Tetanus and botulinum neurotoxins are produced by Clostridia and cause the neuroparalytic syndromes of tetanus and botulism. Tetanus neurotoxin acts mainly at the CNS synapse, while the seven botulinum neurotoxins act peripherally. Clostridial neurotoxins share a similar mechanism of cell intoxication: they block the release of neurotransmitters. They are composed of two disulfide-linked polypeptide chains. The larger subunit is responsible for neurospecific binding and cell penetration. Reduction releases the smaller chain in the neuronal cytosol, where it displays its zinc-endopeptidase activity specific for protein components of the neuroexocytosis apparatus. Tetanus neurotoxin and botulinum neurotoxins B, D, F and G recognize specifically VAMP/synaptobrevin. This integral protein of the synaptic vesicle membrane is cleaved at single peptide bonds, which differ for each neurotoxin. Botulinum A, and E neurotoxins recognize and cleave specifically SNAP-25, a protein of the presynaptic membrane, at two different sites within the carboxyl-terminus. Botulinum neurotoxin type C cleaves syntaxin, another protein of the nerve plasmalemma. These results indicate that VAMP, SNAP-25 a n d syntaxin play a central role in neuroexocytosis. These three proteins are conserved from yeast to humans and are essential in a variety of docking and fusion events in every cell. Tetanus and botulinum neurotoxins form a new group of zinc-endopeptidases with characteristic sequence, mode of zinc coordination, mechanism of activation and target recognition. They will be of great value in the unravelling of the mechanisms of exocytosis and endocytosis, as they are in the clinical treatment of dystonias.

