New Drug Targets Research Articles

State-dependent inhibition of Nav1.8 channels by VX-150 and VX-548.

Nav1.8 channels are an attractive therapeutic target for pain because they are prominent in primary pain-sensing neurons with little expression in most other kinds of neurons. Recently, two Nav1.8-targeted compounds, VX-150 and VX-548, have shown efficacy in clinical trials for reducing pain. We examined the characteristics of Nav1.8 inhibition by these compounds. The active metabolite form of VX-150 (VX-150m) inhibited human Nav1.8 channels with an IC50 of 15 nM. VX-548 (suzetrigine) was even more potent (IC50 0.27 nM). Both VX-150m and VX-548 had the unusual property of "reverse use-dependence", whereby inhibition could be relieved by repetitive depolarizations, a property seen before with another Nav1.8 inhibitor, A-887826. The relief of VX-548 inhibition by large depolarizations occurred with a time constant of ~40 ms that was not concentration-dependent. Re-inhibition at negative voltages occurred with a rate that was nearly proportional to drug concentration, consistent with the idea that relief of inhibition reflects dissociation of drug from the channel and re-inhibition reflects re-binding. The relief of inhibition by depolarization suggests a remarkably strong and unusual state-dependence for both VX-150m and VX-548, with very weak binding to channels with fully activated voltage sensors despite very tight binding to channels with voltage sensors in the resting state. Significance Statement The Nav1.8 sodium channel is a current target for new drugs for pain. This work describes the potency, selectivity, and state-dependent characteristics of inhibition of Nav1.8 channels by VX-150 and VX-548, compounds that have recently shown efficacy for relief of pain in clinical trials but whose mechanism of interaction with channels has not been described. The results show that the compounds share an unusual property whereby inhibition is relieved by depolarization, demonstrating a state-dependence different than most sodium channel inhibitors.

Characterization of ACTN4 as a novel antiviral target against SARS-CoV-2

The various mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pose a substantial challenge in mitigating the viral infectivity. The identification of novel host factors influencing SARS-CoV-2 replication holds potential for discovering new targets for broad-spectrum antiviral drugs that can combat future viral mutations. In this study, potential host factors regulated by SARS-CoV-2 infection were screened through different high-throughput sequencing techniques and further identified in cells. Subsequent analysis and experiments showed that the reduction of m6A modification level on ACTN4 (Alpha-actinin-4) mRNA leads to a decrease in mRNA stability and translation efficiency, ultimately inhibiting ACTN4 expression. In addition, ACTN4 was demonstrated to target nsp12 for binding and characterized as a competitor for SARS-CoV-2 RNA and the RNA-dependent RNA polymerase complex, thereby impeding viral replication. Furthermore, two ACTN4 agonists, YS-49 and demethyl-coclaurine, were found to dose-dependently inhibit SARS-CoV-2 infection in both Huh7 cells and K18-hACE2 transgenic mice. Collectively, this study unveils the pivotal role of ACTN4 in SARS-CoV-2 infection, offering novel insights into the intricate interplay between the virus and host cells, and reveals two potential candidates for future anti-SARS-CoV-2 drug development.

Review and Current Perspectives on DNA Topoisomerase I and II Enzymes of Fungi as Study Models for the Development of New Antifungal Drugs.

Fungal infections represent a growing public health problem, mainly stemming from two phenomena. Firstly, certain diseases (e.g., AIDS and COVID-19) have emerged that weaken the immune system, leaving patients susceptible to opportunistic pathogens. Secondly, an increasing number of pathogenic fungi are developing multi-drug resistance. Consequently, there is a need for new antifungal drugs with novel therapeutic targets, such as type I and II DNA topoisomerase enzymes of fungal organisms. This contribution summarizes the available information in the literature on the biology, topology, structural characteristics, and genes of topoisomerase (Topo) I and II enzymes in humans, two other mammals, and 29 fungi (including Basidiomycetes and Ascomycetes). The evidence of these enzymes as alternative targets for antifungal therapy is presented, as is a broad spectrum of Topo I and II inhibitors. Research has revealed the genes responsible for encoding the Topo I and II enzymes of fungal organisms and the amino acid residues and nucleotide residues at the active sites of the enzymes that are involved in the binding mode of topoisomerase inhibitors. Such residues are highly conserved. According to molecular docking studies, antifungal Topo I and II inhibitors have good affinity for the active site of the respective enzymes. The evidence presented in the current review supports the proposal of the suitability of Topo I and II enzymes as molecular targets for new antifungal drugs, which may be used in the future in combined therapies for the treatment of infections caused by fungal organisms.

