The researchers used computer-aided drug design to identify N3—a mechanism-based inhibitor of the main protease (Mpro) of SARS-CoV-2. The team went on to describe a high-resolution crystal structure of Mpro in complex with N3. Once they had this structure, they could use it as a model to identify more lead Mpro inhibitors. They then tested more than 10,000 compounds using a FRET assay to identify six drug candidates that target Mpro and may hold promise in combating COVID-19.The SARS-CoV-2
Please go through the recently published article..
https://www.nature.com/articles/s41586-020-2223-y
Article Identification of bioactive molecules from Tea plant as SARS...
I used to be a big fan of computer aided drug design. But in the current crisis there is some rush or overuse -certainly excusable due to the terrifying mortality rates- but still needs to be dealt with with great caution.
The ability of a compound to inhibit a viral protease is one thing, its effect in lab models is another thing, and its safety and efficacy in human subjects is another level.
So, as for the huge numbers used on screening, one would feel comfortable only with previously approved or at least known candidate drugs.
The rapid screening of potential candidates through computer simulations is a great tool when one has to deal with an urgent situation like the covid-19 pandemic. It allows the sorting out of potential compounds already established safe to use on humans and also design new strategies not easily achieved through conventional means. Of course, nothing replaces pre-clinical and clinical works, but modern computational methods allow the development of unique solutions without having to incur the associated high-costs of such endeavors.
We recently published a pre-print report showing what protein-ligand modeling allowed us to discover against SARS-COV-2 key proteins targets in record times at low costs:
Preprint Novel anti-SARS-CoV-2 mechanisms of fusion broad range anti-...
