title: Multiscale design of coarse-grained elastic network-based potentials for the μ opioid receptor.
abstract: Despite progress in computer modeling, most biological processes are still out of reach when using all-atom (AA) models. Coarse-grained (CG) models allow classical molecular dynamics (MD) simulations to be accelerated. Although simplification of spatial resolution at different levels is often investigated, simplification of the CG potential in itself has been less common. CG potentials are often similar to AA potentials. In this work, we consider the design and reliability of purely mechanical CG models of the μ opioid receptor (μOR), a G protein-coupled receptor (GPCR). In this sense, CG force fields (FF) consist of a set of holonomic constraints guided by an elastic network model (ENM). Even though ENMs are used widely to perform normal mode analysis (NMA), they are not often implemented as a single FF in the context of MD simulations. In this work, various ENM-like potentials were investigated by varying their force constant schemes and connectivity patterns. A method was established to systematically parameterize ENM-like potentials at different spatial resolutions by using AA data. To do so, new descriptors were introduced. The choice of conformation descriptors that also include flexibility information is important for a reliable parameterization of ENMs with different degrees of sensitivity. Hence, ENM-like potentials, with specific parameters, can be sufficient to accurately reproduce AA MD simulations of μOR at highly coarse-grained resolutions. Therefore, the essence of the flexibility properties of μOR can be captured with simple models at different CG spatial resolutions, opening the way to mechanical approaches to understanding GPCR functions. Graphical Abstract All atom structure, residue interaction network and coarse-grained elastic network models of the μ opioid receptor (μOR).
authors: Laboratoire de Physico-Chimie Informatique, Unité de Chimie Physique Théorique et Structurale, Namur Medicine and Drug Innovation Center (NAMEDIC), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), 61 Rue de Bruxelles, 5000, Namur, Belgium. mathieu.fossepre@unamur.be.|Arrhenius Laboratory, Division of Physical Chemistry, Stockholm University, Svante Arrhenius väg 10-18, 106 91, Stockholm, Sweden. mathieu.fossepre@unamur.be.
authors: Mathieu
authors: M
authors: Fossépré
authors: Laboratoire de Physico-Chimie Informatique, Unité de Chimie Physique Théorique et Structurale, Namur Medicine and Drug Innovation Center (NAMEDIC), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), 61 Rue de Bruxelles, 5000, Namur, Belgium.
authors: Laurence
authors: L
authors: Leherte
authors: Arrhenius Laboratory, Division of Physical Chemistry, Stockholm University, Svante Arrhenius väg 10-18, 106 91, Stockholm, Sweden.|Stellenbosch Institute of Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, 10 Marais Road, 7600, Stellenbosch, South Africa.
authors: Aatto
authors: A
authors: Laaksonen
authors: Laboratoire de Physico-Chimie Informatique, Unité de Chimie Physique Théorique et Structurale, Namur Medicine and Drug Innovation Center (NAMEDIC), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), 61 Rue de Bruxelles, 5000, Namur, Belgium.
authors: Daniel P
authors: DP
authors: Vercauteren
mesh_terms: D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D017450:Receptors, Opioid, mu / Q000737:chemistry*; D015203:Reproducibility of Results
chemical_list: D017450:Receptors, Opioid, mu
keywords: Coarse-graining; Elastic network models; GPCR; Graph theory; Molecular dynamics; Multiscale modeling