"Unveiling the Depths of Protein Space: A Programmable Generative Model Sheds Light"
Originally Published 2 years ago — by Nature.com
Researchers have developed Chroma, a generative model for proteins that can efficiently generate high-quality protein structures with diverse properties. Chroma combines diffusion models and graph neural networks to model the joint likelihood of sequences and three-dimensional structures of protein complexes. The model achieves quasi-linear computational scaling, allowing it to handle larger protein systems. Chroma also enables conditional sampling, allowing for the programmable generation of proteins based on desired properties such as symmetry, shape, protein class, and even textual input. This scalable generative model has the potential to significantly advance the design and construction of functional protein systems.