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How You Can Join the Data-Driven Fight Against Coronavirus


Nick Welke



From the way we work to how we connect with loved ones, the coronavirus pandemic has upended our day-to-day lives. Some restrictions have eased, but the long-term outlook for a return to normalcy remains unclear without an effective vaccine.

But even as researchers work toward a biochemical means to combat COVID-19, there’s no clear timetable for such a solution. Though we have all done our best to minimize infections by following social distancing guidelines, there seems to be little more that can be done by those outside the medical community to bring the crisis to a close.

Except in terms of processing capacity.

Following the lead of some 1.3 million volunteer users, Zencos has joined a distributed computing project called Rosetta@home. Dedicated to fighting the coronavirus at the molecular level through sharing unused processing power, Rosetta@home allows remote computers to process complex calculations during idle hours and share results with researchers. With most workplaces now operating remotely, office computers built for processing big data applications have been sitting unused.

Now, from across the country, these machines are being put to work toward stopping the spread of COVID-19.

The Roots of Rosetta@home and Distributed Computing Research

Developed in 1998 by the Baker Laboratory at the University of Washington, the Rosetta platform is predicated on the idea of combating diseases at their root cause. Viruses and other disorders spread by forming connections with human cells. Led by award-winning biochemist David Baker, Rosetta analyzes virus structures at the cellular level with the goal of inhibiting those connections.

Seven years after its lab creation, Rosetta@home was released to the public to continue those efforts as a distributed computing project on the Berkley Open Infrastructure for Network Computing (BOINC) platform.

A technology that has been around for decades, distributed computing allows computers connected across a network to share resources. Through sharing software components, distributed computing allows a network to then function as a single machine.

In the past, distributed computing has been used to search for extraterrestrial intelligence (SETI@home), collaborate on academic and public-interest projects on distributed.net, and solve encryption algorithms through the RSA Secret-Key Challenge.

Rosetta@home uses idle computers from volunteers across the country to process and predict protein structures that form attachment points between viruses and healthy human cells. Previously, the Baker lab used Rosetta@home to research the molecular mechanics for diseases such as HIV, Alzheimer’s, and malaria.

In terms of its efforts against COVID-19, Rosetta@home studies the points where human cells are vulnerable to attachment by the virus. Each human cell has a receptor site that matches with a spike protein on the coronavirus. By modeling the structure of these proteins, the Baker Lab searches for means to stop the virus at that attachment point. Without an ability to bond with human cells, the virus will be unable to cause infection.

On a massive scale, Rosetta@home is running a database search for the right protein structure that will block what makes COVID-19 contagious. That’s where the effort’s network of volunteers come in.

How Rosetta@home Puts Idle Machines to Work

Once a user, or company, joins the Rosetta@home project, their computers begin tackling the large-scale data problem of fighting COVID-19. Each computer is configured with a screensaver that activates during its idle hours. After a message indicating a test is about to start, the screensaver then downloads a set of proteins from the Baker lab.

These then enlist the computers to perform an evaluation of the proteins as a potential fit with the coronavirus’ receptors at an atomic scale. One the calculation is complete, the results are then transmitted back to researchers and the process repeats. Once the computer is activated by its owner, Rosetta@home’s analysis concludes until off hours resume.

As of mid-May 2020, more than three million computers had joined Rosetta@home, and their combined processing power is impressive. In computer science terms, the act of processing large numbers and non-integers is called a floating point operation. These computer-intensive calculations are commonly seen in crypto-currency mining and are measured in floating point operations per second (FLOPS).

With over a million volunteers, Rosetta@home’s users have in some cases lent multiple personal computers to the project. With the combined resources of over 3 million computers, Rosetta@home is working with the computing power of more than a quadrillion of these operations—or 1.8 teraFLOPS.

A Collaborative Pandemic Response Transcends Business Opportunities

Apart from basic preventative efforts, there is little that data and IT professionals can do to combat the effects of the pandemic. However, Rosetta@home shows there are still vital ways to make a meaningful contribution. In many ways, pathology science and pharmaceutical activities are data-driven, computer-intensive activities.

Though some 3 million computers constitutes a considerable communal effort, most of these come at the individual level. Many organizations have idle computing resources given the ongoing impact of the pandemic, but most are reluctant to join the Rosetta@home effort because of inherent security concerns.

With data security in mind, distributed computing is built upon allowing an outside entity to install software on an organization’s machines. This requires a level of trust that this code will not contain anything malicious or leave their computers vulnerable to hackers.

However, Zencos considered this a manageable risk given the prior experience some on our team have had with the program’s toolset. Plus, distributed computing is the basis of all grid networks, which is a common part of our work using multiple machines to solve a data processing problem. Given Rosetta@home is ultimately a data activity, the project seemed suited to our experience and unused resources. While there’s no business justification for volunteering to join Rosetta@home, the ability to contribute toward accelerating the search for a vaccine was a justification unto itself.

Without question, the fight against the virus constitutes a widespread, ongoing effort with an uncertain outcome. Even Rosetta@home constitutes only a small contribution, but its community of volunteers shows there are ways that non-specialists can help.

In this instance, you don’t have to be a scientist to help with the science.