Chemical Modelling: Applications and Theory Volume 5 (Specialist Periodical Reports, Band 5) - Hardcover

Evans, D. J.; Karadakov, P. B.; Kitchin, J. R.; Lewis, R. A.

Hardcover

ISBN 10: 0854042482 ISBN 13: 9780854042487

Verlag: Royal Society of Chemistry, 2008

Inhaltsangabe

Chemical Modelling: Applications and Theory comprises critical literature reviews of molecular modelling, both theoretical and applied. Molecular modelling in this context refers to modelling the structure, properties and reactions of atoms, molecules & materials. Each chapter is compiled by experts in their fields and provides a selective review of recent literature. With chemical modelling covering such a wide range of subjects, this Specialist Periodical Report serves as the first port of call to any chemist, biochemist, materials scientist or molecular physicist needing to acquaint themselves of major developments in the area. Volume 5 covers literature published from June 2005 to May 2007.

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Chemical Modelling: Applications and Theory comprises critical literature reviews of molecular modelling, both theoretical and applied. Molecular modelling in this context refers to modelling the structure, properties and reactions of atoms, molecules & materials. Each chapter is compiled by experts in their fields and provides a selective review of recent literature, incorporating sufficient historical perspective for the non-specialist to gain an understanding.

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Chemical Modelling Applications and Theory Volume 5

A Review of the Literature Published Between June 2005 and May 2007

By A. Hinchliffe

The Royal Society of Chemistry

Copyright © 2008 The Royal Society of Chemistry
All rights reserved.

ISBN: 978-0-85404-248-7

Contents

Preface Alan Hinchliffe, 7, 
Multiscale modelling of biological systems Christopher J. Woods and Adrian J. Mulholland, 13, 
Computer-aided drug design 2005–2007 Richard A. Lewis, 51, 
Solvation effects Michael Springborg, 67, 
The solid state E. A. Moore, 119, 
Density functional theory studies of alloys in heterogeneous catalysis John R. Kitchin, Spencer D. Miller and David S. Sholl, 50, 
Fluctuation relations, free energy calculations and irreversibility Debra J. Searles and Denis J. Evans, 182, 
Many-body perturbation theory and its application to the molecular tructure problem S. Wilson, 208, 
Experiment and theory in the determination of molecular hyperpolarizabilities in solution; pNA and MNA in dioxane David Pugh, 249, 
The floating spherical Gaussian orbital (FSGO) method A. H. Pakiari, 279, 
Advances in valence bond theory Peter B. Karadakov, 312, 
Numerical methods in chemistry T. E. Simos, 350, 

CHAPTER 1

Multiscale modelling of biological systems

Christopher J. Woods and Adrian J. Mulholland

DOI:10.1039/b608778g

1. Introduction

At what point does a collection of molecules become a biomolecular system? At what length scale does biology begin, and chemistry end? Biological phenomena involve the flow of information across a range of length and timescales. For example, a cell may be placed under physical stress at the macroscopic level, which causes an increase in pressure within its protective membrane. This pressure has the effect of opening or closing mechanosensitive ion channels, thereby changing the flow of individual ions into the cell. This changes the ionic concentration within the cell, which then acts as the trigger for a signal sent via a protein signalling pathway. A chemist would look at this as a molecular system that was capable of converting mechanical forces into electrical signals. A biologist would however look at this as the mechanism a cell uses to adapt to stress, and thereby stay alive. Biology is full of such examples. Every thought we have involves the passage of signals between neurons, which itself requires the conversion of electrical signals into flows of ions. These ions trigger the release of neurotransmitter molecules, which cross the synaptic gap between neurons, and bind to individual receptor proteins at the synapse. This causes a change in protein conformation, which open nearby ion channels, causing ions to rush in or out of the neuron, thereby continuing the signal. Information is constantly flowing between the macroscopic world and the atomic, chemical world. Indeed it is this interplay between the chemical and macroscopic worlds that is a real beauty of biology, and it is the recent advances made by the science of biochemistry that has revealed the elegance of the chemicals of life to all. However, while it is possible to use a microscope to watch how an individual cell responds to external stimuli, it is not possible to 'zoom in' further and observe what is occurring at the chemical level. Experiments can infer what is happening, and can provide supporting evidence for a particular hypothesis, but there is no experimental technique or microscope that allows us to watch a chemical reaction within an enzyme active site. Until such techniques are developed, the most appealing route that currently exists is to use computers to create models of the biochemical world. Computational scientists can create virtual enzymes, and models of cell membranes, and then use these to provide a window through which the interactions of biomolecules can be observed. If the models are constructed on the firm foundations of physics and chemistry, and if their predictions are carefully compared and validated against experiment, then simulations using these models can provide the valuable insight necessary to link the chemical and biological worlds.

Computational scientists have developed many tools for modelling molecules. Computer models are not perfect recreations of reality. Instead, approximations and assumptions have to made, and the model compromised for the sake of computational efficiency. As the size of the system gets larger, and so the size and number of molecules increases, so to does the computational expense of the calculation. This means that the larger the system, the more compromises and approximations must be made. This act of compromise has led computational scientists to develop four main levels of biomolecular modelling:

1. Quantum mechanics (QM). Quantum chemical calculations model the fine detail of the electrons in the molecule. They achieve this by modelling the electrons as a quantum mechanics wavefunction that interacts with the electrostatic potential field generated by the atomic nuclei. Quantum chemical calculations provide the most physically realistic and accurate models of molecules, but this accuracy comes at a cost. While methods have been developed that allow QM calculations on complete proteins, in general the high computational expense of QM methods limits their application to small molecular systems.

2. Molecular mechanics (MM). Atomistic molecular mechanics calculations apply the assumption that the fine detail information about the behaviour of the electrons can be ignored, and instead they are approximated by representing their effects using simple descriptors such as atomic partial charges or polarisabilities. By modelling the electrons implicitly, MM methods are much less expensive than QM methods, and so they are able to model significantly larger systems. By including atomic detail, MM models are still limited to the molecular level, and even today's largest applications can only achieve the modelling of hundreds of thousands of atoms over hundreds of nanoseconds.

3. Coarse grain (CG). Coarse grain (or coarse grained) calculations apply the assumption that the fine detail information about the position of each atom in the molecule can be ignored, and instead groups of atoms are approximated by smearing them out into single 'beads'. So, for example, rather than modelling each atom in a protein, a CG representation would portray each residue as a single bead. This approximation allows CG simulations to achieve length and timescales that are far beyond those possible using atomistic MM models.

4. Continuum. Continuum models apply the assumption that the fine detail information about the location of any particles or groups can be ignored, and instead systems are modelled as continuum regions. For example, implicit solvent models ignore the location of each individual solvent molecule, but instead represent the complete solvent as a fuzzy dielectric continuum. Equally, continuum models of a cell membrane ignore the individual locations of each lipid molecule, and instead model the membrane as a homogenous elastic sheet. By ignoring particles, and instead modelling biological systems as continuous fields or homogenous assemblies, continuum models are able to simulate the largest length scales and longest time-scales of any of the four levels.

These four levels of biomolecular modelling are each well-suited to modelling phenomena at the length and timescales for which they were designed. However, what makes biology work, and what makes it scientifically interesting,...

Details zur Ausgabe

• Verlag: Royal Society of Chemistry
• Erscheinungsdatum: 2008
• Sprache: Englisch
• ISBN 10: 0854042482
• ISBN 13: 9780854042487
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 400
• Herausgeber: Hinchliffe A.
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar