Scientists in the Baker Lab published a preprint in March showing that RFdiffusion can be tuned to generate antibodies. Laboratory testing confirmed that these proteins can bind the influenza virus and other targets as intended.
This proof-of-concept study was recently covered by Nature.
From Nature:
Antibodies — immune molecules that strongly attach to proteins implicated in disease — have conventionally been made using brute-force approaches that involve immunizing animals or screening vast numbers of molecules.
AI tools that can shortcut those costly efforts have the potential to “democratize the ability to design antibodies”, says study co-author Nathaniel Bennett, a computational biochemist at the University of Washington in Seattle. “Ten years from now, this is how we’re going to be designing antibodies.”
“It’s a really promising piece of research” that represents an important step in applying AI protein-design tools to making new antibodies, says Charlotte Deane, an immuno-informatician at the University of Oxford, UK.
Read the full story by Ewen Callaway at nature.com
