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Revolutionizing AI in drug discovery via innovative molecular representation paradigms

CORDIS · observation · Publication date unknown

Revolutionizing AI in drug discovery via innovative molecular representation paradigms Artificial intelligence (AI) in the form of deep learning is driving unprecedented progress in numerous fields, e.g., for protein structure prediction and organic reaction planning. In drug discovery and chemical biology, such progress is an “evolution” rather than a revolution: several tasks still await to be solved by AI, e.g., accurate structure-activity and activity-cliff prediction, and design of structurally innovative chemical matter. Increasingly complex deep learning approaches are leading to progressively smaller gains in model capabilities, calling for a revolution in AI for drug discovery. The springboard for this project is a striking observation: while novel deep learning algorithms are in continuous development, the input ‘raw’ molecular representations they rely on (e.g., SMILES strings and molecular graphs) have not considerably changed in the last four decades – limitin

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recordType

award

status

SIGNED

region

EU

value

1494006

unit

EUR