1. Introduction 111

2. Levinthal's paradox and energy landscapes 115

2.1 Including randomness in the energy function 121

2.2 Some effects of energetic correlations between structurally similar states 126

3. Resolution of problems by funnel theory 128

3.1 Physical origin of free-energy barriers 133

4. Generic mechanisms in folding 138

4.1 Collapse, generic and specific 139

4.2 Helix formation 139

4.3 Nematic ordering 141

4.4 Microphase separation 142

5. Signatures of a funneled energy landscape 145

6. Statistical Hamiltonians and self-averaging 152

7. Conclusions and future prospects 156

8. Acknowledgments 157

9. Appendix: Glossary of terms 157

10. References 158

The current explosion of research in molecular biology was made possible by the profound discovery that hereditary information is stored and passed on in the simple, one-dimensional (1D) sequence of DNA base pairs (Watson & Crick, 1953). The connection between heredity and biological function is made through the transmission of this 1D information, through RNA, to the protein sequence of amino acids. The information contained in this sequence is now known to be sufficient to completely determine a protein's geometrical 3D structure, at least for simpler proteins which are observed to reliably refold when denatured in vitro, i.e. without the aid of any cellular machinery such as chaperones or steric (geometrical) constraints due to the presence of a ribosomal surface (for example Anfinsen, 1973) (see Fig. 1). Folding to a specific structure is typically a prerequisite for a protein to function, and structural and functional probes are both often used in the laboratory to test for the in vitro yield of folded proteins in an experiment.

1. Introduction 328

2. Basic concepts of neutron scattering 329

2.1 Introduction 329

2.2 Neutron-scattering functions 331

2.3 Coherent and incoherent neutron scattering. The particular role of hydrogen in incoherent scattering 332

2.4 Total elastic scattering, EISF and mean square displacement (MSD) 333

2.5 Quasielastic scattering and relaxation function 334

2.6 Inelastic scattering and density of states 335

3. Experimental aspects and instruments 335

3.1 Energy and space resolution 335

3.2 General sample aspects 335

3.3 Potential effects of D2O on dynamics 336

3.4 Experimental 2H (deuterium) labelling 336

4. Physics of protein dynamics 336

4.1 Models 336

4.2 The dynamical transition 338

4.3 Effective force constants 339

5. Dynamics of hydrated protein powders 339

5.1 First experiments on myoglobin 340

5.2 Dynamical transitions in other proteins 340

5.3 The role of hydration water 341

5.4 Influence of the solvent 344

5.5 Diffusional motions within proteins by QENS 346

5.6 Inelastic neutron scattering and vibrational spectra 347

5.7 Conclusions 351

6. Membranes 352

6.1 Lipid bilayers 353

6.2 BR and the purple membrane (PM) 353

6.2.1 The dynamical transition in the PM 353

6.2.2 QENS from oriented PM 354

6.2.3 Hydration dependence of PM motions 355

6.2.4 Local dynamics in PM studied by isotope labelling 356

6.2.5 Dynamics of different BR conformations 357

7. Protein solutions 358

7.1 From powders to solutions 358

7.2 Water dynamics and solvent dependence of the dynamical transition in proteins 359

8. Comparing neutron scattering with other techniques 359

9. Biological relevance 360

9.1 Dynamics–activity relations 360

9.2 Dynamics–stability relations (adaptation to extreme environments) 360

9.3 Protein folding 361

10. Acknowledgements 364

11. References 364

This review of protein dynamics studied by neutron scattering focuses on data collected in the last 10 years. After an introduction to thermal neutron scattering and instrumental aspects, theoretical models that have been used to interpret the data are presented and discussed. Experiments are described according to sample type, protein powders, solutions and membranes. Neutron-scattering results are compared to those obtained from other techniques. The biological relevance of the experimental results is discussed. The major conclusion of the last decade concerns the strong dependence of internal dynamics on the macromolecular environment.

