Generate Biomedicines Uses AI to Create Proteins That Have Never Existed

Generate Biomedicines published a preprint describing a breakthrough in protein science that unlocks the ability to generate novel proteins, at will, towards desired functional or other properties. This is enabled by their new machine learning (ML) model, Chroma, which Generate believes will usher in a new age in which proteins—the most functional molecules of life—can become truly programable, with a transformative impact on human health.

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“The transition from conventional drug discovery to generative biology will mean that we no longer discover suboptimal medicines that nature evolved for its own purposes; instead, we will be creating, or generating, purpose-built, highly efficacious medicines.”

The work reinforces that the immense biodiversity of our planet, encoded by protein sequences resulting from ~3.5 billion years of evolution, is but a drop in the ocean of all possible protein concepts. Generate has demonstrated how these concepts can now be accessed, through their generative ML-based model Chroma, and used in service of a powerful method for designing novel proteins.

“We believe our model will have revolutionary implications. It is akin to learning how to ‘write’ in the mysterious language of proteins. Now that we have this ability, the possibilities of what we can produce are endless.” said Gevorg Grigoryan, Ph.D., Co-Founder and Chief Technology Officer of Generate Biomedicines. “The transition from conventional drug discovery to generative biology will mean that we no longer discover suboptimal medicines that nature evolved for its own purposes; instead, we will be creating, or generating, purpose-built, highly efficacious medicines.”

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The capability to program proteins has promising and important implications for designing novel therapeutics, bringing new medicines to patients faster, cheaper, and better tailored to their specific conditions. As Generate’s platform is constantly learning from each new protein it produces and validates in the laboratory, it will enable therapeutic development on a scale previously unseen.

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