Bioinformatics for Vaccinology

Table of Contents:
Preface xiii Acknowledgements xv Exordium xvii 1 Vaccines: Their place in history 1 Smallpox in history 1 Variolation 3 Variolation in history 5 Variolation comes to Britain 6 Lady Mary Wortley Montagu 9 Variolation and the Sublime Porte 11 The royal experiment 13 The boston connection 14 Variolation takes hold 17 The Suttonian method 18 Variolation in Europe 19 The coming of vaccination 21 Edward Jenner 23 Cowpox 26 Vaccination vindicated 28 Louis Pasteur 29 Vaccination becomes a science 30 Meister, Pasteur and rabies 31 A vaccine for every disease 33 In the time of cholera 34 Haffkine and cholera 36 Bubonic plague 37 The changing face of disease 39 Almroth wright and typhoid 40 Tuberculosis, Koch, and Calmette 43 Vaccine BCG 44 Poliomyelitis 46 Salk and Sabin 47 Diphtheria 49 Whooping cough 50 Many diseases, many vaccines 51 Smallpox: Endgame 53 Further reading 54 2 Vaccines: Need and opportunity 55 Eradication and reservoirs 55 The ongoing burden of disease 57 Lifespans 57 The evolving nature of disease 59 Economics, climate and disease 60 Three threats 60 Tuberculosis in the 21st century 61 HIV and AIDS 62 Malaria: Then and now 63 Influenza 64 Bioterrorism 65 Vaccines as medicines 67 Vaccines and the pharmaceutical industry 68 Making vaccines 70 The coming of the vaccine industry 70 3 Vaccines: How they work 73 Challenging the immune system 73 The threat from bacteria: Robust, diverse, and endemic 74 Microbes, diversity and metagenomics 75 The intrinsic complexity of the bacterial threat 76 Microbes and humankind 77 The nature of vaccines 78 Types of vaccine 80 Carbohydrate vaccines 82 Epitopic vaccines 82 Vaccine delivery 83 Emerging immunovaccinology 84 The immune system 85 Innate immunity 86 Adaptive immunity 88 The microbiome and mucosal immunity 90 Cellular components of immunity 90 Cellular immunity 93 The T cell repertoire 93 Epitopes: The immunological quantum 94 The major histocompatibility complex 95 MHC nomenclature 97 Peptide binding by the MHC 98 The structure of the MHC 99 Antigen presentation 101 The proteasome 101 Transporter associated with antigen processing 103 Class II processing 103 Seek simplicity and then distrust it 104 Cross presentation 105 T cell receptor 106 T cell activation 108 Immunological synapse 109 Signal 1, signal 2, immunodominance 109 Humoral immunity 110 Further reading 112 4 Vaccines: Data and databases 113 Making sense of data 113 Knowledge in a box 114 The science of -omes and -omics 115 The proteome 115 Systems biology 116 The immunome 117 Databases and databanks 118 The relational database 119 The XML database 119 The protein universe 120 Much data, many databases 122 What proteins do 122 What proteins are 124 The amino acid world 124 The chiral nature of amino acids 127 Naming the amino acids 130 The amino acid alphabet 132 Defining amino acid properties 134 Size, charge and hydrogen bonding 135 Hydrophobicity, lipophilicity and partitioning 136 Understanding partitioning 139 Charges, ionization, and pka 140 Many kinds of property 143 Mapping the world of sequences 146 Biological sequence databases 147 Nucleic acid sequence databases 148 Protein sequence databases 149 Annotating databases 150 Text mining 151 Ontologies 153 Secondary sequence databases 154 Other databases 155 Databases in immunology 156 Host databases 156 Pathogen databases 159 Functional immunological databases 161 Composite, integrated databases 162 Allergen databases 163 Further reading 165 Reference 165 5 Vaccines: Data driven prediction of binders, epitopes and immunogenicity 167 Towards epitope-based vaccines 167 T cell epitope prediction 168 Predicting MHC binding 169 Binding is biology 172 Quantifying binding 173 Entropy, enthalpy and entropy-enthalpy compensation 174 Experimental measurement of binding 175 Modern measurement methods 177 Isothermal titration calorimetry 178 Long and short of peptide binding 179 The class I peptide repertoire 180 Practicalities of binding prediction 181 Binding becomes recognition 182 Immunoinformatics lends a hand 183 Motif based prediction 184 The imperfect motif 185 Other approaches to binding prediction 186 Representing sequences 187 Computer science lends a hand 188 Artificial neural networks 188 Hidden Markov models 190 Support vector machines 190 Robust multivariate statistics 191 Partial least squares 191 Quantitative structure activity relationships 192 Other techniques and sequence representations 193 Amino acid properties 194 Direct epitope prediction 195 Predicting antigen presentation 196 Predicting class II MHC binding 197 Assessing prediction accuracy 199 ROC plots 202 Quantitative accuracy 203 Prediction assessment protocols 204 Comparing predictions 206 Prediction versus experiment 207 Predicting B cell epitopes 208 Peak profiles and smoothing 209 Early methods 210 Imperfect B cell prediction 211 References 212 6 Vaccines: Structural approaches 217 Structure and function 217 Types of protein structure 219 Protein folding 220 Ramachandran plots 221 Local structures 222 Protein families, protein folds 223 Comparing structures 223 Experimental structure determination 224 Structural genomics 226 Protein structure databases 227 Other databases 228 Immunological structural databases 229 Small molecule databases 230 Protein homology modelling 231 Using homology modelling 232 Predicting MHC supertypes 233 Application to alloreactivity 235 3D-QSAR 236 Protein docking 238 Predicting B cell epitopes with docking 238 Virtual screening 240 Limitations to virtual screening 241 Predicting epitopes with virtual screening 243 Virtual screening and adjuvant discovery 244 Adjuvants and innate immunity 245 Small molecule adjuvants 246 Molecular dynamics and immunology 248 Molecular dynamics methodology 249 Molecular dynamics and binding 249 Immunological applications 250 Limitations of molecular dynamics 251 Molecular dynamics and high performance computing 252 References 253 7 Vaccines: Computational solutions 257 Vaccines and the world 257 Bioinformatics and the challenge for vaccinology 259 Predicting immunogenicity 260 Computational vaccinology 261 The threat remains 262 Beyond empirical vaccinology 262 Designing new vaccines 263 The perfect vaccine 264 Conventional approaches 265 Genome sequences 266 Size of a genome 267 Reverse vaccinology 268 Finding antigens 269 The success of reverse vaccinology 271 Tumour vaccines 273 Prediction and personalised medicine 275 Imperfect data 276 Forecasting and the future of computational vaccinology 277 Index 283

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

Review :
“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 and computer 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)