Researchers have used an artificial intelligence (AI) model to redesign a crucial protein involved in the delivery of gene therapy, a technique that employs genes to treat, prevent
or cure diseases.
The research, published in the journal Nature Machine Intelligence, optimised proteins to mitigate immune responses, thereby improving the efficacy of gene therapy and reducing side effects.
“Gene therapy holds immense promise, but the body’s pre-existing immune response to viral vectors greatly hampers its success,” said Michael Garton, an assistant professor at the University of Toronto, Canada. “Our research zeroes in on hexons, a fundamental protein in adenovirus vectors, which—but for the immune problem—hold huge potential for
gene therapy,” Garton said.
Immune responses triggered by certain antibodies pose a significant obstacle in getting these vehicles to the right target which can result in reduced efficacy and severe adverse effects, the researchers said.
To overcome this shortcoming, Garton’s lab used AI to custom-design variants of hexons that are distinct from natural sequences. “We want to design something that is distant from all human variants and is, by extension, unrecognisable by the immune system,” said Ph.D. Candidate Suyue Lyu, who is lead author of the study.
Traditional methods of designing new proteins often involve extensive trial and error as well as mounting costs.