Unveiling Novel Drug Leads: Utilizing Molecular Docking Studies for Efficient Drug Discovery

The traditional drug discovery process is often time-consuming and expensive. This review explains the basics of a computer simulation technique called molecular docking. This technique is becoming a valuable tool in drug development because it can predict how small molecules interact with important biological molecules, especially proteins. In other words, it can virtually test how well different molecules might work as drugs. First, it helps find promising starting points for drugs by virtually testing large libraries of molecules. Secondly, it can identify new targets for existing drugs. Thirdly, docking simulations can even predict hoe new compounds might work. However, docking has limitations. This study dives into the world of molecular docking and its applications in cancer. It explores the latest advancements, limitations and advantages of this technique. The focus is on how various software and docking methods can be used to discover new targets for drugs, to breathe new life into existing ones and to design entirely new candidates. Overall, the study emphasizes the value of molecular docking in cancer study, highlighting its potential to improve treatment strategies and drug development.

Rhodiosin from Rhodiola crenulata effectively alleviate postprandial hyperglycemia by inhibiting both the activity and production of α‑glucosidase

BackgroundEffective control of postprandial blood glucose (PBG) level is essential for the prevention and treatment of diabetes and its complications. Several flavonoids have attracted much attention due to their significant PBG-lowering effects. However, there is still a certain gap in the in vivo hypoglycemic activity of most flavonoids compared to first-line drugs available on the market, and are still lack of the PBG-lowering effects of 8-hydroxyflavones and their structure–activity relationship. PurposeEvaluate hypoglycemic effects of 8-hydroxyflavones from Rhodiola crenulata in vitro and in vivo, especially comparatively analyze the relationship between hypoglycemic effects and flavonoid configuration and reveal the possible mechanism of 8-hydroxyflavones in lowering hyperglycemia. MethodsStarch, maltose, sucrose, and glucose tolerance tests in both diabetic and normal mice were used to evaluate and compare the hypoglycemic effects of 8-hydroxyflavones rhodiosin (RHS), rhodionin (RHN), and herbacetin (HBT). Molecular docking, enzyme kinetics, and immunofluorescence analysis were used to research the possible hypoglycemic mechanisms of 8-hydroxyflavones. ResultsRHS (5 and 10 mg/kg) could efficiently decrease PBG levels in both normal and diabetes mice. Moreover, RHS, RHN, and HBT all had significant PBG-lowering effects in transgenic diabetes mice, and the effects were equivalent to or stronger than acarbose. Further mechanism research indicated that 8-hydroxyflavones achieved PBG-lowering effects by inhibiting both the activity and production of glycosidase. Notably, we have innovatively discovered that inhibiting the expression of glycosidases rather than just their activities may be a new target for hypoglycemic drugs. ConclusionWe have firstly comprehensively and systematically clarified PBG-lowering effects of 8-hydroxyflavones from Rhodiola crenulata, and revealed their structure-activity relationships and hypoglycemic mechanisms. The study demonstrated that the substitution of 8-hydroxy groups in flavonoids could significantly enhance their hypoglycemic effects, which were equivalent to or stronger than commercially available drug acarbose. 8-Hydroxyflavones could be used as therapeutic or health drugs with significant potential to reduce postprandial hyperglycemia.

Evaluation of RNA Secondary Stem-Loop Structures in the UTRs of Mouse Hepatitis Virus as New Therapeutic Targets.

