In silico studies of the interactions between propofol and fentanyl using Gaussian accelerated molecular dynamics

Abstract

Fentanyl is a potent opioid analgesic, which for decades has been used routinely in surgical and therapeutic applications. In addition to its analgesic properties, fentanyl also possesses anesthetic properties, which are not well understood. Fentanyl is used in the general anesthesia process to induce and maintain anesthesia in combination with the general anesthetic propofol, which fentanyl is known to potentiate. As the atomic-level mechanism behind the potentiation of propofol is unclear, we have used classical molecular dynamics simulations to study the interactions of these drugs with the Gloeobacter violaceus ion channel (GLIC). This ion channel has been identified as a target for many anesthetic drugs. We identified multiple binding sites using flooding style and Gaussian accelerated molecular dynamics (GaMD) simulations, showing fentanyl acting as a stabiliser that holds propofol within binding sites. Our extensive GaMD simulations were also able to show the pathway by which propofol blocks the channel pore, which has previously been suggested as a mechanism for ion channel modulation. General anesthesia is a multi-drug process and this study provides the first insight into the interactions between two different drugs in the anesthesia process in a relevant biological environment.

Markov state models of proton- and pore-dependent activation in a pentameric ligand-gated ion channel

“…However, the conformational diversity of these states is highly limited, leading to crude representations of the free-energy landscapes from experimental structures alone. Computational methods like molecular dynamics (MD) simulations can be used to sample more of the conformational landscape, and several studies have been conducted on GLIC to study short-timescale motions; such as simulations of the transmembrane domain only Hummer, 2010, 2012a,b), studies of the ion permeation pathway through potential-of-mean-force calculations (Cheng et al, 2010;Fritsch et al, 2011), and steady-state simulations reaching 100 ns to 1 s timescales (Nury et al, 2010;Prevost et al, 2012;Calimet et al, 2013), some also with additional ligands or modulations (Brannigan et al, 2010;Willenbring et al, 2011;LeBard et al, 2012;Murail et al, 2012;Laurent et al, 2016;Heusser et al, 2018;Faulkner and de Leeuw, 2020). Still, due to the large system size and relatively long timescales of the gating transitions, in practice it has not been feasible to sample complete gating transitions, especially if ligand-binding and unbinding events are involved (Chakrapani and Auerbach, 2005;Gonzalez-Gutierrez et al, 2012;Laha et al, 2013;Gonzalez-Gutierrez et al, 2013;Menny et al, 2017).…”

Personalized Medicine for Classical Anesthesia Drugs and Cancer Progression

“…Recently, an in-silico study using Gaussian accelerated molecular dynamics allowed us to further understand the interactions between propofol and fentanyl. Multiple binding sites were identified, demonstrating that fentanyl acts as a stabilizer of propofol on binding sites [70]. More studies like this one are necessary to further extend our knowledge regarding the mechanism of action and the drug interaction of anesthetics.…”