Bioinformatics for Vaccinology

Dr Darren R Flower, Reader in Pharmacy, School of Life and Health Sciences, University of Aston, Birmingham, UK.

“It pulls a number of different disciplines into a concise review that illustrates the potential we have in science to change our world.” (Doody's, April 2009) "This book may well serve as a first line of reference for all biologists andcomputer scientists. This textbook would be an excellent addition to the bookshelf of most scientists who encounter vaccinology in the drug discovery and development processes." ( Virology Journal - October -2009)

• Preface xiiiAcknowledgements xvExordium xvii1 Vaccines: Their place in history 1Smallpox in history 1Variolation 3Variolation in history 5Variolation comes to Britain 6Lady Mary Wortley Montagu 9Variolation and the Sublime Porte 11The royal experiment 13The boston connection 14Variolation takes hold 17The Suttonian method 18Variolation in Europe 19The coming of vaccination 21Edward Jenner 23Cowpox 26Vaccination vindicated 28Louis Pasteur 29Vaccination becomes a science 30Meister, Pasteur and rabies 31A vaccine for every disease 33In the time of cholera 34Haffkine and cholera 36Bubonic plague 37The changing face of disease 39Almroth wright and typhoid 40Tuberculosis, Koch, and Calmette 43Vaccine BCG 44Poliomyelitis 46Salk and Sabin 47Diphtheria 49Whooping cough 50Many diseases, many vaccines 51Smallpox: Endgame 53Further reading 542 Vaccines: Need and opportunity 55Eradication and reservoirs 55The ongoing burden of disease 57Lifespans 57The evolving nature of disease 59Economics, climate and disease 60Three threats 60Tuberculosis in the 21st century 61HIV and AIDS 62Malaria: Then and now 63Influenza 64Bioterrorism 65Vaccines as medicines 67Vaccines and the pharmaceutical industry 68Making vaccines 70The coming of the vaccine industry 703 Vaccines: How they work 73Challenging the immune system 73The threat from bacteria: Robust, diverse, and endemic 74Microbes, diversity and metagenomics 75The intrinsic complexity of the bacterial threat 76Microbes and humankind 77The nature of vaccines 78Types of vaccine 80Carbohydrate vaccines 82Epitopic vaccines 82Vaccine delivery 83Emerging immunovaccinology 84The immune system 85Innate immunity 86Adaptive immunity 88The microbiome and mucosal immunity 90Cellular components of immunity 90Cellular immunity 93The T cell repertoire 93Epitopes: The immunological quantum 94The major histocompatibility complex 95MHC nomenclature 97Peptide binding by the MHC 98The structure of the MHC 99Antigen presentation 101The proteasome 101Transporter associated with antigen processing 103Class II processing 103Seek simplicity and then distrust it 104Cross presentation 105T cell receptor 106T cell activation 108Immunological synapse 109Signal 1, signal 2, immunodominance 109Humoral immunity 110Further reading 1124 Vaccines: Data and databases 113Making sense of data 113Knowledge in a box 114The science of -omes and -omics 115The proteome 115Systems biology 116The immunome 117Databases and databanks 118The relational database 119The XML database 119The protein universe 120Much data, many databases 122What proteins do 122What proteins are 124The amino acid world 124The chiral nature of amino acids 127Naming the amino acids 130The amino acid alphabet 132Defining amino acid properties 134Size, charge and hydrogen bonding 135Hydrophobicity, lipophilicity and partitioning 136Understanding partitioning 139Charges, ionization, and pka 140Many kinds of property 143Mapping the world of sequences 146Biological sequence databases 147Nucleic acid sequence databases 148Protein sequence databases 149Annotating databases 150Text mining 151Ontologies 153Secondary sequence databases 154Other databases 155Databases in immunology 156Host databases 156Pathogen databases 159Functional immunological databases 161Composite, integrated databases 162Allergen databases 163Further reading 165Reference 1655 Vaccines: Data driven prediction of binders, epitopes and immunogenicity 167Towards epitope-based vaccines 167T cell epitope prediction 168Predicting MHC binding 169Binding is biology 172Quantifying binding 173Entropy, enthalpy and entropy-enthalpy compensation 174Experimental measurement of binding 175Modern measurement methods 177Isothermal titration calorimetry 178Long and short of peptide binding 179The class I peptide repertoire 180Practicalities of binding prediction 181Binding becomes recognition 182Immunoinformatics lends a hand 183Motif based prediction 184The imperfect motif 185Other approaches to binding prediction 186Representing sequences 187Computer science lends a hand 188Artificial neural networks 188Hidden Markov models 190Support vector machines 190Robust multivariate statistics 191Partial least squares 191Quantitative structure activity relationships 192Other techniques and sequence representations 193Amino acid properties 194Direct epitope prediction 195Predicting antigen presentation 196Predicting class II MHC binding 197Assessing prediction accuracy 199ROC plots 202Quantitative accuracy 203Prediction assessment protocols 204Comparing predictions 206Prediction versus experiment 207Predicting B cell epitopes 208Peak profiles and smoothing 209Early methods 210Imperfect B cell prediction 211References 2126 Vaccines: Structural approaches 217Structure and function 217Types of protein structure 219Protein folding 220Ramachandran plots 221Local structures 222Protein families, protein folds 223Comparing structures 223Experimental structure determination 224Structural genomics 226Protein structure databases 227Other databases 228Immunological structural databases 229Small molecule databases 230Protein homology modelling 231Using homology modelling 232Predicting MHC supertypes 233Application to alloreactivity 2353D-QSAR 236Protein docking 238Predicting B cell epitopes with docking 238Virtual screening 240Limitations to virtual screening 241Predicting epitopes with virtual screening 243Virtual screening and adjuvant discovery 244Adjuvants and innate immunity 245Small molecule adjuvants 246Molecular dynamics and immunology 248Molecular dynamics methodology 249Molecular dynamics and binding 249Immunological applications 250Limitations of molecular dynamics 251Molecular dynamics and high performance computing 252References 2537 Vaccines: Computational solutions 257Vaccines and the world 257Bioinformatics and the challenge for vaccinology 259Predicting immunogenicity 260Computational vaccinology 261The threat remains 262Beyond empirical vaccinology 262Designing new vaccines 263The perfect vaccine 264Conventional approaches 265Genome sequences 266Size of a genome 267Reverse vaccinology 268Finding antigens 269The success of reverse vaccinology 271Tumour vaccines 273Prediction and personalised medicine 275Imperfect data 276Forecasting and the future of computational vaccinology 277Index 283