Elucidation of the structural basis for ligand binding and translocation in conserved insect odorant receptor co-receptors.

In numerous insects, the olfactory receptor family forms a unique class of heteromeric cation channels. Recent progress in resolving the odorant receptor structures offers unprecedented opportunities for deciphering their molecular mechanisms of ligand recognition. Unexpectedly, these structures in apo or ligand-bound states did not reveal the pathway taken by the ligands between the extracellular space and the deep internal cavities. By combining molecular modeling with electrophysiological recordings, we identified amino acids involved in the dynamic entry pathway and the binding of VUAA1 to Drosophila melanogaster's odorant receptor co-receptor (Orco). Our results provide evidence for the exact location of the agonist binding site and a detailed and original mechanism of ligand translocation controlled by a network of conserved residues. These findings would explain the particularly high selectivity of Orcos for their ligands.

Different Trajectories of Apathy and Depression Among Subjective Cognitive Impairment Individuals with or without Conversion to Dementia: Results from the Memento Cohort in France.

BACKGROUND: Apathy and depression are two early behavioral symptoms in Alzheimer's disease (AD) and related disorders that often occur prior to the onset of cognitive decline and memory disturbances. Both have been associated with an increased risk of conversion to dementia, with a distinct neuropathology. OBJECTIVE: The assessment of the trajectories of apathy and depression and their independent impact on dementia conversion. METHODS: Apathy and Depression were measured using the Neuropsychiatric Inventory for caregiver (NPI) and clinician (NPI-C), among the nondemented individuals reporting subjective cognitive decline (SCD) at baseline. They were followed up over a 60-month period. Some converted to dementia, according to the methodology carried out by the French Memento Cohort. RESULTS: Among individuals with SCD (n = 2,323), the levels of apathy and depression were low and did not evolve significantly over the 60-month period, despite a trend in apathy increasing as of month 24. Regarding SCD individuals who converted to dementia within the 60-month period (n = 27), the prevalence of depression remained globally steady, while the levels of apathy increased over time. CONCLUSION: Apathy and depression have different trajectories among individuals with SCD and apathy alone is more likely-compared to depression-to be associated with conversion to dementia.

The Third Extracellular Loop of Mammalian Odorant Receptors Is Involved in Ligand Binding.

Mammals recognize chemicals in the air via G protein-coupled odorant receptors (ORs). In addition to their orthosteric binding site, other segments of these receptors modulate ligand recognition. Focusing on human hOR1A1, which is considered prototypical of class II ORs, we used a combination of molecular modeling, site-directed mutagenesis, and in vitro functional assays. We showed that the third extracellular loop of ORs (ECL3) contributes to ligand recognition and receptor activation. Indeed, site-directed mutations in ECL3 showed differential effects on the potency and efficacy of both carvones, citronellol, and 2-nonanone.

Extracellular loop 2 of G protein-coupled olfactory receptors is critical for odorant recognition.

G protein-coupled olfactory receptors (ORs) enable us to detect innumerous odorants. They are also ectopically expressed in nonolfactory tissues and emerging as attractive drug targets. ORs can be promiscuous or highly specific, which is part of a larger mechanism for odor discrimination. Here, we demonstrate that the OR extracellular loop 2 (ECL2) plays critical roles in OR promiscuity and specificity. Using site-directed mutagenesis and molecular modeling, we constructed 3D OR models in which ECL2 forms a lid over the orthosteric pocket. We demonstrate using molecular dynamics simulations that ECL2 controls the shape and volume of the odorant-binding pocket, maintains the pocket hydrophobicity, and acts as a gatekeeper of odorant binding. Therefore, we propose the interplay between the specific orthosteric pocket and the variable, less specific ECL2 controls OR specificity and promiscuity. Furthermore, the 3D models created here enabled virtual screening of new OR agonists and antagonists, which exhibited a 70% hit rate in cell assays. Our approach can potentially be generalized to structure-based ligand screening for other G protein-coupled receptors that lack high-resolution 3D structures.

Interactions among key residues regulate mammalian odorant receptor trafficking.

Odorant receptors (ORs) expressed in mammalian olfactory sensory neurons are essential for the sense of smell. However, structure-function studies of many ORs are hampered by unsuccessful heterologous expression. To understand and eventually overcome this bottleneck, we performed heterologous expression and functional assays of over 80 OR variants and chimeras. Combined with literature data and machine learning, we found that the transmembrane domain 4 (TM4) and its interactions with neighbor residues are important for OR functional expression. The data highlight critical roles of T4.62 therein. ORs that fail to reach the cell membrane can be rescued by modifications in TM4. Consequently, such modifications in MOR256-3 (Olfr124) also alter OR responses to odorants. T1614.62 P causes the retention of MOR256-3 in the endoplasmic reticulum (ER), while T1614.62 P/T1484.49 A reverses the retention and makes receptor trafficking to cell membrane. This study offers new clues toward wide-range functional studies of mammalian ORs.

Large-Scale G Protein-Coupled Olfactory Receptor-Ligand Pairing.