1. Introduction 206

2. Quantifying the notions behind the energy landscape 206

2.1 Basic concepts of the Random Energy Model (REM) 206

2.2 Replica-symmetric partition functions and densities of states 209

2.3 The RHP phase diagram and avoided phase transitions 210

2.4 Basic concepts of the entropy of topologically constrained polymers 212

3. Beyond the Random Energy Model 219

3.1 The GREM and the glass transition in a finite RHP 222

4. Basics of configurational diffusion for RHPs and proteins 227

4.1 Kinetics on a correlated energy landscape 231

5. Thermodynamics and kinetics of protein folding 234

5.1 A protein Hamiltonian with cooperative interactions 234

5.2 Variance of native contact energies 235

5.3 Thermodynamics of protein folding 236

5.4 Free-energy surfaces and dynamics for a Hamiltonian with pair-wise interactions 240

5.5 The effects of cooperativity on folding 242

5.6 Transition-state drift 242

5.7 Phase diagram for a model protein 245

5.8 A non-Arrhenius folding-rate curve for proteins 246

6. Non-Markovian configurational diffusion and reaction coordinates in protein folding 247

6.1 An illustrative example 250

6.2 Non-Markovian rate theory and reaction surfaces 251

6.3 Application of non-Markovian rate theory to simulation data 257

7. Structural and energetic heterogeneity in the folding mechanism 259

7.1 The general strategy 261

7.2 An illustrative example 263

7.3 Free-energy functional 264

7.4 Dependence of the barrier height on mean loop length (contact order) and structural variance 268

7.5 Illustrations using lattice model proteins and functional theory 269

7.6 Connections of functional theory with experiments 271

8. Conclusions and future prospects 273

9. Acknowledgments 274

10. Appendices

A. Table of common symbols 275

B. GREM construction for the glass transition 276

C. Effect of a Q-dependent diffusion coefficient 279

D. A frequency-dependent Einstein relation 279

11. References 281

We have seen in Part I of this review that the energy landscape theory of protein folding is a statistical description of a protein's complex potential energy surface, where individual folding events are sampled from an ensemble of possible routes on the landscape. We found that the most likely global structure for the landscape of a protein can be described as that of a partially random heteropolymer with a rugged, yet funneled landscape towards the native structure. Here we develop some quantitative aspects of folding using tools from the statistical mechanics of disordered systems, polymers, and phase transitions in finite-sized systems. Throughout the text we will refer to concepts and equations developed in Part I of the review, and the reader is advised to at least survey its contents before proceeding here. Sections, figures or equations from Part I are often prefixed with I- [e.g. Section I-1.1, Fig. I-1, Eq. (I-1.1)].

