ArticleThe Journal of chemical physics2018
An efficient strategy to estimate thermodynamics and kinetics of G protein-coupled receptor activation using metadynamics and maximum caliber.
Article in The Journal of chemical physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- A Transferable and Robust Computational Framework for Class A GPCR Activation Free Energies.The journal of physical chemistry letters · 2026Article
- Molecular simulations reveal intricate coupling between agonist-bound β-adrenergic receptors and G protein.iScience · 2025Article
- Mechanical stress and anionic lipids synergistically stabilize an atypical structure of the angiotensin II type 1 receptor (AT1).PLoS computational biology · 2024Article
- Stereoselective recognition of morphine enantiomers byNational science review · 2024Article
- A multiscale predictive digital twin for neurocardiac modulation.The Journal of physiology · 2023Article
- Studying Disease-Associated UBE3A Missense Variants Using Enhanced Sampling Molecular Simulations.ACS omega · 2022Article
- Estimation of binding rates and affinities from multiensemble Markov models and ligand decoupling.The Journal of chemical physics · 2022Article
- Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs.Advances in protein chemistry and structural biology · 2022Review
- Metadynamics simulations leveraged by statistical analyses and artificial intelligence-based tools to inform the discovery of G protein-coupled receptor ligands.Frontiers in endocrinology · 2022Review
- Sequencing Directly from Clinical Specimens Reveals Genetic Variations in HCMV-Encoded Chemokine Receptor US28 That May Influence Antibody Levels and Interactions with Human Chemokines.Microbiology spectrum · 2021Article
- Allosteric communication regulates ligand-specific GPCR activity.The FEBS journal · 2021Review
- Markov State Models to Elucidate Ligand Binding Mechanism.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Confronting pitfalls of AI-augmented molecular dynamics using statistical physics.The Journal of chemical physics · 2020Article
- How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs.International journal of molecular sciences · 2020Review
- The Maximum Caliber Variational Principle for Nonequilibria.Annual review of physical chemistry · 2020Review
- Free energy calculations of the functional selectivity of 5-HT2B G protein-coupled receptor.PloS one · 2020Article
- Quantum Mechanical and Molecular Mechanics Modeling of Membrane-Embedded Rhodopsins.The Journal of membrane biology · 2019Review
- Allostery in G protein-coupled receptors investigated by molecular dynamics simulations.Current opinion in structural biology · 2019Review
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Authors and funding
3 authors.
Funding
Abstract
Computational strategies aimed at unveiling the thermodynamic and kinetic properties of G Protein-Coupled Receptor (GPCR) activation require extensive molecular dynamics simulations of the receptor embedded in an explicit lipid-water environment. A possible method for efficiently sampling the conformational space of such a complex system is metadynamics (MetaD) with path collective variables (CVs). Here, we applied well-tempered MetaD with path CVs to one of the few GPCRs for which both inactive and fully active experimental structures are available, the μ-opioid receptor (MOR), and assessed the ability of this enhanced sampling method to estimate the thermodynamic properties of receptor activation in line with those obtained by more computationally expensive adaptive sampling protocols. While n-body information theory analysis of these simulations confirmed that MetaD can efficiently characterize ligand-induced allosteric communication across the receptor, standard MetaD cannot be used directly to derive kinetic rates because transitions are accelerated by a bias potential. Applying the principle of Maximum Caliber (MaxCal) to the free-energy landscape of morphine-bound MOR reconstructed from MetaD, we obtained Markov state models that yield kinetic rates of MOR activation in agreement with those obtained by adaptive sampling. Taken together, these results suggest that the MetaD-MaxCal combination creates an efficient strategy for estimating the thermodynamic and kinetic properties of GPCR activation at an affordable computational cost.
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