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Grant: Alliance Grants

Dalhousie University

$50,000.00

To inform drug design for COVID-19: Computational determination of interactions between COVID-19 gene products and structurally diverse natural products and clinical drugs_x000d_ _x000d_

FY 2020-21

Summary
Vaccines are the preferred public health solution to combating infectious disease, including viruses. However, there remains a strong need to develop small molecule therapeutics as an orthogonal approach to treat viral infections. This proposal aims to provide insight into potential drug leads for COVID-19. X-ray crystal structures of the proteins and enzymes produced from the COVID-19 coronavirus genome are being solved around the world and deposited into publicly available databases. Some of these three-dimensional structures include small molecules bound to active sites, allosteric sites or sites of protein-protein interactions. This insight offers a starting point for the discovery of lead molecules to be developed as antivirals to treat COVID-19 infected patients. However, chemical diversity is much richer and more varied than the few scaffolds identified through X-ray crystallography. In this NSERC Alliance proposal, we will screen, using computational approaches, published X-ray structures of the gene products from the COVID-19 virus alongside structurally diverse molecules (databases) in order to determine docking interactions. We will thus rank the molecules in terms of their computational binding affinity and structural pose. This will provide a diverse dataset of structures to be evaluated as drug leads as a starting point for drug discovery projects. Preliminary results included herein indicate that computational docking predicts and reproduces the very recently published X-ray structural binding of potent inhibitors to the SARS-CoV-2 main protease, the protease responsible for activating the COVID-19 polypeptide. These data demonstrate that computational approaches are a meaningful step towards identification of lead molecules. The results will be published in a timely manner to ensure rapid dissemination of the research results. Furthermore, the results will be shared with the partner organization (IntelliSyn, Montreal) a contract research organization and drug discovery team uniquely poised within Canada to build upon these results.
Program
Alliance Grants
Location
Nova Scotia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
550135-2020
Name nom
Jakeman, David
Department département
Pharmacy, College of
Organization id
79
Institution établissement
Dalhousie University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
50000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
504
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Human pharmaceuticals
Area of application fr
Produits pharmaceutiques administrables à l'homme
Research subject code
3705
Research subject group en
Organic chemistry
Research subject group fr
Chimie organique
Research subject en
Bio-organic chemistry
Research subject fr
Chimie bio-organique
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
To inform drug design for COVID-19: Computational determination of interactions between COVID-19 gene products and structurally diverse natural products and clinical drugs_x000d_ _x000d_
Keyword
NSERC
Application summary
Vaccines are the preferred public health solution to combating infectious disease, including viruses. However, there remains a strong need to develop small molecule therapeutics as an orthogonal approach to treat viral infections. This proposal aims to provide insight into potential drug leads for COVID-19. X-ray crystal structures of the proteins and enzymes produced from the COVID-19 coronavirus genome are being solved around the world and deposited into publicly available databases. Some of these three-dimensional structures include small molecules bound to active sites, allosteric sites or sites of protein-protein interactions. This insight offers a starting point for the discovery of lead molecules to be developed as antivirals to treat COVID-19 infected patients. However, chemical diversity is much richer and more varied than the few scaffolds identified through X-ray crystallography. In this NSERC Alliance proposal, we will screen, using computational approaches, published X-ray structures of the gene products from the COVID-19 virus alongside structurally diverse molecules (databases) in order to determine docking interactions. We will thus rank the molecules in terms of their computational binding affinity and structural pose. This will provide a diverse dataset of structures to be evaluated as drug leads as a starting point for drug discovery projects. Preliminary results included herein indicate that computational docking predicts and reproduces the very recently published X-ray structural binding of potent inhibitors to the SARS-CoV-2 main protease, the protease responsible for activating the COVID-19 polypeptide. These data demonstrate that computational approaches are a meaningful step towards identification of lead molecules. The results will be published in a timely manner to ensure rapid dissemination of the research results. Furthermore, the results will be shared with the partner organization (IntelliSyn, Montreal) a contract research organization and drug discovery team uniquely poised within Canada to build upon these results.