Zuckerman Statistical Physics of Biomolecules

An Introduction
1. Auflage 2011
ISBN: 978-1-4200-7379-9
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 356 Seiten

From the hydrophobic effect to protein-ligand binding, statistical physics is relevant in almost all areas of molecular biophysics and biochemistry, making it essential for modern students of molecular behavior. But traditional presentations of this material are often difficult to penetrate. Statistical Physics of Biomolecules: An Introduction brings "down to earth" some of the most intimidating but important theories of molecular biophysics.

With an accessible writing style, the book unifies statistical, dynamic, and thermodynamic descriptions of molecular behavior using probability ideas as a common basis. Numerous examples illustrate how the twin perspectives of dynamics and equilibrium deepen our understanding of essential ideas such as entropy, free energy, and the meaning of rate constants. The author builds on the general principles with specific discussions of water, binding phenomena, and protein conformational changes/folding. The same probabilistic framework used in the introductory chapters is also applied to non-equilibrium phenomena and to computations in later chapters. The book emphasizes basic concepts rather than cataloguing a broad range of phenomena.
Focuses on what students need to know now

Students build a foundational understanding by initially focusing on probability theory, low-dimensional models, and the simplest molecular systems. The basics are then directly developed for biophysical phenomena, such as water behavior, protein binding, and conformational changes. The book’s accessible development of equilibrium and dynamical statistical physics makes this a valuable text for students with limited physics and chemistry backgrounds.

Zielgruppe

First-year graduate and upper-level undergraduate students in biophysics and/or computational biology programs, students studying statistical mechanics in physics and chemistry programs, and researchers in computer science, physics, and mathematics pursuing an interest in biology.

Autoren/Hrsg.

Zuckerman, Daniel M.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Naturwissenschaften Physik Physik Allgemein

Inhaltsverzeichnis

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 Rea