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Statistical physics of biomolecules : an introduction /
Proteins Don't Know BiologyPrologue: Statistical Physics of Candy, Dirt, and Biology Guiding Principles About This Book Molecular Prologue: A Day in the Life of Butane What Does Equilibrium Mean to a Protein? A Word on Experiments Making Movies: Basic Molecular Dynamics Simulation Basic Protein...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press/Taylor & Francis,
©2010.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Zuckerman, Daniel M. | |
| 245 | 1 | 0 | |a Statistical physics of biomolecules : |b an introduction / |c Daniel M. Zuckerman. |
| 260 | |a Boca Raton, FL : |b CRC Press/Taylor & Francis, |c ©2010. | ||
| 300 | |a 1 online resource (xxi, 324 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |g Chapter 1. |t Proteins Don't Know Biology -- |t Prologue: Statistical Physics of Candy, Dirt, and Biology -- |t Guiding Principles -- |t About This Book -- |t Molecular Prologue: A Day in the Life of Butane -- |t What Does Equilibrium Mean to a Protein? -- |t A Word on Experiments -- |t Making Movies: Basic Molecular Dynamics Simulation -- |t Basic Protein Geometry -- |t A Note on the Chapters -- |g Chapter 2. |t The Heart of It All: Probability Theory -- |t Introduction -- |t Basics of One-Dimensional Distributions -- |t Fluctuations and Error -- |t Two+ Dimensions: Projection and Correlation -- |t Simple Statistics Help Reveal a Motor Protein's Mechanism -- |t Additional Problems: Trajectory Analysis -- |g Chapter 3. |t Big Lessons from Simple Systems: Equilibrium Statistical Mechanics in One Dimension -- |t Introduction -- |t Energy Landscapes Are Probability Distributions -- |t States, Not Configurations -- |t Free Energy: It's Just Common Sense If You Believe in Probability -- |t Entropy: It's Just a Name -- |t Summing Up -- |t Molecular Intuition from Simple Systems -- |t Loose Ends: Proper Dimensions, Kinetic Energy -- |g Chapter 4. |t Nature Doesn't Calculate Partition Functions: Elementary Dynamics and Equilibrium -- |t Introduction -- |t Newtonian Dynamics: Deterministic but Not Predictable -- |t Barrier Crossing--Activated Processes -- |t Flux Balance: The Definition of Equilibrium -- |t Simple Diffusion, Again -- |t More on Stochastic Dynamics: The Langevin Equation -- |t Key Tools: The Correlation Time and Function -- |t Tying It All Together -- |t So Many Ways to ERR: Dynamics in Molecular Simulation -- |t Mini-Project: Double-Well Dynamics -- |g Chapter 5. |t Molecules Are Correlated! Multidimensional Statistical Mechanics -- |t Introduction -- |t A More-Than-Two-Dimensional Prelude -- |t Coordinates and Force Fields -- |t The Single-Molecule Partition Function -- |t Multimolecular Systems -- |t The Free Energy Still Gives the Probability -- |t Summary -- |g Chapter 6. |t From Complexity to Simplicity: The Potential of Mean Force -- |t Introduction: PMFs Are Everywhere -- |t The Potential of Mean Force Is Like a Free Energy -- |t The PMF May Not Yield the Reaction Rate or Transition State -- |t The Radial Distribution Function -- |t PMFs Are the Typical Basis for "Knowledge-Based" ("Statistical") Potentials -- |t Summary: The Meaning, Uses, and Limitations of the PMF -- |g Chapter 7. |t What's Free about "Free" Energy? Essential Thermodynamics -- |t Introduction -- |t Statistical Thermodynamics: Can You Take a Derivative? -- |t You Love the Ideal Gas -- |t Boring but True: The First Law Describes Energy Conservation -- |t G vs. F: Other Free Energies and Why They (Sort of ) Matter -- |t Overview of Free Energies and Derivatives -- |t The Second Law and (Sometimes) Free Energy Minimization -- |t Calorimetry: A Key Thermodynamic Technique -- |t The Bare-Bones Essentials of Thermodynamics -- |t Key Topics Omitted from This Chapter -- |g Chapter 8. |t The Most Important Molecule: Electro-Statistics of Water -- |t Basics of Water Structure -- |t Water Molecules Are Structural Elements in Many Crystal Structures -- |t The pH of Water and Acid-Base Ideas -- |t Hydrophobic Effect -- |t Water Is a Strong Dielectric -- |t Charges in Water + Salt = Screening -- |t A Brief Word on Solubility -- |t Summary -- |t Additional Problem: Understanding Differential Electrostatics -- |g Chapter 9. |t Basics of Binding and Allostery -- |t A Dynamical View of Binding: On- and Off-Rates -- |t Macroscopic Equilibrium and the Binding Constant -- |t A Structural-Thermodynamic View of Binding -- |t Understanding Relative Affinities: ∆∆G and Thermodynamic Cycles -- |t Energy Storage in "Fuels" Like ATP -- |t Direct Statistical Mechanics Description of Binding -- |t Allostery and Cooperativity -- |t Elementary Enzymatic Catalysis -- |t pH AND pKa -- |t Summary -- |g Chapter 10. |t Kinetics of Conformational Change and Protein Folding -- |t Introduction: Basins, Substates, and States -- |t Kinetic Analysis of Multistate Systems -- |t Conformational and Allosteric Changes in Proteins -- |t Protein Folding -- |t Summary -- |g Chapter 11. |t Ensemble Dynamics: From Trajectories to Diffusion and Kinetics -- |t Introduction: Back to Trajectories and Ensembles -- |t One-Dimensional Ensemble Dynamics -- |t Four Key Trajectory Ensembles -- |t From Trajectory Ensembles to Observables -- |t Diffusion and Beyond: Evolving Probability Distributions -- |t The Jarzynski Relation and Single-Molecule Phenomena -- |t Summary -- |g Chapter 12. |t A Statistical Perspective on Biomolecular Simulation -- |t Introduction: Ideas, Not Recipes -- |t First, Choose Your Model: Detailed or Simplified -- |t "Basic" Simulations Emulate Dynamics -- |t Metropolis Monte Carlo: A Basic Method and Variations -- |t Another Basic Method: Reweighting and Its Variations -- |t Discrete-State Simulations -- |t How to Judge Equilibrium Simulation Quality -- |t Free Energy and PMF Calculations -- |t Path Ensembles: Sampling Trajectories -- |t Protein Folding: Dynamics and Structure Prediction -- |t Summary -- |t Index. |
| 588 | 0 | |a Print version record. | |
| 520 | |a Proteins Don't Know BiologyPrologue: Statistical Physics of Candy, Dirt, and Biology Guiding Principles About This Book Molecular Prologue: A Day in the Life of Butane What Does Equilibrium Mean to a Protein? A Word on Experiments Making Movies: Basic Molecular Dynamics Simulation Basic Protein Geometry A Note on the Chapters The Heart of It All: Probability Theory Introduction Basics of One-Dimensional Distributions Fluctuations and Error Two+ Dimensions: Projection and Correlation Simple Statistics Help Reveal a Motor Protein's Mechanism Additional Problems: Trajectory Analysis Big Lessons from Simple Systems: Equilibrium Statistical Mechanics in One DimensionIntroduction Energy Landscapes Are Probability Distributions States, Not Configurations Free Energy: It's Just Common Sense If You Believe in Probability Entropy: It's Just a Name Summing Up Molecular Intuition from Simple Systems Loose Ends: Proper Dimensions, Kinetic Energy Nature Doesn't Calculate Partition Functions: Elementary Dynamics and Equilibrium Introduction Newtonian Dynamics: Deterministic but Not Predictable Barrier Crossing-Activated Processes Flux Balance: The Definition of Equilibrium Simple Diffusion, Again More on Stochastic Dynamics: The Langevin Equation Key Tools: The Correlation Time and Function Tying It All Together So Many Ways to ERR: Dynamics in Molecular Simulation Mini-Project: Double-Well Dynamics Molecules Are Correlated! Multidimensional Statistical Mechanics Introduction A More-Than-Two-Dimensional Prelude Coordinates and Force Fields The Single-Molecule Partition Function Multimolecular Systems The Free Energy Still Gives the Probability Summary From Complexity to Simplicity: The Potential of Mean Force Introduction: PMFs Are Everywhere The Potential of Mean Force Is Like a Free Energy The PMF May Not Yield the Reaction Rate or Transition State The Radial. | ||
| 520 | 8 | |a Probability Distributions The Jarzynski Relation and Single-Molecule Phenomena Summary A Statistical Perspective on Biomolecular Simulation Introduction: Ideas, Not Recipes First, Choose Your Model: Detailed or Simplified "Basic" Simulations Emulate Dynamics Metropolis Monte Carlo: A Basic Method and Variations Another Basic Method: Reweighting and Its Variations Discrete-State Simulations How to Judge Equilibrium Simulation Quality Free Energy and PMF Calculations Path Ensembles: Sampling Trajectories Protein Folding: Dynamics and Structure Prediction Summary Index. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Biophysics. | |
| 650 | 0 | |a Statistical physics. | |
| 650 | 0 | |a Biomolecules. | |
| 650 | 0 | |a Bioinformatics. | |
| 650 | 0 | |a Computational biology. | |
| 650 | 0 | |a Statistics. | |
| 650 | 1 | 2 | |a Biophysics |
| 650 | 2 | 2 | |a Computational Biology |
| 650 | 2 | 2 | |a Statistics as Topic |
| 650 | 6 | |a Biophysique. | |
| 650 | 6 | |a Physique statistique. | |
| 650 | 6 | |a Biomolécules. | |
| 650 | 6 | |a Bio-informatique. | |
| 650 | 6 | |a Statistiques. | |
| 650 | 6 | |a Statistique. | |
| 650 | 7 | |a statistics. |2 aat | |
| 650 | 7 | |a SCIENCE |x Life Sciences |x Biochemistry. |2 bisacsh | |
| 650 | 7 | |a Statistics |2 fast | |
| 650 | 7 | |a Computational biology |2 fast | |
| 650 | 7 | |a Bioinformatics |2 fast | |
| 650 | 7 | |a Biomolecules |2 fast | |
| 650 | 7 | |a Biophysics |2 fast | |
| 650 | 7 | |a Statistical physics |2 fast | |
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| 776 | 0 | 8 | |i Print version: |a Zuckerman, Daniel M. |t Statistical physics of biomolecules. |d Boca Raton, FL : CRC Press/Taylor & Francis, ©2010 |w (DLC) 2009050600 |w (OCoLC)473479036 |
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