conformational Motions a more complete molecular description of catalysis is developed through progress in rapid transient kinetics methods that extended the time range available for observation, leading to the discovery of intermediates that virtually occur in every enzyme catalytic cycle. Various types of evidence in structural biology and biophysics opened a new era in enzymology and focused attention on the role of protein motions during enzyme catalysis. These methods demonstrated conformational heterogeneity in an enzyme catalytic cycle and provided evidence for how molecular binding at distal sites could also control enzymatic activity through induced confor-mational changes. These observations prompted the development of models that connect the dynamics of enzyme conformational changes to catalytic function. Complementary to the experimental studies was the development of computational simulation as a powerful tool to discover protein conformations with low probability and a short lifetime inaccessible to other methods.

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  Computational Approaches to Protein Dynamics

  From Quantum to Coarse-Grained Methods

  • Monika Fuxreiter(Author)
  • 2014(Publication Date)
  • CRC Press

    (Publisher)

  More recently, this induced fit concept has been extended to argue in favor of the importance of prechemical conformational changes (Radhakrishnan and Schlick 2004, 2005, 2006; Radhakrishnan et al. 2006). This prechemistry pro-posal is, essentially, a more focused variant of the induced fit proposal, and argues that subtle side chain rearrangements can play an important role in bringing the system to a catalytically active state, thus guiding the subsequent replication fidelity (Radhakrishnan and Schlick 2004; Radhakrishnan et al. 2006). A counterargument against this proposal has been that while such con-formational changes do exist, they do not play a role in determining the cata-lytic efficiency or fidelity as long as the corresponding free-energy barriers are not rate-limiting (Prasad and Warshel 2011) (due to the fact that the enzyme is not carrying any memory of the previous steps; see Figure 3.2). There has been substantial discussion surrounding these positions; for instance in Mulholland et al. (2012), Prasad et al. (2012), and Wang and Schlick (2008). Therefore, we will not go into great detail and repeat these arguments Conformational and Chemical Landscapes of Enzyme Catalysis 84 here. However, we would like to point out that, critically, the role of the con-formational change in the catalytic process or its relationship to DNA rep-lication fidelity can only be assessed by a proper exploration of the relevant free-energy landscape. The first attempt to use an energy landscape to probe the molecular origin for DNA replication fidelity comes from a study of T7 DNA polymerase (Florián et al. 2005). In this work, the free-energy pathways for the incorporation of R and W nucleotides along the chemical coordinate in the closed protein conformation were plotted along with the approximate free-energy pathways for the R and W open conformations (Figure 3.9).

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  From Enzyme Models to Model Enzymes

  • Anthony J Kirby, Florian Hollfelder, Mike I Page, Andrew Williams(Authors)
  • 2009(Publication Date)
  • Royal Society of Chemistry

    (Publisher)

  3.3 Positioning of Substrate and Catalytic Groups by Covalent Design Systems where the reacting substrate and catalytic functional groups are held in close proximity on the same molecule have been described in Section 1.4, in the context of studying the mechanisms of the reactions involved. The design of relatively simple systems can provide information about the preferred geometries as well as the mechanisms of reactions of interest, but the single most important point for the enzyme modeler is that intramolecular reactions are faster, sometimes very much faster, than their intermolecular equivalents: so that reactions can be observed, and their mechanisms studied without recourse to activated substrate groups. However, in terms of fully developed enzyme models intramolecular reactivity is only indirectly relevant, because the primary interaction that brings the reacting groups together is covalent and permanent, and established by synthesis rather than by a binding step. Nevertheless, the clear implication is that a binding mechanism that brings catalytic and substrate groups into close proximity in the Michaelis complex is likely to favour also stabilization of the transition state for the reaction between them; and can provide a basis for very substantial enhancements of reactivity. 3.4 Binding the Ground State by Noncovalent Interactions Enzymes work by a sophisticated, integrated system of binding and catalysis. The essential first step of every enzyme reaction is substrate binding; by which a specific substrate is selected from the many others available after diffusing into contact with the protein, and enters the active-site ‘‘reaction vessel’’, where it comes into contact with the catalytic apparatus. So, a primary task for the model builder is creating a binding site for a substrate, because the rest of the reaction coordinate for an enzyme-catalyzed reaction is accessible only to bound substrate.

