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Bioinformatics for Vaccinology



Bioinformatics for Vaccinology

Darren R. Flower

ISBN: 978-0-470-69982-9 October 2008 302 Pages

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“… 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.




Exordium: Vaccines: a Very, Very Short Introduction

1 Vaccines: Their Place in History

Smallpox in History


Variolation in History

Variolation Comes to Britain

Lady Mary Wortley Montagu

Variolation and the Sublime Porte

The Royal Experiment

The Boston Connection

Variolation Takes Hold

The Suttonian Method

Variolation in Europe

The Coming of Vaccination

Edward Jenner


Vaccination Vindicated

Louis Pasteur

Vaccination Becomes a Science

Meister, Pasteur, and Rabies

A Vaccine for Every Disease

In the Time of Cholera

Haffkine and Cholera

Bubonic Plague

The Changing Face of Disease

Almroth Wright and Typhoid

Tuberculosis, Koch, and Calmette

Vaccine BCG


Salk and Sabin


Whooping Cough

Many Diseases, Many Vaccines

Smallpox: Endgame

Further Reading

2 Vaccines: Need and Opportunity

Eradication and Reservoirs

The Ongoing Burden of Disease


The Evolving Nature of Disease

Economics, Climate, and Disease

Three Threats

Tuberculosis in the 21st Century


Malaria: Then and Now



Vaccines as Medicines

Vaccines and the Pharmaceutical Industry

Making Vaccines

The Coming of the Vaccine Industry

3 Vaccines: How They Work

Challenging the Immune System

The Threat from Bacteria: Robust, Diverse, and Endemic

MiCrobes, Diversity, and Metagenomics

The Intrinsic Complexity of the Bacterial Threat

Microbes and Humankind

The Nature of Vaccines

Types of Vaccine

Carbohydrate Vaccines

Epitopic Vaccines

Adjuvants and Vaccine Delivery

Emerging Immunovaccinology

The Immune System

Innate Immunity

Adaptive Immunity

The Microbiome and Mucosal Immunity

Cellular Components of Immunity

Cellular Immunity

The T Cell Repertoire

Epitopes: The Immunological Quantum

The Major Histocompatility Complex

MHC Nomenclature

Peptide Binding by the MHC

The Structure of the MHC

Antigen Presentation

The Proteasome

Transporter Associated with Antigen Processing

Class II Processing

Seek Simplicity and Then Distrust It

Cross Presentation

T Cell Receptor

T Cell Activation

Immunological Synapse

Signal 1, Signal 2, Immunodominance

Humoral Immunity

Further Reading

4 Vaccines: Data and Databases

Making Sense of Data

Knowledge in a Box

The Science of -Omes and -Omics

The Proteome

Systems Biology

The Immunome

Databases and Databanks

The Relational Database

The XML Database

The Protein Universe

Much Data, Many Databases

What Proteins Do

What Proteins Are

The Amino Acid World

The Chiral Nature of Amino Acids

Naming the Amino Acids

The Amino Acid Alphabet

Defining Amino Acid Properties

Size, Charge, and Hydrogen Bonding

Hydrophobicity, Lipophilicity, and Partitioning

Understanding Partitioning

Charges, Ionization, and pKa

Many Kinds of Property

Mapping the World of Sequences

Biological Sequence Databases

Nucleic Acid Sequence Databases

Protein Sequence Databases

Annotating Databases

Text Mining


Secondary Sequence Databases

Other Databases

Databases in Immunology

Host Databases

Pathogen Databases

Functional Immunological Databases

Composite, Integrated Databases

Allergen Databases

Further Reading


5 Vaccines: Data Driven Prediction of Binders, Epitopes and Immunogenicity

Towards Epitope-Based Vaccines

T Cell Epitope Prediction

Predicting MHC Binding

Binding is Biology

Quantifying Binding

Entropy, Enthalpy, and Entropy-Enthalpy Compensation

Experimental Measurement of Binding

Modern Measurement Methods

Isothermal Titration Calorimetry

Long and Short of Peptide Binding

The Class I Peptide Repertoire

Practicalities of Binding Prediction

Binding Becomes Recognition

Immunoinformatics Lends a Hand

Motif Based Prediction

The Imperfect Motif

Other Approaches to Binding Prediction

Representing Sequences

Computer Science Lends a Hand

Artificial Neural Networks

Hidden Markov Model

Support Vector Machines

Robust Multivariate Statistics

Partial Least Squares

Quantitative Structure Activity Relationships

Other Techniques and Sequence Representations

Amino Acid Properties

Direct Epitope Prediction

Predicting Antigen Presentation

Predicting Class II MHC Binding

Assessing Prediction Accuracy

Roc Plots

Quantitative Accuracy

Prediction Assessment Protocols

Comparing Predictions

Prediction Versus Experiment

Predicting B Cell Epitopes

Peak Profiles and Smoothing

Early Methods

Imperfect B Cell Prediction


6 Vaccines: Structural Approaches

Structure and Function

Structure and Function

Types of Protein Structure

Protein Folding

Ramachandran Plots

Local Structures

Protein Families, Protein Folds

Comparing Structures

Experimental Structure Determination

Structural Genomics

Protein Structure Databases

Other Databases

Immunological Structural Databases

Small Molecule Databases

Protein Homology Modelling

Using Homology Modelling Predicting MHC Supertypes Application to Alloreactivity


Protein Docking

Predicting B Cell Epitopes with Docking

Virtual Screening

Limitations to Virtual Screening

Predicting Epitopes with Virtual Screening

Virtual Screening and Adjuvant Discovery

Adjuvants and Innate Immunity

Small Molecule Adjuvants

Molecular Dynamics and Immunology

Molecular Dynamics Methodology

Molecular Dynamics and Binding

Immunological Applications

Limitations of Molecular Dynamics

Molecular Dynamics and High Performance Computing


7 Vaccines: Computational Solutions

Vaccines and the World

Bioinformatics and the Challenge for Vaccinology

Predicting Immunogenicity

Computational Vaccinology

The Threat Remains

Beyond Empirical Vaccinology

Designing New Vaccines

The Perfect Vaccine

Conventional Approaches

Genome Sequences

Size of a Genome

Reverse Vaccinology

Finding Antigens

The Success of Reverse Vaccinology

Tumour Vaccines

Prediction and Personalised Medicine

Imperfect Data

Forecasting and the Future of Computational Vaccinology


“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)


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