Developing a Molecular Dynamics Pipeline for Predicting Mutation Outcomes in Precision Vaccinology

• Grant number: 24/14345-4
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: January 07, 2025
• End date: January 06, 2026
• Field of knowledge: Biological Sciences - Immunology - Immunogenetics
• Principal Investigator: Helder Takashi Imoto Nakaya
• Grantee: Peter Park
• Supervisor: Wonpil Im
• Host Institution: Centro de Inovação da USP (INOVA). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Lehigh University, United States
• Associated to the scholarship: 23/09291-0 - Prediction of structural changes in proteins caused by mutations using AlphaFold2 and Molecular Dynamics for Precision Vaccinology, BP.PD

Abstract

Vaccines are essential in preventing infectious diseases and their effectiveness may vary between individuals due to genetic variations that affect the production of cytokines, signaling proteins involved in the immune response. Single nucleotide polymorphisms (SNPs) in cytokine genes can lead to an altered immune response. The use of Molecular Dynamics (MD) simulations has allowed the investigation of the effects of SNPs on genes related to cytokines at the molecular level, providing new insights into changes in protein structure and function. This project aims to integrate genomic data with Structural Biology, analyzing SNPs data from exome data, and evaluating the consequence of non-synonymous mutations in the structure of key cytokines in the immune response, such as: IL2, IL10, IL6, IFNA, IFNB and IFNG. Using AlphaFold2, an artificial intelligence program that predicts the structure of proteins with high accuracy, we will generate structures of control and mutated proteins. CHARMM-GUI is a web-based platform that simplifies the preparation of complex biomolecular simulations and offers a wide-range of tools for batch generation of MD systems. This project aims to develop a workflow, using CHARMM-GUI's tools to set-up MD simulations, and evaluate the outcomes of SNPs in cytokines structural behavior and their binding affinities. The results can provide important information about the mechanism of action of cytokines and about the efficacy of vaccines in patients who have SNPs with high protein conformational impact, thus paving the way for accurate diagnosis, predicting the outcome and efficacy of vaccines from the analysis of the patient's genome.