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Bioinformatics for Vaccinology

Book Description

"... this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues—making the book enticing and useful, all at once..." Human Vaccines, 2010

"... This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies... This book may well serve as a first line of reference for all biologists and computer scientists..." –Virology Journal, 2009

Vaccines have probably saved more lives and reduced suffering in a greater number of people than any other medical intervention in human history, succeeding in eradicating smallpox and significantly reducing the mortality and incidence of other diseases. However, with the emergence of diseases such as SARS and the threat of biological warfare, vaccination has once again become a topic of major interest in public health.

Vaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers.

This is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development by

  • introducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinology

  • putting it into a historical and societal context, and

  • exploring the scope of its methods and applications.

Bioinformatics for Vaccinology is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Dedication
  5. Contents
  6. Preface
  7. Acknowledgements
  8. Exordium
    1. Vaccines: A Very, Very Short Introduction
  9. 1: Vaccines: Their Place in History
    1. Smallpox in history
    2. Variolation
    3. Variolation in history
    4. Variolation comes to Britain
    5. Lady Mary Wortley Montagu
    6. Variolation and the sublime porte
    7. The royal experiment
    8. The Boston connection
    9. Variolation takes hold
    10. The Suttonian method
    11. Variolation in Europe
    12. The coming of vaccination
    13. Edward Jenner
    14. Cowpox
    15. Vaccination vindicated
    16. Louis Pasteur
    17. Vaccination becomes a science
    18. Meister, Pasteur, and rabies
    19. A Vaccine for every disease
    20. In the time of cholera
    21. Haffkine and cholera
    22. Bubonic plague
    23. The changing face of disease
    24. Almroth wright and typhoid
    25. Tuberculosis, Koch, and Calmette
    26. Vaccine BCG
    27. Poliomyelitis
    28. Salk and Sabin
    29. Diphtheria
    30. Whooping cough
    31. Many diseases, many vaccines
    32. Smallpox: Endgame
    33. Further reading
  10. 2: Vaccines: Need and Opportunity
    1. Eradication and reservoirs
    2. The ongoing burden of disease
    3. Lifespans
    4. The evolving nature of disease
    5. Economics, climate, and disease
    6. Three threats
    7. Tuberculosis in the 21 st century
    8. HIV and AIDS
    9. Malaria: then and now
    10. Influenza
    11. Bioterrorism
    12. Vaccines as medicines
    13. Vaccines and the pharmaceutical industry
    14. Making vaccines
    15. The coming of the vaccine industry
  11. 3: Vaccines: How They Work
    1. Challenging the immune system
    2. The threat from bacteria: Robust, diverse, and endemic
    3. Microbes, diversity, and metagenomics
    4. The intrinsic complexity of the bacterial threat
    5. Microbes and humankind
    6. The nature of vaccines
    7. Types of vaccine
    8. Carbohydrate vaccines
    9. Epitopic vaccines
    10. Vaccine delivery
    11. Emerging immunovaccinology
    12. The immune system
    13. Innate immunity
    14. Adaptive immunity
    15. The microbiome and mucosal immunity
    16. Cellular components of immunity
    17. Cellular immunity
    18. The T cell repertoire
    19. Epitopes: The immunological quantum
    20. The major histocompatibility complex
    21. MHC nomenclature
    22. Peptide binding by the MHC
    23. The structure of the MHC
    24. Antigen presentation
    25. The proteasome
    26. Transporter associated with antigen processing
    27. Class II processing
    28. Seek simplicity and then distrust it
    29. Cross presentation
    30. T cell receptor
    31. T cell activation
    32. Immunological synapse
    33. Signal 1, signal 2, immunodominance
    34. Humoral immunity
    35. Further reading
  12. 4: Vaccines: Data and Databases
    1. Making sense of data
    2. Knowledge in a box
    3. The science of -omes and -omics
    4. The proteome
    5. Systems biology
    6. The immunome
    7. Databases and databanks
    8. The relational database
    9. The XML database
