Researchers are leveraging artificial intelligence (AI) to enhance advanced pain management, particularly in drug discovery. An AI algorithm has successfully identified various gut metabolites and FDA-approved drugs that may be repurposed as non-addictive, non-opioid pain treatments.
Feixiong Cheng, Director of the Cleveland Clinic’s Genome Center, along with IBM, is utilizing AI in this research.
The team employed the AI tool to analyze interactions between 369 gut microbial metabolites and 2,308 FDA-approved drugs with 13 receptors associated with pain.
The AI framework pinpointed several compounds that show promise for repurposing in pain relief, with laboratory studies currently underway to validate these findings, as reported in the journal Cell Reports Medicine.
Managing chronic pain with opioids remains challenging due to potential severe side effects and the risk of dependency.
“Recent studies indicate that targeting a specific subset of pain receptors within a protein family known as G protein-coupled receptors (GPCRs) can offer non-addictive pain relief. The key question is how to effectively target these receptors,” explained Yunguang Qiu, a postdoctoral fellow in Dr. Cheng's lab.
To assess whether a molecule is viable as a drug, researchers must predict its interactions with proteins in the body, particularly pain receptors.
This involves creating a 3D understanding of the molecules, relying on extensive 2D data regarding their structural and chemical properties.
The research team utilized this tool to determine if a molecule can bind to a specific pain receptor, the binding site on the receptor, the strength of the attachment, and whether this interaction activates or inhibits signaling effects.
“We believe these foundational models will provide powerful AI technologies to expedite the development of therapeutics for various complex health challenges,” stated Cheng.