Predicted 3D structures of olfactory receptors with details of odorant binding to OR1G1

Combining the Classification and Pharmacophore Approaches to Understand Homogeneous Olfactory Perceptions at Peripheral Level: Focus on Two Aroma Mixtures

The mechanisms involved in the homogeneous perception of odorant mixtures remain largely unknown. With the aim of enhancing knowledge about blending and masking mixture perceptions, we focused on structure-odor relationships by combining the classification and pharmacophore approaches. We built a dataset of about 5000 molecules and their related odors and reduced the multidimensional space defined by 1014 fingerprints representing the structures to a tridimensional 3D space using uniform manifold approximation and projection (UMAP). The self-organizing map (SOM) classification was then performed using the 3D coordinates in the UMAP space that defined specific clusters. We explored the allocating in these clusters of the components of two aroma mixtures: a blended mixture (red cordial (RC) mixture, 6 molecules) and a masking binary mixture (isoamyl acetate/whiskey-lactone [IA/WL]). Focusing on clusters containing the components of the mixtures, we looked at the odor notes carried by the molecules belonging to these clusters and also at their structural features by pharmacophore modeling (PHASE). The obtained pharmacophore models suggest that WL and IA could have a common binding site(s) at the peripheral level, but that would be excluded for the components of RC. In vitro experiments will soon be carried out to assess these hypotheses.

Predicted Three-Dimensional Structure of the GCR1 Putative GPCR in Arabidopsis thaliana and Its Binding to Abscisic Acid and Gibberellin A1

GCR1 has been proposed as a plant analogue to animal G-protein-coupled receptors that can promote or regulate several physiological processes by binding different phytohormones. For instance, abscisic acid (ABA) and gibberellin A1 (GA1) have been shown to promote or regulate germination and flowering, root elongation, dormancy, and biotic and abiotic stresses, among others. They may act through binding to GCR1, which would put GCR1 at the heart of key signaling processes of agronomic importance. Unfortunately, this GPCR function has yet to be fully validated due to the lack of an X-ray or cryo-EM 3D atomistic structure for GCR1. Here, we used the primary sequence data from Arabidopsis thaliana and the GEnSeMBLE complete sampling method to examine 13 trillion possible packings of the 7 transmembrane helical domains corresponding to GCR1 to downselect an ensemble of 25 configurations likely to be accessible to the binding of ABA or GA1. We then predicted the best binding sites and energies for both phytohormones to the best GCR1 configurations. To provide the basis for the experimental validation of our predicted ligand-GCR1 structures, we identify several mutations that should improve or weaken the interactions. Such validations could help establish the physiological role of GCR1 in plants.

Real-time In Vitro Monitoring of Odorant Receptor Activation by an Odorant in the Vapor Phase

Olfactory perception begins with the interaction of odorants with odorant receptors (OR) expressed by olfactory sensory neurons (OSN). Odor recognition follows a combinatorial coding scheme, where one OR can be activated by a set of odorants and one odorant can activate a combination of ORs. Through such combinatorial coding, organisms can detect and discriminate between a myriad of volatile odor molecules. Thus, an odor at a given concentration can be described by an activation pattern of ORs, which is specific to each odor. In that sense, cracking the mechanisms that the brain uses to perceive odor requires the understanding odorant-OR interactions. This is why the olfaction community is committed to "de-orphanize" these receptors. Conventional in vitro systems used to identify odorant-OR interactions have utilized incubating cell media with odorant, which is distinct from the natural detection of odors via vapor odorants dissolution into nasal mucosa before interacting with ORs. Here, we describe a new method that allows for real-time monitoring of OR activation via vapor-phase odorants. Our method relies on measuring cAMP release by luminescence using the Glosensor assay. It bridges current gaps between in vivo and in vitro approaches and provides a basis for a biomimetic volatile chemical sensor.

Molecular Basis of Mammalian Odor Discrimination: A Status Report

Humans have 396 unique, intact olfactory receptors (ORs), G-protein coupled receptors (GPCRs) containing receptor-specific binding sites; other mammals have more. Activation of these transmembrane proteins by an odorant initiates a signaling cascade, evoking an action potential leading to perception of a smell. Because the number of distinguishable odorants vastly exceeds the number of ORs, research has focused on mechanisms of recognition and signaling processes for classes of odorants. In this review, selected recent examples will be presented of "deorphaned" mammalian receptors, where the OR ligands (odorants) as well as key aspects of receptor-odorant interactions were identified using odorant-mediated receptor activation data together with site-directed mutagenesis and molecular modeling. Based on cumulative evidence from OR deorphaning and olfactory receptor neuron activation studies, a receptor-ligand docking model rather than an alternative bond vibration model is suggested to best explain the molecular basis of the exquisitely sensitive odor discrimination in mammals.

Molecular mechanism of activation of human musk receptors OR5AN1 and OR1A1 by (R)-muscone and diverse other musk-smelling compounds

