A µ-opioid receptor modulator that works cooperatively with naloxone.

The µ-opioid receptor (µOR) is a well-established target for analgesia1, yet conventional opioid receptor agonists cause serious adverse effects, notably addiction and respiratory depression. These factors have contributed to the current opioid overdose epidemic driven by fentanyl2, a highly potent synthetic opioid. µOR negative allosteric modulators (NAMs) may serve as useful tools in preventing opioid overdose deaths, but promising chemical scaffolds remain elusive. Here we screened a large DNA-encoded chemical library against inactive µOR, counter-screening with active, G-protein and agonist-bound receptor to 'steer' hits towards conformationally selective modulators. We discovered a NAM compound with high and selective enrichment to inactive µOR that enhances the affinity of the key opioid overdose reversal molecule, naloxone. The NAM works cooperatively with naloxone to potently block opioid agonist signalling. Using cryogenic electron microscopy, we demonstrate that the NAM accomplishes this effect by binding a site on the extracellular vestibule in direct contact with naloxone while stabilizing a distinct inactive conformation of the extracellular portions of the second and seventh transmembrane helices. The NAM alters orthosteric ligand kinetics in therapeutically desirable ways and works cooperatively with low doses of naloxone to effectively inhibit various morphine-induced and fentanyl-induced behavioural effects in vivo while minimizing withdrawal behaviours. Our results provide detailed structural insights into the mechanism of negative allosteric modulation of the µOR and demonstrate how this can be exploited in vivo.

Stepwise activation of a metabotropic glutamate receptor.

Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain that is linked via a cysteine-rich domain to their 7-transmembrane domain1. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the extracellular ligand-binding domain to the G protein-coupling 7-transmembrane domain2. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging, we reveal distinct receptor conformations upon allosteric modulator and G protein binding.

Ligand efficacy modulates conformational dynamics of the µ-opioid receptor.

The µ-opioid receptor (µOR) is an important target for pain management1 and molecular understanding of drug action on µOR will facilitate the development of better therapeutics. Here we show, using double electron-electron resonance and single-molecule fluorescence resonance energy transfer, how ligand-specific conformational changes of µOR translate into a broad range of intrinsic efficacies at the transducer level. We identify several conformations of the cytoplasmic face of the receptor that interconvert on different timescales, including a pre-activated conformation that is capable of G-protein binding, and a fully activated conformation that markedly reduces GDP affinity within the ternary complex. Interaction of ß-arrestin-1 with the µOR core binding site appears less specific and occurs with much lower affinity than binding of Gi.

Large library docking for cannabinoid-1 receptor agonists with reduced side effects.

Large library docking can reveal unexpected chemotypes that complement the structures of biological targets. Seeking new agonists for the cannabinoid-1 receptor (CB1R), we docked 74 million tangible molecules, prioritizing 46 high ranking ones for de novo synthesis and testing. Nine were active by radioligand competition, a 20% hit-rate. Structure-based optimization of one of the most potent of these (Ki = 0.7 uM) led to '4042, a 1.9 nM ligand and a full CB1R agonist. A cryo-EM structure of the purified enantiomer of '4042 ('1350) in complex with CB1R-Gi1 confirmed its docked pose. The new agonist was strongly analgesic, with generally a 5-10-fold therapeutic window over sedation and catalepsy and no observable conditioned place preference. These findings suggest that new cannabinoid chemotypes may disentangle characteristic cannabinoid side-effects from their analgesia, supporting the further development of cannabinoids as pain therapeutics.

Dental composite biodeterioration in the presence of oral Streptococci and extracellular metabolic products.