MHV-A59 is a beta-coronavirus that causes demyelinating encephalitis and hepatitis in mice. Recently, the mouse infection model of MHV-A59 has been used as an alternative animal infection model for SARS-CoV and SARS-CoV-2, aiding the development of new antiviral drugs. In this study, the MHV-A59 model was employed to investigate the potential of SARS-CoV-2 UTRs as new targets for antiviral drugs. Optimal targets within the MHV-A59 UTRs were identified using a shRNA and siRNA design tool, focusing on RNA secondary stem-loop (SL) structures in the UTRs. We then examined whether the designed RNAi constructs could inhibit MHV-A59 replication. In the 5'UTR, the stem-loop 1 (SL1) was identified as the most effective target, while in the 3'UTR, the minimal element for the initiation of negative-strand RNA synthesis (MIN) proved to be the most effective. Importantly, siRNAs targeting SL1 and MIN structures significantly reduced total RNA synthesis, negative-strand genomic RNA synthesis, subgenomic (sg) RNA synthesis, viral titer, and the plaque size of MHV-A59 compared to the control. Although not statistically significant, the combination of siSL1 and siMIN had a stronger effect on inhibiting MHV-A59 replication than either siRNA monotherapy. Interestingly, while the SL1 structure is present in both MHV and SARS-CoV-2, the MIN structure is unique to MHV. Thus, the SL1 of SARS-CoV-2 may represent a novel and promising target for RNAi-based antiviral drugs.

Targeting mutant p53 with arsenic trioxide: A preclinical study focusing on triple negative breast cancer

New treatments are urgently required for triple-negative breast cancer (TNBC). As TP53 is mutated in approximately 80% of TNBC, it is theoretically an attractive target for new drugs for this disease. Arsenic trioxide (ATO), which is used to treat promyelocytic leukaemia, was recently shown to reactivate mutant p53 and restore wild-type functionality. The aim of this study was to evaluate ATO as a potential new treatment for TNBC. Using a panel of 20 cell lines, we found that TNBC cell lines were more sensitive to ATO than non-TNBC cell lines (P = 0.045). Consistent with its ability to reactivate mutant p53, ATO was a more potent inhibitor of proliferation in cell lines with mutant TP53 than the wildtype TP53 (P = 0.027). Direct evidence of mutant p53 reactivation was the induction of multiple wild-type p53 canonical target genes such as CDKN1A, SLC7A11, BBC3, PMAIP1, SESN2, SRXN1 and TXNRD1. Our findings support the activation of mutant p53 by ATO and, furthermore, the possible repurposing of ATO to treat TP53-mutated TNBC.

Anti-HSV activity of nectin-1-derived peptides targeting HSV gD: an in-silico and in-vitro approach

Herpes simplex virus (HSV) infections affect a wide range of the global population. The emergence of resistance to the existing anti-HSV therapy highlights the necessity for an innovative strategy. The interaction of HSV gD with its main host receptor nectin-1 is a potential target for new antiviral drugs. The aim of this study was to develop a peptide derived from nectin-1 targeting HSV gD using the in-silico method and evaluate them for anti-HSV activity. Residues 59-133 of the Nectin-1 V-domain constitute the interaction interface with HSV gD. Bioinformatic tools viz., PEP-FOLD3, ClusPro 2.0, HawkDock and Desmond were used to model the peptide and confirm its binding specificity with HSV gD protein. The peptides with potential interactions were custom synthesized and anti-HSV activity was evaluated in vitro against HSV-1 and HSV-2 by CPE inhibition assay. Five peptide sequences were identified as exhibiting good interaction with HSV-gD proteins. Among them, peptide N1 (residues 76–90) offered maximum protection against HSV-1 (66.57%) and HSV-2 (71.12%) infections. Modification of the identified peptide through peptidomimetic approaches may further enhance the activity and stability of the identified peptide. Communicated by Ramaswamy H. Sarma