1. Introduction 2

2. Structure of the bacterial PSU 5

2.1 Organization of the bacterial PSU 5

2.2 The crystal structure of the RC 9

2.3 The crystal structures of LH-II 11

2.4 Bacteriochlorophyll pairs in LH-II and the RC 13

2.5 Models of LH-I and the LH-I-RC complex 15

2.6 Model for the PSU 17

3. Excitation transfer in the PSU 18

3.1 Electronic excitations of BChls 22

3.1.1 Individual BChls 22

3.1.2 Rings of BChls 22

3.1.2.1 Exciton states 22

3.1.3 Effective Hamiltonian 24

3.1.4 Optical properties 25

3.1.5 The effect of disorder 26

3.2 Theory of excitation transfer 29

3.2.1 General theory 29

3.2.2 Mechanisms of excitation transfer 32

3.2.3 Approximation for long-range transfer 34

3.2.4 Transfer to exciton states 35

3.3 Rates for transfer processes in the PSU 37

3.3.1 Car→BChl transfer 37

3.3.1.1 Mechanism of Car→BChl transfer 39

3.3.1.2 Pathways of Car→BChl transfer 40

3.3.2 Efficiency of Car→BChl transfer 40

3.3.3 B800-B850 transfer 44

3.3.4 LH-II→LH-II transfer 44

3.3.5 LH-II→LH-I transfer 45

3.3.6 LH-I→RC transfer 45

3.3.7 Excitation migration in the PSU 46

3.3.8 Genetic basis of PSU assembly 49

4. Concluding remarks 53

5. Acknowledgments 55

6. References 55

Life as we know it today exists largely because of photosynthesis, the process through which light energy is converted into chemical energy by plants, algae, and photosynthetic bacteria (Priestley, 1772; Barnes, 1893; Wurmser, 1925; Van Niel, 1941; Clayton & Sistrom, 1978; Blankenship et al. 1995; Ort & Yocum, 1996). Historically, photosynthetic organisms are grouped into two classes. When photosynthesis is carried out in the presence of air it is called oxygenic photosynthesis (Ort & Yocum, 1996). Otherwise, it is anoxygenic (Blankenship et al. 1995). Higher plants, algae and cyanobacteria perform oxygenic photosynthesis, which involves reduction of carbon dioxide to carbohydrate and oxidation of water to produce molecular oxygen. Some photosynthetic bacteria, such as purple bacteria, carry out anoxygenic photosynthesis that involves oxidation of molecules other than water. In spite of these differences, the general principles of energy transduction are the same in anoxygenic and oxygenic photosynthesis (Van Niel, 1931, 1941; Stanier, 1961; Wraight, 1982; Gest, 1993). The primary processes of photosynthesis involve absorption of photons by light-harvesting complexes (LHs), transfer of excitation energy from LHs to the photosynthetic reaction centers (RCs), and the primary charge separation across the photosynthetic membrane (Sauer, 1975; Knox, 1977; Fleming & van Grondelle, 1994; van Grondelle et al. 1994). In this article, we will focus on the anoxygenic photosynthetic process in purple bacteria, since its photosynthetic system is the most studied and best characterized during the past 50 years.

1. Introduction 63

1.1 Outline 63

1.2 Universals versus realizations in the study of learning and memory 64

2. Large random cortical networks developing ex vivo 65

2.1 Preparation 65

2.2 Measuring electrical activity 67

3. Spontaneous development 69

3.1 Activity 69

3.2 Connectivity 70

4. Consequences of spontaneous activity: pharmacological manipulations 72

4.1 Structural consequences 72

4.2 Functional consequences 73

5. Effects of stimulation 74

5.1 Response to focal stimulation 74

5.2 Stimulation-induced changes in connectivity 74

6. Embedding functionality in real neural networks 77

6.1 Facing the physiological definition of ‘reward’: two classes of theories 78

6.2 Closing the loop 79

7. Concluding remarks 84

8. Acknowledgments 85

9. References 85

The phenomena of learning and memory are inherent to neural systems that differ from each other markedly. The differences, at the molecular, cellular and anatomical levels, reflect the wealth of possible instantiations of two neural learning and memory universals: (i) an extensive functional connectivity that enables a large repertoire of possible responses to stimuli; and (ii) sensitivity of the functional connectivity to activity, allowing for selection of adaptive responses. These universals can now be fully realized in ex-vivo developing neuronal networks due to advances in multi-electrode recording techniques and desktop computing. Applied to the study of ex-vivo networks of neurons, these approaches provide a unique view into learning and memory in networks, over a wide range of spatio-temporal scales. In this review, we summarize experimental data obtained from large random developing ex-vivo cortical networks. We describe how these networks are prepared, their structure, stages of functional development, and the forms of spontaneous activity they exhibit (Sections 2–4). In Section 5 we describe studies that seek to characterize the rules of activity-dependent changes in neural ensembles and their relation to monosynaptic rules. In Section 6, we demonstrate that it is possible to embed functionality into ex-vivo networks, that is, to teach them to perform desired firing patterns in both time and space. This requires ‘closing a loop’ between the network and the environment. Section 7 emphasizes the potential of ex-vivo developing cortical networks in the study of neural learning and memory universals. This may be achieved by combining closed loop experiments and ensemble-defined rules of activity-dependent change.

