Immunoinformatics, otherwise known as computational immunology is the interface between computer science and experimental immunology. It is a field of science that uses high-throughput genomics and bioinformatics approaches for the understanding of immunological information. One of the major applications of immunoinformatics is an efficient and effective in-silico prediction of antigenicity and immunogenicity during vaccine development.

Conventionally, vaccine antigens are produced by genetic engineering technology. During this process, we have to culture the virus in the laboratory to purify and clone antigenic peptides. This process is very money consuming because it takes a lot of time and effort to identify the proteins in the virus that act as antigens. However, with the help of reverse vaccinology using immunoinformatics pipelines, we can prepare vaccines without culturing microorganisms with aid of genomic information and computer. The major advantage of reverse vaccinology is finding vaccine targets quickly and efficiently without too much expense.

During this process, first, the DNA of a virus is completely sequenced to identify the protein-coding genes and other functional genomic information. Then using computational tools, proteins with antigenic and immunological properties are predicted. Next novel antigenic proteins are purified and are injected into animal models to induce antibody or immune response. Finally, vaccines are produced by isolating the antigenic fragments from animals.

This course introduces you to the world of reverse vaccinology and computational vaccine design. Throughout the course, we will cover various immunoinformatics tools used in the vaccine design pipeline. We will start with the retrieval of the sequence of the antigenic protein. Then in the functional analysis of antigenic protein session, we will look more into antigenicity, allergic nature, and physicochemical properties of antigenic proteins. We will also look for structural features of the antigenic proteins like secondary structures, domains, and motifs. Then, we start analyzing the various types of epitopes in antigenic proteins. Finally, we model the structure of antigen and antibodies and then do docking to analyze their interaction.

The detailed course structure includes;

Introduction-Vaccine Design and Immunoinformatics

· Introduction to Immunology

· Introduction to Vaccine design and Reverse vaccinology

· Course Overview

Functional Analysis of Antigenic Proteins

· Primary protein structure prediction of antigenic protein

· Prediction of antigenicity of antigenic proteins

· Prediction of allergic nature of antigenic proteins

· Prediction of physiochemical properties of antigenic proteins

Structural Analysis of Antigenic Proteins

· Prediction of the secondary structure of the antigenic protein

· Prediction of domains and important sites in antigenic protein

Epitope Prediction

· Continuous B-cell epitope prediction

· Discontinuous B-cell epitope prediction

· Prediction of immunogenic regions in antigenic protein

· Prediction of glycoprotein antigen epitopes

· Cytotoxic T cell epitope prediction

· MHC class I and II prediction

· T cell epitopes processing prediction

· T cell epitopes Immunogenicity prediction

Antigen and Antibody Modelling &Docking

· Automated antigen modelling

· Alignment based antigen modelling

· Antibody modelling

· Antigen-Antibody Docking

Conclusion-Vaccine Design and Immunoinformatics

· Summary

· Paper Discussion

This course is a unique blend of theory and practical, where you will learn basic theory and then perform practical analysis of various vaccine design and immunoinformatics concepts. We assure you that after taking this course, your perspective will be very different for immunology and vaccine design. So, sign up for the course and see how fun, exciting, and rewarding the vaccine design and immunoinformatics tools are. We hope this course will be worth your money and time.