Understanding olfaction at the molecular level is challenging due to the lack of crystallographic models of odorant receptors (ORs). To better understand the molecular mechanism of OR activation, we focused on chiral (R)-muscone and other musk-smelling odorants due to their great importance and widespread use in perfumery and traditional medicine, as well as environmental concerns associated with bioaccumulation of musks with estrogenic/antiestrogenic properties. We experimentally and computationally examined the activation of human receptors OR5AN1 and OR1A1, recently identified as specifically responding to musk compounds. OR5AN1 responds at nanomolar concentrations to musk ketone and robustly to macrocyclic sulfoxides and fluorine-substituted macrocyclic ketones; OR1A1 responds only to nitromusks. Structural models of OR5AN1 and OR1A1 based on quantum mechanics/molecular mechanics (QM/MM) hybrid methods were validated through direct comparisons with activation profiles from site-directed mutagenesis experiments and analysis of binding energies for 35 musk-related odorants. The experimentally found chiral selectivity of OR5AN1 to (R)- over (S)-muscone was also computationally confirmed for muscone and fluorinated (R)-muscone analogs. Structural models show that OR5AN1, highly responsive to nitromusks over macrocyclic musks, stabilizes odorants by hydrogen bonding to Tyr260 of transmembrane α-helix 6 and hydrophobic interactions with surrounding aromatic residues Phe105, Phe194, and Phe207. The binding of OR1A1 to nitromusks is stabilized by hydrogen bonding to Tyr258 along with hydrophobic interactions with surrounding aromatic residues Tyr251 and Phe206. Hydrophobic/nonpolar and hydrogen bonding interactions contribute, respectively, 77% and 13% to the odorant binding affinities, as shown by an atom-based quantitative structure-activity relationship model.

Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

Human G-protein coupled receptors (hGPCRs) constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.

Conformational and Thermodynamic Landscape of GPCR Activation from Theory and Computation

We present a hybrid computational methodology to predict multiple energetically accessible conformations for G protein-coupled receptors (GPCRs) that might play a role in binding to ligands and different signaling partners. To our knowledge, this method, termed ActiveGEnSeMBLE, enables the first quantitative energy profile for GPCR activation that is consistent with the qualitative profile deduced from experiments. ActiveGEnSeMBLE starts with a systematic coarse grid sampling of helix tilts/rotations (∼13 trillion transmembrane-domain conformations) and selects the conformational landscape based on energy. This profile identifies multiple potential active-state energy wells, with the TM3-TM6 intracellular distance as an approximate activation coordinate. These energy wells are then sampled locally using a finer grid to find locally minimized conformation in each energy well. We validate this strategy using the inactive and active experimental structures of β2 adrenergic receptor (hβ2AR) and M2 muscarinic acetylcholine receptor. Structures of membrane-embedded hβ2AR along its activation coordinate are subjected to molecular-dynamics simulations for relaxation and interaction energy analysis to generate a quantitative energy landscape for hβ2AR activation. This landscape reveals several metastable states along this coordinate, indicating that for hβ2AR, the agonist alone is not enough to stabilize the active state and that the G protein is necessary, consistent with experimental observations. The method's application to somatostatin receptor SSTR5 (no experimental structure available) shows that to predict an active conformation it is better to start from an inactive structure template based on a close homolog than to start from an active template based on a distant homolog. The energy landscape for hSSTR5 activation is consistent with hβ2AR in the role of the G protein. These results demonstrate the utility of the ActiveGEnSeMBLE method for predicting multiple conformations along the pathways for activating GPCRs and the corresponding energy landscapes, thereby providing detailed structural insights into the initial molecular events of GPCR function that are not easily accessible by experiments.

G protein-coupled odorant receptors: From sequence to structure

Odorant receptors (ORs) are the largest subfamily within class A G protein-coupled receptors (GPCRs). No experimental structural data of any OR is available to date and atomic-level insights are likely to be obtained by means of molecular modeling. In this article, we critically align sequences of ORs with those GPCRs for which a structure is available. Here, an alignment consistent with available site-directed mutagenesis data on various ORs is proposed. Using this alignment, the choice of the template is deemed rather minor for identifying residues that constitute the wall of the binding cavity or those involved in G protein recognition.

Conserved Residues Control Activation of Mammalian G Protein-Coupled Odorant Receptors

Odorant receptor (OR) genes and proteins represent more than 2% of our genome and 4% of our proteome and constitute the largest subgroup of G protein-coupled receptors (GPCRs). The mechanism underlying OR activation remains poorly understood, as they do not share some of the highly conserved motifs critical for activation of non-olfactory GPCRs. By combining site-directed mutagenesis, heterologous expression, and molecular dynamics simulations that capture the conformational change of constitutively active mutants, we tentatively identified crucial residues for the function of these receptors using the mouse MOR256-3 (Olfr124) as a model. The toggle switch for sensing agonists involves a highly conserved tyrosine residue in helix VI. The ionic lock is located between the "DRY" motif in helix III and a positively charged "R/K" residue in helix VI. This study provides an unprecedented model that captures the main mechanisms of odorant receptor activation.

The predicted ensemble of low-energy conformations of human somatostatin receptor subtype 5 and the binding of antagonists

Human somatostatin receptor subtype 5 (hSSTR5) regulates cell proliferation and hormone secretion. However, the identification of effective therapeutic small-molecule ligands is impeded because experimental structures are not available for any SSTR subtypes. Here, we predict the ensemble of low-energy 3D structures of hSSTR5 using a modified GPCR Ensemble of Structures in Membrane BiLayer Environment (GEnSeMBLE) complete sampling computational method. We find that this conformational ensemble displays most interhelical interactions conserved in class A G protein-coupled receptors (GPCRs) plus seven additional interactions (e.g., Y2.43-D3.49, T3.38-S4.53, K5.64-Y3.51) likely conserved among SSTRs. We then predicted the binding sites for a series of five known antagonists, leading to predicted binding energies consistent with experimental results reported in the literature. Molecular dynamics (MD) simulation of 50 ns in explicit water and lipid retained the predicted ligand-bound structure and formed new interaction patterns (e.g. R3.50-T6.34) consistent with the inactive μ-opioid receptor X-ray structure. We suggest more than six mutations for experimental validation of our prediction. The final predicted receptor conformations and antagonist binding sites provide valuable insights for designing new small-molecule drugs targeting SSTRs.