Deep Apple’s $52 million funding revolutionizing drug discovery

Deep Apple Therapeutics discovers the therapeutics for high-value targets through virtual screening of artificial intelligence (AI)-generated virtual libraries.

With a powerful discovery engine that combines ensemble cryo-EM, deep learning, and molecular docking screens of ultra-large libraries, Deep Apple can go from target identification to lead optimization in less than 12 months – a fraction of the industry standard time – and can pursue biological target signaling inaccessible to conventional discovery approaches.

“ATP created Deep Apple to revolutionize drug discovery in terms of speed, cost, and effectiveness,” said Spiros Liras, founding CEO of Deep Apple and a Venture Partner at ATP.

“We brought together unique capabilities from our founders to build a true deep learning discovery engine that stands apart from the pack of AI-driven approaches to protein structure elucidation and drug discovery.

“Machine-learning enabled processing of cryo-EM data allows us to reveal biologically relevant conformations in the context of interactions with signaling partners – transient binding pockets that may be missed by static models and empirical screening methods. And our virtual large-scale docking enables us to quickly home in on the right drug for the right target.”

The discovery engine is particularly well-suited to expedited hit-finding against integral membrane proteins and is broadly applicable across disease areas.

The company currently is advancing multiple programs focused on GPCR modulators, a proven target class with applications in metabolic disorders, inflammation, immunology, and endocrine diseases.

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