Entropy and Thermodynamics in Biomolecular Simulation

Entropy and Thermodynamics in Biomolecular Simulation

Jorge Numata (Freie Universität Berlin, Germany)
Copyright: © 2009 |Pages: 28
DOI: 10.4018/978-1-60566-076-9.ch041
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Thermodynamics is one of the best established notions in science. Some recent work in biomolecular modeling has sacrificed its rigor in favor of trendy empirical methods. Even in cases where physicsbased energy functions are used, entropy is forgotten or left “for later versions”. This text gives an overview of the utility of a more rigorous treatment of thermodynamics at the molecular level in order to understand protein folding and receptor-ligand binding. An intuitive understanding of thermodynamics is conveyed: enthalpy is the quantity of energy, while entropy stands for its quality. Recent advances in entropy estimation from information theory and physical chemistry are outlined as they apply to biological thermodynamics. The different enthalpic, entropic, and kinetic driving forces behind protein folding and binding are detailed. Finally, some medical applications enabled by an understanding of the free energy folding funnel concept are outlined, such as HIV-1 protease folding inhibitors.
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An Intuitive Notion Of Entropy

Internal energy and enthalpy quantify energy. Entropy measures the quality of that energy; the lower its entropy, the more useful that energy is.

Key Terms in this Chapter

Conformer: Collection of macrostate conformations of a molecule or protein with similar energies around a major energy well. Well-known examples are the boat and chair conformers of cyclohexane and glucose.

Configurational Energy Landscape: Also known as the Potential energy surface. It is a highly dimensional surface depicting the potential energy of a molecule against each distance coordinate.

Free Energy: A criterion for stability which predicts the direction of a process connecting two states. A system will undergo a process spontaneously if it lowers its free energy. For example, a partially unfolded, denatured protein in a high free energy state will fold to its native state with lower free energy. Free energy encompasses together energetic (enthalpic) and entropic driving forces.

Folding Funnel: Also known as the free energy landscape. In its reduced 3D projection, it is a cartoon of what actually is a highly dimensional free energy surface. The folding funnel is a representation of the change in enthalpy (vertical axis) and conformational entropy (both horizontal axes) during protein folding.

Microstate: Individual, unique conformation of a molecule with a given energy. Experimentally indistinguishable from other conformations with identical energy and similar conformation.

Entropy: A counting of the states available to a system in a logarithmic scale. In thermodynamics, this is multiplied by Boltzmann’s constant k B , which is only due to our arbitrary choice for the units of temperature. Entropy in information theory and thermodynamics is equally a measure of the multiplicity of states.

Hydrophobic Effect: The tendency of large solutes to gather together when solvated in associating liquids. The hydrophobic effect causes phase separation of oil drops in water at room temperature mostly to avoid disturbing the hydrogen bonding pattern of water. The disturbance of hydrogen bonding by oil causes a lowering of entropy. Phase separation occurs to raise the water entropy and lower the total free energy of the whole solution. The hydrophobic effect is the main driving force for protein folding, causing polypeptide chains to collapse onto themselves. Generalized to associating solvents other than water, it is known as the solvophobic effect.

Configurational Entropy: It is the conformational entropy plus the entropy due spatial rearrangements. For example, water has an internal molecular conformational freedom (vibrational, rotational and translational) and can also become rearranged in several hydrogen bonding constellations, giving it configurational freedom.

Macrostate: A collection of individual conformations (microstates) with the same energy. Experimentally accessible.

Conformational Entropy: A measure of the internal freedom of a molecule, having contributions from vibrations (like stretching), rotations and translations. It is a logarithmic measure of the density of states (multiplicity) of a macrostate or conformer.

