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Large-Scale Quantum-Mechanical Enzymology

  • Book
  • © 2015

Overview

Authors:
  1. Greg Lever

    1. Massachusetts Institute of Technology, Cambridge, USA

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  • Nominated as an outstanding PhD thesis by the University of Cambridge, UK
  • Establishes linear-scaling density-functional theory (DFT) as a powerful tool for understanding enzyme catalysis
  • Reviews techniques capable of simulating entire enzymes at the ab initio quantum-mechanical level of accuracy
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Theses (Springer Theses)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Introduction

    • Greg Lever
    Pages 1-8

  3. Proteins, Enzymes and Biological Catalysis

    • Greg Lever
    Pages 9-18

  4. Computational Techniques

    • Greg Lever
    Pages 19-77

  5. Validation Studies

    • Greg Lever
    Pages 79-94

  6. Explaining the Closure of Calculated HOMO-LUMO Gaps in Biomolecular Systems

    • Greg Lever
    Pages 95-110

  7. A Density-Functional Perspective on the Chorismate Mutase Enzyme

    • Greg Lever
    Pages 111-141

  8. Concluding Remarks

    • Greg Lever
    Pages 143-148
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About this book

This work establishes linear-scaling density-functional theory (DFT) as a powerful tool for understanding enzyme catalysis, one that can complement quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics simulations. The thesis reviews benchmark studies demonstrating techniques capable of simulating entire enzymes at the ab initio quantum-mechanical level of accuracy. DFT has transformed the physical sciences by allowing researchers to perform parameter-free quantum-mechanical calculations to predict a broad range of physical and chemical properties of materials. In principle, similar methods could be applied to biological problems. However, even the simplest biological systems contain many thousands of atoms and are characterized by extremely complex configuration spaces associated with a vast number of degrees of freedom. The development of linear-scaling density-functional codes makes biological molecules accessible to quantum-mechanical calculation, but has yet to resolve the complexity of the phase space. Furthermore, these calculations on systems containing up to 2,000 atoms can capture contributions to the energy that are not accounted for in QM/MM methods (for which the Nobel prize in Chemistry was awarded in 2013) and the results presented here reveal profound shortcomings in said methods.

Reviews

“The dissertation is beautifully written in clear, precise language. It reads, in fact, almost as a textbook, providing in successive chapters the history, theory, and computational methods as background, then proceeding to discussing a validation computation followed by a detailed analysis of the importance of analyzing boundary conditions, then concluding with an analysis based on total use of DFT, and final thoughts. Anyone interested in this area can learn a great deal from this work.” (G. R. Mayforth, Computing Reviews, April, 2016)

Authors and Affiliations

  • Massachusetts Institute of Technology, Cambridge, USA

    Greg Lever

About the author

Greg Lever obtained a first class M.Sc in Theoretical Physics from University College London (UCL) followed by a Ph.D. in Computational Enzymology at the Cavendish Laborator, University of Cambridge. He is now Postdoctoral Associate at the Massachusetts Institute of Technology (MIT) in the Department of Chemical Engineering.

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