1. Introduction 372

1.1 Residual dipolar couplings as a route to structure and dynamics 372

1.2 A brief history of oriented phase high resolution NMR 374

2. Theoretical treatment of dipolar interactions 376

2.1 Anisotropic interactions as probes of macromolecular structure and dynamics 376

2.1.1 The dipolar interaction 376

2.1.2 Averaging in the solution state 377

2.2 Ordering of a rigid body 377

2.2.1 The Saupe order tensor 378

2.2.2 Orientational probability distribution function 380

2.2.3 The generalized degree of order 380

2.3 Molecular structure and internal dynamics 381

3. Inducing molecular order in high resolution NMR 383

3.1 Tensorial interactions between the magnetic field and anisotropic magnetic susceptibilities 383

3.2 Dilute liquid crystal media: a tunable source of order 384

3.2.1 Bicelles : from membrane mimics to aligning media 385

3.2.2 Filamentous phage 387

3.2.3 Transfer of alignment from ordered media to macromolecules 388

3.3 Magnetic field alignment 389

3.3.1 Paramagnetic assisted alignment 389

3.3.2 Advantages of using magnetic alignment 389

4. The measurement of residual dipolar couplings 391

4.1 Introduction 391

4.2 Frequency based methods 392

4.2.1 Coupling enhanced pulse schemes 392

4.2.2 In phase anti-phase methods (IPAP): 1DNH couplings in proteins 393

4.2.3 Exclusive correlated spectroscopy (E-COSY): 1DNH, 1DNC′ and 2DHNC′ 395

4.2.4 Extraction of splitting values from the frequency domain 396

4.3 Intensity based experiments 397

4.3.1 J-Modulated experiments: the measurement of 1DCαHα in proteins 397

4.3.2 Phase modulated methods 399

4.3.3 Constant time COSY – the measurement of DHH couplings 399

4.3.4 Systematic errors in intensity based experiments 400

5. Interpretation of residual dipolar coupling data 401

5.1 Structure determination protocols utilizing orientational constraints 401

5.1.1 The simulated annealing approach 401

5.1.2 Order matrix analysis of dipolar couplings 402

5.1.3 A discussion of the two approaches 402

5.2 Reducing orientational degeneracy 403

5.2.1 Multiple alignment media in the simulated annealing approach 404

5.2.2 Multiple alignment media in the order matrix approach 405

5.3 Simplifying effects arising due to molecular symmetry 406

5.4 Database approaches for determining protein structure 407

6. Applications to the characterization of macromolecular systems 408

6.1 Protein structure refinement 408

6.2 Protein domain orientation 409

6.3 Oligosaccharides 413

6.4 Biomolecular complexes 415

6.5 Exchanging systems 416

7. Acknowledgements 418

8. References 419

Within its relatively short history, nuclear magnetic resonance (NMR) spectroscopy has managed to play an important role in the characterization of biomolecular structure. However, the methods on which most of this characterization has been based, Nuclear Overhauser Effect (NOE) measurements for short-range distance constraints and scalar couplings measurements for torsional constraints, have limitations (Wüthrich, 1986). For extended structures, such as DNA helices, for example, propagation of errors in the short distance constraints derived from NOEs leaves the relative orientation of remote parts of the structures poorly defined. Also, the low density of observable protons in contact regions of molecules held together by factors other than hydrophobic packing, leads to poorly defined structures. This is especially true in carbohydrate containing complexes where hydrogen bonds often mediate contacts, and in multi-domain proteins where the area involved in domain–domain contact can also be small. Moreover, most NMR based structural applications are concerned with the characterization of a single, rigid conformer for the final structure. This can leave out important mechanistic information that depends on dynamic aspects and, when motion is present, this can lead to incorrect structural representations. This review focuses on one approach to alleviating some of the existing limitations in NMR based structure determination: the use of constraints derived from the measurement of residual dipolar couplings (D).

An understanding of sensory information processing in the nervous system will probably require investigations with a variety of ‘model’ systems at different levels of complexity.

Our choice of a suitable model system was constrained by two conflicting requirements: on one hand the information processing properties of the system should be rather complex, on the other hand the system should be amenable to a quantitative analysis. In this sense the fly represents a compromise.

