recently a group of researchers published a paper at the WHO, describing a "virtual screening" of existing drugs. They used a "supercomputer" to simulate how good these drugs would bind to the Coronavirus' protein.
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As
yet, there are no established drugs or vaccines available. Speeding up drug discovery is urgently
required. We applied a workflow of combined in silico methods (virtual drug screening, molecular
docking and supervised machine learning algorithms) to identify novel drug candidates against
COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug
repositioning and of natural compound datasets from literature mining and the ZINC database to
select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid
protein, and 2’-o-ribose methyltransferase). Supported by the supercomputer MOGON II,
candidate compounds were predicted as presumable SARS-CoV-2 inhibitors. Interestingly, several
approved drugs against hepatitis C virus (HCV), another enveloped (-) ssRNA virus (paritaprevir,
simeprevir, grazoprevir, and velpatasvir) as well as drugs against transmissible diseases, against
cancer, or other diseases were identified as candidates against SARS-CoV-2. This result is
supported by reports that anti-HCV compounds are also active against Middle East Respiratory
Virus Syndrome (MERS) coronavirus. The candidate compounds identified by us may help to
speed up the drug development against SARS-CoV-2.
Same exact method, probably not. But many of the recent CPU projects are doing screening of potential drug candidates. Another batch are looking for potential sites for drugs to interact with and keep the virus from functioning to either infect cells or replicate.
iMac 2.8 i7 12 GB smp8, Mac Pro 2.8 quad 12 GB smp6
MacBook Pro 2.9 i7 8 GB smp3
Hardware configuration: Windows 7 Home Premium SP1 (64-bit) on HP P7-1254 computer. Processor: AMD A6-3620 APU with Radeon (tm) HD Graphics 2.20 Ghz. Had to install ADM Catalyst Center v. 2015.0804.21.41908 with OpenGL version 6.14.10.13399 (from AMD site) to solve "can't find OpenGL" errors. Browser: Chrome 53.0.2785.101 m (64-bit) (current as of September 10, 2016). Now using Folding@Home beta client v. 7.4.15 (64-bit).
To confirm what Joe_H said, I have seen several projects run on my CPU that are checking for possible interactions between SARS-CoV-2 and some candidate drugs as a way to thwart part of the process the virus uses to penetrate the host cell or to prevent it from multiplying. Some other projects that ran on my system are for studying how a certain protein of the virus works or what gaps open that may provide potential spots for interfering with the functioning of the virus.
While different researchers across the world are taking different approaches to COVID-19, I am convinced F@H simulations is one potential way that could produce useful results.
Folding@home is a part of the COVID moonshot project that is working on finding an antiviral for COVID-19. FAH has been running simulations on several molecules from this project for the past month and coordinating its research with other collaborators in this area.