Computational design of COVID19 inhibitors
Title: |
Computational design of COVID19 inhibitors |
DNr: |
SNIC 2020/6-96 |
Project Type: |
SNIC Medium Storage |
Principal Investigator: |
Jens Carlsson <jens.carlsson.lab@gmail.com> |
Affiliation: |
Uppsala universitet |
Duration: |
2020-04-20 – 2022-01-01 |
Classification: |
10203 |
Homepage: |
http://www.carlssonlab.org |
Keywords: |
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Abstract
A protein involved in the viral lifecycle, Mpro, has emerged as a target for the identification of potent COVID19 inhibitors, which could lead to development of a first drug. Researchers have already released several fragment-bound crystal structures as part of an open-science effort to battle the pandemic. We are preparing virtual screens of compound libraries that are commercially available and connected to these fragment structures. Funding to our project allows us to purchase promising candidates from this library, which will be evaluated experimentally. Our next step is to determine which molecules should be prioritized, by further processing our dataset through structure-based virtual screening. To accomplish a rapid evaluation of these compounds, we require a sudden increase in computing resources and storage capacities.