In these two papers we explore how optical information is processed by the fly's visual system. Our objective is to unravel the logical organization of the fly's visual system and its underlying functional and computational principles. Our approach is at a highly integrative level. There are different levels of analysing and ‘understanding’ complex systems, like a brain or a sophisticated computer.

Homing endonucleases are encoded by open reading frames that are embedded within group I, group II and archael introns, as well as inteins (intervening sequences that are spliced and excised post-translationally). These enzymes initiate transfer of those elements (and themselves) by generating strand breaks in cognate alleles that lack the intervening sequence, as well as in additional ectopic sites that broaden the range of intron and intein mobility. Homing endonucleases can be divided into several unique families that are remarkable in several respects: they display extremely high DNA-binding specificities which arise from long DNA target sites (14–40 bp), they are tolerant of a variety of sequence variations in these sites, and they display disparate DNA cleavage mechanisms. A significant number of homing endonucleases also act as maturases (highly specific cofactors for the RNA splicing reactions of their cognate introns). Of the known homing group I endonuclease families, two (HNH and His-Cys box enzymes) appear to be diverged from a common ancestral nuclease. While crystal structures of several representatives of the LAGLIDADG endonuclease family have been determined, only structures of single members of the HNH (I-HmuI), His-Cys box (I-PpoI) and GIY-YIG (I-TevI) families have been elucidated. These studies provide an important source of information for structure–function relationships in those families, and are the centerpiece of this review. Finally, homing endonucleases are significant targets for redesign and selection experiments, in hopes of generating novel DNA binding and cutting reagents for a variety of genomic applications.

The breakthroughs in single molecule spectroscopy of the last decade and the recent advances in super resolution microscopy have boosted the popularity of cyanine dyes in biophysical research. These applications have motivated the investigation of the reactions and relaxation processes that cyanines undergo in their electronically excited states. Studies show that the triplet state is a key intermediate in the photochemical reactions that limit the photostability of cyanine dyes. The removal of oxygen greatly reduces photobleaching, but induces rapid intensity fluctuations (blinking). The existence of non-fluorescent states lasting from milliseconds to seconds was early identified as a limitation in single-molecule spectroscopy and a potential source of artifacts. Recent studies demonstrate that a combination of oxidizing and reducing agents is the most efficient way of guaranteeing that the ground state is recovered rapidly and efficiently. Thiol-containing reducing agents have been identified as the source of long-lived dark states in some cyanines that can be photochemically switched back to the emissive state. The mechanism of this process is the reversible addition of the thiol-containing compound to a double bond in the polymethine chain resulting in a non-fluorescent molecule. This process can be reverted by irradiation at shorter wavelengths. Another mechanism that leads to non-fluorescent states in cyanine dyes is cis–trans isomerization from the singlet-excited state. This process, which competes with fluorescence, involves the rotation of one-half of the molecule with respect to the other with an efficiency that depends strongly on steric effects. The efficiency of fluorescence of most cyanine dyes has been shown to depend dramatically on their molecular environment within the biomolecule. For example, the fluorescence quantum yield of Cy3 linked covalently to DNA depends on the type of linkage used for attachment, DNA sequence and secondary structure. Cyanines linked to the DNA termini have been shown to be mostly stacked at the end of the helix, while cyanines linked to the DNA internally are believed to partially bind to the minor or major grooves. These interactions not only affect the photophysical properties of the probes but also create a large uncertainty in their orientation.

