A Cornflower Extract Containing N-Feruloylserotonin Reduces Inflammation in Human Skin by Neutralizing CCL17 and CCL22 and Inhibiting COX-2 and 5-LOX.

Thymus and Activation-Regulated Chemokine (TARC/CCL17) and Macrophage-Derived Chemokine (MDC/CCL22) are two key chemokines exerting their biological effect via binding and activating a common receptor CCR4, expressed at the surface of type 2 helper T (Th2) cells. By recruiting Th2 cells in the dermis, CCL17 and CCL22 promote the development of inflammation in atopic skin. The aim of this research was to develop a plant extract whose biological properties, when applied topically, could be beneficial for people with atopic-prone skin. The strategy which was followed consisted in identifying ligands able to neutralize the biological activity of CCL17 and CCL22. Thus, an in silico molecular modeling and a generic screening assay were developed to screen natural molecules binding and blocking these two chemokines. N-Feruloylserotonin was identified as a neutraligand of CCL22 in these experiments. A cornflower extract containing N-feruloylserotonin was selected for further in vitro tests: the gene expression modulation of inflammation biomarkers induced by CCL17 or CCL22 in the presence or absence of this extract was assessed in the HaCaT keratinocyte cell line. Additionally, the same cornflower extract in another vehicle was evaluated in parallel with N-feruloylserotonin for cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) enzymatic cellular inhibition. The cornflower extract was shown to neutralize the two chemokines in vitro, inhibited COX-2 and 5-LOX, and demonstrated anti-inflammatory activities due mainly to the presence of N-feruloylserotonin. Although these findings would need to be confirmed in an in vivo study, the in vitro studies lay the foundation to explain the benefits of the cornflower extract when applied topically to individuals with atopic-prone skin.

Controlling the Circadian Clock with High Temporal Resolution through Photodosing.

Circadian clocks, biological timekeepers that are present in almost every cell of our body, are complex systems whose disruption is connected to various diseases. Controlling cellular clock function with high temporal resolution in an inducible manner would yield an innovative approach for the circadian rhythm regulation. In the present study, we present structure-guided incorporation of photoremovable protecting groups into a circadian clock modifier, longdaysin, which inhibits casein kinase I (CKI). Using photodeprotection by UV or visible light (400 nm) as the external stimulus, we have achieved quantitative and light-inducible control over the CKI activity accompanied by an accurate regulation of circadian period in cultured human cells and mouse tissues, as well as in living zebrafish. This research paves the way for the application of photodosing in achieving precise temporal control over the biological timing and opens the door for chronophotopharmacology to deeper understand the circadian clock system.

In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations.

Acting during phase II metabolism, sulfotransferases (SULTs) serve detoxification by transforming a broad spectrum of compounds from pharmaceutical, nutritional, or environmental sources into more easily excretable metabolites. However, SULT activity has also been shown to promote formation of reactive metabolites that may have genotoxic effects. SULT subtype 1E1 (SULT1E1) was identified as a key player in estrogen homeostasis, which is involved in many physiological processes and the pathogenesis of breast and endometrial cancer. The development of an in silico prediction model for SULT1E1 ligands would therefore support the development of metabolically inert drugs and help to assess health risks related to hormonal imbalances. Here, we report on a novel approach to develop a model that enables prediction of substrates and inhibitors of SULT1E1. Molecular dynamics simulations were performed to investigate enzyme flexibility and sample protein conformations. Pharmacophores were developed that served as a cornerstone of the model, and machine learning techniques were applied for prediction refinement. The prediction model was used to screen the DrugBank (a database of experimental and approved drugs): 28% of the predicted hits were reported in literature as ligands of SULT1E1. From the remaining hits, a selection of nine molecules was subjected to biochemical assay validation and experimental results were in accordance with the in silico prediction of SULT1E1 inhibitors and substrates, thus affirming our prediction hypotheses.

Inhibitory potency of flavonoid derivatives on influenza virus neuraminidase.