OBJECTIVE: Secondary caries is a primary cause of early restoration failure. While primary dental caries has been extensively researched, our knowledge about the impact of secondary caries on dental restorations is relatively limited. In this study, we examined how different clinically relevant microbially-influenced environments impact the degradation of nano-filled (FIL) and micro-hybrid (AEL) dental composites. METHODS: Material strength of two commercial dental composites was measured following incubation in aqueous media containing: i) cariogenic (Streptococcus mutans) and non-cariogenic bacteria (Streptococcus sanguinis) grown on sucrose or glucose, ii) abiotic mixtures of artificial saliva and sucrose and glucose fermentation products (volatile fatty acids and ethanol) in proportions known to be produced by these microorganisms, and iii) abiotic mixtures of artificial saliva and esterase, a common oral extracellular enzyme. RESULTS: Nano-filled FIL composite strength decreased in all three types of incubations, while micro-hybrid AEL composite strength only decreased significantly in biotic incubations. The strength of both composites was statistically significantly decreased in all biotic incubations containing both cariogenic and non-cariogenic bacteria beyond that induced by either abiotic mixtures of fermentation products or esterase alone. Finally, there were no statistically significant differences in composite strength decrease among the tested biotic conditions. CONCLUSIONS: The results show that conditions created during the growth of both cariogenic and non-cariogenic oral Streptococci substantially reduce commercial composite strength, and this effect warrants further study to identify the mechanism(s). CLINICAL SIGNIFICANCE: Dental biofilms of oral Streptococci bacteria significantly affect the mechanical strength of dental restorations.

Step-wise activation of a Family C GPCR.

Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain (ECD) that is linked via a cysteine-rich domain (CRDs) to their 7-transmembrane (TM) domain. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the ECD to the G protein-coupling TM. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging we reveal distinct receptor conformations upon allosteric modulator and G protein binding.

Relationships between composite roughness and Streptococcus mutans biofilm depth under shear in vitro.

OBJECTIVE: To investigate the effect of substrate, surface roughness, and hydraulic residence time (HRT) on Streptococcus mutans biofilms growing on dental composites under conditions relevant to the oral cavity. METHODS: Dental composites were prepared with varying amounts of polishing and incubated in a CDC bioreactor with an approximate shear of 0.4 Pa. S. mutans biofilms developed in the bioreactors fed sucrose or glucose and at 10-h or 40-h HRT for one week. Biofilms were characterized by confocal laser microscopy (CLM). Composite surface roughness was characterized by optical profilometry, and pre- and post-incubation composite surface fine structure and elemental composition were determined using scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS). RESULTS: Polishing had a significant impact on surface roughness, varying by a factor of 15 between the polished samples and the unpolished control. S. mutans biofilms grew statistically significantly thicker on the unpolished composites. Biofilm thickness was greater at shorter 10-h HRT compared to 40-h HRT. In most cases, biofilm thickness was not statistically significantly greater in sucrose-fed bioreactors than in glucose-fed bioreactors. SEM-EDS analysis did not identify any significant change in elemental composition after aging. CONCLUSIONS: Accurate characterization of oral cavity biofilms must consider shear forces and the use of techniques that minimize alteration of the biofilm structure. Under shear, surface smoothness is the most important factor determining S. mutans biofilm thickness followed by HRT, while sucrose presence did not result in significantly greater biofilm thickness. CLINICAL SIGNIFICANCE: The obvious patterns of S. mutans growth along sub-micron scale grooving created by the polishing process suggested that initial biofilm attachment occurred in the shear-protected grooves. These results suggest that fine polishing may help prevent the initial formation of S. mutans biofilms compared to unpolished/coarse polished composites.

Conformational dynamics of the µ-opioid receptor determine ligand intrinsic efficacy.

The µ-opioid receptor (µOR) is an important target for pain management and the molecular understanding of drug action will facilitate the development of better therapeutics. Here we show, using double electron-electron resonance (DEER) and single-molecule fluorescence resonance energy transfer (smFRET), how ligand-specific conformational changes of the µOR translate into a broad range of intrinsic efficacies at the transducer level. We identify several cytoplasmic receptor conformations interconverting on different timescales, including a pre-activated receptor conformation which is capable of G protein binding, and a fully activated conformation which dramatically lowers GDP affinity within the ternary complex. Interaction of ß-arrestin-1 with the µOR core binding site appears less specific and occurs with much lower affinity than binding of G protein Gi.

