M2OR: a database of olfactory receptor-odorant pairs for understanding the molecular mechanisms of olfaction.

Mammalian sense of smell is triggered by interaction between odorant molecules and a class of proteins, called olfactory receptors (ORs). These receptors, expressed at the surface of olfactory sensory neurons, encode myriad of distinct odors via a sophisticated activation pattern. However, determining the molecular recognition spectrum of ORs remains a major challenge. The Molecule to Olfactory Receptor database (M2OR, https://m2or.chemsensim.fr/) provides curated data that allows an easy exploration of the current state of the research on OR-molecule interaction. We have gathered a database of 75,050 bioassay experiments for 51 395 distinct OR-molecule pairs. Drawn from published literature and public databases, M2OR contains information about OR responses to molecules and their mixtures, receptor sequences and experimental details. Users can obtain information on the activity of a chosen molecule or a group of molecules, or search for agonists for a specific OR or a group of ORs. Advanced search allows for fine-grained queries using various metadata such as species or experimental assay system, and the database can be queried by multiple inputs via a batch search. Finally, for a given search query, users can access and download a curated aggregation of the experimental data into a binarized combinatorial code of olfaction.

Citronellol biosynthesis in pelargonium is a multistep pathway involving progesterone 5ß-reductase and/or iridoid synthase-like enzymes.

Citronellol is a pleasant-smelling compound produced in rose (Rosa spp.) flowers and in the leaves of many aromatic plants, including pelargoniums (Pelargonium spp.). Although geraniol production has been well studied in several plants, citronellol biosynthesis has been documented only in crab-lipped spider orchid (Caladenia plicata) and its mechanism remains open to question in other species. We therefore profiled 10 pelargonium accessions using RNA sequencing and gas chromatography-MS analysis. Three enzymes from the progesterone 5ß-reductase and/or iridoid synthase-like enzymes (PRISE) family were characterized in vitroand subsequently identified as citral reductases (named PhCIRs). Transgenic RNAi lines supported a role for PhCIRs in the biosynthesis of citronellol as well as in the production of mint-scented terpenes. Despite their high amino acid sequence identity, the 3 enzymes showed contrasting stereoselectivity, either producing mainly (S)-citronellal or a racemate of both (R)- and (S)-citronellal. Using site-directed mutagenesis, we identified a single amino acid substitution as being primarily responsible for the enzyme's enantioselectivity. Phylogenetic analysis of pelargonium PRISEs revealed 3 clades and 7 groups of orthologs. PRISEs from different groups exhibited differential affinities toward substrates (citral and progesterone) and cofactors (NADH/NADPH), but most were able to reduce both substrates, prompting hypotheses regarding the evolutionary history of PhCIRs. Our results demonstrate that pelargoniums evolved citronellol biosynthesis independently through a 3-step pathway involving PRISE homologs and both citral and citronellal as intermediates. In addition, these enzymes control the enantiomeric ratio of citronellol thanks to small alterations of the catalytic site.

Exploring Dihydroflavonol-4-Reductase Reactivity and Selectivity by QM/MM-MD Simulations.

Flavonoids are secondary metabolites ubiquitously found in plants. Their antioxidant properties make them highly interesting natural compounds for use in pharmacology. Therefore, unravelling the mechanisms of flavonoid biosynthesis is an important challenge. Among all the enzymes involved in this biosynthetic pathway, dihydroflavonol-4-reductase (DFR) plays a key role in the production of anthocyanins and proanthocyanidins. Here, we provide new information on the mechanism of action of this enzyme by using QM/MM-MD simulations applied to both dihydroquercetin (DHQ) and dihydrokaempferol (DHK) substrates. The consideration of these very similar compounds shed light on the major role played by the enzyme on the stabilization of the transition state but also on the activation of the substrate before the reaction through near-attack conformer effects.

Functional molecular switches of mammalian G protein-coupled bitter-taste receptors.

Bitter taste receptors (TAS2Rs) are a poorly understood subgroup of G protein-coupled receptors (GPCRs). The experimental structure of these receptors has yet to be determined, and key-residues controlling their function remain mostly unknown. We designed an integrative approach to improve comparative modeling of TAS2Rs. Using current knowledge on class A GPCRs and existing experimental data in the literature as constraints, we pinpointed conserved motifs to entirely re-align the amino-acid sequences of TAS2Rs. We constructed accurate homology models of human TAS2Rs. As a test case, we examined the accuracy of the TAS2R16 model with site-directed mutagenesis and in vitro functional assays. This combination of in silico and in vitro results clarifies sequence-function relationships and proposes functional molecular switches that encode agonist sensing and downstream signaling mechanisms within mammalian TAS2Rs sequences.

Reverse chemical ecology in a moth: machine learning on odorant receptors identifies new behaviorally active agonists.

