Mentioned in 4 AI use cases across 2 industries
Think of OpenFold3 as a super–high‑resolution 3D microscope for molecules that doesn’t need a lab experiment. You give it the sequence of a protein (or protein complex), and it predicts the detailed 3D shape and how different proteins might fit together—like solving a 3D jigsaw puzzle from just the list of pieces.
Think of AlphaFold 2 as a revolutionary microscope that predicts how single proteins fold in 3D. The “next frontier” the article discusses is like upgrading from looking at a single Lego brick to understanding whole Lego machines: how multiple proteins, RNAs, DNA, and small molecules interact, move, and change shape in real time inside a cell.
This is like a super-smart screening funnel for drug-like mini-proteins. Instead of testing millions of molecules in the lab, it uses a combination of AI predictions and physics-based simulations to quickly sort through candidates and highlight the handful most likely to stick to a disease target.
This is like an AI-powered "design studio" for proteins: it uses AlphaFold-style structure prediction to help scientists quickly design and evaluate many protein variants on a computer before committing to slow and expensive lab experiments.