Artificial intelligence (AI) can help identify molecules that could serve as new drugs for mental health disorders. A study from Uppsala University published in Science Advances finds that AI can be used to predict the three-dimensional structures of important receptors and thereby speed up the development of potential drugs.

In drug development, experimental methods are often used to determine the three-dimensional structures of target proteins and understand how molecules bind to them. This information is needed to design drug molecules efficiently. However, the process of determining structures can be demanding, meaning this strategy cannot always be used.

In the study, researchers at Uppsala University used AI to create a model of the unknown three-dimensional structure of a receptor. In this case, the TAAR1 receptor, which is an interesting target protein for the development of drugs for mental health disorders. Drug molecules that activate TAAR1 have shown promising results in the treatment of schizophrenia and depression.

Accurate results

Using supercomputers, the researchers searched chemical libraries containing millions of molecules to find those that best fit the model. Molecules predicted to bind to the receptor were tested in experiments by research colleagues at Karolinska Institutet. An unexpectedly large number of the molecules activated TAAR1, and one of the most potent also showed promising effects in animal experiments.

During the final stage of the study, experimental structures for TAAR1 suddenly became available and the researchers were able to compare them with the AI models.

According to Jens Carlsson, who led Uppsala University's part of the study, the accuracy of AI-generated structures was astonishing. He said, he could not believe the results. The results also show that modeling with AI is significantly better than traditional methods. We can now use the same strategy for receptors we previously could only dream of working with.

Source:

Phys Org