Bioinformatics for Vaccinology

Bioinformatics for Vaccinology......Page 4
Contents......Page 10
Preface......Page 16
Acknowledgements......Page 18
Exordium......Page 20
Smallpox in history......Page 24
Variolation......Page 26
Variolation in history......Page 28
Variolation comes to Britain......Page 29
Lady Mary Wortley Montagu......Page 32
Variolation and the Sublime Porte......Page 34
The royal experiment......Page 36
The boston connection......Page 37
Variolation takes hold......Page 40
The Suttonian method......Page 41
Variolation in Europe......Page 42
The coming of vaccination......Page 44
Edward Jenner......Page 46
Cowpox......Page 49
Vaccination vindicated......Page 51
Louis Pasteur......Page 52
Vaccination becomes a science......Page 53
Meister, Pasteur and rabies......Page 54
A vaccine for every disease......Page 56
In the time of cholera......Page 57
Haffkine and cholera......Page 59
Bubonic plague......Page 60
The changing face of disease......Page 62
Almroth wright and typhoid......Page 63
Tuberculosis, Koch, and Calmette......Page 66
Vaccine BCG......Page 67
Poliomyelitis......Page 69
Salk and Sabin......Page 70
Diphtheria......Page 72
Whooping cough......Page 73
Many diseases, many vaccines......Page 74
Smallpox: Endgame......Page 76
Further reading......Page 77
Eradication and reservoirs......Page 78
Lifespans......Page 80
The evolving nature of disease......Page 82
Three threats......Page 83
Tuberculosis in the 21st century......Page 84
HIV and AIDS......Page 85
Malaria: Then and now......Page 86
Influenza......Page 87
Bioterrorism......Page 88
Vaccines as medicines......Page 90
Vaccines and the pharmaceutical industry......Page 91
The coming of the vaccine industry......Page 93
Challenging the immune system......Page 96
The threat from bacteria: Robust, diverse, and endemic......Page 97
Microbes, diversity and metagenomics......Page 98
The intrinsic complexity of the bacterial threat......Page 99
Microbes and humankind......Page 100
The nature of vaccines......Page 101
Types of vaccine......Page 103
Epitopic vaccines......Page 105
Vaccine delivery......Page 106
Emerging immunovaccinology......Page 107
The immune system......Page 108
Innate immunity......Page 109
Adaptive immunity......Page 111
Cellular components of immunity......Page 113
The T cell repertoire......Page 116
Epitopes: The immunological quantum......Page 117
The major histocompatibility complex......Page 118
MHC nomenclature......Page 120
Peptide binding by the MHC......Page 121
The structure of the MHC......Page 122
The proteasome......Page 124
Class II processing......Page 126
Seek simplicity and then distrust it......Page 127
Cross presentation......Page 128
T cell receptor......Page 129
T cell activation......Page 131
Signal 1, signal 2, immunodominance......Page 132
Humoral immunity......Page 133
Further reading......Page 135
Making sense of data......Page 136
Knowledge in a box......Page 137
The proteome......Page 138
Systems biology......Page 139
The immunome......Page 140
Databases and databanks......Page 141
The XML database......Page 142
The protein universe......Page 143
What proteins do......Page 145
The amino acid world......Page 147
The chiral nature of amino acids......Page 150
Naming the amino acids......Page 153
The amino acid alphabet......Page 155
Defining amino acid properties......Page 157
Size, charge and hydrogen bonding......Page 158
Hydrophobicity, lipophilicity and partitioning......Page 159
Understanding partitioning......Page 162
Charges, ionization, and pka......Page 163
Many kinds of property......Page 166
Mapping the world of sequences......Page 169
Biological sequence databases......Page 170
Nucleic acid sequence databases......Page 171
Protein sequence databases......Page 172
Annotating databases......Page 173
Text mining......Page 174
Ontologies......Page 176
Secondary sequence databases......Page 177
Other databases......Page 178
Host databases......Page 179
Pathogen databases......Page 182
Functional immunological databases......Page 184
Composite, integrated databases......Page 185
Allergen databases......Page 186
Reference......Page 188
Towards epitope-based vaccines......Page 190
T cell epitope prediction......Page 191
Predicting MHC binding......Page 192
Binding is biology......Page 195
Quantifying binding......Page 196
Entropy, enthalpy and entropy-enthalpy compensation......Page 197
Experimental measurement of binding......Page 198
Modern measurement methods......Page 200
Isothermal titration calorimetry......Page 201
Long and short of peptide binding......Page 202
The class I peptide repertoire......Page 203
Practicalities of binding prediction......Page 204
Binding becomes recognition......Page 205
Immunoinformatics lends a hand......Page 206
Motif based prediction......Page 207
The imperfect motif......Page 208
Other approaches to binding prediction......Page 209
Representing sequences......Page 210
Artificial neural networks......Page 211
Support vector machines......Page 213
Partial least squares......Page 214
Quantitative structure activity relationships......Page 215
Other techniques and sequence representations......Page 216
Amino acid properties......Page 217
Direct epitope prediction......Page 218
Predicting antigen presentation......Page 219
Predicting class II MHC binding......Page 220
Assessing prediction accuracy......Page 222
ROC plots......Page 225
Quantitative accuracy......Page 226
Prediction assessment protocols......Page 227
Comparing predictions......Page 229
Prediction versus experiment......Page 230
Predicting B cell epitopes......Page 231
Peak profiles and smoothing......Page 232
Early methods......Page 233
Imperfect B cell prediction......Page 234
References......Page 235
Structure and function......Page 240
Types of protein structure......Page 242
Protein folding......Page 243
Ramachandran plots......Page 244
Local structures......Page 245
Comparing structures......Page 246
Experimental structure determination......Page 247
Structural genomics......Page 249
Protein structure databases......Page 250
Other databases......Page 251
Immunological structural databases......Page 252
Small molecule databases......Page 253
Protein homology modelling......Page 254
Using homology modelling......Page 255
Predicting MHC supertypes......Page 256
Application to alloreactivity......Page 258
3D-QSAR......Page 259
Predicting B cell epitopes with docking......Page 261
Virtual screening......Page 263
Limitations to virtual screening......Page 264
Predicting epitopes with virtual screening......Page 266
Virtual screening and adjuvant discovery......Page 267
Adjuvants and innate immunity......Page 268
Small molecule adjuvants......Page 269
Molecular dynamics and immunology......Page 271
Molecular dynamics and binding......Page 272
Immunological applications......Page 273
Limitations of molecular dynamics......Page 274
Molecular dynamics and high performance computing......Page 275
References......Page 276
Vaccines and the world......Page 280
Bioinformatics and the challenge for vaccinology......Page 282
Predicting immunogenicity......Page 283
Computational vaccinology......Page 284
Beyond empirical vaccinology......Page 285
Designing new vaccines......Page 286
The perfect vaccine......Page 287
Conventional approaches......Page 288
Size of a genome......Page 289
Reverse vaccinology......Page 291
Finding antigens......Page 292
The success of reverse vaccinology......Page 294
Tumour vaccines......Page 296
Prediction and personalised medicine......Page 297
Imperfect data......Page 299
Forecasting and the future of computational vaccinology......Page 300
Index......Page 306