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