Part Ⅰ Mysteries，Metaphors，Models 3
Chapter 1 What the Ancients Knew 3
1.1 Heat 3
1.1.1 Heat is a form of energy 4
1.1.2 Just a little history 6
1.1.3 Preview：The concept of free energy 8
1.2 How life generates order 9
1.2.1 The puzzle of biological order 9
1.2.2 Osmotic flow as a paradigm for free energy transduction 12
1.2.3 Preview：Disorder as information 14
1.3 Excursion：Commercials，philosophy，pragmatics 15
1.4 How to do better on exams （and discover new physical laws） 18
1.4.1 Most physical quantities carry dimensions 18
1.4.2 Dimensional analysis can help you catch errors and recall definitions 20
1.4.3 Dimensional analysis can also help you formulate hypotheses 22
1.4.4 Some notational conventions involving flux and density 22
1.5 Other key ideas from physics and chemistry 23
1.5.1 Molecules are small 23
1.5.2 Molecules are particular spatial arrangements of atoms 25
1.5.3 Molecules have well-defined internal energies 26
1.5.4 Low-density gases obey a universal law 27
The big picture 28
Track 2 30
Problems 31
Chapter 2 What’s Inside Cells 35
2.1 Cell physiology 37
2.1.1 Internal gross anatomy 40
2.1.2 External gross anatomy 43
2.2 The molecular parts list 45
2.2.1 Small molecules 46
2.2.2 Medium-sized molecules 48
2.2.3 Big molecules 50
2.2.4 Macromolecular assemblies 54
2.3 Bridging the gap：Molecular devices 54
2.3.1 The plasma membrane 55
2.3.2 Molecular motors 58
2.3.3 Enzymes and regulatory proteins 58
2.3.4 The overall flow of information in cells 59
The big picture 62
Track 2 63
Problems 64
Part Ⅱ Diffusion，Dissipation，Drive 69
Chapter 3 The Molecular Dance 69
3.1 The probabilistic facts of life 69
3.1.1 Discrete distributions 70
3.1.2 Continuous distributions 71
3.1.3 Mean and variance 73
3.1.4 Addition and multiplication rules 75
3.2 Decoding the ideal gas law 78
3.2.1 Temperature reflects the average kinetic energy of thermal motion 78
3.2.2 The complete distribution of molecular velocities is experimentally measurable 82
3.2.3 The Boltzmann distribution 83
3.2.4 Activation barriers control reaction rates 86
3.2.5 Relaxation to equilibrium 87
3.3 Excursion：A lesson from heredity 89
3.3.1 Aristotle weighs in 89
3.3.2 Identifying the physical carrier of genetic information 90
3.3.3 Schrodinger’s summary：Genetic information is structural 96
The big picture 101
Track 2 104
Problems 105
Chapter 4 Random Walks，Friction，and Diffusion 108
4.1 Brownian motion 109
4.1.1 Just a little more history 109
4.1.2 Random walks lead to diffusive behavior 110
4.1.3 The diffusion law is model independent 117
4.1.4 Friction is quantitatively related to diffusion 118
4.2 Excursion：Einstein’s role 121
4.3 Other random walks 122
4.3.1 The conformation of polymers 122
4.3.2 Vista：Random walks on Wall Street 126
4.4 More about diffusion 127
4.4.1 Diffusion rules the subcellular world 127
4.4.2 Diffusion obeys a simple equation 128
4.4.3 Precise statistical prediction of random processes 131
4.5 Functions，derivatives，and snakes under the rug 132
4.5.1 Functions describe the details of quantitative relationships 132
4.5.2 A function of two variables can be visualized as a landscape 134
4.6 Biological applications of diffusion 135
4.6.1 The permeability of artificial membranes is diffusive 135
4.6.2 Diffusion sets a fundamental limit on bacterial metabolism 138
4.6.3 The Nernst relation sets the scale of membrane potentials 139
4.6.4 The electrical resistance of a solution reflects frictional dissipation 142
4.6.5 Diffusion from a point gives a spreading，Gaussian profile 142
The big picture 144
Track 2 147
Problems 153
Chapter 5 Life in the Slow Lane：The Low Reynolds-Number World 158
5.1 Friction in fluids 158
5.1.1 Sufficiently small particles can remain in suspension indefinitely 158
5.1.2 The rate of sedimentation depends on solvent viscosity 160
5.1.3 It’s hard to mix a viscous liquid 161
5.2 Low Reynolds number 163
5.2.1 A critical force demarcates the physical regime dominated by friction 164
5.2.2 The Reynolds number quantifies the relative importance of friction and inertia 166
5.2.3 The time-reversal properties of a dynamical law signal its dissipative character 169
5.3 Biological applications 172
5.3.1 Swimming and pumping 172
5.3.2 To stir or not to stir？ 177
5.3.3 Foraging，attack，and escape 178
5.3.4 Vascular networks 179
5.3.5 Viscous drag at the DNA replication fork 182
5.4 Excursion：The character of physical Laws 184
The big picture 185
Track 2 187
Problems 190
Chapter 6 Entropy，Temperature，and Free Energy 195
6.1 How to measure disorder 196
6.2.Entropy 199
6.2.1 The Statistical Postulate 199
