Validation of a Computationally Efficient Model of the Mu-Opioid Receptor

Abstract

The mu-opioid receptor (MOR) is a transmembrane protein and the primary target for pain-modulating drugs. Opioid drugs come with detrimental side-effects such as physical dependence and addiction. However, recent studies show that understanding structural properties and dynamics of MOR may aid in the design of opioid drugs with reduced side-effects. Molecular dynamics simulations allow researchers to study changes in protein conformation at an atomistic level. However, modeling systems including MOR embedded in a lipid bilayer can be computationally expensive. This study evaluates a modeling approach that uses harmonic restraints on the transmembrane regions of MOR to model the rigidity of the lipid bilayer without explicitly simulating lipid molecules, reducing the number of atoms in the simulation. The proposed model allows MOR to be simulated 49% faster than a simulation explicitly including the lipid bilayer. To assess the accuracy of the proposed model, simulations were performed of MOR in a lipid bilayer, the free MOR in water and MOR in water with harmonic restraints applied to all transmembrane residues using NAMD 3.0 alpha and the CHARMM36 force field. Dynamic properties of MOR were shown to be different in each system, with the free MOR having a higher root mean square deviation (RMSD) than MOR with an explicitly modeled lipid bilayer. The systems with harmonic restraint constants of 0.001 kcal/mol/Å2 applied to the transmembrane residues had RMSD values comparable to those in an explicitly modeled lipid bilayer. This study demonstrates that using restraints on the transmembrane residues of MOR is a feasible way of modeling the ligand-free receptor with reduced computational costs. This model could allow the dynamics of MOR in a lipid bilayer environment to be studied more efficiently. KEYWORDS: Molecular Dynamics; Atomistic Simulations; Computational Modeling; Mu-Opioid Receptor; G-Protein Coupled Receptor; Lipid Bilayer, Opioid, Transmembrane Protein