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Multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis.

ABSTRACT: Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis.

SUBMITTER: Gherib R

PROVIDER: S-EPMC3907816 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis.

Gherib Rami R Dokainish Hisham M HM Gauld James W JW

International journal of molecular sciences 20131231 1

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora ...[more]

PMID: 24384841

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Project description:CONSPECTUS: As is well-known, enzymes are proteins designed to accelerate specific life essential chemical reactions by many orders of magnitude. A folded protein is a highly dynamical entity, best described as a hierarchy or ensemble of interconverting conformations on all time scales from femtoseconds to minutes. We are just beginning to learn what role these dynamics play in the mechanism of chemical catalysis by enzymes due to extraordinary difficulties in characterizing the conformational space, that is, the energy landscape, of a folded protein. It seems clear now that their role is crucially important. Here we discuss approaches, based on vibrational spectroscopies of various sorts, that can reveal the energy landscape of an enzyme-substrate (Michaelis) complex and decipher which part of the typically very complicated landscape is relevant to catalysis. Vibrational spectroscopy is quite sensitive to small changes in bond order and bond length, with a resolution of 0.01 Å or less. It is this sensitivity that is crucial to its ability to discern bond reactivity. Using isotope edited IR approaches, we have studied in detail the role of conformational heterogeneity and dynamics in the catalysis of hydride transfer by LDH (lactate dehydrogenase). Upon the binding of substrate, the LDH·substrate system undergoes a search through conformational space to find a range of reactive conformations over the microsecond to millisecond time scale. The ligand is shuttled to the active site via first forming a weakly bound enzyme·ligand complex, probably consisting of several heterogeneous structures. This complex undergoes numerous conformational changes spread throughout the protein that shuttle the enzyme·substrate complex to a range of conformations where the substrate is tightly bound. This ensemble of conformations all have a propensity toward chemistry, but some are much more facile for carrying out chemistry than others. The search for these tightly bound states is clearly directed by the forces that the protein can bring to bear, very much akin to the folding process to form native protein in the first place. In fact, the conformational subspace of reactive conformations of the Michaelis complex can be described as a "collapse" of reactive substates compared with that found in solution, toward a much smaller and much more reactive set. These studies reveal how dynamic disorder in the protein structure can modulate the on-enzyme reactivity. It is very difficult to account for how the dynamical nature of the ground state of the Michaelis complex modulates function by transition state concepts since dynamical disorder is not a starting feature of the theory. We find that dynamical disorder may well play a larger or similar sized role in the measured Gibbs free energy of a reaction compared with the actual energy barrier involved in the chemical event. Our findings are broadly compatible with qualitative concepts of evolutionary adaptation of function such as adaptation to varying thermal environments. Our work suggests a methodology to determine the important dynamics of the Michaelis complex.

Project description:The catalytic properties of RNA have been a subject of fascination and intense research since their discovery over 30 years ago. Very recently, several classes of nucleolytic ribozymes have emerged and been characterized structurally. Among these, the twister ribozyme has been center-stage, and a topic of debate about its architecture and mechanism owing to conflicting interpretations of different crystal structures, and in some cases conflicting interpretations of the same functional data. In the present work, we attempt to clean up the mechanistic "debris" generated by twister ribozymes using a comprehensive computational RNA enzymology approach aimed to provide a unified interpretation of existing structural and functional data. Simulations in the crystalline environment and in solution provide insight into the origins of observed differences in crystal structures, and coalesce on a common active site architecture, and dynamical ensemble in solution. We use GPU-accelerated free energy methods with enhanced sampling to ascertain microscopic nucleobase pK a values of the implicated general acid and base, from which predicted activity-pH profiles can be compared directly with experiments. Next, ab initio quantum mechanical/molecular mechanical (QM/MM) simulations with full dynamic solvation under periodic boundary conditions are used to determine mechanistic pathways through multi-dimensional free energy landscapes for the reaction. We then characterize the rate-controlling transition state, and make predictions about kinetic isotope effects and linear free energy relations. Computational mutagenesis is performed to explain the origin of rate effects caused by chemical modifications and make experimentally testable predictions. Finally, we provide evidence that helps to resolve conflicting issues related to the role of metal ions in catalysis. Throughout each stage, we highlight how a conserved L-platform structural motif, to- gether with a key L-anchor residue, forms the characteristic active site scaffold enabling each of the catalytic strategies to come together not only for the twister ribozyme, but the majority of the known small nucleolytic ribozyme classes.

Dataset Information

Multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis.

Publications

Multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis.

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