6.2.2 Entropy is a constant times the maximal value of disorder 200
6.3 Temperature 202
6.3.1 Heat flows to maximize disorder 202
6.3.2 Temperature is a statistical property of a system in equilibrium 203
6.4 The Second Law 206
6.4.1 Entropy increases spontaneously when a constraint is removed 206
6.4.2 Three remarks 209
6.5 Open systems 210
6.5.1 The free energy of a subsystem reflects the competition between entropy and energy 210
6.5.2 Entropic forces can be expressed as derivatives of the free energy 213
6.5.3 Free energy transduction is most efficient when it proceeds in small，controlled steps 214
6.5.4 The biosphere as a thermal engine 216
6.6 Microscopic systems 217
6.6.1 The Boltzmann distribution follows from the Statistical Postulate 218
6.6.2 Kinetic interpretation of the Boltzmann distribution 220
6.6.3 The minimum free energy principle also applies to microscopic subsystems 223
6.6.4 The free energy determines the populations of complex two-state systems 225
6.7 Excursion：“RNA folding as a two-state system” by J.Liphardt，I.Tinoco，Jr.，and C.Bustamante 226
The big picture 229
Track 2 232
Problems 239
Chapter 7 Entropic Forces at Work 245
7.1 Microscopic view of entropic forces 246
7.1.1 Fixed-volume approach 246
7.1.2 Fixed-pressure approach 247
7.2 Osmotic pressure 248
7.2.1 Equilibrium osmotic pressure follows the ideal gas law 248
7.2.2 Osmotic pressure creates a depletion force between large molecules 251
7.3 Beyond equilibrium：Osmotic flow 254
7.3.1 Osmotic forces arise from the rectification of Brownian motion 255
7.3.2 Osmotic flow is quantitatively related to forced permeation 259
7.4 A repulsive interlude 260
7.4.1 Electrostatic interactions are crucial for proper cell functioning 261
7.4.2 The Gauss Law 263
7.4.3 Charged surfaces are surrounded by neutralizing ion clouds 264
7.4.4 The repulsion of like-charged surfaces arises from compression of their ion clouds 269
7.4.5 Oppositely charged surfaces attract by counterion release 272
7.5 Special properties of water 273
7.5.1 Liquid water contains a loose network of hydrogen bonds 273
7.5.2 The hydrogen-bond network affects the solubility of small molecules in water 276
7.5.3 Water generates an entropic attraction between nonpolar objects 280
The big picture 281
Track 2 283
Problems 290
Chapter 8 Chemical Forces and Self-Assembly 294
8.1 Chemical potential 294
8.1.1 μ measures the availability of a particle species 295
8.1.2 The Boltzmann distribution has a simple generalization accounting for particle exchange 298
8.2 Chemical reactions 299
8.2.1 Chemical equilibrium occurs when chemical forces balance 299
8.2.2 Δ G gives a universal criterion for the direction of a chemical reaction 301
8.2.3 Kinetic interpretation of complex equilibria 306
8.2.4 The primordial soup was not in chemical equilibrium 307
8.3 Dissociation 308
8.3.1 Ionic and partially ionic bonds dissociate readily in water 308
8.3.2 The strengths of acids and bases reflect their dissociation equilibrium constants 309
8.3.3 The charge on a protein varies with its environment 311
8.3.4 Electrophoresis can give a sensitive measure of protein composition 312
8.4 Self-assembly of amphiphiles 315
8.4.1 Emulsions form when amphiphilic molecules reduce the oil-water interface tension 315
8.4.2 Micelles self-assemble suddenly at a critical concentration 317
8.5 Excursion：On fitting models to data 321
8.6 Self-assembly in cells 322
8.6.1 Bilayers self-assemble from two-tailed amphiphiles 322
8.6.2 Vista：Macromolecular folding and aggregation 327
8.6.3 Another trip to the kitchen 330
The big picture 332
Track 2 335
Problems 337
Part Ⅲ Molecules，Machines，Mechanisms 341
Chapter 9 Cooperative Transitions in Macromolecules 341
9.1 Elasticity models of polymers 342
9.1.1 Why physics works （when it does work） 342
9.1.2 Four phenomenological parameters characterize the elasticity of a long，thin rod 344
9.1.3 Polymers resist stretching with an entropic force 347
9.2 Stretching single macromolecules 350
9.2.1 The force-extension curve can be measured for single DNA molecules 350
9.2.2 A two-state system qualitatively explains DNA stretching at low force 352
9.3 Eigenvalues for the impatient 354
9.3.1 Matrices and eigenvalues 354
9.3.2 Matrix multiplication 357
9.4 Cooperativity 358
9.4.1 The transfer matrix technique allows a more accurate treatment of bend cooperativity 358
9.4.2 DNA also exhibits linear stretching elasticity at moderate applied force 361
9.4.3 Cooperativity in higher-dimensional systems gives rise to infinitely sharp phase transitions 363
9.5 Thermal，chemical，and mechanical switching 363