1. Summary 288

2. Introduction 288

3. Relationship between neuroenergetics and neurotransmitter flux 294

4. A model of coupling between neuroenergetics and neurotransmission 296

5. Relationship between neuroenergetics and neural spiking frequency 297

6. Comparison with previous electrophysiological and fMRI measurements 298

7. Contributions of non-oxidative energetics to a primarily oxidative brain 299

8. Possible explanation for non-oxidative energetics contributions 300

9. A model of total neuronal activity to support cerebral function 302

10. Implications for interpretation of fMRI studies 305

11. The restless brain 306

12. Acknowledgements 310

13. Appendix A. CMRO2by13C-MRS 310

14. Appendix B.Vcycand test of model 313

15. Appendix C. CMRO2by calibrated BOLD 316

16. Appendix D. Comparison of spiking activity of a neuronal ensemble with CMRO2318

17. References 320

In vivo13C magnetic resonance spectroscopy (MRS) studies of the brain have quantitatively assessed rates of glutamate–glutamine cycle (Vcyc) and glucose oxidation (CMRGlc(ox)) by detecting 13C label turnover from glucose to glutamate and glutamine. Contrary to expectations from in vitro and ex vivo studies, the in vivo13C-MRS results demonstrate that glutamate recycling is a major metabolic pathway, inseparable from its actions of neurotransmission. Furthermore, both in the awake human and in the anesthetized rat brain, Vcyc and CMRGlc(ox) are stoichiometrically related, where more than two thirds of the energy from glucose oxidation supports events associated with glutamate neurotransmission. The high energy consumption of the brain measured at rest and its quantitative relation to neurotransmission reflects a sizeable activity level for the resting brain. The high activity of the non-stimulated brain, as measured by cerebral metabolic rate of oxygen use (CMRO2), establishes a new neurophysiological basis of cerebral function that leads to reinterpreting functional imaging data because the large baseline signal is commonly discarded in cognitive neuroscience paradigms. Changes in energy consumption (ΔCMRO2%) can also be obtained from magnetic resonance imaging (MRI) experiments, using the blood oxygen level- dependent (BOLD) image contrast, provided that all the separate parameters contributing to the functional MRI (fMRI) signal are measured. The BOLD-derived ΔCMRO2% when compared with alterations in neuronal spiking rate (Δν%) during sensory stimulation in the rat reveals a stoichiometric relationship, in good agreement with 13C-MRS results. Hence fMRI when calibrated so as to provide ΔCMRO2% can provide high spatial resolution evaluation of neuronal activity. Our studies of quantitative measurements of changes in neuroenergetics and neurotransmission reveal that a stimulus does not provoke an arbitrary amount of activity in a localized region, rather a total level of activity is required where the increment is inversely related to the level of activity in the non-stimulated condition. These biophysical experiments have established relationships between energy consumption and neuronal activity that provide novel insights into the nature of brain function and the interpretation of fMRI data.

1. Summary 169

2. Introduction 170

3. Sanger's method and other enzymic methods 170

3.1 Random approach 171

3.2 Direct approach 171

3.3 Enzyme technology 175

3.4 Sample preparation 175

3.5 Labels and DNA labelling 176

3.5.1 Radioisotopes 176

3.5.2 Chemiluminescent detection 176

3.5.3 Fluorescent dyes 177

3.6 Fragment separation and analysis 180

3.6.1 Electrophoresis 180

3.6.2 Mass spectrometry – an alternative 182

4. Maxam & Gilbert and other chemical methods 183

5. Pyrosequencing – DNA sequencing in real time by the detection of released PPi 187

6. Single molecule sequencing with exonuclease 190

7. Conclusion 192

8. Acknowledgements 192

9. References 193

The four best known DNA sequencing techniques are reviewed. Important practical issues covered are read-length, speed, accuracy, throughput, cost, as well as the automation of sample handling and preparation. The methods reviewed are: (i) the Sanger method and its most important variants (enzymic methods); (ii) the Maxam & Gilbert method and other chemical methods; (iii) the PyrosequencingTM method – DNA sequencing in real time by the detection of released pyrophosphate (PPi); and (iv) single molecule sequencing with exonuclease (exonuclease digestion of a single molecule composed of a single strand of fluorescently labelled deoxynucleotides). Each method is briefly described, the current literature is covered, advantages, disadvantages, and the most suitable applications of each method are discussed.

