New AI tool to counter emergent mutations of Covid

Researchers have developed a new method using artificial intelligence (AI) to counter emergent mutations of the coronavirus and speed up vaccine development to stop the pathogen responsible for killing thousands of people worldwide.

The method developed by researchers at University of Southern California Viterbi School of Engineering in the US is easily adaptable to analyse potential mutations of the virus, ensuring the best possible vaccines are quickly identified -- solutions that give humans a big advantage over the evolving contagion.

Their machine-learning model can accomplish vaccine design cycles that once took months or years in a matter of seconds and minutes, said the study published in the journal Scientific Reports.

"This AI framework, applied to the specifics of this virus, can provide vaccine candidates within seconds and move them to clinical trials quickly to achieve preventive medical therapies without compromising safety," said Paul Bogdan, Associate Professor at USC Viterbi and corresponding author of the study.

"Moreover, this can be adapted to help us stay ahead of the coronavirus as it mutates around the world."

When applied to SARS-CoV-2 -- the virus that causes Covid-19 -- the computer model quickly eliminated 95 per cent of the compounds that could have possibly treated the pathogen and pinpointed the best options, the study said.


The AI-assisted method predicted 26 potential vaccines that would work against the coronavirus.

From those, the scientists identified the best 11 from which to construct a multi-epitope vaccine, which can attack the spike proteins that the coronavirus uses to bind and penetrate a host cell.

Vaccines target the region -- or epitope -- of the contagion to disrupt the spike protein, neutralising the ability of the virus to replicate.


The method is especially useful during this stage of the pandemic as the coronavirus begins to mutate in populations around the world.

Some scientists are concerned that the mutations may minimise the effectiveness of vaccines which are now being distributed.

Recent variants of the virus that have emerged in the UK, South Africa and Brazil seem to spread more easily, which scientists say will rapidly lead to many more cases, deaths and hospitalisations.


But Bogdan said that if SARS-CoV-2 becomes uncontrollable by current vaccines, or if new vaccines are needed to deal with other emerging viruses, then USC's AI-assisted method can be used to design other preventive mechanisms quickly.

"The proposed vaccine design framework can tackle the three most frequently observed mutations and be extended to deal with other potentially unknown mutations," Bogdan said.

The raw data for the research comes from a giant bioinformatics database called the Immune Epitope Database (IEDB) in which scientists around the world have been compiling data about the coronavirus, among other diseases. - IANS