Probably worth mentioning that David Baker’s lab released a similar model (predicts protein structure along with bound DNA and ligands), just a couple of months ago, and it is open source [1].

It’s also worth remembering that it was David Baker who originally came up with the idea of extending AlphaFold from predicting just proteins to predicting ligands as well [2].

1. https://github.com/baker-laboratory/RoseTTAFold-All-Atom

2. https://alexcarlin.bearblog.dev/generalized/

Unlike AlphaFold 3, which predicts only a small, preselected subset of ligands, RosettaFold All Atom predicts a much wider range of small molecules. While I am certain that neither network is up to the task of designing an enzyme, these are exciting steps.

One of the more exciting aspects of the RosettaFold paper is that they train the model for predicting structures, but then also use the structure predicting model as the denoising model in a diffusion process, enabling them to actually design new functional proteins. Presumably, DeepMind is working on this problem as well.