There are now well-established examples of carriers and pores which facilitate the transfer of ions across thin lipid membranes. In the absence of such agents, lipid bilayer membranes are extremely impermeable to the common inorganic ions. Thus, the conductance of a pure lecithin + decane or glyceryl mono-oleate + decane membrane in M/10 NaCl is less than10−9Ω −1 cm−2. However, on the addition of small lipid-soluble molecules such as valinomycin, or surface-active polypeptides such as gramicidin A, the conductance may become so high (> 10−1 ω−l cm−2) that the resistance of the membrane merges into that of the aqueous phase. This review is concerned with the extent to which we now understand how these added substances transfer ions across lipid membranes. Attention has been concentrated on the simpler systems, i.e. the lipid-soluble ions, the 1–1 carriets, a simple pore and, with some loss of simplicity, a substance which prodeces interacting pores. Only molecules of known primary structure are discussed.

1. Introduction 17

2. Dynamics of many-body systems 19

2.1 Effective dynamics of reduced systems 21

2.2 The constraint of thermodynamic equilibrium 24

2.3 Mean-field theories 25

3. Solvation free energy and electrostatics 27

3.1 Microscopic view of the Born model 27

3.2 Ion–Ion interactions in bulk solution 29

3.3 Continuum electrostatics and the PB equation 29

3.4 Limitations of continuum dielectric models 32

3.5 The dielectric barrier 33

3.6 The transmembrane potential and the PB-V equation 35

4. Statistical mechanical equilibrium theory 40

4.1 Multi-ion PMF 40

4.2 Equilibrium probabilities of occupancy 43

4.3 Coupling to the membrane potential 44

4.4 Ionic selectivity 48

4.5 Reduction to a one-dimensional (1D) free-energy profile 49

5. From MD toI–V: a practical guide 50

5.1 Extracting the essential ingredients from MD 51

5.1.1 Channel conductance from equilibrium and non-equilibrium MD 51

5.1.2 PMF techniques 52

5.1.3 Friction and diffusion coefficient techniques 53

5.1.4 About computational times 55

5.2 Ion permeation models 56

5.2.1 The 1D-NP electrodiffusion theory 56

5.2.2 Discrete-state Markov chains 57

5.2.3 The GCMC/BD algorithm 58

5.2.4 PNP electrodiffusion theory 62

6. Computational studies of ion channels 63

6.1 Computational studies of gA 65

6.1.1 Free-energy surface for K+ permeation 66

6.1.2 Mean-force decomposition 69

6.1.3 Cation-binding sites 69

6.1.4 Channel conductance 70

6.1.5 Selectivity 72

6.2 Computational studies of KcsA 72

6.2.1 Multi-ion free-energy surface and cation-binding sites 73

6.2.2 Channel conductance 74

6.2.3 Mechanism of ion conduction 77

6.2.4 Selectivity 78

6.3 Computational studies of OmpF 79

6.3.1 The need to compare the different level of approximations 79

6.3.2 Equilibrium protein fluctuations and ion distribution 80

6.3.3 Non-equilibrium ion fluxes 80

6.3.4 Reversal potential and selectivity 84

6.4 Successes and limitations 87

6.4.1 Channel structure 87

6.4.2 Ion-binding sites 87

6.4.3 Ion conduction 88

6.4.4 Ion selectivity 89

7. Conclusion 90

8. Acknowledgments 93

9. References 93

The goal of this review is to establish a broad and rigorous theoretical framework to describe ion permeation through biological channels. This framework is developed in the context of atomic models on the basis of the statistical mechanical projection-operator formalism of Mori and Zwanzig. The review is divided into two main parts. The first part introduces the fundamental concepts needed to construct a hierarchy of dynamical models at different level of approximation. In particular, the potential of mean force (PMF) as a configuration-dependent free energy is introduced, and its significance concerning equilibrium and non-equilibrium phenomena is discussed. In addition, fundamental aspects of membrane electrostatics, with a particular emphasis on the influence of the transmembrane potential, as well as important computational techniques for extracting essential information from all-atom molecular dynamics (MD) simulations are described and discussed. The first part of the review provides a theoretical formalism to ‘translate’ the information from the atomic structure into the familiar language of phenomenological models of ion permeation. The second part is aimed at reviewing and contrasting results obtained in recent computational studies of three very different channels; the gramicidin A (gA) channel, which is a narrow one-ion pore (at moderate concentration), the KcsA channel from Streptomyces lividans, which is a narrow multi-ion pore, and the outer membrane matrix porin F (OmpF) from Escherichia coli, which is a trimer of three β-barrel subunits each forming wide aqueous multi-ion pores. Comparison with experiments demonstrates that current computational models are approaching semi-quantitative accuracy and are able to provide significant insight into the microscopic mechanisms of ion conduction and selectivity. We conclude that all-atom MD with explicit water molecules can represent important structural features of complex biological channels accurately, including such features as the location of ion-binding sites along the permeation pathway. We finally discuss the broader issue of the validity of ion permeation models and an outlook to the future.

It is generally acknowledged that geometrical and conformational properties of biopolymers have an important effect on their biochemical behaviour. It is less easily recognized that these properties depend also on their macromolecular electronic characteristics.

The aim of this review is to demonstrate the significance of such macromolecular electronic effects. Particularly useful for this sake is the recently much developed concept of ‘molecular electrostatic potential’ (MEP) (Scrocco & Tomasi, 1973, 1978) by which is defined the electrostatic (Coulomb) potential created in the neighbouring space by the nuclear charges and the eletronic distribution of a molecule.

1. Introduction 2

2. What is the significance of the shared structural properties of disease-associated protein fibrils? 3

2.1 Mechanism of amyloid fibril formation in vitro 6

2.1.1 In vitro fibril formation involves transient population of ordered aggregates of intermediate stability, or protofibrils 6

