Statistical physics of biomolecules : an introduction /: an introduction. (©2010)

• Record Type: Book
• Further Information: Note: Daniel M. Zuckerman.
• Other Names: Zuckerman, Daniel M
• Contents: Proteins Don’t Know Biology; Prologue: 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 Dimension; Introduction; 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 Distribution Function; PMFs Are the Typical Basis for "Knowledge-Based" ("Statistical") Potentials; Summary: The Meaning, Uses, and Limitations of the PMF; ; What’s Free about "Free" Energy? Essential Thermodynamics ; Introduction; Statistical Thermodynamics: Can You Take a Derivative?; You Love the Ideal Gas; Boring but True: The First Law Describes Energy Conservation; G vs. F: Other Free Energies and Why They (Sort of ) Matter; Overview of Free Energies and Derivatives; The Second Law and (Sometimes) Free Energy Minimization; Calorimetry: A Key Thermodynamic Technique; The Bare-Bones Essentials of Thermodynamics; Key Topics Omitted from This Chapter; ; The Most Important Molecule: Electro-Statistics of Water; Basics of Water Structure; Water Molecules Are Structural Elements in Many Crystal Structures; The pH of Water and Acid–Base Ideas; Hydrophobic Effect; Water Is a Strong Dielectric; Charges in Water + Salt = Screening; A Brief Word on Solubility; Summary; Additional Problem: Understanding Differential Electrostatics; ; Basics of Binding and Allostery; A Dynamical View of Binding: On- and Off-Rates; Macroscopic Equilibrium and the Binding Constant; A Structural-Thermodynamic View of Binding; Understanding Relative Affinities: ∆∆G and Thermodynamic Cycles; Energy Storage in "Fuels" Like ATP; Direct Statistical Mechanics Description of Binding; Allostery and Cooperativity; Elementary Enzymatic Catalysis; pH AND pKa; Summary; ; Kinetics of Conformational Change and Protein Folding; Introduction: Basins, Substates, and States; Kinetic Analysis of Multistate Systems; Conformational and Allosteric Changes in Proteins; Protein Folding; Summary; ; Ensemble Dynamics: From Trajectories to Diffusion and Kinetics; Introduction: Back to Trajectories and Ensembles; One-Dimensional Ensemble Dynamics; Four Key Trajectory Ensembles; From Trajectory Ensembles to Observables; Diffusion and Beyond: Evolving 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; ;
• Publisher Details: Boca Raton, FL : CRC Press/Taylor & Francis
• Publication Date: 2010
• Copyright Date: 2010
• Extent: 1 online resource (xxi, 334 pages), illustrations
• Subjects: 572; Biophysics; Statistical physics; Biomolecules; Biophysics; Computational Biology; Statistics as Topic; Biomolecules; Biophysics; Statistical physics; Electronic books
• Languages: English
• ISBNs: 9781420073799; 1420073796
• Related ISBNs: 9781420073782; 1420073788
• Notes: Note: Includes bibliographical references and index.; Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.