Here is how Boltz-1 (green), DynamicBind (magenta), and GNINA (blue) dock a collection of random molecules. GNINA, using a classical sampling algorithm (MCMC) hits all concave regions while the ML samplers have distinct preferences. Boltz is the most likely to induce a fit.

I’ll be at machine learning in structural biology workshop at NeurIPS this Friday and have a PhD internship position in my group this coming summer. Say hi if you are interested! roche.wd3.myworkdayjobs.com/ROG-A2O-GENE...