Reduced interferon antagonism but similar drug sensitivity in Omicron variant compared to Delta variant SARS-CoV-2 isolates

The SARS-CoV-2 Omicron variant is currently causing a large number of infections in many countries. A number of antiviral agents are approved or in clinical testing for the treatment of COVID-19. Despite the high number of mutations in the Omicron variant, we here show that Omicron isolates display similar sensitivity to eight of the most important anti-SARS-CoV-2 drugs and drug candidates (including remdesivir, molnupiravir, and PF-07321332, the active compound in paxlovid), which is of timely relevance for the treatment of the increasing number of Omicron patients. Most importantly, we also found that the Omicron variant displays a reduced capability of antagonising the host cell interferon response. This provides a potential mechanistic explanation for the clinically observed reduced pathogenicity of Omicron variant viruses compared to Delta variant viruses.

High Dose Vardenafil Blunts the Hypertensive Effects of Toll-Like Receptor 3 Activation During Pregnancy

The maternal innate immune system plays a central role in preeclampsia (PE). Toll-like receptors (TLRs) are innate immune system receptors that recognize characteristics of extracellular endogenous ligands or pathogens, and their activation leads to a pro-inflammatory immune response. We and others have reported that excessive activation of TLRs causes pregnancy-dependent hypertension in animals and is associated with PE in women. Activation of TLR3 by poly I:C mimics the innate immune system activation by viruses that women who develop PE encounter during pregnancy. Vardenafil was approved by the FDA for erectile dysfunction but has recently been examined as a potential PE medication due to studies done with a similar drug, sildenafil. Preclinical as well as recent clinical studies demonstrate the potential effectiveness of sildenafil for PE. However, vardenafil is more potent than sildenafil and acts by increasing expression of placental growth factor in addition to increasing cGMP levels. We hypothesized that vardenafil will be more potent and effective in reducing the negative health effects in a mouse model of virus-induced PE. Pregnant mice were injected with the TLR3 agonist poly I:C (PPIC) on gestational days 13, 15, and 17. We treated PPIC mice with a high dose of vardenafil (50 mg human equivalent), a lower dose of vardenafil (20 mg human equivalent), or sildenafil (50 mg human equivalent) on gestational days 15–17 after hypertension was established. Daily i.p. injections of either high dose or low dose vardenafil significantly decreased systolic blood pressure in PPIC mice whereas sildenafil had no effect. There were no differences in body weight between the groups. The splenomegaly induced in PPIC mice was ameliorated in high dose vardenafil-treated PPIC mice, while low dose vardenafil-treated and sildenafil-treated PPIC mice still exhibited splenomegaly. High dose vardenafil-treated PPIC mice also did not exhibit any fetal demise characteristic of PPIC mice, while low dose vardenafil-treated and sildenafil-treated PPIC mice still had significantly increased incidences of fetal demise. These data support the notion that high dose vardenafil may be safe and effective at reducing blood pressure during a virus-associated hypertensive pregnancy.

NeuRank: learning to rank with neural networks for drug–target interaction prediction

Background Experimental verification of a drug discovery process is expensive and time-consuming. Therefore, recently, the demand to more efficiently and effectively identify drug–target interactions (DTIs) has intensified. Results We treat the prediction of DTIs as a ranking problem and propose a neural network architecture, NeuRank, to address it. Also, we assume that similar drug compounds are likely to interact with similar target proteins. Thus, in our model, we add drug and target similarities, which are very effective at improving the prediction of DTIs. Then, we develop NeuRank from a point-wise to a pair-wise, and further to list-wise model. Conclusion Finally, results from extensive experiments on five public data sets (DrugBank, Enzymes, Ion Channels, G-Protein-Coupled Receptors, and Nuclear Receptors) show that, in identifying DTIs, our models achieve better performance than other state-of-the-art methods.

Comparative Genomic Analyses Reveal Potential Factors Responsible for the ST6 Oxacillin-Resistant Staphylococcus lugdunensis Endemic in a Hospital

