A crowdsourcing project drawing on individual and corporate computing power worldwide has created a supercomputer to help accelerate coronavirus research.
Gamers, bitcoin “miners” and companies large and small have teamed up for an unprecedented data-crunching effort that aims to harness idle computing power to accelerate research for a coronavirus treatment.
The project led by computational biologists has effectively created the world’s most powerful supercomputer that can handle trillions of calculations needed to understand the structure of the virus.
More than 400,000 users downloaded the application in the past two weeks from “[email protected],” according to director Greg Bowman, a professor of biochemistry and molecular biophysics at Washington University in St. Louis, where the project is based.
The “distributed computing” effort ties together thousands of devices to create a virtual supercomputer.
The project originally launched at Stanford University 20 years ago was designed to use crowdsourced computing power for simulations to better understand diseases, especially “protein folding” anomalies that can make pathogens deadly.
“The simulations allow us to watch how every atom moves throughout time,” Bowman told AFP.
The massive analysis looks for “pockets” or holes in the virus where a drug can be squeezed in.
“Our primary objective is to hunt for binding sites for therapeutics,” Bowman said.
The powerful computing effort can test potential drug therapies, a technique known as computational drug design.
Bowman said he is optimistic about this effort because the team previously found a “druggable” target in the Ebola virus and because COVID-19 is structurally similar to the SARS virus which has been the subject of many studies.
“The best opportunity for the near-term future is if we can find an existing drug that can bind to one of these sites,” he said.
“If that happens it could be used right away.”
This is likely to include drugs like the antimalarials chloroquine and hydroxychloroquine which may be “repurposed” for COVID-19.
Bowman said the project has been able to boost its power to some 400 petaflops—with each petaflop having a capacity to carry out one quadrillion calculations per second—or three times more powerful than the world’s top supercomputers.
Other supercomputers are also working in parallel. The Oak Ridge National Laboratory said earlier this month that by using IBM’s most powerful supercomputer it had identified 77 potential compounds that could bind to the main “spike” protein of the coronavirus to disarm the pathogen.
No end to compute power
The [email protected] project is fueled by crowdsourced computing power from people’s desktops, laptops and even PlayStation consoles, as well as more powerful business computers and servers.
“There is no end to the compute power than we can use in principle,” Bowman said. Large tech firms including Microsoft-owned GitHub are also participating, and the project is in discussions with others.
Anyone with a relatively recent computer can contribute by installing a program which downloads a small amount of data for analysis. People can choose which disease they wish to work on.
“It’s like bitcoin mining, but in the service of humanity,” said Quentin Rhoads-Herrera of the security firm Critical Start, which has provided its powerful password “hash cracker” computer designed to decrypt passwords to the project.
Rhoads-Herrera said his team of security researchers, sometimes described as “white hat hackers,” were encouraging more people to get involved.
Computer chipmaker Nvidia, which makes powerful graphics processors for gaming devices, called on gamers to join the effort as well.
“The response has been record-breaking, with tens of thousands of new users,” joining, said Nvidia spokesman Hector Marinez.
One of the largest contributions comes from a Reddit group of PC enthusiasts and gamers which has some 24,000 members participating.
“It is a fantastic weapon against the feeling of helplessness,” said Pedro Valadas, a lawyer in Portugal who heads the Reddit community and is a part of the project’s advisory board.
“The fact that anyone, at home, with a computer, can play a role and help fight against (disease) for the common good is a powerful statement,” Valadas told AFP.
We need your help! [email protected] is joining researchers around the world working to better understand the 2019 Coronavirus (2019-nCoV) to accelerate the open science effort to develop new life-saving therapies.
By downloading [email protected], you can donate your unused computational resources to the [email protected] Consortium, where researchers working to advance our understanding of the structures of potential drug targets for 2019-nCoV that could aid in the design of new therapies.
The data you help us generate will be quickly and openly disseminated as part of an open science collaboration of multiple laboratories around the world, giving researchers new tools that may unlock new opportunities for developing lifesaving drugs.
2019-nCoV is a close cousin to SARS coronavirus (SARS-CoV), and acts in a similar way. For both coronaviruses, the first step of infection occurs in the lungs, when a protein on the surface of the virus binds to a receptor protein on a lung cell.
A therapeutic antibody is a type of protein that can block the viral protein from binding to its receptor, therefore preventing the virus from infecting the lung cell. A therapeutic antibody has already been developed for SARS-CoV, but to develop therapeutic antibodies or small molecules for 2019-nCoV, scientists need to better understand the structure of the viral spike protein and how it binds to the human ACE2 receptor required for viral entry into human cells.
Proteins are not stagnant—they wiggle and fold and unfold to take on numerous shapes. We need to study not only one shape of the viral spike protein, but all the ways the protein wiggles and folds into alternative shapes in order to best understand how it interacts with the ACE2 receptor, so that an antibody can be designed.
Low-resolution structures of the SARS-CoV spike protein exist and we know the mutations that differ between SARS-CoV and 2019-nCoV. Given this information, we are uniquely positioned to help model the structure of the 2019-nCoV spike protein and identify sites that can be targeted by a therapeutic antibody. We can build computational models that accomplish this goal, but it takes a lot of computing power.
This is where you come in! With many computers working towards the same goal, we aim to help develop a therapeutic remedy as quickly as possible.
One protein from 2019-nCoV, a protease encoded by the viral RNA, has already been crystallized.
Although the 2019-nCoV spike protein of interest has not yet been resolved bound to ACE2, our objective is to use the homologous structure of the SARS-CoV spike protein to identify therapeutic antibody targets.