Stoichiometric models of sucrose and glucose fermentation by oral streptococci: Implications for free acid formation and enamel demineralization.

OBJECTIVES: The objective of this study is to develop stoichiometric models of sugar fermentation and cell biosynthesis for model cariogenic Streptococcus mutans and non-cariogenic Streptococcus sanguinis to better understand and predict metabolic product formation. METHODS: Streptococcus mutans (strain UA159) and Streptococcus sanguinis (strain DSS-10) were grown separately in bioreactors fed brain heart infusion broth supplemented with either sucrose or glucose at 37 °C. Cell mass concentration and fermentation products were measured at different hydraulic residence times (HRT) to determine cell growth yield. RESULTS: Sucrose growth yields were 0.080 ± 0.0078 g cell/g and 0.18 ± 0.031 g cell/g for S. sanguinis and S. mutans, respectively. For glucose, this reversed, with S. sanguinis having a yield of 0.10 ± 0.0080 g cell/g and S. mutans 0.053 ± 0.0064 g cell/g. Stoichiometric equations to predict free acid concentrations were developed for each test case. Results demonstrate that S. sanguinis produces more free acid at a given pH than S. mutans due to lesser cell yield and production of more acetic acid. Greater amounts of free acid were produced at the shortest HRT of 2.5 hr compared to longer HRTs for both microorganisms and substrates. SIGNIFICANCE: The finding that the non-cariogenic S. sanguinis produces greater amounts of free acids than S. mutans strongly suggests that bacterial physiology and environmental factors affecting substrate/metabolite mass transfer play a much greater role in tooth or enamel/dentin demineralization than acidogenesis. These findings enhance the understanding of fermentation production by oral streptococci and provide useful data for comparing studies under different environmental conditions.

Logistic Regression Analysis of LC-MS/MS Data of Monomers Eluted from Aged Dental Composites: A Supervised Machine-Learning Approach.

Compound identification by database searching that matches experimental with library mass spectra is commonly used in mass spectrometric (MS) data analysis. Vendor software often outputs scores that represent the quality of each spectral match for the identified compounds. However, software-generated identification results can differ drastically depending on the initial search parameters. Machine learning is applied here to provide a statistical evaluation of software-generated compound identification results from experimental tandem MS data. This task was accomplished using the logistic regression algorithm to assign an identification probability value to each identified compound. Logistic regression is usually used for classification, but here it is used to generate identification probabilities without setting a threshold for classification. Liquid chromatography coupled with quadrupole-time-of-flight tandem MS was used to analyze the organic monomers leached from resin-based dental composites in a simulated oral environment. The collected tandem MS data were processed with vendor software, followed by statistical evaluation of these results using logistic regression. The assigned identification probability to each compound provides more confidence in identification beyond solely by database matching. A total of 21 distinct monomers were identified among all samples, including five intact monomers and chemical degradation products of bisphenol A glycidyl methacrylate (BisGMA), oligomers of bisphenol-A ethoxylate methacrylate (BisEMA), triethylene glycol dimethacrylate (TEGDMA), and urethane dimethacrylate (UDMA). The logistic regression model can be used to evaluate any database-matched liquid chromatography-tandem MS result by training a new model using analytical standards of compounds present in a chosen database and then generating identification probabilities for candidates from unknown data using the new model.

Negative allosteric modulation of the glucagon receptor by RAMP2.

Receptor activity-modifying proteins (RAMPs) modulate the activity of many Family B GPCRs. We show that RAMP2 directly interacts with the glucagon receptor (GCGR), a Family B GPCR responsible for blood sugar homeostasis, and broadly inhibits receptor-induced downstream signaling. HDX-MS experiments demonstrate that RAMP2 enhances local flexibility in select locations in and near the receptor extracellular domain (ECD) and in the 6th transmembrane helix, whereas smFRET experiments show that this ECD disorder results in the inhibition of active and intermediate states of the intracellular surface. We determined the cryo-EM structure of the GCGR-Gs complex at 2.9 Å resolution in the presence of RAMP2. RAMP2 apparently does not interact with GCGR in an ordered manner; however, the receptor ECD is indeed largely disordered along with rearrangements of several intracellular hallmarks of activation. Our studies suggest that RAMP2 acts as a negative allosteric modulator of GCGR by enhancing conformational sampling of the ECD.