3. Toxic properties of protofibrils 7

3.1 Protofibrils, rather than fibrils, are likely to be pathogenic 7

3.2 The toxic protofibril may be a mixture of related species 8

3.3 Morphological similarities of protofibrils suggest a common mechanism of toxicity 9

3.4 Are the amyloid diseases a subset of a much larger class of previously unrecognized protofibril diseases? 9

3.5 Fibrils, in the form of aggresomes, may function to sequester toxic protofibrils 9

4. Amyloid pores, a common structural link among protein aggregation neurodegenerative diseases 10

4.1 Mechanistic studies of amyloid fibril formation reveal common features, including pore-like protofibrils 10

4.1.1 Amyloid-β (Aβ) (Alzheimer's disease) 10

4.1.2 α-Synuclein (PD and diffuse Lewy body disease) 12

4.1.3 ABri (familial British dementia) 13

4.1.4 Superoxide dismutase-1 (amyotrophic lateral sclerosis) 13

4.1.5 Prion protein (Creutzfeldt–Jakob disease, bovine spongiform encephalopathy, etc.) 14

4.1.6 Huntingtin (Huntington's disease) 14

4.2 Amyloidogenic proteins that are not linked to disease also from pore-like protofibrils 15

4.3 Amyloid proteins form non-fibrillar aggregates that have properties of protein channels or pores 15

4.3.1 Aβ ‘channels’ 15

4.3.2 α-Synuclein ‘pores’ 16

4.3.3 PrP ‘channels’ 16

4.3.4 Polyglutamine ‘channels’ 17

4.4 Nature uses β-strand-mediated protein oligomerization to construct pore-forming toxins 17

5. Mechanisms of protofibril induced toxicity in protein aggregation diseases 19

5.1 The amyloid pore can explain the age-association and cell-type selectivity of the neurodegenerative diseases 19

5.2 Protofibrils may promote their own accumulation by inhibiting the proteasome 20

6. Testing the amyloid pore hypothesis by attempting to disprove it 21

7. Acknowledgments 22

8. References 22

Protein fibrillization is implicated in the pathogenesis of most, if not all, age-associated neurodegenerative diseases, but the mechanism(s) by which it triggers neuronal death is unknown. Reductionist in vitro studies suggest that the amyloid protofibril may be the toxic species and that it may amplify itself by inhibiting proteasome-dependent protein degradation. Although its pathogenic target has not been identified, the properties of the protofibril suggest that neurons could be killed by unregulated membrane permeabilization, possibly by a type of protofibril referred to here as the ‘amyloid pore’. The purpose of this review is to summarize the existing supportive circumstantial evidence and to stimulate further studies designed to test the validity of this hypothesis.

The bacterial flagellar motor is a reversible rotary nano-machine, about 45 nm in diameter, embedded in the bacterial cell envelope. It is powered by the flux of H+ or Na+ ions across the cytoplasmic membrane driven by an electrochemical gradient, the proton-motive force or the sodium-motive force. Each motor rotates a helical filament at several hundreds of revolutions per second (hertz). In many species, the motor switches direction stochastically, with the switching rates controlled by a network of sensory and signalling proteins. The bacterial flagellar motor was confirmed as a rotary motor in the early 1970s, the first direct observation of the function of a single molecular motor. However, because of the large size and complexity of the motor, much remains to be discovered, in particular, the structural details of the torque-generating mechanism. This review outlines what has been learned about the structure and function of the motor using a combination of genetics, single-molecule and biophysical techniques, with a focus on recent results and single-molecule techniques.

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.

Determination of the structure of integral membrane proteins is a challenging task that is essential to understand how fundamental biological processes (such as photosynthesis, respiration and solute translocation) function at the atomic level. Crystallisation of membrane proteins in 3D has led to the determination of four atomic resolution structures [photosynthetic reaction centres (Allen et al. 1987; Chang et al. 1991; Deisenhofer & Michel, 1989; Ermler et al. 1994); porins (Cowan et al. 1992; Schirmer et al. 1995; Weiss et al. 1991); prostaglandin H2 synthase (Picot et al. 1994); light harvesting complex (McDermott et al. 1995)], and crystals of membrane proteins formed in the plane of the lipid bilayer (2D crystals) have produced two more structures [bacteriorhodopsin (Henderson et al. 1990); light harvesting complex (Kühlbrandt et al. 1994)].

Intracellular calcium plays an essential role in the transduction of most hormonal, neuronal, visual, and muscle stimuli. (Recent reviews include Putney, 1993; Berridge, 1993a,b; Tsunoda, 1993; Gnegy, 1993; Bachs et al. 1992; Hanson & Schulman, 1992; Villereal & Byron, 1992; Premack & Gardner, 1992; Means et al. 1991).

Protein–protein recognition plays an essential role in structure and function. Specific non-covalent interactions stabilize the structure of macromolecular assemblies, exemplified in this review by oligomeric proteins and the capsids of icosahedral viruses. They also allow proteins to form complexes that have a very wide range of stability and lifetimes and are involved in all cellular processes. We present some of the structure-based computational methods that have been developed to characterize the quaternary structure of oligomeric proteins and other molecular assemblies and analyze the properties of the interfaces between the subunits. We compare the size, the chemical and amino acid compositions and the atomic packing of the subunit interfaces of protein–protein complexes, oligomeric proteins, viral capsids and protein–nucleic acid complexes. These biologically significant interfaces are generally close-packed, whereas the non-specific interfaces between molecules in protein crystals are loosely packed, an observation that gives a structural basis to specific recognition. A distinction is made within each interface between a core that contains buried atoms and a solvent accessible rim. The core and the rim differ in their amino acid composition and their conservation in evolution, and the distinction helps correlating the structural data with the results of site-directed mutagenesis and in vitro studies of self-assembly.