The constant risk of emerging new influenza virus strains that are resistant to established inhibitors like oseltamivir leaves influenza neuraminidase (NA) a prominent target for drug design. The inhibitory activity of several flavonoid derivatives was experimentally tested in comparison to oseltamivir for the NA expressed by the seasonal influenza virus strains A/California/7/09 (A(H1N1)pdm09), A/Perth/16/09 (A(H3N2)), and B/Brisbane/60/08. IC50 values of polyphenols confirmed moderate inhibition in the µM range. Structurally, the amount and site of glycosylation of tested flavonoids have no significant influence on their inhibitory potency. In a pharmacophore-based docking approach the structure-activity relationship was evaluated. Molecular dynamics simulations revealed highly flexible parts of the enzyme and the contribution of salt bridges to the structural stability of NA. The findings of this study elucidate the impact of flavonoids on viral neuraminidase activity and the analysis of their modes of action provide valuable information about the mechanism of NA inhibition.

Quantification of endocannabinoids in biological systems by chromatography and mass spectrometry: a comprehensive review from an analytical and biological perspective.

The endocannabinoids anandamide (arachidonoyl ethanolamide, AEA) and 2-arachidonoyl glycerol (2AG) are physiologically occurring, biologically active compounds on CB(1) and CB(2) receptors with multiple physiological functions. AEA and 2AG have been identified and quantified in many mammalian biological fluids and tissues, such as human plasma, adipocytes, tissues and tissue microdialysates, at concentrations in the picomolar-to-nanomolar range under basal conditions. In this article, recently published chromatographic and mass spectrometric analytical methods, i.e., HPLC with fluorescence or ultraviolet detection, LC-MS, LC-MS/MS, GC-MS and GC-MS/MS, are reviewed and discussed, notably from the quantitative point of view. We focus on and emphasize the particular importance of blood sampling, sample storage and work-up including solvent and solid-phase extraction and derivatization procedures, matrix-effects, and stability of analytes. As 2AG spontaneously isomerizes to its CB(1)/CB(2) receptors biologically inactive 1-arachidonoyl glycerol (1AG) by acyl migration, this phenomenon and its particular importance for accurate quantification of 2AG are discussed in detail. Due to the electrical neutrality of AEA and 2AG their solvent extraction by toluene offers the least matrix-effect and minimum isomerization. LC-MS/MS is the most frequently used analytical technique for AEA and 2AG. At present, the utility of the GC-MS/MS methodology seems to be limited to AEA measurement in human plasma, bronchoalveolar liquid (BAL) and microdialysate samples. Despite great instrumental advances in the LC-MS/MS methodology, sampling and sample treatment remains one of the most crucial analytical steps in 2AG analysis. Extension of the LC-MS/MS methodology, for instance to microdialysate and BAL samples from clinical studies, is a big analytical challenge in endocannabinoid analysis in clinical settings. Currently available LC-MS/MS and GC-MS/MS methods should be useful to investigate the metabolism of AEA and 2AG beyond hydrolysis, i.e., by ß- and ω-oxidation pathways.

Stable isotope liquid chromatography-tandem mass spectrometry assay for fatty acid amide hydrolase activity.

Fatty acid amide hydrolase (FAAH) is the main enzyme responsible for the hydrolysis of the endocannabinoid anandamide (arachidonoyl ethanolamide, AEA) to arachidonic acid (AA) and ethanolamine (EA). Published FAAH activity assays mostly employ radiolabeled anandamide or synthetic fluorogenic substrates. We report a stable isotope liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for specific, sensitive, and high-throughput capable FAAH activity measurements. The assay uses AEA labeled with deuterium on the EA moiety (d4-AEA) as substrate and measures the specific reaction product tetradeutero-EA (d4-EA) and the internal standard ¹³C2-EA. Selected reaction monitoring of m/z 66→m/z 48 (d4-EA) and m/z 64→m/z 46 (¹³C2-EA) in the positive electrospray ionization mode after liquid chromatographic separation on a HILIC (hydrophilic interaction liquid chromatography) column is performed. The assay was developed and thoroughly validated using recombinant human FAAH (rhFAAH) and then was applied to human blood and dog liver samples. rhFAAH-catalyzed d4-AEA hydrolysis obeyed Michaelis-Menten kinetics (K(M)=12.3 µM, V(max)=27.6 nmol/min mg). Oleoyl oxazolopyridine (oloxa) was a potent, partial noncompetitive inhibitor of rhFAAH (IC50=24.3 nM). Substrate specificity of other fatty acid ethanolamides decreased with decreasing length, number of double bonds, and lipophilicity of the fatty acid skeleton. In human whole blood, we detected FAAH activity that was inhibited by oloxa.