The concept of reverse chemical ecology (exploitation of molecular knowledge for chemical ecology) has recently emerged in conservation biology and human health. Here, we extend this concept to crop protection. Targeting odorant receptors from a crop pest insect, the noctuid moth Spodoptera littoralis, we demonstrate that reverse chemical ecology has the potential to accelerate the discovery of novel crop pest insect attractants and repellents. Using machine learning, we first predicted novel natural ligands for two odorant receptors, SlitOR24 and 25. Then, electrophysiological validation proved in silico predictions to be highly sensitive, as 93% and 67% of predicted agonists triggered a response in Drosophila olfactory neurons expressing SlitOR24 and SlitOR25, respectively, despite a lack of specificity. Last, when tested in Y-maze behavioral assays, the most active novel ligands of the receptors were attractive to caterpillars. This work provides a template for rational design of new eco-friendly semiochemicals to manage crop pest populations.

Zebrafish olfactory receptors ORAs differentially detect bile acids and bile salts.

The fish olfactory receptor ORA family is orthologous to the mammalian vomeronasal receptors type 1. It consists of six highly conserved chemosensory receptors expected to be essential for survival and communication. We deorphanized the zebrafish ORA family in a heterologous cell system. The six receptors responded specifically to lithocholic acid (LCA) and closely related C24 5ß-bile acids/salts. LCA attracted zebrafish as strongly as food in behavioral tests, whereas the less potent cholanic acid elicited weaker attraction, consistent with the in vitro results. The ORA-ligand recognition patterns were probed with site-directed mutagenesis guided by in silico modeling. We revealed the receptors' structure-function relationship underlying their specificity and selectivity for these compounds. Bile acids/salts are putative fish semiochemicals or pheromones sensed by the olfactory system with high specificity. This work identified their receptors and provided the basis for probing the roles of ORAs and bile acids/salts in fish chemosensation.

Conserved Residues Control the T1R3-Specific Allosteric Signaling Pathway of the Mammalian Sweet-Taste Receptor.

Mammalian sensory systems detect sweet taste through the activation of a single heteromeric T1R2/T1R3 receptor belonging to class C G-protein-coupled receptors. Allosteric ligands are known to interact within the transmembrane domain, yet a complete view of receptor activation remains elusive. By combining site-directed mutagenesis with computational modeling, we investigate the structure and dynamics of the allosteric binding pocket of the T1R3 sweet-taste receptor in its apo form, and in the presence of an allosteric ligand, cyclamate. A novel positively charged residue at the extracellular loop 2 is shown to interact with the ligand. Molecular dynamics simulations capture significant differences in the behavior of a network of conserved residues with and without cyclamate, although they do not directly interact with the allosteric ligand. Structural models show that they adopt alternate conformations, associated with a conformational change in the transmembrane region. Site-directed mutagenesis confirms that these residues are unequivocally involved in the receptor function and the allosteric signaling mechanism of the sweet-taste receptor. Similar to a large portion of the transmembrane domain, they are highly conserved among mammals, suggesting an activation mechanism that is evolutionarily conserved. This work provides a structural basis for describing the dynamics of the receptor, and for the rational design of new sweet-taste modulators.

Metal Ions Activate the Human Taste Receptor TAS2R7.

Divalent and trivalent salts exhibit a complex taste profile. They are perceived as being astringent/drying, sour, bitter, and metallic. We hypothesized that human bitter-taste receptors may mediate some taste attributes of these salts. Using a cell-based functional assay, we found that TAS2R7 responds to a broad range of divalent and trivalent salts, including zinc, calcium, magnesium, copper, manganese, and aluminum, but not to potassium, suggesting TAS2R7 may act as a metal cation receptor mediating bitterness of divalent and trivalent salts. Molecular modeling and mutagenesis analysis identified 2 residues, H943.37 and E2647.32, in TAS2R7 that appear to be responsible for the interaction of TAS2R7 with metallic ions. Taste receptors are found in both oral and extraoral tissues. The responsiveness of TAS2R7 to various mineral salts suggests it may act as a broad sensor, similar to the calcium-sensing receptor, for biologically relevant metal cations in both oral and extraoral tissues.

Allosteric Modulation Mechanism of the mGluR5 Transmembrane Domain.

Positive allosteric modulators (PAMs) of metabotropic glutamate receptor type 5 (mGluR5), a prototypical class C G protein-coupled receptor (GPCR), have shown therapeutic potential for various neurological disorders. Understanding the allosteric activation mechanism is essential for the rational design of mGluR5 PAMs. We studied the actions of positive and negative allosteric modulators within the transmembrane domain of mGluR5, using enhance-sampling all-atom molecular dynamics simulations. We found dual binding modes of the PAM, associated with distinct shapes of the allosteric pocket. The negative allosteric modulators, in contrast, showed only one binding mode. The simulations revealed the mechanism by which the PAM activated the receptor, in the absence of the orthosteric agonist (the so-called allosteric agonism). The mechanism relied on dynamic communications between amino-acid motifs that are highly conserved across class C GPCRs. The findings may guide structure-based design and virtual screening of allosteric modulators for mGluR5 as well as for other class C GPCRs.