1. Introduction 370

2. Infrared (IR) spectroscopy – general principles 372

2.1 Vibrations 372

2.2 Information that can be derived from the vibrational spectrum 372

2.3 Absorption of IR light 375

3. Protein IR absorption 376

3.1 Amino-acid side-chain absorption 376

3.2 Normal modes of the amide group 381

4. Interactions that shape the amide I band 382

4.1 Overview 382

4.2 Through-bond coupling 383

4.3 Hydrogen bonding 383

4.4 Transition dipole coupling (TDC) 383

5. The polarization and IR activity of amide I modes 387

5.1 The coupled oscillator system 387

5.2 Optically allowed transitions 388

5.3 The infinite parallel β-sheet 388

5.4 The infinite antiparallel β-sheet 389

5.5 The infinite α-helix 390

6. Calculation of the amide I band 391

6.1 Overview 391

6.2 Perturbation treatment by Miyazawa 393

6.3 The parallel β-sheet 394

6.4 The antiparallel β-sheet 395

6.5 The α-helix 396

6.6 Other secondary structures 398

7. Experimental analysis of protein secondary structure 398

7.1 Band fitting 398

7.2 Methods using calibration sets 401

7.3 Prediction quality 403

8. Protein stability 404

8.1 Thermal stability 404

8.2 1H/2H exchange 406

9. Molecular reaction mechanisms of proteins 408

9.1 Reaction-induced IR difference spectroscopy 408

9.2 The origin of difference bands 409

9.3 The difference spectrum seen as a fingerprint of conformational change 410

9.4 Molecular interpretation: strategies of band assignment 416

10. Outlook 419

11. Acknowledgements 420

12. References 420

This review deals with current concepts of vibrational spectroscopy for the investigation of protein structure and function. While the focus is on infrared (IR) spectroscopy, some of the general aspects also apply to Raman spectroscopy. Special emphasis is on the amide I vibration of the polypeptide backbone that is used for secondary-structure analysis. Theoretical as well as experimental aspects are covered including transition dipole coupling. Further topics are discussed, namely the absorption of amino-acid side-chains, 1H/2H exchange to study the conformational flexibility and reaction-induced difference spectroscopy for the investigation of reaction mechanisms with a focus on interpretation tools.

1. Mechanisms of nucleic acid (NA) unwinding by helicases 432

2. Helicases may take advantage of ‘breathing’ fluctuations in dsNAs 434

2.1 Stability and dynamics of dsNAs 434

2.2 dsNAs ‘breathe’ in isolation 435

2.3 Thermodynamics of terminal base pairs of dsNA 438

2.4 Thermal fluctuations may be responsible for sequential base-pair opening at replication forks 439

2.5 Helicases may capture single base-pair opening events sequentially 440

3. Biochemical properties of helicases 443

3.1 Binding of NAs 443

3.2 Binding and hydrolysis of NTP 445

3.3 Coordination between NA binding and NTP binding and hydrolysis activities 446

4. Helicase structures and mechanistic consequences 447

4.1 Amino-acid sequence analysis reveals conserved motifs that constitute the NTP-binding pocket and a portion of the NA-binding site 447