Changes of blood endocannabinoids during anaesthesia: a special case for fatty acid amide hydrolase inhibition by propofol?

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: • Available data from animal studies suggest that the narcotic drug propofol interacts with the endocannabinoid system. Inhibition of enzymatic degradation of anandamide could explain some of the characteristics of propofol. Direct measurements have not been reported yet in humans. WHAT THIS STUDY ADDS: • Propofol does not change the time course of anandamide plasma concentrations during anaesthesia. Furthermore, propofol does not inhibit fatty acid amide hydrolase activity ex vivo or in vitro. Thus, specific characteristics of the narcotic drug propofol cannot be explained by peripheral inhibition of anandamide degradation in humans. AIMS: The aim of our study was to describe the time course of endocannabinoids during different anaesthesia protocols in more detail, and to challenge the hypothesis that propofol acts as a FAAH inhibitor. METHODS: Endocannabinoids were measured during the first hour of anaesthesia in 14 women and 14 men undergoing general anaesthesia with propofol and in 14 women and 14 men receiving thiopental/sevoflurane. We also incubated whole human blood samples ex vivo with propofol and the known FAAH inhibitor oloxa and determined FAAH enzyme kinetics. RESULTS: Plasma anandamide decreased similarly with propofol and thiopental/sevoflurane anaesthesia, and reached a nadir after 10 min. Areas under the curve for anandamide (mean and 95% CI) were 53.3 (47.4, 59.2) nmol l(-1) 60 min with propofol and 48.5 (43.1, 53.8) nmol l(-1) 60 min with thiopental/sevoflurane (P= NS). Anandamide and propofol plasma concentrations were not correlated at any time point. Ex vivo FAAH activity was not inhibited by propofol. Enzyme kinetics (mean ± SD) of recombinant human FAAH were K(m) = 16.9 ± 8.8 µmol l(-1) and V(max) = 44.6 ± 15.8 nmol mg(-1) min(-1) FAAH without, and K(m) = 16.6 ± 4.0 µmol l(-1) and V(max) = 44.0 ± 7.6 nmol mg( 1 ) min(-1) FAAH with 50 µmol l(-1) propofol (P= NS for both). CONCLUSIONS: Our findings challenge the idea that propofol anaesthesia and also propofol addiction are directly mediated by FAAH inhibition, but we cannot exclude other indirect actions on cannabinoid receptors.

Peripheral endocannabinoid microdialysis: in vitro characterization and proof-of-concept in human subjects.

In vivo endocannabinoid (EC) microdialysis has only seldom been performed, mostly in rodent brain tissue. Low solubility in aqueous media, adsorption to surfaces, and instability with co-present human serum albumin (HSA) are the major obstacles in EC microdialysis. The addition of hydroxypropyl-ß-cyclodextrine (HPCD) to the perfusion fluid has been previously described to facilitate lipid microdialysis, but the general biophysical properties of HPCD, especially with respect to peripheral EC microdialysis, have not been described before. We report on the characterization of EC microdialysis using an in vitro system using Ringer's solution with 10% HPCD as the perfusion fluid and with fatty acid-free HSA as the matrix fluid. The endocannabinoids anandamide (AEA) and 2-arachidonoyl glycerol (2AG) were measured using LC-MS/MS. AEA was stable in the perfusion and matrix fluids, whereas 2AG was only stable in the perfusion fluid. In the matrix fluid, 2AG underwent rapid isomerization to 1-arachidonoyl glycerol. A relative recovery of 3.5% for AEA was found with 10% HPCD in the perfusion fluid and a flow rate of 1 µL/min. For 2AG, a similar relative recovery of 3.5% was estimated. Since 2AG was found unstable in the matrix fluid, a reliable calculation of the relative recovery rates was not possible. Delivery and recovery experiments revealed unequal inward and outward EC transport across the microdialysis membrane. Contrary to usual microdialysis findings, we observed increasing recovery rates for AEA with increasing flow rates. Long equilibration times of several hours were necessary to obtain constant relative recovery rates. In a proof-of-concept study in humans, we collected AEA from subcutaneous abdominal adipose tissue employing the described methodology. Our study suggests that the microdialysis technique is not suitable for the exact quantification of tissue EC concentrations, but it allows for their rough estimation.

