1. Introduction 258

2. Set-up of MD simulations 260

2.1 Constant-pressure dynamics 260

2.2 Grand-canonical dynamics 261

2.3 Boundary conditions 261

3. Force fields 262

3.1 Proteins 262

3.2 Nucleic acids 265

3.3 Carbohydrates 266

3.4 Phospholipids 266

3.5 Polarization 267

4. Electrostatics 267

4.1 Spherical truncation methods 268

4.2 Ewald summation methods 269

4.3 Fast multipole (FM) methods 271

4.4 Reaction-field methods 271

5. Implicit solvation models 271

6. Speeding-up the simulation 273

6.1 SHAKE and its relatives 273

6.2 Multiple time-step algorithms 274

6.3 Other algorithms 275

7. Conformational space sampling 275

7.1 Multiple copy simultaneous search (MCSS) and locally enhanced sampling (LES) 275

7.2 Steered or targeted MD 276

7.3 Self-guided MD 276

7.4 Leaving the standard 3D Cartesian coordinate system: 4D MD and internal coordinate MD 277

7.5 Temperature variations 277

8. Thermodynamic calculations 278

8.1 Lambda (λ) dynamics 278

8.2 Extracting thermodynamic information from simulations 279

8.3 Non-Boltzmann thermodynamic integration (NBTI) 279

8.4 Other methods 279

9. QM/MM calculations 282

10. MD simulations of protein folding and unfolding 283

10.1 High-temperature effects 284

10.2 Co-solvent and polarization effects 288

10.3 External force effects 288

11. On the horizon 291

12. Acknowledgements 292

13. References 292

Molecular dynamics simulations are widely used today to tackle problems in biochemistry and molecular biology. In the 25 years since the first simulation of a protein computers have become faster by many orders of magnitude, algorithms and force fields have been improved, and simulations can now be applied to very large systems, such as protein–nucleic acid complexes and multimeric proteins in aqueous solution. In this review we give a general background about molecular dynamics simulations, and then focus on some recent technical advances, with applications to biologically relevant problems.

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.

1. History 342

2. Activation barriers 343

2.1 Redox potentials 344

2.2 Reorganization energy 344

3. Electronic coupling 345

4. Ru-modified proteins 348

4.1 Reorganization energy 349

4.1.1 Cyt c 349

4.1.2 Azurin 350

4.2 Tunneling timetables 352

5. Multistep tunneling 357

6. Protein–protein reactions 359

6.1 Hemoglobin (Hb) hybrids 359

6.2 Cyt c/cyt b5 complexes 360

6.3 Cyt c/cyt c peroxidase complexes 360

6.4 Zn–cyt c/Fe–cyt c crystals 361

7. Photosynthesis and respiration 362

7.1 Photosynthetic reaction centers (PRCs) 362

7.2 Cyt c oxidase (CcO) 364

8. Concluding remarks 365

9. Acknowledgments 366

10. References 366

Electron transfer processes are vital elements of energy transduction pathways in living cells. More than a half century of research has produced a remarkably detailed understanding of the factors that regulate these ‘currents of life’. We review investigations of Ru-modified proteins that have delineated the distance- and driving-force dependences of intra-protein electron-transfer rates. We also discuss electron transfer across protein–protein interfaces that has been probed both in solution and in structurally characterized crystals. It is now clear that electrons tunnel between sites in biological redox chains, and that protein structures tune thermodynamic properties and electronic coupling interactions to facilitate these reactions. Our work has produced an experimentally validated timetable for electron tunneling across specified distances in proteins. Many electron tunneling rates in cytochrome c oxidase and photosynthetic reaction centers agree well with timetable predictions, indicating that the natural reactions are highly optimized, both in terms of thermodynamics and electronic coupling. The rates of some reactions, however, significantly exceed timetable predictions; it is likely that multistep tunneling is responsible for these anomalously rapid charge transfer events.