4.2 Organization of hepatitis virus C NS3 RNA helicase 449

4.2.1 Biochemical properties of HCV NS3 449

4.2.2 Crystal structures of HCV NS3 helicase 450

4.2.2.1 The apoprotein 450

4.2.2.2 The protein–dU8 complex 450

4.2.3 A possible unwinding mechanism 452

4.2.4 What is the functional oligomeric state of HCV NS3? 452

4.3 Organization of the PcrA helicase 453

4.3.1 The apoenzyme and ADP–PcrA complex 454

4.3.2 The protein–DNA–sulfate complex 456

4.3.3 The PcrA–DNA–ADPNP complex 456

4.3.4 A closer look at the NTP-binding site in the crystal structure of PcrA–ADPNP–DNA 457

4.3.5 Communication between domains A and B 457

4.3.6 How might ssDNA stimulate the ATPase activity of PcrA? 457

4.3.7 A possible helicase translocation mechanism 458

4.3.8 A possible unwinding mechanism 458

4.4 Organization of the Rep helicase 459

4.4.1 Biochemical properties 459

4.4.2 Crystal structure of Rep bound to ssDNA 462

4.5 Organization of the RecG helicase 462

4.6 Hexameric helicases 466

4.6.1 Insights from crystal structures of hexameric helicases 467

4.6.2 Possible translocation and unwinding mechanisms 468

5. Conclusions 469

6. Acknowledgments 472

7. References 472

Helicases are proteins that harness the chemical free energy of ATP hydrolysis to catalyze the unwinding of double-stranded nucleic acids. These enzymes have been much studied in isolation, and here we review what is known about the mechanisms of the unwinding process. We begin by considering the thermally driven ‘breathing’ of double-stranded nucleic acids by themselves, in order to ask whether helicases might take advantage of some of these breathing modes. We next provide a brief summary of helicase mechanisms that have been elucidated by biochemical, thermodynamic, and kinetic studies, and then review in detail recent structural studies of helicases in isolation, in order to correlate structural findings with biophysical and biochemical results. We conclude that there are certainly common mechanistic themes for helicase function, but that different helicases have devised solutions to the nucleic acid unwinding problem that differ in structural detail. In Part II of this review (to be published in the next issue of this journal) we consider how these mechanisms are further modified to reflect the functional coupling of these proteins into macromolecular machines, and discuss the role of helicases in several central biological processes to illustrate how this coupling actually works in the various processes of gene expression.

1. Triple-helical nucleic acids 89

1.1 History 89

1.2 Use of oligomers in triplex formation 90

2. Modes of triplex formation 90

2.1 Intermolecular triplexes 90

2.2 Intramolecular triplexes (H-DNA) 92

2.3 R-DNA (recombination DNA) 92

2.4 PNA (peptide nucleic acids) 93

3. Triplex structural models 93

3.1 YR-Y triplexes 94

3.2 GT-A base triplets 94

3.3 TC-G base triplets 94

3.4 TA-T and C+G-C base triplets 94

3.5 RR-Y triplexes 94

4. Modifications of TFOs 95

4.1 Backbone modification of oligonucleotides 95

4.2 Modification of the ribose in oligonucleotides 96

4.3 Base modification of oligonucleotides 97

5. Gene targeting and modification via triplex technology 98

5.1 Transcription and replication inhibition 99

5.2 TFO-directed mutagenesis 99

5.3 TFO-induced recombination 100

5.4 Future challenges in triplex-directed genome modification 100

6. References 101

The first description of triple-helical nucleic acids was by Felsenfeld and Rich in 1957 (Felsenfeld et al. 1957). While studying the binding characteristics of polyribonucleotides by fiber diffraction studies, they determined that polyuridylic acid [poly(U)] and polyadenylic acid [poly(A)] strands were capable of forming a stable complex of poly(U) and poly(A) in a 2:1 ratio. It was therefore concluded that the nucleic acids must be capable of forming a helical three-stranded structure. The formation of the three-stranded complex was preferred over duplex formation in the presence of divalent cations (e.g. 10 mm MgCl2). The reaction was quite specific, since the (U-A) molecule did not react with polycytidylic acid [(poly(C)], polyadenylic acid or polyinosinic acid [(poly(I)] (Felsenfeld et al. 1957). It was later found that poly(dT-dC) and poly(dG-dA) also have the capacity to form triple-stranded structures (Howard & Miles, 1964; Michelson & Monny, 1967). Other triple helical combinations of polynucleotide strands were identified from X-ray fiber-diffraction studies including, (A)n.2(I)n and (A)n.2(T)n (Arnott & Selsing, 1974). X-ray diffraction patterns of triple-stranded fibers of poly(A).2poly(U) and poly(dA).2poly(dT) showed an A-form conformation of the Watson–Crick strands. The third strand was bound in a parallel orientation to the purine strand by Hoogsteen hydrogen bonds (Hoogsteen, 1959; Arnott & Selsing, 1974). In 1968, the first potential biological role of these structures was identified by Morgan & Wells (1968). Using an in vitro assay, they found that transcription by E. coli RNA polymerase was inhibited by an RNA third strand. Thus, the recent developments identifying the potential of triplex formation for gene regulation and genome modification came more than 20 years after this first study of transcription inhibition by triplex formation.

Max Ferdinand Perutz, molecular biologist; born Vienna 19 May 1914; Director, MRC Unit for Molecular Biology 1947–62; FRS 1954; Reader, Davy Faraday Research Laboratory, Royal Institution 1954–68, Fullerian Professor of Physiology 1973–79; Chairman, MRC Laboratory of Molecular Biology 1962–79; Nobel Prize for Chemistry (jointly) 1962; CBE 1963; Chairman, European Molecular Biology Organisation 1963–69; CH 1975; OM 1988; married 1942 Gisela Peiser (one son, one daughter); died Cambridge 6 February 2002.