1. Introduction 308

2. Plan of this article 312

3. Natural mechanisms of development of novel protein functions 313

3.1 Divergence 313

3.2 Recruitment 316

3.3 ‘Mixing and matching’ of domains, including duplication/oligomerization, and domain swapping or fusion 316

4. Classification schemes for protein functions 317

4.1 General schemes 317

4.2 The EC classification 318

4.3 Combined classification schemes 319

4.4 The Gene Ontology Consortium 321

5. Methods for assigning protein function 321

5.1 Detection of protein homology from sequence, and its application to function assignment 321

5.2 Detection of structural similarity, protein structure classifications, and structure/function correlations 326

5.3 Function prediction from amino-acid sequence 327

5.3.1 Databases of single motifs 328

5.3.2 Databases of profiles 329

5.3.3 Databases of multiple motifs 330

5.3.4 Precompiled families 331

5.3.5 Function identification from sequence by feature extraction 331

5.4 Methods making use of structural data 332

6. Applications of full-organism information: inferences from genomic context and protein interaction patterns 334

7. Conclusions 335

8. Acknowledgements 335

9. References 335

The sequence of a genome contains the plans of the possible life of an organism, but implementation of genetic information depends on the functions of the proteins and nucleic acids that it encodes. Many individual proteins of known sequence and structure present challenges to the understanding of their function. In particular, a number of genes responsible for diseases have been identified but their specific functions are unknown. Whole-genome sequencing projects are a major source of proteins of unknown function. Annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino-acid sequence alone. 3D structure can aid the assignment of function, motivating the challenge of structural genomics projects to make structural information available for novel uncharacterized proteins. Structure-based identification of homologues often succeeds where sequence-alone-based methods fail, because in many cases evolution retains the folding pattern long after sequence similarity becomes undetectable. Nevertheless, prediction of protein function from sequence and structure is a difficult problem, because homologous proteins often have different functions. Many methods of function prediction rely on identifying similarity in sequence and/or structure between a protein of unknown function and one or more well-understood proteins. Alternative methods include inferring conservation patterns in members of a functionally uncharacterized family for which many sequences and structures are known. However, these inferences are tenuous. Such methods provide reasonable guesses at function, but are far from foolproof. It is therefore fortunate that the development of whole-organism approaches and comparative genomics permits other approaches to function prediction when the data are available. These include the use of protein–protein interaction patterns, and correlations between occurrences of related proteins in different organisms, as indicators of functional properties. Even if it is possible to ascribe a particular function to a gene product, the protein may have multiple functions. A fundamental problem is that function is in many cases an ill-defined concept. In this article we review the state of the art in function prediction and describe some of the underlying difficulties and successes.

Voltage-gated ion channels are membrane proteins that play a central role in the propagation and transduction of cellular signals (Hille, 1992). Calcium ions entering cells through voltage-gated calcium channels serve as the trigger for neurotransmitter release, muscle contraction, and the release of hormones. Voltage-gated sodium channels initiate the nerve action potential and provide for its rapid propagation because the ion fluxes through these channels regeneratively cause more channels to open.

This review will consider solution studies of structure and interactions of DNA and DNA complexes using linear dichroism spectroscopy, with emphasis on the technique of orientation by flow. The theoretical and experimental background to be given may serve, in addition, as a general introduction into the state of the art of linear dichroism spectroscopy, particularly as it is applied to biophysical problems.

This article tries to be a compact summary of some recent research on cytochrome c oxidase (EC 1.9.3.1), an important enzyme in membrane bioenergetics. Cytochrome oxidase is the terminal catalyst of the mitochondrial respiratory chain. It uses the electrons flowing through the chain to reduce oxygen molecules to water. Four electrons and four protons are consumed in the reduction of O2 to two molecules of water (Fig. 1). Cytochrome oxidase contains four redoxactive metal centres. Two of these are copper atoms, two haem A groups. These four centres are employed in the dioxygen-binding site and in the electron-transferring pathways from cytochrome c. The enzyme is also called cytochrome aa3, because the protein-bound haems are functionally and spectroscopically different.

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.

To deepen our understanding of the principles determining the folding and functioning of globular proteins the determination of their three-dimensional structures must be supplemented with the characterization of their internal motions. Although dynamical events in proteins occur on time-scale ranging from femtoseconds to at least seconds, the physical properties of globular proteins are such that picosecond (ps) time-scale motions make a particularly important contribution to the internal fluctuations of the atoms from their mean positions.