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  Proteins

  Concepts in Biochemistry

  • Paulo Almeida(Author)
  • 2016(Publication Date)
  • Garland Science

    (Publisher)

  Indeed, many enzymes, such as hexokinase and triose phosphate isomerase, undergo large conformational changes upon binding of a substrate. The same is true in many cases upon binding of other ligands that enhance or suppress the enzyme activity, which we call activators or inhibitors , respectively. However, this does not mean that substrate binding is tight. The binding constants of substrates are actually not very large. Their reciprocal, the dissociation constants ( K d ) are typi-cally in the range of μ M to mM. Too tight binding would in fact be counterproductive: lowering the Gibbs energy of the substrate too much would increase the activation barrier to reach the transition state ( Figure 7.2 ). Kinetically, an enzyme works by lowering the Gibbs energy of the transition state of a chemical reaction. It does so because the active site , where the substrate binds and the chemistry takes place on the enzyme, is complementary to the transition state in the position and organization of the chemical groups. Binding stabilizes the transition state. The concept of transition-state stabilization by complementar-ity was clearly formulated by Pauling in 1948: “I think that enzymes are molecules that are complementary in structure to the activated complexes of the reactions that they catalyze . . . . The attraction of the enzyme for the activated complex would thus lead to a decrease in its energy, and hence . . . to an increase in the rate of the reaction.” Products Substrates Δ G ‡ Δ G ‡ ‡ Gibbs energy Reaction coordinate Figure 7.2 The effect of improving substrate binding (dashed line) without a concomitant decrease in the Gibbs energy of the transition state would be to increase the activation energy and reduce the rate of the reaction compared to reaction in the absence of enzyme (solid line). 316 Chapter 7 ENZYME KINETICS Figure 7.3 The course of a reaction in the absence (solid line) and the presence (dashed line) of an enzyme.

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  Organized Multienzyme Systems: Catalytic Properties

  • G. Rickey Welch(Author)
  • 2012(Publication Date)
  • Academic Press

    (Publisher)

  VI. THERMODYNAMICS OF SUBUNIT INTERACTIONS AND THE PRINCIPLES OF STRUCTURAL KINETICS The classical induced-fit and symmetry models relate some simple features of polymeric enzyme structure to the mathematical structure of ligand-binding equations. Similarly one may hope to relate enzyme quaternary structure to the mathematical expression of the velocity of an enzyme reaction step. The term structural kinetics has been given to this attempt to express how subunit interactions and quaternary constraints control the rate of an enzymatic process (Ricard et al, 1974a; Nari et a/., 1974; Ricard, 1978). Indeed, one may consider in all logic that it is function that is the driving force of neo-Darwinian Evolution and that a given type of quaternary structure has been selected because it exhibits some type of functional advantage. The most obvious of these functional advantages is an improve-ment of the catalytic efficiency of the enzyme molecule. It is therefore an important matter to examine, in a very simple case, what the physical nature of this improvement could be. 4. POLYMERIC ENZYME SYSTEMS 207 A. Functional Efficiency of an Enzymatic Reaction Let there be the simple one-substrate, one-product enzyme reaction k 2 MS] fee E ï = i E S ^ = EP: (67) fc-i k c fc-2 [P] and the corresponding energy profile shown in Fig. 13. An important aspect of this energy profile is the existence of extra costs of energy, å, in going from the initial state to any of the transition states along the reaction coordinate (Ricard, 1978; Albery and Knowles, 1976). These extra costs of energy correspond to the free energy difference between the initial state and any of the transition states. One must have ï ââ = Ar;? AGI, (68) e sx = AG + AG c i -AG t _ 1 , e S p = AG + AG* + AG| -AG*-X -AG*_ C . In these expressions å^, å 8 ÷, and å äÑ are the extra costs between the initial state and the ES*, EX*, and EP* transition states, respectively.

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