The discovery that different ligands can modulate G-protein coupled receptors (GPCRs) in very different manners has spurred a great deal of interest in this pharmaceutically relevant class of proteins. Ligands binding to the extracellular site of these membrane bound proteins have been found to stabilize the protein such that it can operate through either of two main signalling transduction pathways: G-protein or beta-arrestin.<br/>This difference in opportunities to modulate GPCRs is especially relevant in the case of the Mu opioid receptor (MOR), where a biased Mu agonist is believed to trigger positive analgesic effects that a classic Mu agonist drug provides while reducing its side effects (constipation, tolerance, nausea and respiratory depression).<br/>This presentation will introduce internal Pfizer efforts to achieve novel MOR biased agonists, exploring (I) novel High Throughput Screening methodologies, (II) collaborations with biophysical groups to measure bias in multiple conditions and (III) chemistry efforts to explore different pharmacological readouts while improving potency and physical chemical properties.<br/>The presentation will then focus on how computational techniques like docking, Molecular Dynamics simulations, field-based analysis and water analysis, have been applied to understand different bias profiles, selectivity among GPCR opioid receptors, as well as understanding how the bias profile and agonism activity may diverge.

Designing for bias: Computational methods to drive rational design of G-protein biased agonists

2019 Fall National Meeting

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