"Computational Lipophilicity Calculations of Fluorinated Morphine Deriv" by Mirabella Romano, Allison Vu et al.
 

Student Scholar Symposium Abstracts and Posters

Document Type

Poster

Publication Date

Spring 5-7-2025

Faculty Advisor(s)

Dr. Matthew Gartner, Nayiri Alexander, Makena Augenstein

Abstract

The opioid epidemic impacts 60 million people worldwide every year. Morphine, a commonly prescribed opioid, binds to the μ opioid receptor (MOR) in the body via protonation of the tertiary amino group of morphine and the MOR. An unfortunate side effect of this binding process is its non-selectivity in both peripheral and central tissues. While activation within inflamed peripheral tissues results in pain relief, activation within central tissues results in the unwanted and addictive side effects of opioids. Because there is a discrepancy in pH between healthy (central) and inflamed (peripheral) tissue, selective binding within the inflamed tissues results in pain relief without addictive properties. Fluorination of the morphine molecule results in a reduction of pKa that induces selective protonation (binding) within the lower pH environments of inflamed tissues while avoiding activation within the CNS. Additionally, the removal of the C and D rings of morphine alters its steric properties, potentially improving receptor fit and binding efficiency by increasing the flexibility of the molecule. These structural modifications also influence lipophilicity, measured by the partition coefficient (logP), which impacts the drug’s ability to cross lipid membranes. Computational logP calculations using XLOGP3 found that morphine has a logP of 0.88, whereas fluorinated derivatives exhibit increased lipophilicity: fluoromorphine β-C1 (1.91), fluoromorphine β-C2 (0.85), and fluoromorphine β-C3 (2.05). The significantly higher logP values of β-C1 and β-C3 suggest enhanced partitioning into lipid-rich inflamed tissues, improving selectivity while minimizing CNS interactions. The aim of this study involves further assessment of these derivatives using molecular docking simulations that will be conducted in Schrödinger software to predict ligand-receptor interactions with MOR. Gathering Gibbs free energy (ΔG) and logP data will determine which derivative(s) should be synthesized and studied further.

Comments

Presented at the Spring 2025 Student Scholar Symposium at Chapman University.

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