A research team at the University of Illinois Urbana-Champaign has used deep learning and large-scale computer simulations to understand why synthetic cannabinoids, known as new psychoactive substances (NPS), often cause harmful side effects. The findings were published in the journal eLife.
Chemical and biomolecular engineering professor Diwakar Shukla explained that NPS are frequently sold under names such as Fubinaca, Chimica, and Pinaca. "The largest class of NPS are often sold as the street drugs Fubinaca, Chimica and Pinaca," said Shukla. "In addition to the adverse side effects, the formulas used to produce NPS vary, making them challenging to detect in standard drug screenings."
Unlike classical cannabinoids, which primarily activate what is known as the "G protein pathway" in the brain, synthetic cannabinoids tend to trigger a different signaling route called the "beta arrestin pathway." This difference in receptor binding can result in more severe psychological effects.
Shukla described some of the technical challenges involved in studying these compounds: "New psychoactive substances bind very strongly to cannabinoid receptors in the brain and are slow to unbind, making them difficult to observe and simulate in standard laboratory or computer experiments," he said. "It can take a huge amount of computer time to see these rare binding and unbinding events."
Graduate student Soumajit Dutta used an advanced simulation technique called Transition-Based Reweighting Method (TRAM) to estimate how slowly these molecules bind and unbind from brain receptors. This approach made it possible for researchers to study rare molecular processes without needing excessive computing resources.
The team also relied on Folding@Home, a distributed computing platform where volunteers worldwide contribute their computer power. By running many simulations simultaneously and using algorithms to guide further simulations, they could investigate long or rare events that would be difficult with limited computational capacity.
This combination of methods enabled the researchers to identify structural differences between synthetic and classical cannabinoids that influence how they interact with human brain receptors. These insights may help guide future drug design efforts aimed at creating safer cannabinoid-based medications by avoiding activation of pathways linked with adverse effects.
According to Shukla, "By revealing the NPS signal via pathways associated with more adverse effects, researchers can now focus on designing new molecules that avoid triggering these pathways for medical use." He added that future work could aim for compounds that do not bind as tightly or unbind more easily from brain receptors, which may reduce potential harm.
The study was supported by grants from the National Institutes of Health (R35GM-142745) and the National Science Foundation. Shukla is also affiliated with several other university departments and research centers.
