Design of In Silico Protein & mRNA Vaccines: A Computational Approach to Vaccine Development
From Sequence to Vaccine: Accelerating Vaccine Development with In Silico Design
About This Course
The advent of computational vaccine design has revolutionized the field of immunology, enabling the development of protein and mRNA vaccines at an accelerated pace. With the success of COVID-19 mRNA vaccines, there is a growing need for computational tools that can predict, optimize, and validate the efficacy of novel vaccine candidates. This workshop introduces participants to in silico methods used to design vaccine candidates, including the selection of appropriate antigens, epitopes, adjuvants, and delivery systems.
The workshop covers the design of protein and mRNA vaccines, focusing on techniques like epitope prediction, protein folding (using tools such as MODELLER), codon optimization for mRNA, and mRNA vaccine construct design. Participants will also learn how to simulate vaccine immunogenicity, assess immune response using immune system modeling, and explore delivery methods for optimal efficacy. The program combines theory with dry-lab practical sessions on popular computational tools, enabling participants to create design-ready vaccine candidates for preclinical testing.
Aim
This workshop aims to provide participants with the skills and knowledge to design protein and mRNA vaccines using computational tools. It will cover the complete workflow from sequence analysis, antigen selection, and vaccine construct design to mRNA synthesis and delivery system modeling. Participants will also learn how in silico approaches can accelerate vaccine development by identifying potential epitopes, improving immune response, and reducing experimental costs.
Workshop Objectives
Participants will learn to:
- Identify and select candidate antigens for vaccine development using sequence analysis tools.
- Predict B-cell and T-cell epitopes using computational algorithms.
- Design mRNA constructs and optimize codon usage for efficient translation.
- Model vaccine immune responses using simulation tools.
- Create in silico protein and mRNA vaccine designs ready for experimental validation.
Workshop Structure
Day 1: Introduction to In Silico Vaccine Design & Antigen Selection
- Overview of Vaccine Types: Protein-based vs. mRNA-based vaccines
- Antigen Discovery: Identifying and selecting potential antigens for vaccine development
- Tools for Antigen Prediction: Epitope prediction tools, sequence alignment, and structure-based antigen design
- Key Concepts: Immune system interactions, B-cell and T-cell epitopes
- Tools: IEDB, NetMHC, HLA class I/II prediction tools, Vaxign
- Mini task: Identify potential antigens for a virus (e.g., SARS-CoV-2) using IEDB and NetMHC tools
Day 2: Protein Structure Prediction and Vaccine Design
- Protein Structure Prediction: Techniques for predicting the 3D structure of antigens (homology modeling, ab initio, and threading)
- Vaccine Design: Designing a stable, immunogenic protein vaccine candidate
- mRNA Vaccine Design: Optimizing mRNA constructs for efficient translation, codon optimization, and delivery mechanisms
- Tools: PyMOL, SWISS-MODEL, Rosetta, mRNA design tools (RNAfold, mfold)
- Mini task: Design a protein-based vaccine candidate and optimize its mRNA sequence for codon usage
Day 3: Molecular Docking, Immunogenicity Evaluation, and Research-Grade Reporting
- Molecular Docking: Docking the antigen with immune receptors (e.g., TCR, BCR) to predict immunogenicity
- Immunogenicity Evaluation: Evaluating the immune response through computational methods (e.g., MHC binding, T-cell receptor interactions)
- Vaccine Optimization: Refining the vaccine candidate to improve stability, efficacy, and immune response
- Reproducibility and Reporting: Best practices for reporting vaccine design results, ensuring reproducibility, and avoiding overclaims
- Tools: AutoDock, Chimera, MDAnalysis, VMD, and optional PLUMED overview
- Mini task: Create a 1-page in silico vaccine design report (including antigen structure, mRNA optimization, and docking results)
Who Should Enrol?
- Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
- Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
- University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
- Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
- Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.
Important Dates
Registration Ends
01/14/2026
IST 07:00 PM
Workshop Dates
01/14/2026 – 01/16/2026
IST 08:00 PM
Workshop Outcomes
Participants will be able to:
- Design protein and mRNA vaccine candidates using in silico methods.
- Predict potential T-cell and B-cell epitopes for optimal immune response.
- Optimize mRNA constructs for enhanced translation and stability.
- Apply immune system modeling to predict vaccine efficacy.
- Generate vaccine constructs ready for preclinical validation.
Fee Structure
Student Fee
₹1799 | $70
Ph.D. Scholar / Researcher Fee
₹2799 | $80
Academician / Faculty Fee
₹3799 | $95
Industry Professional Fee
₹4799 | $110
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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