Revolutionizing Drug Discovery: Harnessing Machine Learning Algorithms

Drug discovery is a crucial element of biomedical research, with the goal of finding and creating new medical treatments for a variety of illnesses. Yet, the conventional process of finding new drugs is frequently impeded by its intrinsic difficulties, such as expensive expenses, long durations, and poor success rates in trials with patients. Recently, the incorporation of machine learning (ML) algorithms has become a revolutionary method to streamline and improve different phases of drug discovery. This summary offers a glimpse into the rapidly growing area of drug discovery using machine learning algorithms, emphasizing its potential to transform the process of developing treatments. The usual process of discovering drugs involves various stages such as identifying the target, finding lead compounds, conducting preclinical tests, undergoing clinical trials, and obtaining regulatory approval. All these phases require a lot of labor, time, and resources, leading to high attrition rates and limited success in turning potential compounds into approved therapies. Nevertheless, researchers can enhance and speed up crucial parts of the drug discovery process by using ML algorithms. ML algorithms use data to aid in drug discovery by utilizing computational models to examine large quantities of biological, chemical, and clinical data. These algorithms can learn from various types of data, such as genomic data, chemical structures, protein interactions, and clinical outcomes, to discover hidden patterns, find new targets for drugs, and forecast the effectiveness and safety of potential treatments. Moreover, machine learning algorithms allow for the investigation of intricate connections between molecular structures and biological effects, making it easier to create improved drug candidates with better effectiveness and specificity. Important uses of machine learning in pharmaceutical research involve finding and confirming targets, screening compounds and improving leads, repurposing drugs, and tailoring treatments for individuals. Commonly used for classification and regression tasks, supervised learning algorithms like support vector machines and random forests predict compound activity, toxicity, and pharmacokinetic properties. Clustering and dimensionality reduction techniques utilized in unsupervised learning algorithms help analyze vast datasets and discover new drug-target interactions. Advanced abilities for analyzing molecular structures, virtual screening, and designing new drugs are provided by deep learning models like convolutional neural networks and recurrent neural networks. Multiple case studies demonstrate how ML algorithms can significantly impact drug discovery. Collaboration among academia, industry, and research institutions has resulted in the creation of new ML-based methods for drug development, identifying targets, and categorizing patients. Nevertheless, there are challenges accompanying the widespread use of ML in drug discovery. In healthcare, it is crucial to address ethical considerations, regulatory hurdles, and data privacy concerns to ensure the responsible and ethical use of ML algorithms. The potential for transforming drug discovery and therapeutic development is immense with the incorporation of machine learning algorithms. Through utilizing data-driven methods, researchers can speed up the discovery of new potential drugs, enhance the effectiveness of treatments, and ultimately enhance the results for patients. Ongoing innovation, teamwork, and cross-disciplinary studies are crucial to fully leverage the potential of ML in revolutionizing drug discovery and precision medicine.

Components of the microenvironment of soft tissue sarcomas. Part I

Soft tissue sarcomas (STS) are a rare heterogeneous group of malignant neoplasms characterized by aggressive course and poor response to treatment. This determines the relevance of research aimed at studying the pathogenesis of STS. The tumor microenvironment consists of stromal, immune cells, blood, lymphatic vessels, and extracellular matrix. By now, it is known that STS is characterized by complex relationships between tumor cells and components of the microenvironment. Dynamic interactions between tumor cells and components of the microenvironment enhance adaptation to changing environmental conditions, which provides high aggressive potential of STS and resistance to antitumor therapy. Basic research aimed at investigating the role of microenvironmental components in STS carcinogenesis may serve as a key to the discovery of both new prognostic predictor biomarkers and targets for new antitumor drugs. This review article is devoted to the role and interaction of STS cells with components of the microenvironment.

