Using AI and Big Data to Identify a Potential COVID-19 Peptide Treatment
On a molecular level, humans are susceptible to COVID-19 because a virus protein is able to bind to a human protein. If that interaction can be stopped, so could this disease. Researchers at Carleton University have synthesized a new protein that is able to do this.
Using artificial intelligence and Canada’s most powerful supercomputer, Ashkan Golshani and Frank Dehne analyzed millions of possible protein interactions. They have been developing algorithms that predict protein communications and potential drug treatments since 2003 and, using the IBM Blue Gene/Q supercomputer, they were able to predict that there would be a new type of protein that could stop the SARS-CoV-2 virus from infecting human cells. The researchers designed this new protein, and synthesized it. In a lab setting, it has been successful at preventing coronavirus infection with an efficacy of 75 per cent.
“We are trying to design a treatment for the disease, and these results show that this peptide should be an option,” says Golshani, a professor in the Department of Biology.
Peptide drugs are small proteins that are capable of interrupting interactions between other key proteins. Golshani and Dehne’s approach zeroed in on the interaction of two key proteins: the SARS-CoV-2 spike protein, and the human receptor called angiotensin-converting enzyme 2—more commonly called ACE2.
“The spike protein interacts with the ACE2 receptor in human cells, and that’s how COVID-19 infection starts,” says Golshani.
“Using artificial intelligence, we have been working to design new peptides that can interfere with the communication between these two proteins.”
The novel peptide could help treat people with severe COVID-19 symptoms, or prevent the progression of mild symptoms to more severe ones.