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Large-Scale Quantum-Mechanical Enzymology / by Greg Lever.

Springer Nature - Springer Physics and Astronomy (R0) eBooks 2015 English International Available online

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Format:
Book
Author/Creator:
Lever, Greg., Author.
Series:
Springer Theses, Recognizing Outstanding Ph.D. Research, 2190-5053
Language:
English
Subjects (All):
Biophysics.
Chemistry, Physical and theoretical.
Bioinformatics.
Proteins.
Enzymology.
Biological and Medical Physics, Biophysics.
Physical Chemistry.
Computational Biology/Bioinformatics.
Protein Science.
Local Subjects:
Biological and Medical Physics, Biophysics.
Physical Chemistry.
Computational Biology/Bioinformatics.
Protein Science.
Enzymology.
Physical Description:
1 online resource (162 p.)
Edition:
1st ed. 2015.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2015.
Language Note:
English
Summary:
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.
Contents:
Introduction
Proteins, Enzymes and Biological Catalysis
Computational Techniques
Validation Studies
Explaining the Closure of CHOMO-LUMO Gaps in Biomolecular Systems
A Density-Functional Perspective on the Chorismate Mutase Enzyme
Concluding Remarks.
Notes:
Description based upon print version of record.
Includes bibliographical references at the end of each chapters.
ISBN:
3-319-19351-1

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