    10. The protein universe
    11. Much data, many databases
    12. What proteins do
    13. What proteins are
    14. The amino acid world
    15. The chiral nature of amino acids
    16. Naming the amino acids
    17. The amino acid alphabet
    18. Defining amino acid properties
    19. Size, charge, and hydrogen bonding
    20. Hydrophobicity, lipophilicity, and partitioning
    21. Understanding partitioning
    22. Charges, ionization, and pKa
    23. Many kinds of property
    24. Mapping the world of sequences
    25. Biological sequence databases
    26. Nucleic acid sequence databases
    27. Protein sequence databases
    28. Annotating databases
    29. Text mining
    30. Ontologies
    31. Secondary sequence databases
    32. Other databases
    33. Databases in immunology
    34. Host databases
    35. Pathogen databases
    36. Functional immunological databases
    37. Composite, integrated databases
    38. Allergen databases
    39. Further reading
    40. Reference
  13. 5: Vaccines: Data Driven Prediction of Binders, Epitopes and Immunogenicity
    1. Towards epitope-based vaccines
    2. T cell epitope prediction
    3. Predicting MHC binding
    4. Binding is biology
    5. Quantifying binding
    6. Entropy, enthalpy, and entropy-enthalpy compensation
    7. Experimental measurement of binding
    8. Modern measurement methods
    9. Isothermal titration calorimetry
    10. Long and short of peptide binding
    11. The class I peptide repertoire
    12. Practicalities of binding prediction
    13. Binding becomes recognition
    14. Immunoinformatics lends a hand
    15. Motif based prediction
    16. The imperfect motif
    17. Other approaches to binding prediction
    18. Representing sequences
    19. Computer science lends a hand
    20. Artificial neural networks
    21. Hidden Markov models
    22. Support vector machines
    23. Robust multivariate statistics
    24. Partial least squares
    25. Quantitative structure activity relationships
    26. Other techniques and sequence representations
    27. Amino acid properties
    28. Direct epitope prediction
    29. Predicting antigen presentation
    30. Predicting class II MHC binding
    31. Assessing prediction accuracy
    32. ROC plots
    33. Quantitative accuracy
    34. Prediction assessment protocols
    35. Comparing predictions
    36. Prediction versus experiment
    37. Predicting B cell epitopes
    38. Peak profiles and smoothing
    39. Early methods
    40. Imperfect B cell prediction
    41. References
  14. 6: Vaccines: Structural approaches
    1. Structure and function
    2. Types of protein structure
    3. Protein folding
    4. Ramachandran plots
    5. Local structures
    6. Protein families, protein folds
    7. Comparing structures
    8. Experimental structure determination
    9. Structural genomics
    10. Protein structure databases
    11. Other databases
    12. Immunological structural databases
    13. Small molecule databases
    14. Protein homology modelling
    15. Using homology modelling
    16. Predicting MHC supertypes
    17. Application to alloreactivity
    18. 3D-QSAR
    19. Protein docking
    20. Predicting B cell epitopes with docking
    21. Virtual screening
    22. Limitations to virtual screening
    23. Predicting epitopes with virtual screening
    24. Virtual screening and adjuvant discovery
    25. Adjuvants and innate immunity
    26. Small molecule adjuvants
    27. Molecular dynamics and immunology
    28. Molecular dynamics methodology
    29. Molecular dynamics and binding
    30. Immunological applications 1
    31. Limitations of molecular dynamics
    32. Molecular dynamics and high performance computing
    33. References
  15. 7: Vaccines: Computational solutions
    1. Vaccines and the world
    2. Bioinformatics and the challenge for vaccinology
    3. Predicting immunogenicity
    4. Computational vaccinology
    5. The threat remains
    6. Beyond empirical vaccinology
    7. Designing new vaccines
    8. The perfect vaccine
    9. Conventional approaches
    10. Genome sequences
    11. Size of a genome
    12. Reverse vaccinology
    13. Finding antigens
    14. The success of reverse vaccinology
    15. Tumour vaccines
    16. Prediction and personalised medicine
    17. Imperfect data
    18. Forecasting and the future of computational vaccinology
  16. Index