Immuno-Informatics
Course description:
Immunoinformatic, otherwise known as computational immunology, is the interface
between
computer science and experimental immunology. This course introduces you to the
world of
reverse vaccinology and computational vaccine design. Throughout the course, we
will cover
various immunoinformatic 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 several types of
epitopes in antigenic
proteins. Finally, we model the structure of antigen and antibodies and then do
docking to analyze
their interaction.
Recommended Books:
1. Scho¨nbach, C., Ranganathan, S., Brusic, V. (Eds.). (2007). Immunoinformatics
(Vol. 1).
Springer Science Business Media.
2. Bock, G. R., Goode, J. A. (Eds.). (2004). Immunoinformatics: bioinformatic
strategies
for better understanding of immune function. John Wiley Sons.
Course Learning Outcomes:
After completing this course, students will be trained to predict the pathological
mechanisms and
the counter responses generated by the human body. The students will discuss
mechanisms with
clinicians to cure immunology issues.
Assessment system:
Quizzes 10-15%
Assignments 5-10%
MSE 30-40%
ESE 40-50%
Lecture Plan:
S.NO. Lecture Topic Quizzes Assignments
1. Introduction to Immunology
2. Introduction to Vaccine design and Reverse
vaccinology
3. Primary protein structure prediction of antigenic
protein
4. Prediction of allergic nature of antigenic
proteins
5. Prediction of physiochemical properties of
antigenic proteins
6. Prediction of antigenicity of antigenic proteins 2
7. Prediction of the secondary structure of the
antigenic protein
8. Prediction of domains and important sites in
antigenic protein
9. Continuous B-cell epitope prediction
10. Discontinuous B-cell epitope prediction
11. Prediction of immunogenic regions in
antigenic protein
12. Prediction of glycoprotein antigen epitopes
13. Cytotoxic T cell epitope prediction
14. MHC class I and II prediction 4
15. Automated antigen modelling 4
16. Alignment based antigen modelling