Research Article pubs.acs.org/acscatalysis
Cite This: ACS Catal. 2018, 8, 2683−2692
Decoding Allosteric Networks in Biocatalysts: Rational Approach to Therapies and Biotechnologies Johannes T. Cramer,†,‡,∥ Jana I. Führing,† Petra Baruch,‡ Christian Brütting,§ Hans-Joachim Knölker,*,§ Rita Gerardy-Schahn,† and Roman Fedorov*,‡ †
Institute of Clinical Biochemistry, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany Institute for Biophysical Chemistry/Research Division for Structural Biochemistry, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany § Department of Chemistry, Technische Universität Dresden, Bergstrasse 66, 01069 Dresden, Germany ‡
S Supporting Information *
ABSTRACT: Biocatalysts utilize allosteric mechanisms to control selectivity, catalytic activity, and the transport of reaction components. The allosteric control of catalysis has a high potential for the development of drugs and technologies. In particular, it opens the way to specific regulation of vital enzymes with conserved active sites. Using the central metabolic enzyme UDP-glucose pyrophosphorylase from the pathogen Leishmania major (LmUGP), we demonstrate how specific allosteric inhibition sites and their links to the catalytic center can be revealed rationally, through analysis of molecular interfaces along the enzymatic reaction cycle. Two previously unknown specific allosteric inhibition sites in LmUGP were rationally identified and experimentally verified. The molecular scaffold for allosteric inhibitor targeting the pathogen’s enzyme was developed. This led to the identification of murrayamine-I as an allosteric inhibitor that selectively blocks LmUGP. The presented approach opens up the possibility of using central metabolic enzymes with highly conserved active sites as allosteric drug targets, thus solving the cross-reactivity problem. In particular, it paves the ways to antimicrobial treatments. KEYWORDS: allostery, enzyme catalysis, inhibitors, cross-reactivity, drug-target
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INTRODUCTION Biocatalysts enable enormous acceleration of chemical reactions and exhibit precise control of regio- and stereoselectivity. These properties, together with the transport of reaction components, are facilitated by allosteric mechanisms. Understanding how biocatalysts are regulated by allosteric mechanisms enables their rational manipulation, which is valuable for biomedical and biotechnological applications,1,2 including the development of new functional materials.3,4 It is also essential for optimizing enzymes for industrial usage and adapting the elements of biomolecular mechanisms for chemical catalysis.5,6 Many families of enzymes with vital cellular functions (e.g., ATPases, GTPases, nucleotidyltransferases, heme-containing enzymes, and others) have highly conserved catalytic centers within each family. Due to their central role in cellular processes, these enzymes could be attractive targets for the development of new therapies and biotechnologies. However, targeting active sites of these enzymes may interfere with other important biological processes through unspecific inhibition (or crossreactivity).7−9 At the same time, allosteric mechanisms facilitating regulation of activity and exchange of reaction components are often specific for each enzyme. Allosteric effects thus can be used to avoid cross-reactivity issues and develop specific agents targeting allosteric sites in enzymes or regulate isozymes in a particular organ or tissue. This strategy opens up possibilities of using the catalytically conserved enzymes as new therapeutic or biotechnological © XXXX American Chemical Society
targets. However, the identification of allosteric networks regulating catalysis is challenging due to their size, complexity, and dynamic nature. Physical mechanisms of allosteric signal transmission through these networks are still under debate.1,10 Allosteric enzymes exist in an equilibrium between the catalytically active (R*) and inactive (R) states: R ↔ R*. An allosteric effector binds to an active conformation of the enzyme, stabilizing it and thus shifting the equilibrium toward R*.11 Conformational transitions between R and R* utilize allosteric networks linking the catalytic center with the remote binding site of an allosteric effector. The Helmholtz free energy of transition from the inactive to the active state can be written as ΔFR → R * = F(R*) − F(R) ⎞ ⎛ = − kBT ln⎜⎜∑ e−En(R*)/ kBT /∑ e−En(R)/ kBT ⎟⎟ ⎠ ⎝ n n = − kBT ln
Q R* QR
(1)
where En are the energies of the microstates and Q is a partition function. In harmonic approximation using normal coordinate Received: October 30, 2017 Revised: February 9, 2018 Published: February 15, 2018 2683
DOI: 10.1021/acscatal.7b03714 ACS Catal. 2018, 8, 2683−2692
Research Article
ACS Catalysis
mode analysis (NMA) using an elastic network model (ENM)30 and dynamical network analysis.31,32 These methods, based on the classical Molecular Mechanics (MM) representation,33 allow modeling the dynamic properties of very large molecular systems.34 The theoretical approaches have some principal limitations resulting from the classical potential (force-field) in the equations of motion for all particles in the system and the usage of Lennard-Jones potentials for van der Waals interactions as well as a harmonic approximation for the potential energy of the molecule.35 In particular, these limitations do not allow correct description of the hydrogen bond properties which have partially quantum nature and play a fundamentally important role in all biological processes, including allosteric regulation.14,36 Due to their inherent limitations, none of the experimental or theoretical methods prevails as best for identification and characterization of allosteric networks. Rather each method has particular strengths in describing events that occur over specific time scales and magnitudes of conformational change.37 In our recent studies of a central metabolic enzyme, UDPglucose pyrophosphorylase (UGP),7,23,38 we demonstrated how the allosteric mechanisms regulating catalysis, selectivity, and the transport of reaction components could be revealed via reconstruction of the complete enzymatic cycles. UGP is a central enzyme in carbohydrate metabolism and belongs to the large and diverse nucleotidyltransferase (NT) enzyme superfamily, whose members are involved in many vital cellular processes.39 UGP catalyzes the synthesis of the activated form of glucose, UDP-Glc, from uridine triphosphate (UTP) and glucose-1-phosphate (Glc-1P) in the following reaction.
system, the partition function becomes the product of partition functions for each vibrational normal mode: 3N − 6
Q=
∏
3N − 6
Q j(ν) =
j=1
∏ j=1
e−hνj /2kBT 1 − e−hνj / kBT
(2)
where ν is a frequency of the jth normal mode and N is the number of atoms. Since the activation of the high-frequency vibrations requires higher energies than kBT/2, the partition functions Q(R) or Q(R*) can be approximated by a product of partition functions for the low-frequency modes: Q ≈ ΠkQk (vlow). These modes correspond to relatively large amplitude conformational changes involving collective motions of atoms grouped into the macromolecular subdomains. Thus, a large number of variables in statistical ensemble of states can be replaced by a few allocated degrees of freedom describing the movements of subdomains. Then the free energy of allosteric transition from the inactive to the active state of enzyme can be expressed as ΔFR → R * =
∑ [Fα(R*) − Fα(R)] + ∑ [Fαβ(R*) − Fαβ(R)] α
α
