AI-Based Approach Could Help Develop New Protein-Based COVID-19 Antibody Therapies

A new approach to generating synthetic proteins using artificial intelligence (AI) has huge potential for developing efficient industrial enzymes as well as new protein-based medicine, such as antibodies and vaccines for the treatment of COVID-19.

Researchers at Chalmers University of Technology (Gothenburg, Sweden) have demonstrated that AI is now capable of generating novel, functionally active proteins. Proteins are large, complex molecules that play a crucial role in all living cells, building, modifying, and breaking down other molecules naturally inside our cells. They are also widely used in industrial processes and products, and in our daily lives. Protein-based drugs are very common - the diabetes drug insulin is one of the most prescribed. Some of the most expensive and effective cancer medicines are also protein-based, as well as the antibody formulas currently being used to treat COVID-19.


Current methods used for protein engineering rely on introducing random mutations to protein sequences. However, with each additional random mutation introduced, the protein activity declines. In a breakthrough in the field of synthetic proteins, the Chalmers researchers have developed an AI-based approach called ProteinGAN, which uses a generative deep learning approach. In essence, the AI is provided with a large amount of data from well-studied proteins; it studies this data and attempts to create new proteins based on it.

At the same time, another part of the AI tries to figure out if the synthetic proteins are fake or not. The proteins are sent back and forth in the system until the AI cannot tell apart natural and synthetic proteins anymore. This method is well known for creating photos and videos of people who do not exist, but in this study, it was used for producing highly diverse protein variants with naturalistic-like physical properties that could be tested for their functions.

The proteins widely used in everyday products are not always entirely natural but are made through synthetic biology and protein engineering techniques. Using these techniques, the original protein sequences are modified in the hope of creating synthetic novel protein variants that are more efficient, stable, and tailored towards particular applications. The new AI-based approach is of importance for developing efficient industrial enzymes as well as new protein-based therapies, such as antibodies and vaccines for the treatment of COVID-19.

“What we are now able to demonstrate offers fantastic potential for a number of future applications, such as faster and more cost-efficient development of protein-based drugs,” said Aleksej Zelezniak, Associate Professor at the Department of Biology and Biological Engineering.

Related Links:
Chalmers University of Technology