Population-specific vulnerability to ocean change in a multistressor environment.

Variation in environmental conditions across a species' range can alter their responses to environmental change through local adaptation and acclimation. Evolutionary responses, however, may be challenged in ecosystems with tightly coupled environmental conditions, where changes in the covariance of environmental factors may make it more difficult for species to adapt to global change. Here, we conduct a 3-month-long mesocosm experiment and find evidence for local adaptation/acclimation in populations of red sea urchins, Mesocentrotus franciscanus, to multiple environmental drivers. Moreover, populations differ in their response to projected concurrent changes in pH, temperature, and dissolved oxygen. Our results highlight the potential for local adaptation/acclimation to multivariate environmental regimes but suggest that thresholds in responses to a single environmental variable, such as temperature, may be more important than changes to environmental covariance. Therefore, identifying physiological thresholds in key environmental drivers may be particularly useful for preserving biodiversity and ecosystem functioning.

The impact of long-term aging in artificial saliva media on resin-based dental composite strength.

Although salivary liquid can degrade constituents in resin-based dental composites in short-term incubations, there is a knowledge gap on how longer-term aging impacts their bulk strength. We address this through extended aging studies with resin-based dental composites in different environments. Two commercial composites (FIL and AEL) were aged aseptically at 37°C in air (A, control), artificial saliva (AS), and esterase enzyme amended AS (EAS). Diametral and pushout strength were measured after periods of 120-180 days. At 120 days, the diametral strength of composites aged in air was 69.9 ± 11.0 and 57.7 ± 3.31 MPa in FIL and AEL, respectively. These were significantly greater compared to composites aged in AS (32.1 ± 7.01 and 46.2 ± 9.38 MPa in FIL and AEL, respectively) or EAS (36.7 ± 8.49 and 43.5 ± 5.51 MPa in FIL and AEL, respectively). In contrast, pushout strength for both composites were smaller in A compared to those aged in AS and EAS, results attributed to AS absorption and polymer expansion. No significant change in either diametral or pushout strength occurred after 120 days. There was no significant difference between aging in AS and EAS, suggesting that esterase did not significantly decrease the bulk material strength to a greater extent than AS under the test conditions. Aqueous diffusivities for the composites ranged from 8.4 to 11 × 10-13  m2 /s, with associated porosities ranging from 0.06% to 0.10%. These results indicate that saturation of a typical dental composite occurs over a time frame of 4-5 months, longer than typical aging studies. Together, the results demonstrate the importance of aging time on composite strength.

Enhanced Competition at the Nano-Bio Interface Enables Comprehensive Characterization of Protein Corona Dynamics and Deep Coverage of Proteomes.

Introducing engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. This enables scalable systems that leverage protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Here the importance of the protein to NP-surface ratio (P/NP) is demonstrated and protein corona formation dynamics are modeled, which determine the competition between proteins for binding. Tuning the P/NP ratio significantly modulates the protein corona composition, enhancing depth and precision of a fully automated NP-based deep proteomic workflow (Proteograph). By increasing the binding competition on engineered NPs, 1.2-1.7× more proteins with 1% false discovery rate are identified on the surface of each NP, and up to 3× more proteins compared to a standard plasma proteomics workflow. Moreover, the data suggest P/NP plays a significant role in determining the in vivo fate of nanomaterials in biomedical applications. Together, the study showcases the importance of P/NP as a key design element for biomaterials and nanomedicine in vivo and as a powerful tuning strategy for accurate, large-scale NP-based deep proteomic studies.

Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

Superatomic solid solutions.

