Publications

The following published works use MDEntropy. To add your publication to the list, open an issue on GitHub with the relevant information or edit docs/publications.bib and submit a pull request.

Dynamic and Kinetic Elements of μ-Opioid Receptor Functional Selectivity

While the therapeutic effect of opioids analgesics is mainly attributed to μ-opioid receptor (MOR) activation leading to G protein signaling, their side effects have mostly been linked to β-arrestin signaling. To shed light on the dynamic and kinetic elements underlying MOR functional selectivity, we carried out close to half millisecond high-throughput molecular dynamics simulations of MOR bound to a classical opioid drug (morphine) or a potent G protein-biased agonist (TRV-130). Statistical analyses of Markov state models built using this large simulation dataset combined with information theory enabled, for the first time: a) Identification of four distinct metastable regions along the activation pathway, b) Kinetic evidence of a different dynamic behavior of the receptor bound to a classical or G protein-biased opioid agonist, c) Identification of kinetically distinct conformational states to be used for the rational design of functionally selective ligands that may eventually be developed into improved drugs; d) Characterization of multiple activation/deactivation pathways of MOR, and e) Suggestion from calculated transition timescales that MOR conformational changes are not the rate-limiting step in receptor activation.

Kinetic Machine Learning Unravels Ligand-Directed Conformational Change of μ Opioid Receptor

  • Evan N. Feinberg; Amir Barati Farimani; Carlos Xavier Hernandez; Vijay S. Pande
  • BioRxiv 2017
  • doi: 10.1101/170886

The μ Opioid Receptor (μOR) is a G-Protein Coupled Receptor (GPCR) that mediates pain and is a key target for clinically administered analgesics. The current generation of prescribed opiates – drugs that bind to μOR – engender dangerous side effects such as respiratory depression and addiction in part by stabilizing off-target conformations of the receptor. To determine both the key conformations of μOR to atomic resolution as well as the transitions between them, long timescale molecular dynamics (MD) simulations were conducted and analyzed. These simulations predict new and potentially druggable metastable states that have not been observed by crystallography. We applied cutting edge algorithms (e.g., tICA and Transfer Entropy) to guide our analysis and distill the key events and conformations from simulation, presenting a transferrable and systematic analysis scheme. Our approach provides a complete, predictive model of the dynamics, structure of states, and structure-ligand relationships of μOR with broad applicability to GPCR biophysics and medicinal chemistry.