Supercomputers are playing their part in urgent research into the novel coronavirus, which could help speed up the development of treatments.
The powerful machines are able to process huge amounts of data in a matter of days, compared to months on a regular computer.
This means they can screen libraries of potential antiviral drugs, including those that have already been licensed to treat other diseases.
“We are using the immense power of supercomputers to rapidly search vast numbers of potential compounds that could inhibit the novel coronavirus, and using the same computers again, but with different algorithms, to refine that list to the compounds with the best binding affinity,” said Prof Peter Coveney from University College London.
“That way, we are identifying the most promising compounds ahead of further investigations in a traditional laboratory to find the most effective treatment or vaccination for Covid-19.”
Scientists at UCL have access to some of the world’s most power supercomputers, as part of a consortium with more than a hundred researchers from across the US and Europe.
The world’s fastest, Summit, at Oak Ridge National Lab in the US and the world number nine, SuperMUC-NG in Germany, are included, and can analyse libraries of drug compounds to identify those capable of binding to the spikes on the surface of coronavirus, which the virus uses to invade cells, so as to prevent it from infecting human cells.
These machines could help by identifying virus proteins or parts of protein that stimulate immunity which could be used to develop a vaccine.
They can also study the spread of the virus within communities, as well as analysing its origin and structure, and how it interacts with human cells.
“This is a much quicker way of finding suitable treatments than the typical drug development process,” Coveney said.
“It normally takes pharma companies 12 years and US$2-billion to take one drug from discovery to market but we are rewriting the rules by using powerful computers to find a needle in a haystack in a fraction of that time and cost.”