AI scans 4.6 million compounds in hours to predict hydrogen positions in drug-like molecules
New York University researchers have trained an AI model to learn chemical patterns associated with stability in drug-like molecules and accurately predict where their hydrogen atoms should be positioned.
Image: Phys.org
New York University researchers have trained an AI model to learn chemical patterns associated with stability in drug-like molecules and accurately predict where their hydrogen atoms should be positioned.
Originally published at Phys.org
