These aren't protein crystal structures, they are metal-organic frameworks (MOFs), so AlphaFold probably wouldn't work well on these ones.
It would be really interesting to see an equivalent model trained to predict these structures. The physical chemistry of transition metal complexes, especially when multiple metals are in close proximity to each other and connected by shared ligands, is much more complicated than proteins. The reason is because of multireference effects - essentially the quantum entanglement of multiple possible electron configurations. These are exceedingly difficult calculations to perform - common approximations are O(n^8) or worse and require highly specialized knowledge to apply correctly - so an ML model that can efficiently make predictions in this space would be a major transformative breakthrough.
It would be really interesting to see an equivalent model trained to predict these structures. The physical chemistry of transition metal complexes, especially when multiple metals are in close proximity to each other and connected by shared ligands, is much more complicated than proteins. The reason is because of multireference effects - essentially the quantum entanglement of multiple possible electron configurations. These are exceedingly difficult calculations to perform - common approximations are O(n^8) or worse and require highly specialized knowledge to apply correctly - so an ML model that can efficiently make predictions in this space would be a major transformative breakthrough.