9.5.1 The helix-coil transition can be observed by using polarized light 364
9.5.2 Three phenomenological parameters describe a given helix-coil transition 366
9.5.3 Calculation of the helix-coil transition 369
9.5.4 DNA also displays a cooperative “melting” transition 373
9.5.5 Applied mechanical force can induce cooperative structural transitions in macromolecules 375
9.6 Allostery 376
9.6.1 Hemoglobin binds four oxygen molecules cooperatively 376
9.6.2 Allostery often involves relative motion of molecular subunits 379
9.6.3 Vista：Protein substates 380
The big picture 382
Track 2 384
Problems 396
Chapter 10 Enzymes and Molecular Machines 401
10.1 Survey of molecular devices found in cells 402
10.1.1 Terminology 402
10.1.2 Enzymes display saturation kinetics 403
10.1.3 All eukaryotic cells contain cyclic motors 404
10.1.4 One-shot machines assist in cell locomotion and spatial organization 407
10.2 Purely mechanical machines 409
10.2.1 Macroscopic machines can be described by an energy landscape 409
10.2.2 Microscopic machines can step past energy barriers 413
10.2.3 The Smoluchowski equation gives the rate of a microscopic machine 415
10.3 Molecular implementation of mechanical principles 422
10.3.1 Three ideas 423
10.3.2 The reaction coordinate gives a useful reduced description of a chemical event 423
10.3.3 An enzyme catalyzes a reaction by binding to the transition state 425
10.3.4 Mechanochemical motors move by random-walking on a two-dimensional landscape 431
10.4 Kinetics of real enzymes and machines 432
10.4.1 The Michaelis-Menten rule describes the kinetics of simple enzymes 433
10.4.2 Modulation of enzyme activity 436
10.4.3 Two-headed kinesin as a tightly coupled，perfect ratchet 437
10.4.4 Molecular motors can move even without tight coupling or a power stroke 446
10.5 Vista：Other molecular motors 451
The big picture 451
Track 2 455
Problems 464
Chapter 11 Machines in Membranes 469
11.1 Electroosmotic effects 469
11.1.1 Before the ancients 469
11.1.2 Ion concentration differences create Nernst potentials 470
11.1.3 Donnan equilibrium can create a resting membrane potential 474
11.2 Ion pumping 476
11.2.1 Observed eukaryotic membrane potentials imply that these cells are far from Donnan equilibrium 476
11.2.2 The Ohmic conductance hypothesis 478
11.2.3 Active pumping maintains steady-state membrane potentials while avoiding large osmotic pressures 481
11.3 Mitochondria as factories 486
11.3.1 Busbars and driveshafts distribute energy in factories 487
11.3.2 The biochemical backdrop to respiration 487
11.3.3 The chemiosmotic mechanism identifies the mitochondrial inner membrane as a busbar 491
11.3.4 Evidence for the chemiosmotic mechanism 492
11.3.5 Vista：Cells use chemiosmotic coupling in many other contexts 496
11.4 Excursion：“Powering up the flagellar motor” by H.C.Berg and D.Fung 497
The big picture 499
Track 2 501
Problems 503
Chapter 12 Nerve Impulses 505
12.1 The problem of nerve impulses 506
12.1.1 Phenomenology of the action potential 506
12.1.2 The cell membrane can be viewed as an electrical network 509
12.1.3 Membranes with Ohmic conductance lead to a linear cable equation with no traveling wave solutions 514
12.2 Simplified mechanism of the action potential 518
12.2.1 The puzzle 518
12.2.2 A mechanical analogy 519
12.2.3 Just a little more history 521
12.2.4 The time course of an action potential suggests the hypothesis of voltage gating 524
12.2.5 Voltage gating leads to a nonlinear cable equation with traveling wave solutions 527
12.3 The full Hodgkin-Huxley mechanism and its molecular underpinnings 532
12.3.1 Each ion conductance follows a characteristic time course when the membrane potential changes 532
12.3.2 The patch clamp technique allows the study of single ion channel behavior 536
12.4 Nerve，muscle，synapse 545
12.4.1 Nerve cells are separated by narrow synapses 545
12.4.2 The neuromuscular junction 546
12.4.3 Vista：Neural computation 548
The big picture 549
Track 2 552
Problems 553
Epilogue 557
Appendix A Global List of Symbols and Units 559
Notation 559
Named quantities 560
Dimensions 565
Units 565
Appendix B Numerical Values 569
Fundamental constants 569
Magnitudes 569
Specialized values 571
Appendix C Additional Problems 575
Problems for Chapter 1 575
Problems for Chapter 2 577
Problems for Chapter 3 578
Problems for Chapter 4 579
Problems for Chapter 5 584
Problems for Chapter 6 586
Problems for Chapter 7 588
Problems for Chapter 8 592
Problems for Chapter 9 594
Problems for Chapter 10 596
Problems for Chapter 11 602
Problems for Chapter 12 604
Credits 607
Bibliography 609
Index 623