AI scans 4.6 million compounds in hours to predict hydrogen positions in drug-like molecules

Researchers trained an AI model to predict stable hydrogen positions and tautomers directly from two-dimensional chemical structures. The open-source tool evaluates millions of compounds in hours without expensive quantum mechanics calculations. It allows researchers to spot misassigned ligand forms in structural databases and improve computer simulations of drug targets.

Summary written by AI Business Lens with an AI model from the article at phys.org. It is not the article, and the publisher has not reviewed it. For publishers.

Read the original at phys.org   Generate teaching or study materials

Instructors get discussion guides, assignments, and mini-cases. Students and readers get a plain summary, points to raise, an exercise, and a self-check. All built from the full article. A free account saves stories and gives you three generations. Stories stay on the brief for 14 days. After that this page keeps the link to the original.

More in Chemistry

• AI model predicts peptide bitterness and enables novel flavor designPhys.org — Biology · September 23, 2026