The anatomy of mammalian sweet taste receptors.

All sweet-tasting compounds are detected by a single G-protein coupled receptor (GPCR), the heterodimer T1R2-T1R3, for which no experimental structure is available. The sweet taste receptor is a class C GPCR, and the recently published crystallographic structures of metabotropic glutamate receptor (mGluR) 1 and 5 provide a significant step forward for understanding structure-function relationships within this family. In this article, we recapitulate more than 600 single point site-directed mutations and available structural data to obtain a critical alignment of the sweet taste receptor sequences with respect to other class C GPCRs. Using this alignment, a homology 3D-model of the human sweet taste receptor is built and analyzed to dissect out the role of key residues involved in ligand binding and those responsible for receptor activation. Proteins 2017; 85:332-341. © 2016 Wiley Periodicals, Inc.

Update of the ATTRACT force field for the prediction of protein-protein binding affinity.

Determining the protein-protein interactions is still a major challenge for molecular biology. Docking protocols has come of age in predicting the structure of macromolecular complexes. However, they still lack accuracy to estimate the binding affinities, the thermodynamic quantity that drives the formation of a complex. Here, an updated version of the protein-protein ATTRACT force field aiming at predicting experimental binding affinities is reported. It has been designed on a dataset of 218 protein-protein complexes. The correlation between the experimental and predicted affinities reaches 0.6, outperforming most of the available protocols. Focusing on a subset of rigid and flexible complexes, the performance raises to 0.76 and 0.69, respectively. © 2017 Wiley Periodicals, Inc.

Fine-tuning of microsolvation and hydrogen bond interaction regulates substrate channelling in the course of flavonoid biosynthesis.

In the course of metabolite formation, some multienzymatic edifices, the so-called metabolon, are formed and lead to a more efficient production of these natural compounds. One of the major features of these enzyme complexes is the facilitation of direct transfer of the metabolite between enzyme active sites by substrate channelling. Biophysical insights into substrate channelling remain scarce because the transient nature of these macromolecular complexes prevents the observation of high resolution structures. Here, using molecular modelling, we describe the substrate channelling of a flavonoid compound between DFR (dihydroflavonol-4-reductase) and LAR (leucoanthocyanidin reductase). The simulation presents crucial details concerning the kinetic, thermodynamic, and structural aspects of this diffusion. The formation of the DFR-LAR complex leads to the opening of the DFR active site giving rise to a facilitated diffusion, in about 1 µs, of the DFR product towards LAR cavity. The theoretically observed substrate channelling is supported experimentally by the fact that this metabolite, i.e. the product of the DFR enzyme, is not stable in the media. Moreover, along this path, the influence of the solvent is crucial. The metabolite remains close to the surface of the complex avoiding full solvation. In addition, when the dynamic behaviour of the system leads to a loss of interaction between the metabolite and the enzymes, water molecules through bridging H-bonds prevent the former from escaping to the bulk.

Isolation and functional characterization of a τ-cadinol synthase, a new sesquiterpene synthase from Lavandula angustifolia.

In this paper we characterize three sTPSs: a germacrene D (LaGERDS), a (E)-ß-caryophyllene (LaCARS) and a τ-cadinol synthase (LaCADS). τ-cadinol synthase is reported here for the first time and its activity was studied in several biological models including transiently or stably transformed tobacco species. Three dimensional structure models of LaCADS and Ocimum basilicum γ-cadinene synthase were built by homology modeling using the template structure of Gossypium arboreum δ-cadinene synthase. The depiction of their active site organization provides evidence of the global influence of the enzymes on the formation of τ-cadinol: instead of a unique amino-acid, the electrostatic properties and solvent accessibility of the whole active site in LaCADS may explain the stabilization of the cadinyl cation intermediate. Quantitative PCR performed from leaves and inflorescences showed two patterns of expression. LaGERDS and LaCARS were mainly expressed during early stages of flower development and, at these stages, transcript levels paralleled the accumulation of the corresponding terpene products (germacrene D and (E)-ß-caryophyllene). By contrast, the expression level of LaCADS was constant in leaves and flowers. Phylogenetic analysis provided informative results on potential duplication process leading to sTPS diversification in lavender.

Exploiting antigenic diversity for vaccine design: the chlamydia ArtJ paradigm.

