AI-designed serotonin tracker could help develop neurological drugs –

A serotonin sensor designed using artificial intelligence (AI) could help scientists study sleep and mental health and potentially find new neurological drugs.

The U.S. National Institutes of Health said the co-funded research used artificial intelligence to transform the bacterial protein into a new research tool.

We hope that the protein, which “captures” serotonin molecules and allows them to be tracked, could detect subtle changes in serotonin levels in real time during sleep, fear and social interactions.

The technique could also be used to test the effectiveness of new psychoactive drugs, according to the NIH, which is funded by the US government.

This study on mice was funded by the NIH’s Brain Research Initiative through the Advancement of Innovative Neurotechnologies (BRAIN), which aims to revolutionize the understanding of the brain in healthy and diseased conditions.

She was led by researchers in the laboratory of Dr. Lin Tian, ​​principal investigator at the University of California, Davis School of Medicine.

In the study, researchers transformed a bacterial protein in the form of a Venus-fly that captures nutrients into a highly sensitive fluorescent sensor that turns on when it captures serotonin.

Tian’s laboratory builds on the work of scientists in the laboratory of Dr. Loren Looger, of the Janelia Hughes Institute of Medicine Research Campus, Ashburn, Virginia, who used traditional genetic engineering techniques to convert a bacterial protein into an acetylcholine neurotransmitter sensor.

Tian collaborated with Looger’s team and used artificial intelligence to completely redesign a protein known as OpuBC to capture serotonin instead.

The researchers used machine learning algorithms to help the computer “come up with” 250,000 new designs. After three rounds of testing, the scientists decided on one.

Experiments on mouse brain sections showed that the sensor responds to serotonin signals sent between neurons at synaptic communication points.

Further experiments on cells in Petri dishes suggest that the sensor could effectively monitor changes in these drug-induced signals, including cocaine, MDMA, and several commonly used antidepressants.

Studies of mice showed that the sensor monitored the expected increase in serotonin levels when the mice were awake and decreased while the mice were asleep.

They also noticed a larger drop when the mice eventually entered a deeper, REM sleep state.

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