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Proto: A programming language for generative biology | Arc Institute

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For years, biological research has relied on assembling natural components through trial-and-error or screening thousands of candidates until something worked. While powerful AI models for protein design, RNA engineering, and gene regulation have the potential to accelerate this process, they remain isolated in computational silos, out of reach for many experimental biologists. Today, the Laboratory of Evolutionary Design, led by Brian Hie, is releasing Proto, a framework that integrates these diverse AI tools to enable complex, multi-modal biological design.

A conversation with Brian Hie, Aditi Merchant, Daniel Guo, and Ben Viggiano Predicted structures of symmetric protein complexes designed using Proto, spanning a range of oligomeric states and symmetry groups. Credit: Hie Lab. For years, biological research has relied on assembling natural components through trial-and-error or screening thousands of candidates until something worked. While powerful AI models for protein design, RNA engineering, and gene regulation have the potential to accelerate this process, they remain isolated in computational silos, out of reach for many experimental…

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