Noradrenaline and adrenoreceptors regulate prostaglandin F2A formation in endometrium after experimentally-induced inf lammation in the pig

Abstract Endometritis is the most common pathology in animals. However, in the context of an inflamed endometrium, alterations occur in the production of prostaglandins (PG s) and the noradrenergic innervation of the uterus, although the precise relationship between noradrenaline (NA), adrenoreceptors (AR s), and the output of PG F2α remains unclear. To clarify this issue, the participation of α1-, α2- and β-AR s in NA-influenced PG F synthase (PG FS) and PG 9-ketoreductase/carbonyl reductase (CBR1) protein abundances in the porcine inflamed endometrium, and the secretion of PG F2α from the tissue were determined. E. coli suspension (E. coli group) or saline (CO N group) was injected into the uterine horns. After eight days, severe acute endometritis was diagnosed in the E. coli group. Endometrial explants were treated with NA and/or α1-, α2- and β-AR s antagonists. In the CO N and E. coli groups, NA increased endometrial PG FS and CBR1 protein abundances and PG F2α secretion, compared to the control values (obtained from an endometrium that had not undergone any in vitro treatment). In the E. coli group, NA-stimulated CBR1 protein abundance and PG F2α release were higher, while PG FS protein abundance was lower than in the CO N group. In the latter group, the antagonists of α1A-, α1D-, α2B- and α2C-AR s isoforms and β2- AR s subtype decreased NA-stimulated PG FS protein abundances, compared to NA action alone. In the E. coli group, this effect on PG FS abundances evoked α1D-, α2C-, β1- and β2-AR s antagonists with NA. Antagonists of α1B-, α2B-, β1- and β2-AR s in the CO N group and antagonists of α1B-, α1D-, α2A-, α2C-, β1- and β2-AR s in the E. coli group eliminated a rise in the NA-stimulated CBR1 abundance of protein versus the NA influence alone. In comparison to NA effect alone, α1D-, α2C- and β2-AR s antagonists with NA reduced PG F2α secretion in both the CON and E. coli groups. Such effect on PG F2α release was also exerted in the E. coli group by α1B-, α2A- and β1-AR s antagonists with NA. Summarizing, in the porcine inflamed endometrium, NA increases PG FS protein abundance via α1D-, α2C- and β(1, 2)-AR s, and CBR1 protein abundance and PG F2α release by α1(B, D)-, α2(A, C) and β(1, 2)-AR s. The obtained findings suggest that, in an indirect manner, NA may affect the PG F2α-regulated processes by influencing its production and secretion. The results could offer new targets for drugs to regulate inflammation and improve uterine and ovarian functions.

Antimanic-like effect of dipyridamole in the methylphenidate-induced hyperlocomotion.

Adenosinergic system has been implicated in the pathophysiology of bipolar disorder and drugs that affect adenosine neurotransmission have shown some efficacy as add-on therapy in manic patients. Thus, the aim of the present study was to screen adenosinergic drugs for antimanic-like effect in methylphenidate (MPH)-induced hyperlocomotion in mice. Male and female Swiss mice received a single allopurinol (50 and 200 mg/kg, ip), dipyridamole (20 mg/kg, ip), or inosine (50 mg/kg, ip) administration before an acute MPH challenge (5mg/kg, sc). In experiments with repeated treatment, male mice received a daily administration of allopurinol (25 and 50 mg/kg, ip), dipyridamole (20 mg/kg, ip), or inosine (50 mg/kg, ip) for 14 days. Finally, pretreatment with aminophylline (2mg/kg, sc), an unspecific adenosine receptor antagonist, was used to evaluate a putative adenosinergic mediation. Locomotor activity was measured in the automated activity chamber for 20 min. Acute and repeated dipyridamole reduced the increase in locomotor activity induced by MPH, while allopurinol and inosine had no effect. Aminophylline blocked the effect of dipyridamole in MPH-induced hyperlocomotion. The present results suggest that dipyridamole may have an antimanic-like effect through adenosine receptors and reinforce the proposal that the adenosine system may be an interesting target for new antimanic drugs.

FgGmtB Plays an Important Role in Growth, Reproduction, Virulence and Deoxynivalenol Biosynthesis of Fusarium graminearum.

