Democratised data could accelerate early-stage drug discovery
A new multi-sector public-private partnership is bringing together 18 partners across nine countries to generate large, datasets of protein-ligand interactions. The project Ligand-AI is funded by the Innovative Health Initiative (IHI), aims to use the datasets to train AI models to predict candidate molecules as suitable binders for thousands of human proteins.
“This project brings together scientists and companies from across disciplines within an open science ecosystem. It is heartening to see these diverse scientific communities coalesce around a common vision to generate and share valuable chemical data openly with the world,” said Dr Aled Edwards, CEO of the Structural Genomics Consortium and project coordinator.
Over the next five years, experts across academia, research organisations and technology and industry companies will collaborate to generate open and accessible AI-ready protein-ligand data at scale as a public resource. The project has a budget of more than €60 million.
The Ligand-AI consortium is led by Pfizer and the Structural Genomics Consortium (SGC), and will interrogate thousands of proteins relevant to existing and unmet disease areas including rare, neurological and oncological conditions.
The latest organisations to join the consortium are integrated drug discovery services provider Chemspace, and chemical compound supplier Enamine.
“For us, Ligand-AI project represents a unique opportunity to contribute our approach to exploration of chemical space through DNA-encoded library (DEL) technologies to achieve a truly global impact,” said Chemspace CEO Dr Olga Tarkhanova.
By generating billions of accessible datapoints using complementary screening technologies, the project intends to accelerate the early drug discovery process.
