4.00
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Hands-on Guide on Computational Vaccinology and Chimeric Vaccines

Categories: Vaccine Discovery
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About Course

Vaccine development has been very successful in the prevention of highly contagious or serious disease. Vaccines are the most cost-effective public health interventions. Chimeric vaccines are types of recombinant vaccines, produced by substituting genes from the target pathogen in a closely related organism, for similar genes. 

Chimeric vaccines are useful in studying infectious diseases, including many neglected diseases. Immuno-Bioinformatics is being extensively used in designing B-, T-cell epitopes, vaccines, antibodies, adjuvants, diagnostic kits, and therapeutics. Bioinformatics is also involved in medication development aimed at bio-productive and pharmaceutical/vaccine development.

You don’t need any prior Bioinformatics, programming or immunoinformatics knowledge or skills for this course. This hands-on course will help you construct vaccines using subtractive genomics and reverse vaccinology techniques, even if you lack a proper understanding of the underlying concepts of Bioinformatics databases, servers, tools and the algorithms working behind them. 

In the Computational Vaccinology and Chimeric Vaccines course, you will be learning how to develop a vaccine against Dracunculus medinensis which causes guinea worm disease in humans. The video lecture series will take you from the basics such as proteome retrieval of Dracunculus medinensis and all the way to computational development of a chimeric vaccine.

This course will include the following sections:

Section 1: Target Identification

Description: This section will focus on making sure that the students learn about how to identify the target in order to start the process of computational construction of vaccines.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Select the target for the vaccine.
  2. Remove duplicates from the retrieved biological data.
  3. Screen Non-homologous Proteins.

Section 2: Immunoinformatics Approach for Epitope Prediction

Description: In this section students will learn how to use immunoinformatics approaches in order to perform epitope prediction. Immunoinformatics approaches are both cost-effective and convenient.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Screen Antigenicity of Protein.
  2. Predict Linear B-Cell Epitope.
  3. Assess Linear B-Cell Epitope.
  4. Predict CTL Epitope.

Section 3: Computational Construction of the Vaccine

Description: In this section students will be able to understand and learn the assessment and prediction necessary in order for the construction of the vaccine.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Assess CTL Epitope.
  2. Predict and Assess HTL Epitopes.
  3. Map Vaccine Construct.
  4. Perform Secondary and Tertiary Structure Prediction of Vaccines.
  5. Tertiary Structure Refinement And Validation.
  6. Predict Discontinuous B-Cell Epitope Prediction.

Section 4: Molecular Dynamics and Immune Simulation

Description: In this section students will learn how to perform molecular dynamics and immune simulation on the constructed vaccine to see if it stays stable.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Perform Molecular Dynamic Simulation.
  2. Perform Immune Simulation.
  3. Perform In Silico Cloning.

Section 5: Supplementary 1

Description: In this section students will learn how to perform codon optimization in order to improve the efficacy of vaccines.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Perform Codon Optimization.

Section 6: Supplementary 2

Description: In this section students will learn how to perform disulfide engineering on the vaccine protein to improve protein stability.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Perform Disulfide Engineering.

Section 7: Supplementary 3

Description: In this section students will learn how to dock TLR4 receptor with a protein in order to assess the binding affinity between the vaccine construct and TLR4.

Learning Outcomes:  Upon completion of this section, students will be able to:

  1. Perform Molecular Docking between TLR4 and a protein.

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What Will You Learn?

  • Retrieval of Proteome, Antigenicity and Location Prediction
  • Prediction and Evaluation of cytotoxic T-Lymphocytes (CTL) Epitopes
  • Prediction and assessment of Helper T-Lymphocytes (HTL) Epitopes
  • Prediction and assessment of Linear B-Lymphocytes (LBL) Epitopes
  • Molecular Docking Studies
  • Estimation of Population Coverage
  • Mapping of Vaccine Construct
  • Codon optimization and In Silico Cloning
  • Immune Simulation
  • Molecular Dynamic Simulation
  • Docking between vaccine protein & TLR4 receptor
  • Screening of B Cell Epitopes Disulfide Engineering of Vannice protein
  • Tertiary Structure Prediction, Refinement & Validation
  • Primary & Secondary Structure Prediction & Analysis

Course Content

Target Identification

  • Target Selection
    03:20
  • Removing Duplicates
    03:46
  • Screening Non-homologous Proteins
    06:42

Immunoinformatics Approach for Epitope Prediction

Computational Construction of the Vaccine

Molecular Dynamics and Immune Simulation

Supplementary 1

Supplementary 2

Supplementary 3

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Student Ratings & Reviews

4.0
Total 2 Ratings
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AK
1 year ago
It was okay, but the content was too little and some servers did not work
2 years ago
The course provides a practical and systematic approach to get the related information for the development of vaccines.

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