Chroma uses a diffusion process, efficient neural architecture, and a low-temperature sampling algorithm to achieve protein design by Bayesian inference under external constraints like symmetries, substructure, shape, and natural-language prompts.
Experimental characterization of 310 proteins designed by Chroma shows that the generated proteins are highly expressed, properly fold, and possess favourable biophysical properties. Crystal structures of two designed proteins closely match Chroma samples.