RAPID: IIBR Informatics: Predicting All-atom Structure of SARS-CoV-2 Related Protein Complex from 3D Cryo-Electron Microscopy Data

  • Funded by National Science Foundation (NSF)
  • Total publications:0 publications

Grant number: unknown

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $200,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Dong Si
  • Research Location

    United States of America
  • Lead Research Institution

    University of Washington
  • 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

The outbreak of novel coronavirus disease (COVID-19) has caused a global pandemic. Knowledge on the molecular basis of novel coronavirus (SARS-CoV-2) related protein complexes is essential to providing insight of the virus and how it infects human cells, a first step in developing novel drugs and vaccines to combat SARS-CoV-2. This study will enable development of all-atom structure prediction of CoV-related protein complexes, including complex surfaces of human cells the virus infects. Prediction results will be broadly and quickly disseminated through interactive web applications to maximize the impact of the research. The results will lead to a broad range of biomedical applications, such as a better understanding of important biological functions, disease processes, development of novel drugs and vaccines, and improved preventive therapies leading to reduced health care costs.

The project seeks to study ab initio all-atom structure prediction of CoV-related protein complexes based on electron cryo-microscopy (cryo-EM). Methods based on the state-of-the-art technologies of image processing for pre-processing the data, deep learning for complex structure prediction, and dynamic optimization for final refinement to reveal fundamental mechanisms of CoV-related macromolecules will be developed. The project will also provide an open-source and interactive web portal for public access of the developed tools. The work could have immediate impact on steps taken to halt the spread of SARS-CoV-2 and the current pandemic. Training opportunities for students at all levels, particularly women and underrepresented minorities will also be carried out. The results of the project can be found at: http://faculty.washington.edu/dongsi.

This RAPID award is made by the Infrastructure Innovation for Biological Research (IIBR Informatics) Program in the Division of Biological Infrastructure, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.