Abstract
Background: Predicting the impact of missense protein variants on drug binding would have a widespread implications on the practice of genomic medicine, including matching a molecular therapy and dosage to an individual’s genome sequence. Genetic variation is widespread within G-protein-coupled receptors, which can affect overall structure and conformation of the receptors. These structural changes in turn impact ligand binding interactions, which may change the overall dosage requirements for target drugs. In this study, we used molecular docking simulations to explore the effect of missense variants on opioid drug binding affinity to the opioid receptor mu 1 (OPMR1). Methods: Using high-throughput, in silico docking simulations, the binding interactions of 27 opioid drugs to naturally occurring variants in opioid receptor mu 1 (OPRM1) were used to predict changes to ligand binding affinity. The binding energy of the small molecules to the wild-type receptor was compared to an experimentally derived inhibitory constant (Ki) for validation, and the variant-induced disruptions in variant:drug interactions used to predict the impact on the effective drug dosage. Results: The binding energies for each drug-variant receptor pair relative to the wildtype receptor and drug showed trends across drugs, with some variants showing enhancing (238I, 302I) or diminishing (235M, 235N) effects on binding affinity. The 153V variant showed increased binding affinity for certain drugs, and decreased affinity for others. The simulation results correlated well with experimentally derived inhibitory constants (R2 = 0.69), and an exponential regression model revealed how changes in relative binding energy between wildtype and variant structures predict changes to Ki.Conclusions: The simulation results illustrate the potential for integrating genetic variation into the process of development of small molecule therapies to support genomic-driven medicine. Depending on the drug and location, amino acid variation can either increase or decrease the strength of the molecular interactions and should be considered when determining drug dosage. The scale of variation and the cost of experimental characterization underscores the potential for accurate simulation based methods to inform clinical decisions.
Positive Transcriptional Regulation of the Human μ Opioid Receptor Gene by Poly(ADP-ribose) Polymerase-1 and Increase of Its DNA Binding Affinity Based on Polymorphism of G−172→ T