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Books on the topic 'Molecular simulation techniques'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Madeleine, Meyer, Pontikis Vassilis, and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Computer simulation in materials science: Interatomic potentials, simulation techniques, and applications. Dordrecht: Kluwer Academic Publishers, 1991.

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2

Hans-Dieter, Höltje, ed. Molecular modeling: Basic principles and applications. 2nd ed. Weinheim: Wiley-VCH, 2003.

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3

1928-, Watson James D., ed. Molecular biology of the gene. 5th ed. Delhi: Pearson Education, 2004.

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4

1928-, Watson James D., ed. Molecular biology of the gene. 5th ed. San Francisco, California: Pearson/Benjamin Cummings, 2004.

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5

1928-, Watson James D., ed. Molecular biology of the gene. 4th ed. Menlo Park, California: Benjamin/Cummings, 1987.

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6

1928-, Watson James D., ed. Molecular biology of the gene. 4th ed. Menlo Park, California: Benjamin/Cummings Pub. Co., 1988.

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7

1928-, Watson James D., ed. Molecular biology of the gene. 6th ed. San Francisco: Pearson/Benjamin Cummings, 2008.

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8

1928-, Watson James D., ed. Molecular biology of the gene. 5th ed. San Francisco: Pearson/Benjamin Cummings, 2004.

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9

Real-time biomolecular simulations: The behavior of biological macromolecules from a cellular systems perspective. New York: McGraw Hill, 2007.

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10

Hoover, William G., and Carol Griswold Hoover. Microscopic and Macroscopic Simulation Techniques: Kharagpur Lectures. World Scientific Publishing Co Pte Ltd, 2018.

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11

Kholmurodov, Kholmirzo T. Models in Bioscience and Materials Research: Molecular Dynamics and Related Techniques. Nova Science Publishers, Incorporated, 2013.

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12

Allen, Michael P., and Dominic J. Tildesley. Computer Simulation of Liquids. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.001.0001.

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This book provides a practical guide to molecular dynamics and Monte Carlo simulation techniques used in the modelling of simple and complex liquids. Computer simulation is an essential tool in studying the chemistry and physics of condensed matter, complementing and reinforcing both experiment and theory. Simulations provide detailed information about structure and dynamics, essential to understand the many fluid systems that play a key role in our daily lives: polymers, gels, colloidal suspensions, liquid crystals, biological membranes, and glasses. The second edition of this pioneering book aims to explain how simulation programs work, how to use them, and how to interpret the results, with examples of the latest research in this rapidly evolving field. Accompanying programs in Fortran and Python provide practical, hands-on, illustrations of the ideas in the text.

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13

Molecular Gas Dynamics: Theory, Techniques, and Applications (Modeling and Simulation in Science, Engineering and Technology). Birkhäuser Boston, 2006.

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14

Folkers, Gerd, Wolfgang Sippl, Didier Rognan, and Hans-Dieter Höltje. Molecular Modeling: Basic Principles and Applications. 2nd ed. Wiley-VCH, 2003.

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15

Molecular modeling: Basic principles and applications. 2nd ed. Weinheim: Wiley-VCH, 2003.

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16

Hans-Dieter, Höltje, ed. Molecular modeling: Basic principles and applications. 3rd ed. Weinheim: VCH, 2008.

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17

Allen, Michael P., and Dominic J. Tildesley. Quantum simulations. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0013.

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This chapter covers the introduction of quantum mechanics into computer simulation methods. The chapter begins by explaining how electronic degrees of freedom may be handled in an ab initio fashion and how the resulting forces are included in the classical dynamics of the nuclei. The technique for combining the ab initio molecular dynamics of a small region, with classical dynamics or molecular mechanics applied to the surrounding environment, is explained. There is a section on handling quantum degrees of freedom, such as low-mass nuclei, by discretized path integral methods, complete with practical code examples. The problem of calculating quantum time correlation functions is addressed. Ground-state quantum Monte Carlo methods are explained, and the chapter concludes with a forward look to the future development of such techniques particularly to systems that include excited electronic states.

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18

Computational and Visualization Techniques for Structural Bioinformatics Using Chimera Chapman HallCRC Mathematical Computational Biology. CRC Press, 2013.

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19

Zaheer Ul-Haq and Angela K. Wilson, eds. Frontiers in Computational Chemistry: Volume 6. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150368481220601.