GDP-mannose transporters (GMTs) have been implicated in the virulence of some important pathogenic fungi, and guanosine diphosphate (GDP) mannose transporters transport GDP-mannose from the cytosol to the Golgi lumen prior to mannosylation, where mannose attaches to the modified protein. GMTs could be potential targets for new antifungal drugs, as disruption of any step in GDP-mannose biosynthesis can affect fungal viability, growth, or virulence. To date, the GDP-mannose transporter has been extensively studied in yeast, but its biological function in fungi, particularly F. graminearum, is still unclear. In this experimental study, the role of the GDP-mannose transporter in F. graminearum was investigated by analysing the VRG4 gene. FgGmtA and FgGmtB were blastp-derived from their Scvrg4 protein sequences and proved to be their functional homologues. The mutant and complementary strains of FgGmtA, FgGmtB and FgGmtA&B genes were generated and used to evaluate the effect of the two GMTs genes on mycelial growth, asexual reproduction, sexual reproduction, cell wall sensitivity, glyphosate synthesis and drug susceptibility. Only in the FgGmtB and FgGmtA&B mutants was the rate of mycelial growth slowed, conidium production increased, sexual reproduction impaired, cell wall sensitivity increased, glycemic content decreased, and drug sensitivity reduced. The results of the pathogenicity assessment of GMTs showed that only FgGmtB affects the patogenicity of F. graminearum. At the same time, the effect of GMTs on the ability of rhinoceros to synthesise DON toxins was investigated and the results showed that the ability of ΔFgGmtB and ΔFgGmtA&B mutants to produce the DON toxin was significantly reduced, and the expression of toxin-related genes was also reduced.

Homeostatic status of thyroid hormones and brain water movement as determinant factors in biology of cerebral gliomas: a pilot study using a bioinformatics approach.

The expression and localization of the water channel transporters, aquaporins (AQPs), in the brain are substantially modified in gliomas during tumorigenesis, cell migration, edema formation, and resolution. We hypothesized that the molecular changes associated with AQP1 and AQP4 in the brain may potentially be anticancer therapeutic targets. To test this hypothesis, a bioinformatics analysis of publicly available data from international consortia was performed. We used RNA-seq as an experimental strategy and identified the number of differential AQP1 and AQP4 transcript expressions in glioma tissue compared to normal brain tissue. AQPs genes are overexpressed in patients with glioma. Among the glioma subtypes, AQP1 and AQP4 were overexpressed in astrocytoma (low-grade glioma) and classical (high-grade glioma). Overall survival analysis demonstrated that both AQP genes can be used as prognostic factors for patients with low-grade glioma. Additionally, we observed a correlation between the expression of genes involved in the tyrosine and thyroid hormone pathways and AQPs, namely: PNMT, ALDH1A3, AOC2, HGDATP1B1, ADCY5, PLCB4, ITPR1, ATP1A3, LRP2, HDAC1, MED24, MTOR, and ACTB1 (Spearman's coefficient = geq 0.20 and p-value = ≤ 0.05). Our findings indicate that the thyroid hormone pathways and AQPs 1 and 4 are potential targets for new anti-tumor drugs and therapeutic biomarkers for malignant gliomas.

Structural determination and kinetic analysis of the transketolase from Vibrio vulnificus reveal unexpected cooperative behavior.

Vibrio vulnificus (vv) is a multidrug-resistant human bacterial pathogen whose prevalence is expected to increase over the years. Transketolases (TK), transferases catalyzing two reactions of the nonoxidative branch of the pentose-phosphate pathway and therefore linked to several crucial metabolic pathways, are potential targets for new drugs against this pathogen. Here, the vvTK is crystallized and its structure is solved at 2.1 Å. A crown of 6 histidyl residues is observed in the active site and expected to participate in the thiamine pyrophosphate (cofactor) activation. Docking of fructose-6-phosphate and ferricyanide used in the activity assay, suggests that both substrates can bind vvTK simultaneously. This is confirmed by steady-state kinetics showing a sequential mechanism, on the contrary to the natural transferase reaction which follows a substituted mechanism. Inhibition by the I38-49 inhibitor (2-(4-ethoxyphenyl)-1-(pyrimidin-2-yl)-1H-pyrrolo[2,3-b]pyridine) reveals for the first time a cooperative behavior of a TK and docking experiments suggest a previously undescribed binding site at the interface between the pyrophosphate and pyridinium domains.

