Tingjun Hou

Previously, generative models for drug discovery worked like an artist painting without choosing a canvas. They learned from existing molecules and simply produced similar ones, without considering how the space of possible compounds is organized. SpaceGFN changes the approach: now chemical space is a construction set where the user specifies the parts and the assembly rules.

Imagine a huge garage with hundreds of parking spots. You're driving a tiny car, a future drug molecule, and you want to find the one free bay where it fits perfectly. But these bays aren't concrete; they're woven from DNA or RNA chains, and no one has posted the parking rules.

A dance of hundreds of particles: some pairs spin slowly and gracefully, others twitch in a frantic rhythm. To understand the essence of the dance, you need to watch the slow movements: they are the main choreography of the system. In molecular science, such slow movements are called 'slow modes,' and they determine how a protein folds into a ball or how a drug binds to its target.