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Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The sixth volume of this series features these six different perspectives on the application of computational chemistry in rational drug design: 1. Computer-aided molecular design in computational chemistry 2. The role of ensemble conformational sampling using molecular docking & dynamics in drug discovery 3. Molecular dynamics applied to discover antiviral agents 4. Pharmacophore modeling approach in drug discovery against the tropical infectious disease malaria 5. Advances in computational network pharmacology for Traditional Chinese Medicine (TCM) research 6. Progress in electronic-structure based computational methods: from small molecules to large molecular systems of biological significance

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20

Watson, James. Biologia molecular del gen. 5th ed. Editorial Medica Panamericana, 2006.

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21

Molecular biology of the gene. Pearson, 2013.

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22

Molecular biology of the gene. Pearson, 2014.

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23

Watson, James. Molecular Biology of the Gene. 4th ed. Benjamin-Cummings Publishing Company, 1997.

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24

D, Watson James. Molecular biology of the gene. 4th ed. Benjamin-Cummings Publishing Company, 2001.

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25

Watson, James. Molecular biology of the gene. Benjamin-Cummings Publishing Company, Subs of Addison Wesley Longman, Inc, 2005.

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26

Gann, Alexander, Watson James D, Richard Losick, Tania A. Baker, Stephen P. Bell, and Michael Levine. Molecular biology of the gene. 6th ed. Benjamin Cummings, 2007.

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27

Gann, Alexander, Watson James D, Richard Losick, Tania A. Baker, Stephen P. Bell, and Michael Levine. Molecular biology of the gene. 5th ed. Benjamin Cummings, 2003.

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28

Uversky, Vladimir N., and Yuri Lyubchenko. Bio-Nanoimaging: Protein Misfolding and Aggregation. Elsevier Science & Technology Books, 2013.

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29

Uversky, Vladimir, and Yuri Lyubchenko. Bio-Nanoimaging: Protein Misfolding and Aggregation. Elsevier Science & Technology Books, 2013.

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30

D, Watson James. Molecular Biology of the Gene: Volume 1. 4th ed. Benjamin-Cummings Publishing Company, 1986.

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31

Allen, Michael P., and Dominic J. Tildesley. Advanced Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0009.

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This chapter describes the ways in which the Monte Carlo importance sampling method may be adapted to improve the calculation of ensemble averages, particularly those associated with free energy differences. These approaches include umbrella sampling, non-Boltzmann sampling, the Wang–Landau method, and nested sampling. In addition, a range of special techniques have been developed to accelerate the simulation of flexible molecules, such as polymers. These approaches are illustrated with scientific examples and program code. The chapter also explains the analysis of such simulations using techniques such as weighted histograms, and acceptance ratio calculations. Practical advice on selection of methods, parameters, and the direction in which to make comparisons, are given. Monte Carlo methods for modelling phase equilibria and chemical reactions at equilibrium are described.

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32

D, Watson James, Alan M. Weiner, Nancy H. Hopkins, Jeffrey W. Roberts, and Joan Argetsinger Steitz. Molecular Biology of the Gene, Volume II (4th Edition). 4th ed. Benjamin Cummings, 1987.

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33

1936-, Martin Yvonne Connolly, and Willett Peter 1953-, eds. Designing bioactive molecules: Three-dimensional techniques and applications. Washington, DC: American Chemical Society, 1998.

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34

Designing Bioactive Molecules: Three-Dimensional Techniques and Applications (Computer Applications in Chemistry Collection). An American Chemical Society Publication, 1998.

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35

Boero, Mauro, and Masaru Tateno. Quantum-theoretical approaches to proteins and nucleic acids. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533046.013.17.

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This article describes quantum methods used to study proteins and nucleic acids: Hartree–Fock all-electron approaches, density-functional theory approaches, and hybrid quantum-mechanics/molecular-mechanics approaches. In addition to an analysis of the electronic structure, quantum-mechanical approaches for simulating proteins and nucleic acids can elucidate the cleavage and formation of chemical bonds in biochemical reactions. This presents a computational challenge, and a number of methods have been proposed to overcome this difficulty, including enhanced temperature methods such as high-temperature molecular dynamics, parallel tempering and replica exchange. Alternative methods not relying on the knowledge a priori of the final products make use of biasing potentials to push the initial system away from its local minimum and to enhance the sampling of the free-energy landscape. This article considers two of these biasing techniques, namely Blue Moon and metadynamics.

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36

Drug Design: Cutting Edge Approaches. Royal Society of Chemistry, 2003.

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