Researchers are exploring the potential of artificial intelligence (AI) to enhance advanced pain management through drug discovery. A recent AI algorithm has pinpointed several gut metabolites and FDA-approved medications that could be repurposed as non-addictive, non-opioid pain relief options.

Feixiong Cheng, Director of the Genome Center at Cleveland Clinic, along with IBM, is leveraging AI to advance drug discovery for pain management.

The team utilized a cutting-edge AI tool to analyze interactions between 369 gut microbial metabolites and 2,308 FDA-approved drugs with 13 receptors associated with pain.

Their AI framework successfully identified various compounds that might be suitable for repurposing as pain treatments. Ongoing lab studies aim to validate these findings, as reported in the journal Cell Reports Medicine.

Chronic pain management with opioids remains challenging due to the risks of side effects and dependency.

"Recent findings suggest that targeting a specific subset of pain receptors within a class known as G protein-coupled receptors (GPCRs) can yield non-addictive pain relief. The key question is how to effectively target these receptors", explained Yunguang Qiu, a postdoctoral fellow in Cheng's lab.

To assess a molecule's viability as a drug, researchers must predict its interactions with bodily proteins, particularly pain receptors.

This requires a comprehensive 3D understanding of both the molecules and the receptors, derived from extensive 2D data on their structural and chemical characteristics.

The research team's AI tool predicts a molecule's ability to bind to specific pain receptors, the precise binding locations, the strength of the attachment, and whether such binding will activate or deactivate signaling pathways.

Cheng stated, "We believe these foundational models will empower advanced AI technologies to expedite the development of therapeutics for various complex health challenges".

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