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Editorial Advisory Board
Table of Contents
Ralf Herwig
Andriani Daskalaki
Andriani Daskalaki
Chapter 1
Peter Ghazal
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Pathway Biology Approach to Medicine
Chapter 2
Peter Wellstead, Sree Sreenath, Kwang-Hyun Cho
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Systems and Control Theory for Medical Systems Biology
Chapter 3
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Mathematical Description of Time Delays in Pathways Cross Talk
Chapter 4
Elisabeth Maschke-Dutz
In this chapter basic mathematical methods for the deterministic kinetic modeling of biochemical systems are described. Mathematical analysis... Sample PDF
Deterministic Modeling in Medicine
Chapter 5
Andrew Kuznetsov
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Synthetic Biology as a Proof of Systems Biology
Chapter 6
Tuan D. Pham
Computational models have been playing a significant role for the computer-based analysis of biological and biomedical data. Given the recent... Sample PDF
Computational Models for the Analysis of Modern Biological Data
Chapter 7
Vanathi Gopalakrishnan
This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of... Sample PDF
Computer Aided Knowledge Discovery in Biomedicine
Chapter 8
Thomas Meinel
The function of proteins is a main subject of research in systems biology. Inference of function is now, more than ever, required by the upcoming of... Sample PDF
Function and Homology of Proteins Similar in Sequence: Phylogenetic Profiling
Chapter 9
Nikolaos G. Sgourakis, Pantelis G. Bagos, Stavros J. Hamodrakas
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Computational Methods for the Prediction of GPCRs Coupling Selectivity
Chapter 10
Pantelis G. Bagos, Stavros J. Hamodrakas
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Bacterial ß-Barrel Outer Membrane Proteins: A Common Structural Theme Implicated in a Wide Variety of Functional Roles
Chapter 11
L.K. Flack
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Clustering Methods for Gene-Expression Data
Chapter 12
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The presentation and interpretation of microarray-based genome-wide gene expression profiles as complex biological entities are considered to be... Sample PDF
Uncovering Fine Structure in Gene Expression Profile by Maximum Entropy Modeling of cDNA Microarray Images and Kernel Density Methods
Chapter 13
Wasco Wruck
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Gene Expression Profiling with the BeadArrayTM Platform
Chapter 14
Djork-Arné Clevert, Axel Rasche
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The Affymetrix GeneChip® Microarray Platform
Chapter 15
Jacek Majewski
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Alternative Isoform Detection Using Exon Arrays
Chapter 16
Prerak Desai
The use of systems biology to study complex biological questions is gaining ground due to the ever-increasing amount of genetic tools and genome... Sample PDF
Gene Expression in Microbial Systems for Growth and Metabolism
Chapter 17
Heike Stier
Alternative splicing is an important part of the regular process of gene expression. It controls time and tissue dependent expression of specific... Sample PDF
Alternative Splicing and Disease
Chapter 18
Axel Kowald
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Mathematical Modeling of the Aging Process
Chapter 19
Evgenia Makrantonaki
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The Sebaceous Gland: A Model of Hormonal Aging
Chapter 20
R. Seigneuric, N.A.W. van Riel, M.H.W. Starmans, A. van Erk
Complex diseases such as cancer have multiple origins and are therefore difficult to understand and cure. Highly parallel technologies such as DNA... Sample PDF
Systems Biology Applied to Cancer Research
Chapter 21
Matej Orešic, Antonio Vidal-Puig
In this chapter the authors report on their experience with the analysis and modeling of data obtained from studies of animal models related to... Sample PDF
Systems Biology Strategies in Studies of Energy Homeostasis In Vivo
Chapter 22
Axel Rasche
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Approaching Type 2 Diabetes Mellitus by Systems Biology
Chapter 23
Alia Benkahla, Lamia Guizani-Tabbane, Ines Abdeljaoued-Tej, Slimane Ben Miled, Koussay Dellagi
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Systems Biology and Infectious Diseases
Chapter 24
Daniela Albrecht, Reinhard Guthke
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Systems Biology of Human-Pathogenic Fungi
Chapter 25
Jessica Ahmed
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Development of Specific Gamma Secretase Inhibitors
Chapter 26
Paul Wrede
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In Machina Systems for the Rational De Novo Peptide Design
Chapter 27
Ferda Mavituna, Raul Munoz-Hernandez, Ana Katerine de Carvalho Lima Lobato
This chapter summarizes the fundamentals of metabolic flux balancing as a computational tool of metabolic engineering and systems biology. It also... Sample PDF
Applications of Metabolic Flux Balancing in Medicine
Chapter 28
Roberta Alfieri, Luciano Milanesi
This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different... Sample PDF
Multi-Level Data Integration and Data Mining in Systems Biology
Chapter 29
Hendrik Hache
In this chapter, different methods and applications for reverse engineering of gene regulatory networks that have been developed in recent years are... Sample PDF
Methods for Reverse Engineering of Gene Regulatory Networks
Chapter 30
Alok Mishra
This chapter introduces the techniques that have been used to identify the genetic regulatory modules by integrating data from various sources. Data... Sample PDF
Data Integration for Regulatory Gene Module Discovery
Chapter 31
Elizabeth Santiago-Cortés
Biological systems are composed of multiple interacting elements; in particular, genetic regulatory networks are formed by genes and their... Sample PDF
Discrete Networks as a Suitable Approach for the Analysis of Genetic Regulation
Chapter 32
A. Maffezzoli
In this chapter, authors review main methods, approaches, and models for the analysis of neuronal network data. In particular, the analysis concerns... Sample PDF
Investigating the Collective Behavior of Neural Networks: A Review of Signal Processing Approaches
Chapter 33
Paolo Vicini
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The System for Population Kinetics: Open Source Software for Population Analysis
Chapter 34
Julia Adolphs
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Photosynthesis: How Proteins Control Excitation Energy Transfer
Chapter 35
Michael R. Hamblin
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Photodynamic Therapy: A Systems Biology Approach
Chapter 36
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Alexey R. Brazhe, Nadezda A. Brazhe, Alexey N. Pavlov, Georgy V. Maksimov
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Interference Microscopy for Cellular Studies
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Chapter 39
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Protein Interactions and Diseases
Chapter 40
Bernard de Bono
From a genetic perspective, disease can be interpreted in terms of a variation in molecular sequence or expression (dose) that impairs normal... Sample PDF
The Breadth and Depth of BioMedical Molecular Networks: The Reactome Perspective
Chapter 41
Jorge Numata
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Entropy and Thermodynamics in Biomolecular Simulation
Chapter 42
Isabel Reinecke, Peter Deuflhard
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Model Development and Decomposition in Physiology
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