Exploring the Infectious Drug Target Glutathione S-Transferase in Plasmodium falciparum with the Inhibitory Potential of Azadirachta indica Phytocompounds

Background. Neem compounds are being studied for their potential as new and effective antimalarial drugs, and there is mounting evidence that they may help treat malaria. The PfGST enzyme is crucial to the malaria parasite’s survival, making it a desirable target for new antimalarial drugs, and the study aims to examine the bark region compounds as PfGST inhibitors. Methods. The structure of PfGST is examined for quality analysis, the active site is predicted based on a web server, and the bark region compounds are docked for their binding potential. Final molecules are identified for the absorption, distribution, metabolism, and excretion (ADME) analysis to confirm the possible future leads that target malaria. Results. This study reports that IMPHY000093, IMPHY001448, and IMPHY005310 can be potential inhibitors, showing strong binding potential in hydrogen bonds, scoring values, and ADME analysis. Results are confirmed by the possible re-docking poses by the docking method, and the binding score is used for the evaluations. Conclusion. Neem’s active ingredients have shown promise as a new class of antimalarial medications. Neem compounds may boost the efficacy of other antimalarial drugs and the host immune system by inhibiting GST, which is involved in the metabolism of the malaria parasite.

On the origin of the electronic and magnetic circular dichroism of naphthyl C-glycosides: Anomeric configuration

Aryl C-glycosides, in which the glycosidic bond is changed to a carbon–carbon bond, are an important family of biologically-active compounds. They often serve as secondary metabolites or exhibit antibiotic and cytostatic activities. Their stability to hydrolysis has made them attractive targets for new drugs. Their conformational behavior often strongly influences the resulting function. Their detailed structural and conformational description is thus highly desirable.This work studies the structure of three different naphthyl C-glycosides using UV–vis absorption as well as electronic and magnetic circular dichroism. It also describes their conformational preferences using a combination of molecular dynamics and DFT calculations. The reliability of these preferences has been verified by simulations of spectral properties and a comparison with their measured spectra. In particular, ECD spectroscopy has been shown to distinguish easily between α- and β-pseudoanomers of aryl C-glycosides. Computer simulations and spectral decomposition have revealed how the resulting ECD patterns of the naphthyl glycosides studied are influenced by different conformer populations. In conclusion, reliable ECD patterns cannot be calculated by separating the naphthyl rotation from other conformational motions. MCD patterns have been similar for all the naphthyl C-glycosides studied. No clear diagnostic features have been found for either the pseudoanomeric configuration or the preferred hydroxymethyl rotamer. Nevertheless, the work has demonstrated the potential of MCD for the study of aryl glycosides interacting with proteins.

Novel Insights into the Wattle and Daub Model of Entamoeba Cyst Wall Formation and the Importance of Actin Cytoskeleton.

The "Wattle and Daub" model of cyst wall formation in Entamoeba invadens has been used to explain encystment in Entamoeba histolytica, the causal agent of amoebiasis, and this process could be a potential target for new antiamoebic drugs. In this study, we studied the morphological stages of chitin wall formation in E. invadens in more detail using fluorescent chitin-binding dyes and the immunolocalization of cyst wall proteins. It was found that chitin deposition was mainly initiated on the cell surface at a specific point or at different points at the same time. The cystic wall grew outward and gradually covered the entire surface of the cyst over time, following the model of Wattle and Daub. The onset of chitin deposition was guided by the localization of chitin synthase 1 to the plasma membrane, occurring on the basis of the Jacob lectin in the cell membrane. During encystation, F-actin was reorganized into the cortical region within the early stages of encystation and remained intact until the completion of the chitin wall. The disruption of actin polymerization in the cortical region inhibited proper wall formation, producing wall-less cysts or cysts with defective chitin walls, indicating the importance of the cortical actin cytoskeleton for proper cyst wall formation.

