Using artificial intelligence (AI), a research team at the University of Southern California’s Viterbi School of Engineering developed a method to speed the analysis of vaccines and zero in on the best potential preventive medical therapy, according to a news release from the university.
The method is easily adaptable to analyze 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, the study said.
When applied to SARS-CoV-2 – the virus that causes COVID-19 – the computer model quickly eliminated 95 percent of the compounds that could’ve possibly treated the pathogen and pinpointed the best options.
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, neutralizing the ability of the virus to replicate.
The study explains that the USC scientists used only one B-cell epitope and one T-cell epitope, whereas applying a bigger dataset and more possible combinations can develop a more comprehensive and quicker vaccine design tool. The study estimates the method can perform accurate predictions with over 700,000 different proteins in the dataset.
The raw data for the research comes from a bioinformatics database called the Immune Epitope Database (IEDB) in which scientists around the world have been compiling data about the coronavirus, among other diseases. IEDB contains over 600,000 known epitopes from some 3,600 different species, along with the Virus Pathogen Resource, a complementary repository of information about pathogenic viruses. The genome and spike protein sequence of SARS-CoV-2 comes from the National Center for Biotechnology Information.