Dynamics at the serine loop underlie differential affinity of cryptochromes for CLOCK:BMAL1 to control circadian timing.

Mammalian circadian rhythms are generated by a transcription-based feedback loop in which CLOCK:BMAL1 drives transcription of its repressors (PER1/2, CRY1/2), which ultimately interact with CLOCK:BMAL1 to close the feedback loop with ~24 hr periodicity. Here we pinpoint a key difference between CRY1 and CRY2 that underlies their differential strengths as transcriptional repressors. Both cryptochromes bind the BMAL1 transactivation domain similarly to sequester it from coactivators and repress CLOCK:BMAL1 activity. However, we find that CRY1 is recruited with much higher affinity to the PAS domain core of CLOCK:BMAL1, allowing it to serve as a stronger repressor that lengthens circadian period. We discovered a dynamic serine-rich loop adjacent to the secondary pocket in the photolyase homology region (PHR) domain that regulates differential binding of cryptochromes to the PAS domain core of CLOCK:BMAL1. Notably, binding of the co-repressor PER2 remodels the serine loop of CRY2, making it more CRY1-like and enhancing its affinity for CLOCK:BMAL1.

Methylation deficiency disrupts biological rhythms from bacteria to humans.

The methyl cycle is a universal metabolic pathway providing methyl groups for the methylation of nuclei acids and proteins, regulating all aspects of cellular physiology. We have previously shown that methyl cycle inhibition in mammals strongly affects circadian rhythms. Since the methyl cycle and circadian clocks have evolved early during evolution and operate in organisms across the tree of life, we sought to determine whether the link between the two is also conserved. Here, we show that methyl cycle inhibition affects biological rhythms in species ranging from unicellular algae to humans, separated by more than 1 billion years of evolution. In contrast, the cyanobacterial clock is resistant to methyl cycle inhibition, although we demonstrate that methylations themselves regulate circadian rhythms in this organism. Mammalian cells with a rewired bacteria-like methyl cycle are protected, like cyanobacteria, from methyl cycle inhibition, providing interesting new possibilities for the treatment of methylation deficiencies.

Publisher Correction: Methylation deficiency disrupts biological rhythms from bacteria to humans.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Core Statistical Methods for Chemogenomic Data.

Chemogenomic modeling involves the construction of algorithmic or statistical models for prediction on new input data and is often based on noisy, multidescriptor data. A deeper understanding of such data through statistical analyses can underpin informed study design and increase information gain from prediction results and model performances. This chapter mediates basic statistical concepts and provides step-by-step instructions to explore and visualize chemogenomic data based on the statistics-centered, open-source software R. Directions on executing essential techniques such as the calculation of correlations, hypothesis testing, and clustering are provided.

Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families.

Computational models for predicting the activity of small molecules against targets are now routinely developed and used in academia and industry, partially due to public bioactivity databases. While models based on bigger datasets are the trend, recent studies such as chemogenomic active learning have shown that only a fraction of data is needed for effective models in many cases. In this article, the chemogenomic active learning method is discussed and used to newly analyze public databases containing nuclear hormone receptor and cytochrome P450 enzyme family bioactivity. In addition to existing results on kinases and G-protein coupled receptors, results here demonstrate the active learning methodology's effectiveness on extracting informative ligand-target pairs in sparse data scenarios. Experiments to assess the domain of the applicability demonstrate the influence of ligand profiles of similar targets within the family.

