Encoding mu-opioid receptor biased agonism with interaction fingerprints

Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the mu-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein-ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling.

Automated summary

By conducting molecular dynamics simulations of two biased ligands and a reference molecule, a protein-ligand interaction fingerprint distinguishing biased ligands was identified. Virtual screening of a database containing 68,740 ligands highlighted exemplary molecules with biased agonism, showcasing the utility of this approach in searching for biased MOR ligands and enhancing understanding of MOR biased signaling.