Exploring the Binding Energies of Morphine Derivatives Using Chem-informatics

Students: Aleia Bandy, Nadia Gabel, Karina Suarez

Faculty Mentor: Mark Perri

Chemistry

College of Science, Technology, and Business

Opioid painkillers are widely prescribed by doctors in order to relieve chronic or severe pain. In the U.S., over x prescriptions were prescribed last year. Opioid painkillers are known to be highly addictive. Our research aims to explore why opioid painkillers are so addictive by examining the binding energy of morphine and fentanyl to the Mu opioid receptor. We expected fentanyl to have a much higher binding energy than morphine, due to its higher affinity for the Mu opioid receptor. In order to achieve this, we first downloaded morphine bound to the Mu opioid receptor from the RSC PDB. We then removed the morphine ligand and utilized AutoDock Vina to measure the binding energy at a pH of 7.4. In doing so, we observed the amino acid residue interactions at the active site. We then repeated the process using fentanyl as the ligand of interest. We compared the binding energies and the active site amino acid residue interactions for both. (From these results, we are able to confirm that fentanyl has a higher affinity due to its higher binding energy. Put more findings here.) Currently, we hope to continue using cheminformatics in order to examine the Mu opioid receptor interaction with ligands. This will help further explain the mechanisms underlying chemical addiction to opioids.