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Large-Scale Quantum-Mechanical Enzymology 2015 ed. [Hardback]

  • Formāts: Hardback, 148 pages, height x width: 235x155 mm, weight: 474 g, 12 Illustrations, color; 18 Illustrations, black and white; XVII, 148 p. 30 illus., 12 illus. in color., 1 Hardback
  • Sērija : Springer Theses
  • Izdošanas datums: 25-Jun-2015
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319193503
  • ISBN-13: 9783319193502
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Large-Scale Quantum-Mechanical Enzymology 2015 ed.Palielināt
  • Formāts: Hardback, 148 pages, height x width: 235x155 mm, weight: 474 g, 12 Illustrations, color; 18 Illustrations, black and white; XVII, 148 p. 30 illus., 12 illus. in color., 1 Hardback
  • Sērija : Springer Theses
  • Izdošanas datums: 25-Jun-2015
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319193503
  • ISBN-13: 9783319193502
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783319193502.html
Keywords:
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.

Recenzijas

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)

1 Introduction
1(8)
1.1 Modelling and Simulation: In Silico Techniques
3(2)
1.2 Synergy Between Theory and Experiment
5(2)
1.3 Dissertation Outline
7(2)
References
8(1)
2 Proteins, Enzymes and Biological Catalysis
9(10)
2.1 Amino Acids
9(2)
2.2 Protein Structure
11(3)
2.3 Enzyme Catalysis
14(3)
2.4 Summary
17(2)
References
18(1)
3 Computational Techniques
19(60)
3.1 Many-Body Quantum Mechanics
20(3)
3.2 Density-Functional Theory
23(17)
3.2.1 Exchange and Correlation
28(5)
3.2.2 Basis Sets
33(2)
3.2.3 The Pseudopotential Approximation
35(5)
3.3 Linear-Scaling DFT
40(3)
3.4 The Onetep Code
43(14)
3.4.1 The Periodic Cardinal Sine Function Basis Set
44(2)
3.4.2 Cutoff Coulomb Interactions
46(2)
3.4.3 Implicit Solvation
48(3)
3.4.4 Calculating the Local/Partial Density of States
51(1)
3.4.5 Empirical Dispersion Corrections
52(1)
3.4.6 Electrostatic Embedding and the QM/EE Approach
53(1)
3.4.7 Natural Bond Orbital Analysis
54(2)
3.4.8 Density Derived Electrostatic and Chemical Method for Computing Net Atomic Charges
56(1)
3.5 Structural Optimisation
57(10)
3.5.1 Calculation of Forces
57(2)
3.5.2 Normal Mode Analysis
59(2)
3.5.3 Transition State Searching
61(1)
3.5.4 Linear and Quadratic Synchronous Transit Methods
62(3)
3.5.5 The Eigenvector-Following Approach
65(2)
3.6 Classical Force Fields
67(2)
3.7 Hybrid Quantum Mechanics/Molecular Mechanics Approaches
69(3)
3.8 Summary
72(7)
References
72(7)
4 Validation Studies
79(16)
4.1 Ethene
80(2)
4.2 Alanine Dipeptide
82(7)
4.3 Pericyclic Chorismate Rearrangement
89(2)
4.4 Summary
91(4)
References
93(2)
5 Explaining the Closure of Calculated HOMO-LUMO Gaps in Biomolecular Systems
95(16)
5.1 Introduction
95(1)
5.2 Vanishing HOMO-LUMO Gaps
96(1)
5.3 Water Clusters
97(7)
5.4 Protein Systems
104(4)
5.5 Summary
108(3)
References
110(1)
6 A Density-Functional Perspective on the Chorismate Mutase Enzyme
111(32)
6.1 Introduction
112(5)
6.2 General Preparation and Optimisation of Systems
117(6)
6.2.1 Specific Preparation of the Enzyme System
118(3)
6.2.2 Specific Preparation of System in Solution
121(2)
6.3 Rearrangement in Enzyme
123(3)
6.4 Natural Bond Orbital Analysis
126(2)
6.5 Structural Analysis
128(2)
6.6 Rearrangement in Solution
130(2)
6.7 DDEC and NPA Charge Analysis
132(3)
6.8 Discussion
135(3)
6.9 Summary
138(5)
References
139(4)
7 Concluding Remarks
143(5)
7.1 Summary of Dissertation
143(3)
7.2 Suggestions for Further Work
146(2)
References 148
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.