In atomic solids, substitutional doping of atoms into the lattice of a material to form solid solutions is one of the most powerful approaches to modulating its properties and has led to the discovery of various metal alloys and semiconductors. Herein we have prepared solid solutions in hierarchical solids that are built from atomically precise clusters. Two geometrically similar metal chalcogenide clusters, Co6Se8(PEt3)6 and Cr6Te8(PEt3)6, were combined as random substitutional mixture, in three different ratios, in a crystal lattice together with fullerenes. This does not alter the underlying crystalline structure of the [cluster][C60]2 material, but it influences its electronic and magnetic properties. All three solid solutions showed increased electrical conductivities compared with either the Co- or Cr-based parent material, substantially so for two of the Co:Cr ratios (up to 100-fold), and lowered activation barriers for electron transport. We attribute this to the existence of additional energy states arising from the materials' structural heterogeneity, which effectively narrow transport gaps.

Structural insights into differences in G protein activation by family A and family B GPCRs.

Family B heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) play important roles in carbohydrate metabolism. Recent structures of family B GPCR-Gs protein complexes reveal a disruption in the α-helix of transmembrane segment 6 (TM6) not observed in family A GPCRs. To investigate the functional impact of this structural difference, we compared the structure and function of the glucagon receptor (GCGR; family B) with the ß2 adrenergic receptor (ß2AR; family A). We determined the structure of the GCGR-Gs complex by means of cryo-electron microscopy at 3.1-angstrom resolution. This structure shows the distinct break in TM6. Guanosine triphosphate (GTP) turnover, guanosine diphosphate release, GTP binding, and G protein dissociation studies revealed much slower rates for G protein activation by the GCGR compared with the ß2AR. Fluorescence and double electron-electron resonance studies suggest that this difference is due to the inability of agonist alone to induce a detectable outward movement of the cytoplasmic end of TM6.

Membrane Proteins Have Distinct Fast Internal Motion and Residual Conformational Entropy.

The internal motions of integral membrane proteins have largely eluded comprehensive experimental characterization. Here the fast side-chain dynamics of the α-helical sensory rhodopsin II and the ß-barrel outer membrane protein W have been investigated in lipid bilayers and detergent micelles by solution NMR relaxation techniques. Despite their differing topologies, both proteins have a similar distribution of methyl-bearing side-chain motion that is largely independent of membrane mimetic. The methyl-bearing side chains of both proteins are, on average, more dynamic in the ps-ns timescale than any soluble protein characterized to date. Accordingly, both proteins retain an extraordinary residual conformational entropy in the folded state, which provides a counterbalance to the absence of the hydrophobic effect. Furthermore, the high conformational entropy could greatly influence the thermodynamics underlying membrane-protein functions, including ligand binding, allostery, and signaling.

Understanding temporal and spatial variations of viral disease in the US: The need for a one-health-based data collection and analysis approach.

Viral diseases exhibit spatial and temporal variation, and there are many factors that can affect their occurrence. The identification of these factors is critical in the efforts to predict and lessen viral disease burden. Because viral infection is able to spread to humans from the environment, animals, and other humans, the One-Health framework can be used to investigate the critical pathways through which viruses are transported and transmitted. A holistic approach, incorporating publicly available clinical data for human, livestock, and wildlife disease occurrence, together with environmental data reported in federal and state databases such as parameters related to land use, environmental quality, and weather, can enhance the understanding of variations in disease patterns, leading to the design and implementation of surveillance systems. An example analysis approach is presented for Michigan, United States, which is a state with large urban centers as well as a sizeable rural and agricultural population. Analysis of publicly available data from 2017 indicates that gastrointestinal (GI) and influenza-associated illnesses in Michigan may have been related with agricultural land use to a higher extent than with developed land use during that year. Meanwhile, hepatitis A virus appears to be most closely related with developed land use in dense population areas. GI illnesses may be related to precipitation, and this relationship is strongest in the springtime, although GI illnesses are most common in the winter months. Integration of human-related clinical data, animal disease data, and environmental data can ultimately be used for prioritization of the most critical locations and times for viral outbreaks in both urban and rural environments.