COVID-19 - Exploration of potential therapeutics against underexplored targets.
- Funded by UK Research and Innovation (UKRI)
- Total publications:5 publications
Grant number: EP/V010948/1
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$192,769.06Funder
UK Research and Innovation (UKRI)Principal Investigator
PendingResearch Location
United KingdomLead Research Institution
University of OxfordResearch Priority Alignment
N/A
Research Category
Therapeutics research, development and implementation
Research Subcategory
Pre-clinical studies
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 genome of SARS CoV-2 encodes proteins which perform various functions essential for the replication of the virus. By exploiting our knowledge of the 3D structures of these proteins we can identify and/or design small molecules (i.e. drugs) that bind to viral proteins to prevent them from performing their normal function. COVID-19 research groups worldwide been determining 3D structures of proteins encoded within the viral genome. The focus has been on high-profile target proteins of Cov-2, including the protease, spike protein and helicases. Perhaps surprisingly, less effort is being directed towards other promising targets for which there is structural information. We focus on two underexplored proteins, NSP9 (involved in RNA processing) and E protein (a viroporin). NSP9 helps the virus to replicate its genome. By identifying a compound that binds to NSP9, we would have a potential drug to halt viral replication in infected cells. E protein is a viroporin, forming channels in infected cell and viral membranes. Molecules which 'plug' the channel ("channel blockers") are potential anti-viral drugs. For target proteins, we will combine advanced molecular simulations in Oxford with AI-driven identification of potential compounds by IBM to enable and accelerate identification of compounds which could be repurposed as candidate anti-viral drugs. The IBM generative AI method has already been successful in identifying new antimicrobials that have since been experimentally validated. The work here will be undertaken as part of a long-standing collaboration between Oxford and IBM and the strong relationship will ensure delivery of this highly collaborative effort.
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