AI Designs Over 7,000 New Proteins to Help Speed Up Medicine and Research

A research team from Chongqing University and Zhejiang University has developed an AI tool that created 7,245 new proteins—entirely through computer design. These proteins are made to latch onto targets like viruses or cancer markers, and can be used in medicines, lab tests, and scientific research.

Why Make New Proteins?

Special proteins can act like tiny tools that grab onto harmful cells or help detect diseases. They're essential in making drugs, vaccines, and diagnostic kits. But creating them by hand takes time and money. That’s why researchers and companies are turning to AI to make the process faster and more efficient.

Faster Design for Biotech and Pharma

The AI tool helps cut months of lab work down to weeks. It doesn’t just make proteins—it also predicts which ones will dissolve well in liquid and hold their shape when heated, so they’re less likely to clog lab equipment or break down during storage or transport. This makes them ready for testing and easier to manufacture.

“Our AI pipeline lets us design high-performance proteins quickly and at low cost,” said Prof. Weiwei Xue. “This gives smaller labs and companies a chance to compete and innovate.”

Big Data, Fast Filtering

To begin, the team collected over 1,300 existing protein structures from a public database. The AI generated five new versions of each, then quickly screened them for key features like stability and ability to stick to their target. Only the best-performing ones were selected—saving labs time by skipping weak candidates.

Ready for Real Use in the Lab and Clinic

More than 70% of the new proteins were predicted to dissolve cleanly in liquids like water or buffer solutions—important for use in lab tests, injection drugs, or test strips. About 60% stayed stable at high temperatures, which helps during shipping, storage, or sterilization.

Designed for Flexibility and Fit

The proteins were based on 55 different structure types, including parts of antibodies already used in approved drugs. The variety helps ensure the proteins can fit many different types of disease targets. Nearly half were predicted to bind even more tightly than older designs—important for accuracy in tests and strength in treatments.

Why It Matters

This work shows how AI can help speed up and lower the cost of developing proteins used in medicine. For drug and biotech companies, that means a faster pipeline. For hospitals and labs, it could lead to more reliable and affordable tests. And for researchers, it’s a new way to explore biology—faster and smarter than before. 

The research is published by Frontiers of Computer Science. 

Reference

1) https://link.springer.com/journal/11704

2) DOI: 10.1007/s11704-024-31060-3

(Newswise/VKR)