Generating functional and multistate proteins with a multimodal diffusion transformer
Jing, B.; Sappington, A.; Bafna, M.; Shah, R.; Tang, A.; Krishna, R.; Klivans, A.; Diaz, D. J.; Berger, B.
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Generating proteins with the full diversity and complexity of functions found in nature is a grand challenge in protein design. Here, we present ProDiT, a multimodal diffusion model that unifies sequence and structure modeling paradigms to enable the design of functional proteins at scale. Trained on sequences, 3D structures, and annotations for 214M proteins across the evolutionary landscape, ProDiT generates diverse, novel proteins that preserve known active and binding site motifs and can be successfully conditioned on a wide range of molecular functions, spanning 465 Gene Ontology terms. We introduce a diffusion sampling protocol to design proteins with multiple functional states, and demonstrate this protocol by scaffolding enzymatic active sites from carbonic anhydrase and lysozyme to be allosterically deactivated by a calcium effector. Our results showcase ProDiTs unique capacity to satisfy design specifications inaccessible to existing generative models, thereby expanding the protein design toolkit.
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