We present an interdisciplinary approach that, by incorporating a range of experimental and computational techniques, allows the identification and characterization of functional/immunogenic domains. This approach has been applied to ArtJ, an arginine-binding protein whose orthologs in Chlamydiae trachomatis (CT ArtJ) and pneumoniae (CPn ArtJ) are shown to have different immunogenic properties despite a high sequence similarity (60% identity). We have solved the crystallographic structures of CT ArtJ and CPn ArtJ, which are found to display a type II transporter fold organized in two α-ß domains with the arginine-binding region at their interface. Although ArtJ is considered to belong to the periplasm, we found that both domains contain regions exposed on the bacterial surface. Moreover, we show that recombinant ArtJ binds to epithelial cells in vitro, suggesting a role for ArtJ in host-cell adhesion during Chlamydia infection. Experimental epitope mapping and computational analysis of physicochemical determinants of antibody recognition revealed that immunogenic epitopes reside mainly in the terminal (D1) domain of both CPn and CT ArtJ, whereas the surface properties of the respective binding-prone regions appear sufficiently different to assume divergent immunogenic behavior. Neutralization assays revealed that sera raised against CPn ArtJ D1 partially reduce both CPn and CT infectivity in vitro, suggesting that functional antibodies directed against this domain may potentially impair chlamydial infectivity. These findings suggest that the approach presented here, combining functional and structure-based analyses of evolutionary-related antigens can be a valuable tool for the identification of cross-species immunogenic epitopes for vaccine development.

ProLIF: a library to encode molecular interactions as fingerprints.

Interaction fingerprints are vector representations that summarize the three-dimensional nature of interactions in molecular complexes, typically formed between a protein and a ligand. This kind of encoding has found many applications in drug-discovery projects, from structure-based virtual-screening to machine-learning. Here, we present ProLIF, a Python library designed to generate interaction fingerprints for molecular complexes extracted from molecular dynamics trajectories, experimental structures, and docking simulations. It can handle complexes formed of any combination of ligand, protein, DNA, or RNA molecules. The available interaction types can be fully reparametrized or extended by user-defined ones. Several tutorials that cover typical use-case scenarios are available, and the documentation is accompanied with code snippets showcasing the integration with other data-analysis libraries for a more seamless user-experience. The library can be freely installed from our GitHub repository ( https://github.com/chemosim-lab/ProLIF ).

Prediction of protein-protein interaction sites using electrostatic desolvation profiles.

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces.

Binding site prediction and improved scoring during flexible protein-protein docking with ATTRACT.

The ATTRACT protein-protein docking program combined with a coarse-grained protein model has been used to predict protein-protein complex structures in CAPRI rounds 13-19. For six targets acceptable or better quality solutions have been submitted (high quality predictions for targets 32, 40, 41, and 42). The improved performance compared to previous rounds can be attributed in part to the inclusion of conformational flexibility during systematic searches and an optimized scoring function. In addition, a recently developed method for the prediction of putative protein binding sites based on the electrostatic penalty to place neutral low dielectric probes on the protein surface was applied to the most recent targets. The approach resulted in useful predictions of putative binding sites that can help to limit the systematic docking searches. Possible improvements of the docking approach in particular at the scoring and refinement steps are discussed.

Novel scaffold of natural compound eliciting sweet taste revealed by machine learning.

Sugar replacement is still an active issue in the food industry. The use of structure-taste relationships remains one of the most rational strategy to expand the chemical space associated to sweet taste. A new machine learning model has been setup based on an update of the SweetenersDB and on open-source molecular features. It has been implemented on a freely accessible webserver. Cellular functional assays show that the sweet taste receptor is activated in vitro by a new scaffold of natural compounds identified by the in silico protocol. The newly identified sweetener belongs to the lignan chemical family and opens a new chemical space to explore.

Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor.

Odorant receptors expressed at the peripheral olfactory organs are key proteins for animal volatile sensing. Although they determine the odor space of a given species, their functional characterization is a long process and remains limited. To date, machine learning virtual screening has been used to predict new ligands for such receptors in both mammals and insects, using chemical features of known ligands. In insects, such approach is yet limited to Diptera, whereas insect odorant receptors are known to be highly divergent between orders. Here, we extend this strategy to a Lepidoptera receptor, SlitOR25, involved in the recognition of attractive odorants in the crop pest Spodoptera littoralis larvae. Virtual screening of 3 million molecules predicted 32 purchasable ones whose function has been systematically tested on SlitOR25, revealing 11 novel agonists with a success rate of 28%. Our results show that Support Vector Machine optimizes the discovery of novel agonists and expands the chemical space of a Lepidoptera OR. More, it opens up structure-function relationship analyses through a comparison of the agonist chemical structures. This proof-of-concept in a crop pest could ultimately enable the identification of OR agonists or antagonists, capable of modifying olfactory behaviors in a context of biocontrol.