Gut microbiome‐related metabolites in plasma are associated with general cognition

AbstractBackgroundIncreasing evidence suggests a role of metabolism in neurological disorders including Alzheimer’s disease (AD). The human metabolome is determined by genes and modifiable factors such as gut microbiota, diet, medication, and other lifestyle choices. We hypothesized that metabolites related to endophenotypes of brain health maybe derived or influenced by these modifiable factors. Identifying the determinants of metabolites associated with AD‐related endophenotypes may help to discover new targets for drugs and prevention.MethodWe profiled plasma samples of 1082 participants of the Rotterdam study for 1387 metabolites using a non‐targeted metabolomics platform. After preprocessing and quality control, plasma levels of 991 metabolites were available for analysis of 1068 cognitively normal participants. We assessed the role of metabolites in general cognition (G‐factor) and magnetic resonance imaging (MRI) markers using linear regression. Replication analysis was performed for general cognition in an independent dataset. To identify the source of brain health‐associated metabolites, we estimated the explained variance (EV) of metabolites by genes, gut‐microbiome, medication use, and clinical features using gradient boosting decision tree (GBDT). Multiple testing correction was performed based on the false discovery rate (FDR) by Benjamini Hochberg (FDR<0.05).ResultAmong the 991 analyzed metabolites, 14 showed significant associations with general cognition, 21 metabolites with total brain volume, and one with total white matter lesions. In the replication analysis of metabolites associated with cognition, 9 metabolites showed consistent association with G‐factor. While genetics explained more than 5% of the variance of all associated metabolites, for three cognition‐associated metabolites (ergothioneine, 3‐hydroxy‐2‐methylpyridine sulfate, 4‐vinylguaiacol sulfate), modifiable lifestyle factors, medication and microbiota additionally explained up to 15% of their variance, with lifestyle factors showing the largest influence. Among the metabolites associated with brain imaging phenotypes, clinical factors and medication explained more than 5% of the variance of four metabolites (3‐hydroxysebacate, 3‐hydroxybutyrylcarnitine, sphingomyelin (d18:2/24:2), unnamed metabolite).ConclusionOur study provides evidence for the association between circulating metabolites and cognition or brain imaging phenotypes in participants without cognitive impairment. The levels of these metabolites are influenced by genetics and in part by modifiable factors. Further, studies are warranted to elucidate the complex relationship between gut microbiota, diet, genome, metabolome, and cognition.

Anti-angiogenic Drug Resistance: Roles and Targeting of Non-coding RNAs (microRNAs and long non-coding RNAs).

Cancers with a high capability for angiogenesis are frequently regarded as being difficult to treat. Anti-angiogenesis drugs are considered the primary therapy for these types of cancers. Due to intrinsic or acquired anti-angiogenesis resistance, therapies result in moderate clinical consequences, despite some hopeful findings. The importance of non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long non-coding (lncRNAs), and circular RNAs (circRNAs) in drug resistance mechanisms in cancer treatment has been discovered in the previous decade. Anti-angiogenic drug resistance can be influenced by ncRNA dysregulation. Hence, ncRNAs are potential drug resistance targets for new anti-angiogenic drugs in the inhibition of angiogenesis in tumors. Furthermore, some ncRNAs can be employed as biomarkers for anti-angiogenic drug responses and can be used to monitor cancer non-invasively. Combination treatment approaches, combined with routine anti-angiogenesis and some drugs that target the ncRNAs causing resistance, can be potential ways to overcome anti-angiogenesis resistance. For the first time, we explain the mechanisms of anti-angiogenic drug resistance and the related miRNAs and lncRNAs and their signaling pathways in commonly used antiangiogenic drugs implicated in this review article. These ncRNAs could be suggestions for targeting and reducing anti-angiogenic drugs in the future.