GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆⁹-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

The P2Y receptors (P2YRs) are G protein‐coupled receptors (GPCRs) consisting of eight members, subdivided into two groups, P2Y₁‐ and P2Y₁₂‐like receptor subtypes. They are activated by extracellular nucleotides and represent current (P2Y₂, P2Y₁₂) or potential future drug targets. The chemical nature of the highly polar endogenous agonists represents a challenge in the discovery and design of potent and bioavailable compounds. A number of mutants and several homology models of P2YR subtypes have been created and updated on the basis of the recently published X‐ray crystal structures of the human P2Y₁ and P2Y₁₂Rs. The models were used for prediction of the binding sites of agonists and antagonists, and mutants were constructed for confirmation. Pharmacological data on mutants published for the P2Y₁‐like receptors (P2Y₁, P2Y₂, P2Y₄, P2Y₆, and P2Y₁₁R) were evaluated to analyze the role of specific amino acids and that of corresponding amino acid residues in related P2Y receptor subtypes. In several P2YR subtypes, an ionic lock between extracellular loop 2 and transmembrane region VII was postulated to be essential for agonist‐induced receptor activation. Mutagenesis and homology modeling data suggest that the nucleotide antagonist (1′R,2′S,4′S,5′S)‐4‐(2‐iodo‐6‐methylaminopurin‐9‐yl)‐1‐[(phosphato)methyl]‐2‐(phosphato)bicyclo[3.1.0]hexane (MRS2500), which was co‐crystallized with the human P2Y₁R, binds differently from agonistic nucleotides to a site partly overlapping with that of orthosteric agonists. Hetero‐oligomerization of P2YRs with other P2YR subtypes or other GPCRs may allosterically modulate receptor‐ligand interactions and/or G protein coupling. The collected information will contribute to the understanding of the architecture of P2Y₁‐like nucleotide receptors and will consequently be useful for the design of novel agonists and antagonists.This article is categorized under: Molecular and Statistical Mechanics > Free Energy Methods Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Interactions Software > Molecular Modeling

Sources for commercially available compounds have been experiencing continuous growth for several years, reaching their peak in billion- to trillion-sized combinatorial Chemical Spaces. To assess the quality of a compound collection to provide relevant chemistry, a benchmark set of pharmaceutically relevant structures is required that enables an unbiased comparison. For this purpose, the ChEMBL database was mined for molecules displaying biological activity, and three benchmark sets of successive orders of magnitude were created by systematic filtering and processing: Set L ("large-sized," 379k), Set M ("medium-sized," 25k), and Set S ("small-sized," 3k). Tailored for broad coverage of the physicochemical and topological landscape, the benchmark Set S was then employed to analyze the chemical diversity capacities of commercial combinatorial Chemical Spaces and enumerated compound libraries. Among the three utilized search methods─FTrees (pharmacophore features), SpaceLight (molecular fingerprints), and SpaceMACS (maximum common substructure)─eXplore and REAL Space consistently performed best. In general, each Chemical Space was able to provide a larger number of compounds more similar to the respective query molecule than the enumerated libraries, while also individually offering unique scaffolds for each method.