GPCRdb in 2025: adding odorant receptors, data mapper, structure similarity search and models of physiological ligand complexes.

G protein-coupled receptors (GPCRs) are membrane-spanning transducers mediating the actions of numerous physiological ligands and drugs. The GPCR database GPCRdb supports a large global research community with reference data, analysis, visualization, experiment design and dissemination. Here, we describe our sixth major GPCRdb release starting with an overview of all resources for receptors and ligands.

Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?

The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy.

Electron Paramagnetic Resonance Gives Evidence for the Presence of Type 1 Gonadotropin-Releasing Hormone Receptor (GnRH-R) in Subdomains of Lipid Rafts.

This study investigated the effect of type 1 gonadotropin releasing hormone receptor (GnRH-R) localization within lipid rafts on the properties of plasma membrane (PM) nanodomain structure. Confocal microscopy revealed colocalization of PM-localized GnRH-R with GM-enriched raft-like PM subdomains. Electron paramagnetic resonance spectroscopy (EPR) of a membrane-partitioned spin probe was then used to study PM fluidity of immortalized pituitary gonadotrope cell line αT3-1 and HEK-293 cells stably expressing GnRH-R and compared it with their corresponding controls (αT4 and HEK-293 cells).

Publisher Correction: GPCRmd uncovers the dynamics of the 3D-GPCRome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

GPCRmd uncovers the dynamics of the 3D-GPCRome.

G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level.

Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity.

Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs.

Synthesis, molecular modelling studies and biological evaluation of new oxoeicosanoid receptor 1 agonists.

The oxoeicosanoid receptor 1 (OXER1) is a member of the G-protein coupled receptors (GPCR) family, and is involved in inflammatory processes and oncogenesis. As such it is an attractive target for pharmacological intervention. The present study aimed to shed light on the molecular fundaments of OXER1 modulation using chemical probes structurally related to the natural agonist 5-oxo-ETE.

Challenges and Opportunities in Drug Discovery of Biased Ligands.

The observation of biased agonism in G protein-coupled receptors (GPCRs) has provided new approaches for the development of more efficacious and safer drugs. However, in order to rationally design biased drugs, one must understand the molecular basis of this phenomenon. Computational approaches can help in exploring the conformational universe of GPCRs and detecting conformational states with relevance for distinct functional outcomes.

Membrane cholesterol effect on the 5-HT receptor: Insights into the lipid-induced modulation of an antipsychotic drug target.

The serotonin 5-hydroxytryptamine 2A (5-HT ) receptor is a G-protein-coupled receptor (GPCR) relevant for the treatment of CNS disorders. In this regard, neuronal membrane composition in the brain plays a crucial role in the modulation of the receptor functioning. Since cholesterol is an essential component of neuronal membranes, we have studied its effect on the 5-HT receptor dynamics through all-atom MD simulations.

Membrane cholesterol access into a G-protein-coupled receptor.

Cholesterol is a key component of cell membranes with a proven modulatory role on the function and ligand-binding properties of G-protein-coupled receptors (GPCRs). Crystal structures of prototypical GPCRs such as the adenosine A receptor (AR) have confirmed that cholesterol finds stable binding sites at the receptor surface suggesting an allosteric role of this lipid. Here we combine experimental and computational approaches to show that cholesterol can spontaneously enter the AR-binding pocket from the membrane milieu using the same portal gate previously suggested for opsin ligands.

In silico Exploration of the Conformational Universe of GPCRs.

The structural plasticity of G protein coupled receptors (GPCRs) leads to a conformational universe going from inactive to active receptor states with several intermediate states. Many of them have not been captured yet and their role for GPCR activation is not well understood. The study of this conformational space and the transition dynamics between different receptor populations is a major challenge in molecular biophysics.

MEMBPLUGIN: studying membrane complexity in VMD.

Summary: Computer simulations are giving way to more complex and accurate studies of biological membranes by molecular dynamics (MD) simulations. The analysis of MD trajectories comprises the biophysical characterization of membrane properties or the study of protein-lipid interactions and dynamics. However, there is a lack of automated tools to analyse MD simulations of complex membrane or membrane-protein systems.