G protein-coupled receptors (GPCRs) conserve common structural folds and activation mechanisms, yet their ligand spectra and functions are highly diverse. This work investigated how the amino-acid sequences of olfactory receptors (ORs)-the largest GPCR family-encode diversified responses to various ligands. We established a proteochemometric (PCM) model based on OR sequence similarities and ligand physicochemical features to predict OR responses to odorants using supervised machine learning. The PCM model was constructed with the aid of site-directed mutagenesis, in vitro functional assays, and molecular simulations. We found that the ligand selectivity of the ORs is mostly encoded in the residues up to 8 Å around the orthosteric pocket. Subsequent predictions using Random Forest (RF) showed a hit rate of up to 58%, as assessed by in vitro functional assays of 111 ORs and 7 odorants of distinct scaffolds. Sixty-four new OR-odorant pairs were discovered, and 25 ORs were deorphanized here. The best model demonstrated a 56% deorphanization rate. The PCM-RF approach will accelerate OR-odorant mapping and OR deorphanization.

Discovery and Mechanism of Action of Small Molecule Inhibitors of Ceramidases.

Sphingolipid metabolism is tightly controlled by enzymes to regulate essential processes in human physiology. The central metabolite is ceramide, a pro-apoptotic lipid catabolized by ceramidase enzymes to produce pro-proliferative sphingosine-1-phosphate. Alkaline ceramidases are transmembrane enzymes that recently attracted attention for drug development in fatty liver diseases. However, due to their hydrophobic nature, no specific small molecule inhibitors have been reported. We present the discovery and mechanism of action of the first drug-like inhibitors of alkaline ceramidase 3 (ACER3). In particular, we chemically engineered novel fluorescent ceramide substrates enabling screening of large compound libraries and characterized enzyme:inhibitor interactions using mass spectrometry and MD simulations. In addition to revealing a new paradigm for inhibition of lipid metabolising enzymes with non-lipidic small molecules, our data lay the ground for targeting ACER3 in drug discovery efforts.

An automated platform for structural analysis of membrane proteins through serial crystallography.

Membrane proteins are central to many pathophysiological processes, yet remain very difficult to analyze structurally. Moreover, high-throughput structure-based drug discovery has not yet been exploited for membrane proteins because of lack of automation. Here, we present a facile and versatile platform for in meso membrane protein crystallization, enabling rapid atomic structure determination at both cryogenic and room temperatures. We apply this approach to human integral membrane proteins, which allowed us to identify different conformational states of intramembrane enzyme-product complexes and analyze by molecular dynamics simulations the structural dynamics of the ADIPOR2 integral membrane protein. Finally, we demonstrate an automated pipeline combining high-throughput microcrystal soaking, automated laser-based harvesting, and serial crystallography, enabling screening of small-molecule libraries with membrane protein crystals grown in meso. This approach brings needed automation to this important class of drug targets and enables high-throughput structure-based ligand discovery with membrane proteins.

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.

Molecular insights into the biased signaling mechanism of the µ-opioid receptor.

GPCR functional selectivity opens new opportunities for the design of safer drugs. Ligands orchestrate GPCR signaling cascades by modulating the receptor conformational landscape. Our study provides insights into the dynamic mechanism enabling opioid ligands to preferentially activate the G protein over the ß-arrestin pathways through the µ-opioid receptor (µOR). We combine functional assays in living cells, solution NMR spectroscopy, and enhanced-sampling molecular dynamic simulations to identify the specific µOR conformations induced by G protein-biased agonists. In particular, we describe the dynamic and allosteric communications between the ligand-binding pocket and the receptor intracellular domains, through conserved motifs in class A GPCRs. Most strikingly, the biased agonists trigger µOR conformational changes in the intracellular loop 1 and helix 8 domains, which may impair ß-arrestin binding or signaling. The findings may apply to other GPCR families and provide key molecular information that could facilitate the design of biased ligands.

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.

Recent Smell Loss Is the Best Predictor of COVID-19 Among Individuals With Recent Respiratory Symptoms.

In a preregistered, cross-sectional study, we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n = 4148) or negative (C19-; n = 546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean ± SD, C19+: -82.5 ± 27.2 points; C19-: -59.8 ± 37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC = 0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4 < OR < 10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.

Smell and taste changes are early indicators of the COVID-19 pandemic and political decision effectiveness.

In response to the COVID-19 pandemic, many governments have taken drastic measures to avoid an overflow of intensive care units. Accurate metrics of disease spread are critical for the reopening strategies. Here, we show that self-reports of smell/taste changes are more closely associated with hospital overload and are earlier markers of the spread of infection of SARS-CoV-2 than current governmental indicators. We also report a decrease in self-reports of new onset smell/taste changes as early as 5 days after lockdown enforcement. Cross-country comparisons demonstrate that countries that adopted the most stringent lockdown measures had faster declines in new reports of smell/taste changes following lockdown than a country that adopted less stringent lockdown measures. We propose that an increase in the incidence of sudden smell and taste change in the general population may be used as an indicator of COVID-19 spread in the population.

The best COVID-19 predictor is recent smell loss: a cross-sectional study.

BACKGROUND: COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19. METHODS: This preregistered, cross-sectional study used a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified singular and cumulative predictors of COVID-19 status and post-COVID-19 olfactory recovery. RESULTS: Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset. CONCLUSIONS: As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (10

More Than Smell-COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis.

Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± standard deviation), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis. The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms.

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.

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.