Innovative Multiscale Modeling Techniques for Membrane-Bound Proteins

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 1R35GM160192-01

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2025
    2030
  • Known Financial Commitments (USD)

    $369,500
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    ASSISTANT PROFESSOR Yu-ming Huang
  • Research Location

    United States of America
  • Lead Research Institution

    WAYNE STATE UNIVERSITY
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Pathogen morphology, shedding & natural history

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Innovative Multiscale Modeling Techniques for Membrane-Bound Proteins SUMMARY Our laboratory develops computer models to investigate biomolecular diffusion and interactions with a particular emphasis on membrane-bound proteins and lipid metabolism. The study of diffusion using empirical techniques faces serious obstacles in capturing the intermediate-state details of kinetic processes. Even computational tools encounter inherent tradeoffs in balancing long-timescale simulations with those that reveal precise atomistic details, particularly for lipid droplet (LD) proteins. This R35 MIRA proposal has two complementary research directions. First. we will develop computational tools to model diffusion and molecular interactions and apply them to the SARS-CoV-2 spike protein, otherwise well studied during pandemic-related research and similar to other viruses. My research offers to accelerate drug discovery, coronavirus vaccine development, and treatments for other viruses. Second, we will investigate the protein networks that regulate lipid metabolism on LDs, focusing on how the ABHD5 protein interacts with LD membranes and lipid-regulating proteins. By combining computational approaches and experimental validation, my long-term research trajectory aims to advance understanding of lipid metabolism and inform potential therapeutic strategies for diseases that include diabetes and cancer.