Health · Medical Research · 6 hrs ago
University of Toronto team gets $2.3 million for peptide AI project
A team led by University of Toronto scientist Joseph Brown has received $2.3 million to develop OpenPep.
The project will create an open database and AI model to predict which peptides bind to target proteins.
Peptides are short chains of amino acids that can be engineered to act as medicines, but research data about them is scattered across labs, projects and companies.
This lack of shared data has made peptide discovery slow and has limited the information available to train AI models.
OpenPep aims to make peptide research faster and more collaborative by letting researchers use and contribute to the resource.
The team plans to produce up to 500 proteins linked to diseases and test large libraries of peptides against them; it will also ask researchers to suggest proteins to target.
A University of Toronto-led team has received US$2.3 million to develop an open-access peptide database and AI model.
The project, called OpenPep, aims to help researchers predict which peptides bind to target proteins.
The funding comes through Google.org’s Impact Challenge: AI for Science initiative.
The team says peptide discovery is slowed by a lack of data, which is scattered across labs, projects and companies.
Researchers plan to produce up to 500 disease-relevant proteins and test large peptide libraries against them.
- Who
- A team led by Joseph Brown, assistant professor at the University of Toronto’s Leslie Dan Faculty of Pharmacy.
- What
- It received US$2.3 million to develop an open-access database and AI model for peptide binding.
- When
- The funding was reported on October 14, 2026.
- Where
- The project is led by the University of Toronto in Canada.
- Why
- The team aims to address the shortage and fragmentation of data used in peptide discovery.
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- Funding
- US$2.3 million
- Project
- OpenPep
- Funding source
- Google.org Impact Challenge: AI for Science
- Protein targets
- Up to 500 disease-relevant proteins
- Lead researcher
- Joseph Brown, University of Toronto’s Leslie Dan Faculty of Pharmacy
What people are saying
That challenge inspired us to gather large amounts of data so we can build chemically-informed models and speed up the pace of discovery.
OpenPep aims to do just that-breaking down fragmented data barriers so scientists around the world can openly share knowledge and build on one another's discoveries.