A femtomolar-range suicide germination stimulant for the parasitic plant Striga hermonthica.

The parasitic plant Striga hermonthica has been causing devastating damage to the crop production in Africa. Because Striga requires host-generated strigolactones to germinate, the identification of selective and potent strigolactone agonists could help control these noxious weeds. We developed a selective agonist, sphynolactone-7, a hybrid molecule originated from chemical screening, that contains two functional modules derived from a synthetic scaffold and a core component of strigolactones. Cooperative action of these modules in the activation of a high-affinity strigolactone receptor ShHTL7 allows sphynolactone-7 to provoke Striga germination with potency in the femtomolar range. We demonstrate that sphynolactone-7 is effective for reducing Striga parasitism without impinging on host strigolactone-related processes.

Balancing Inflammation: Computational Design of Small-Molecule Toll-like Receptor Modulators.

As essential proteins of the innate immune system, Toll-like receptors (TLRs) are involved in a plethora of physiological pathologies and their modulation is an ongoing quest in the field of drug discovery. Although TLRs recognize an unusually broad range of different molecular patterns, only a few small-molecule TLR modulators have been reported to date. Recent advances in crystallography and in silico techniques provide promising opportunities for TLR investigations and drug design. Here, three application areas for computational approaches are considered: (i) exploration of TLR structure and activation; (ii) understanding TLR modulation; and (iii) TLR drug discovery. By providing an overview on state-of-the-art computational methods, we highlight the value of molecular modeling in mechanistically understanding TLR function and guiding drug design.

More than a look into a crystal ball: protein structure elucidation guided by molecular dynamics simulations.

The 'form follows function' principle implies that a structural determination of protein structures is indispensable to understand proteins in their biological roles. However, experimental methods still show shortcomings in the description of the dynamic properties of proteins. Therefore, molecular dynamics (MD) simulations represent an essential tool for structural biology to investigate proteins as flexible and dynamic entities. Here, we will give an overview on the impact of MD simulations on structural investigations, including studies that aim at a prediction of protein-folding pathways, protein-assembly processes and the sampling of conformational space by computational means.

Structural Characteristics of the Allosteric Binding Site Represent a Key to Subtype Selective Modulators of Muscarinic Acetylcholine Receptors.

The high conservation of the orthosteric acetylcholine binding site of muscarinic receptors (MAChR) represents a considerable challenge in terms of designing subtype selective drugs. A promising approach to gain subtype selectivity is to include allosteric or dualsteric targeting that aims to address more specific extracellular binding sites. Despite recent advances in crystallography of G protein coupled receptors (GPCRs), structural information for all 5 MAChR subtypes is not yet available. Here we report structural models of the active and the inactive receptor state of all subtypes derived by homology modelling in combination with MD simulations. The comparison of the allosteric binding site unveils the characteristics for each subtype on a structural level and indicates anchor points for rational design of selective drugs. Additionally, homology models offer the possibility for a rational explanation of dualsteric subtype selectivity, as we show for the M2 over M5 selectivity of the dualsteric ligands Atr-6-naph and Iper-6-phth.

The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes.

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

Computational tools for in silico fragment-based drug design.

Fragment-based strategy in drug design involves the initial discovery of low-molecular mass molecules. Owing to their small-size, fragments are molecular tools to probe specific sub-pockets within a protein active site. Once their interaction within the enzyme cavity is clearly understood and experimentally validated, they represent a unique opportunity to design potent and efficient larger compounds. Computer-aided methods can essentially support the identification of suitable fragments. In this review, available tools for computational drug design are discussed in the frame of fragmentbased approaches. We analyze and review (i) available commercial fragment libraries with respect to their properties and size, (ii) computational methods for the construction of such a library, (iii) the different strategies and software packages for the selection of the fragments with predicted affinity to a given target, and (iv) tools for the in silico linkage of fragments into an actual high-affinity lead structure candidate.