3D pharmacophore models are three‐dimensional ensembles of chemically defined interactions of a ligand in its bioactive conformation. They represent an elegant way to decipher chemically encoded ligand information and have therefore become a valuable tool in drug design. In this review, we provide an overview on the basic concept of this method and summarize key studies for applying 3D pharmacophore models in virtual screening and mechanistic studies for protein functionality. Moreover, we discuss recent developments in the field. The combination of 3D pharmacophore models with molecular dynamics simulations could be a quantum leap forward since these approaches consider macromolecule–ligand interactions as dynamic and therefore show a physiologically relevant interaction pattern. Other trends include the efficient usage of 3D pharmacophore information in machine learning and artificial intelligence applications or freely accessible web servers for 3D pharmacophore modeling. The recent developments show that 3D pharmacophore modeling is a vibrant field with various applications in drug discovery and beyond.This article is categorized under: Computer and Information Science > Chemoinformatics Computer and Information Science > Computer Algorithms and Programming Molecular and Statistical Mechanics > Molecular Interactions

G protein-coupled receptors modulate a plethora of physiological processes and mediate the effects of one-third of FDA-approved drugs. Depending on which ligand activates a receptor, it can engage different intracellular transducers. This ‘biased signaling’ paradigm requires that we now characterize physiological signaling not just by receptors but by ligand-receptor pairs. Ligands eliciting biased signaling may constitute better drugs with higher efficacy and fewer adverse effects. However, ligand bias is very complex, making reproducibility and description challenging. Here, we provide guidelines and terminology for any scientists to design and report ligand bias experiments. The guidelines will aid consistency and clarity, as the basic receptor research and drug discovery communities continue to advance our understanding and exploitation of ligand bias. Scientific insight, biosensors, and analytical methods are still evolving and should benefit from and contribute to the implementation of the guidelines, together improving translation from in vitro to disease-relevant in vivo models.

G protein-coupled receptors constitute the largest family of membrane receptors and modulate almost every physiological process in humans. Binding of agonists to G protein-coupled receptors induces a shift from inactive to active receptor conformations. Biophysical studies of the dynamic equilibrium of receptors suggest that a portion of receptors can remain in inactive states even in the presence of saturating concentrations of agonist and G protein mimetic. However, the molecular details of agonist-bound inactive receptors are poorly understood. Here we use the model of bitopic orthosteric/allosteric (i.e. dualsteric) agonists for muscarinic M₂ receptors to demonstrate the existence and function of such inactive agonist·receptor complexes on a molecular level. Using all-atom molecular dynamics simulations, dynophores (i.e. a combination of static three-dimensional pharmacophores and molecular dynamics-based conformational sampling), ligand design, and receptor mutagenesis, we show that inactive agonist·receptor complexes can result from agonist binding to the allosteric vestibule alone, whereas the dualsteric binding mode produces active receptors. Each agonist forms a distinct ligand binding ensemble, and different agonist efficacies depend on the fraction of purely allosteric (i.e. inactive) versus dualsteric (i.e. active) binding modes. We propose that this concept may explain why agonist·receptor complexes can be inactive and that adopting multiple binding modes may be generalized also to small agonists where binding modes will be only subtly different and confined to only one binding site.

Small molecules interfering with Rac1 activation are considered as potential drugs and are already studied in animal models. A widely used inhibitor without reported attenuation of RhoA activity is NSC23766 [( N 6-[2-[[4-(diethylamino)-1-methylbutyl]amino]-6-methyl-4-pyrimidinyl]-2-methyl-4,6-quinolinediamine trihydrochloride]. We found that NSC23766 inhibits the M2 muscarinic acetylcholine receptor (M2 mAChR)-induced Rac1 activation in neonatal rat cardiac myocytes. Surprisingly, NSC27366 concomitantly suppressed the carbachol-induced RhoA activation and a M2 mAChR-induced inotropic response in isolated neonatal rat hearts requiring the activation of Rho-dependent kinases. We therefore aimed to identify the mechanisms by which NSC23766 interferes with the differentially mediated, M2 mAChR-induced responses. Interestingly, NSC23766 caused a rightward shift of the carbachol concentration response curve for the positive inotropic response without modifying carbachol efficacy. To analyze the specificity of NSC23766, we compared the carbachol and the similarly Gi βγ -mediated, adenosine-induced activation of Gi protein–regulated potassium channel (GIRK) channels in human atrial myocytes. Application of NSC23766 blocked the carbachol-induced K+ current but had no effect on the adenosine-induced GIRK current. Similarly, an adenosine A1 receptor-induced positive inotropic response in neonatal rat hearts was not attenuated by NSC23766. To investigate its specificity toward the different mAChR types, we studied the carbachol-induced elevation of intracellular Ca2+ concentrations in human embryonic kidney 293 (HEK-293) cells expressing M1, M2, or M3 mAChRs. NSC23766 caused a concentration-dependent rightward shift of the carbachol concentration response curves at all mAChRs. Thus, NSC23766 is not only an inhibitor of Rac1 activation, but it is within the same concentration range a competitive antagonist at mAChRs. Molecular docking analysis at M2 and M3 mAChR crystal structures confirmed this interpretation.