Folding@Home in the fight against COVID-19

A few weeks back, I heard about Folding@Home as a way to help in the COVID-19 fight. Here’s a link to the original article that aired on WTOP news.


To quote the article, “Folding@home is a new project focused on disease research, and in this case, possible cures for coronavirus. Here’s how it works: Anyone interested in helping donates their computer’s processing power to the project, which is used during intermittent downtime to process data. It’s done through a program that is downloaded online. Once set up, your computer becomes a part of a sort of super computer that works to process large amounts of information.”


I talked to a friend in IT, got his verification that this was a good thing to do, and loaded it up. My new online teaching setup involves two laptops to make everything work. The second one largely serves as a doc reader/scanner. Since it is doing so little active work, I figured it may as well run Folding@Home in the background.

I posted a link about it at the time on my socials. My hope was other folks might commit other machines that were sitting, or had idle time, and let it become a node in the network of computers crunching numbers and simulations on these research projects. As you might be able to see, this is not the newest laptop that I am using, but it is working out fine. Folks might have an older system that can be set up and committed to crunch numbers.

It’s been a few weeks now since I installed Folding@Home (or maybe it just feels like it). It’s been cool checking in, watching the computer crunch numbers on a wide variety of COVID-19 related projects, at different universities all over the country.

I figured I would share this update on Folding@home’s efforts to assist researchers around the world taking up the global fight against COVID-19. Maybe some other folks would be inspired to load the software and contribute to the cause.

After initial quality control and limited testing phases, Folding@home team has released an initial wave of projects simulating potentially druggable protein targets from SARS-CoV-2 (the virus that causes COVID-19) and the related SARS-CoV virus (for which more structural data is available) into full production on Folding@home. Many thanks to the large number of Folding@home donors who have assisted us thus far by running in beta or advanced modes.

This initial wave of projects focuses on better understanding how these coronaviruses interact with the human ACE2 receptor required for viral entry into human host cells, and how researchers might be able to interfere with them through the design of new therapeutic antibodies or small molecules that might disrupt their interaction.

In the coming days, we hope to take advantage of some of the new structural biology and biochemical data that is being rapidly released by researchers around the world who are working to understand these viruses and strategies for defeating them. This work has been largely disseminated by preprint servers such as bioRxiv and chemRxiv, which aim to make research rapidly available to both other researchers and the public for other scientists to broadly evaluate and immediately start building on. We have also forged several new collaborations with other laboratories where we hope Folding@home will provide valuable support in COVID-19 research efforts.

While we will rapidly release the simulation datasets for others to use or analyze, we aim to look for alternative conformations and hidden pockets within the most promising drug targets, which can only be seen in simulation and not in static X-ray structures. We hope that these structures—once validated by emerging compound screening data—could help direct the virtual screening campaigns or the targeting of new pockets for which atomistic structures were not yet available.

Below, we provide short descriptions of the projects. Note that all input files are being made available on GitHub here for other researchers to take advantage of:

This repository will evolve over the coming days as we add more projects and documentation. We will start posting datasets with structures on publicly available servers as soon as we have useful data to report.

All projects are using the new GPU-accelerated Core22 based on the open source OpenMM biomolecular simulation engine.

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