Brazil-based oil company Petrobras will direct part of the processing capacity of its high-performance computers (HPC) to contribute to the Folding@home Project effort on studying the coronavirus behavior in the human body and how the disease progresses, from the interaction of viral proteins, making way for for the development of medication and vaccines.
Launched in 2000, the Folding@home project is a distributed computing project for simulating protein dynamics, including the process of protein folding and the movements of proteins implicated in a variety of diseases. It brings together citizen scientists who volunteer to run simulations of protein dynamics on their personal computers.
Insights from this data are helping scientists to better understand biology, and providing new opportunities for developing therapeutics. Among other advancements, this project has already helped in identifying the protein which links the SARS-CoV-2 betacoronavirus (the virus that causes COVID-19) to human cells.
Up to two supercomputers in Petrobras’ service may have their processing capacity redirected to this research: the Santos Dumont, Latin America’s largest supercomputer, located in the National Scientific Computing Lab (Laboratório Nacional de Computação Científica - LNCC), in Petrópolis (RJ), which recently had its capacity enhanced by collaboration with another lab, the company and its partners in the Libra Consortium; and OBGON, result of the partnership with Senai-Cimatec, installed in Salvador (BA).
For the initiative, the company will mobilize 60% of Santos Dumont’s capacity—2 petaflops (equivalent to the computational capacity of 2 million laptops)—in addition to 50% of Senai-Cimatec capacity, corresponding to one petaflop (1 million laptops).
The use of these supercomputers allows for accelerating the simulation time in order for researchers to achieve results faster in their research.
In addition to this initiative, Petrobras will mobilize its high performance computational resources for research projects of Brazilian universities in fighting coronavirus. One of the potential projects, in a partnership with both PUC-Rio and Senai-Cimatec, is the use of artificial intelligence techniques (deep learning) in order to help differentiate the X-ray exam of a regular flu patient and the X-ray exam of a coronavirus patient.
The algorithms create repetition patterns and, by comparing the data, it is possible to arrive at a diagnosis. It is a test cheaper and faster than, for example, tomography and PCR blood exams.
These initiatives integrate a broad front led by Petrobras, which is mobilizing its professionals from various fields of knowledge that may contribute in fighting the coronavirus, in partnership with universities, companies, social organizations, Brazilian and foreign institutions. Its goal is to propose solutions that may use the company’s technological structure, equipment and technical consulting in order to aid the effort in fighting the pandemic, in the prevention, treatment and hospital support fronts.
In the same way, Petrobras is also dedicated to initiatives such as donation supply to institutions—including, for example, safety and hygiene items to the UFRJ hospital—and mobilizing its structures for storage, among others.
On the Folding@home Project. Viruses have proteins that they use to suppress our immune systems and reproduce themselves. To help tackle coronavirus, researchers want to understand how these viral proteins work and how to design therapeutics to stop them.
Folding@home’s specialty is in using computer simulations to understand proteins’ moving parts. Watching how the atoms in a protein move relative to one another is important because it captures valuable information that is inaccessible by any other means.
Taking the experimental structures as starting points, Folding@home can simulate how all the atoms in the protein move, effectively filling in the rest that experiments miss. Doing so can reveal new therapeutic opportunities.
In a recent paper, Folding@home simulated a protein from Ebola virus that is typically considered undruggable because the snapshots from experiments don’t have obvious druggable sites. But the simulations uncovered an alternative structure that does have a druggable site. Experiments confirmed the computational prediction, and now there is a search for drugs that bind this newly discovered binding site.
Folding@home seeks to do the same thing with SARS-CoV-2. On 10 March, after initial quality control and limited testing phases, the Folding@home team released an initial wave of projects simulating potentially druggable protein targets from SARS-CoV-2 and the related SARS-CoV virus (for which more structural data is available) into full production on Folding@home.
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.