How Network Science Surfaced 81 Potential COVID-19 Therapies

Researchers have harnessed the computational tools of network science to generate a list of 81 drugs used for other diseases that show promise in treating COVID-19. Some are already familiar-including the malaria and lupus treatments chloroquine and hydroxychloroquine-while many others are new, with no known clinical trials underway.

Since the concept was first proposed in 2007, network medicine has applied the science of interconnected relationships among large groups to networks of genes, proteins, interactions and other biomedical factors. Both Harvard and MIT Open Courseware today offer classes in network medicine, while cancer research in particular has experienced a proliferation of network medicine studies and experimental treatments.

Albert-Laszlo Barabasi, distinguished university professor at Northeastern University in Boston, is generally considered the founder of both network medicine and modern network science. In a recent interview via email, Barabasi said COVID-19 represents a tremendous opportunity for a still fledgling science.

In many ways, the COVID offers a great test for us to marshal the set of highly predictive tools that we as a community [have developed] in the past two decades," Barabasi said.

Last month, Barabasi and ten co-authors from Northeastern, Harvard and Brigham and Women's Hospital in Boston published a pre-print paper proposing a network medicine-based framework for repurposing drugs as COVID-19 therapies. The paper has not been submitted for peer-review yet, says Deisy Morselli Gysi, a postdoctoral researcher at Northeastern's Network Science Institute.

The paper is not under review anywhere," she said. But we are planning of course to submit it once we have [laboratory] results."

The 81 potential COVID-19 drugs their computational pipeline discovered, that is, are now being investigated in wet-lab studies.

The number-one COVID-19 drug their network-based models predicted was the AIDS-related protease inhibitor ritonavir. The U.S. Centers for Disease Control's ClinicalTrials.gov website lists 108 active or recruiting trials (as of May 6) involving ritonavir, with a number of the current trials being for COVID-19 or related conditions.

However, the second-ranked potential COVID-19 drug their models surfaced was the antibacterial and anti-tuberculosis drug isoniazid. ClinicalTrials, again as of May 6, listed 65 active or recruiting studies for this drug - none of which, however, were for coronavirus. The third and fourth-ranked drugs (the antibiotic troleandomycin and cilostazol a drug for strokes and heart conditions) also have no current coronavirus-related clinical trials, according to ClinicalTrials.gov.

Barabasi said the group's study took its lead from a massively-collaborative paper from March 27 which identified 26 of the 29 proteins that make up the SARS-CoV-2 coronavirus particle. The study then identified 332 human proteins that bind to those 26 coronavirus proteins.

Barabasi, Gysi and co-researchers then mapped those 332 proteins to the larger map of all human proteins and their interactions. This interactome" (a molecular biology concept first proposed in 1999) tracks all possible interactions between proteins.

Of those 332 proteins that interact with the 26 known and studied coronavirus proteins, then, Barabasi's group found that 208 of them interact with one another. These 208 proteins form an interactive network, or what the group calls a large connected component" (LCC). And a vast majority of these LCC proteins are expressed in the lung, which would explain why coronavirus manifests so frequently in the respiratory system: Coronavirus is made up of building blocks that each can chemically latch onto a network of interacting proteins, most of which are found in lung tissue.

However, the lung was not the only site in the body where Barabasi and co-authors discovered coronavirus network-based activity. They also discovered several brain regions whose expressed proteins interact in large connected networks with coronavirus proteins. Meaning their model predicts coronavirus could manifest in brain tissue as well for some patients.

That's important, Gysi said, because when their models made this prediction, no substantial reporting had yet emerged about neurological COVID-19 comorbidities. Today, though, it's well-known that some patients experience a neurological-based loss of taste and smell, while others experience strokes at higher rates.

Brains and lungs aren't the only possible hosts for the novel coronavirus. The group's findings also indicate that coronavirus may manifest in some patients in reproductive organs, in the digestive system (colon, esophagus, pancreas), kidney, skin and the spleen (which could relate to immune system dysfunction seen in some patients).

Of course the first drug the FDA approved for emergency use specifically for COVID-19 is the protease inhibitor remdesivir. However Barabasi and Gysi's group did not surface that drug at all in their study.

This is for a good reason, Gysi explained. Remdesivir targets the SARS-CoV-2 virus specifically and not any interactions between the virus and the human body. So remdesivir would not have showed up on the map of their network science-based analysis, she said.

Barabasi said his team is also investigating how network science can assist medical teams conducting contact tracing for COVID-19 patients.

There is no question that the contact tracing algorithms will be network science based," Barabasi said.

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