Oxacillin-resistant Staphylococcus lugdunensis (ORSL) is considered a life-threatening isolate in healthcare settings. Among ORSL clones, ST6-SCCmec II strains are associated with an endemic spread in hospitals. We analyzed the complete genome of ORSL CGMH-SL118, a representative strain. Results revealed that this strain contained three MGEs (two prophages and one plasmid) other than the SCCmec II element, which showed remarkable differences in genome organization compared to the reference strains from NCBI. Eight multidrug-resistant genes were identified. All but blaZ were carried by MGEs, such as the SCCmec II element [mecA, ant (9)-Ia, and ermA] and the prophage φSPbeta [aac (6')-aph (2'), aph (3')-III, and ant (6)-Ia], indicating that MGEs carrying multidrug-resistant genes may be important for ST6 strains. The prophage φSPbeta contains sasX gene, which was responsible for the pathogenesis of Staphylococcus aureus. A phage-mediated resistant island containing fusB (SlRIfusB-118) was found near φSPbeta, which was highly homologous to type III SeRIfusB-5907 of Staphylococcus epidermidis. In contrast to previous studies, over 20% of ST6 isolates showed a fusidic acid-resistant phenotype, suggesting that phage-mediated intraspecies transmission of resistant islands may become an important issue for ST6 strains. Sixty-eight clinical isolates of ST6 Staphylococcus lugdunensis (50 OSSL, oxacillin-sensitive S. lugdunensis, and 18 ORSL, including CGMH-SL118) collected from various types of specimens in the hospital were studied. Among these isolates in this study, ORSL showed similar drug-resistant genes and phenotypes as CGMH-SL118. The comparative genomic analyses highlight the contribution of MGEs in the development and dissemination of antimicrobial resistance in ST6 strains, suggesting that resistance determinants and virulence factors encoded by MGEs provide a survival advantage for successful colonization and spread in healthcare settings.

Development of nanomedicines and nano-similars: recent advances in regulatory landscape

Background: Nanopharmaceuticals serve as emerging forms of modern medicines which include nanomedicines, nanosimilars, nanotheranostics, nanodevices and many more. In last two decades, a large number of nano-based products has reached to the market and are being used clinically. Objectives: Unlike, conventional pharmaceutical products, nanopharmaceuticals behave differently both in vitro and in vivo and therefore, development of their generic versions needs special attention to replicate the similar drug release pattern leading to the identical therapeutic outcome. Further, drug-device combinations and 3D products are latest advancements in precise medicine delivery and development. Methods: The regulatory guidelines for these products are being framed at many stages by various regulatory agencies like USFDA/EMA and still are in infancy at the moment if we look at wider prospective and applications of nanomedicine. Results: For a formulation scientist, it is much needed that well-explained and directive guidelines should be available before leading to the development of the generic versions of these nano-cargos. Conclusion: Here, in this review, we have summarized the silent features of the regulatory perspectives related to the nanotechnology based next generation therapeutics and diagnostics.

Exploring Televend, a new hybrid darknet and messaging app market for prohibited drugs

Background and Aims. Digital technologies continue to facilitate drug trading. Televend’s backend is hosted on the darknet—like a cryptomarket, but purchases are made through the messaging app Telegram—like an app-mediated market. Here, we provide an initial characterisation of the Televend drug market. Design. Web scrapes and global cross-sectional web survey of drug buyers (Global Drug Survey; GDS).Setting. Televend and White House Market (WHM) (Jun–Jul 2021). Participants. 15,513 drug buyers (Dec 2020–Mar 2021)Measurements. For scrapes: Drug listing information including advertised product, vendor name, country of origin and destination. For survey: Modes of drug sourcing in the last 12 months, drug types sourced, demographic and drug use characteristics. Findings. Televend was 10% of the size of the largest drug cryptomarket (WHM) (4,515/44,830 listings per week). Televend listings increased slightly (4.9%), while WHM listing totals decreased slightly (-2.6%) over the same 8-week period. Both markets predominantly contained drug-related listings covering similar drug categories, with similar country of origin and destination. While around 1/10 reported sourcing from darknet markets (11.3%) or apps (9.0%), very few GDS drug buyers reported use of Televend (0.73%). Most Televend buyers (68/114) reported buying cannabis, then cocaine (20), MDMA (17), and LSD (12). The Televend and darknet groups had similar demographic and drug use characteristics; whereas compared with app purchasers, older age increased the odds of Televend use (aRRR=1.06, p<.001), identifying as a woman decreased the odds (aRRR=0.43, p=.004), while last-year use of a greater number of drug types (aRRR=1.20, p<.001) and less frequent drug use (aRRR=0.998, p=.032) increased the odds of Televend purchase. Conclusions. While smaller, Televend is not noticeably different in its drug offerings to its largest cryptomarket competitor, and at this time, our data suggest that Televend attracts a cohort more similar to darknet than to app drug buyers.

Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell's endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed "degradability", is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinases with similar drug-target engagement, suggesting yet unknown factors influencing degradability. We therefore developed a machine learning model, MAPD (Model-based Analysis of Protein Degradability), to predict degradability from protein features that encompass post-translational modifications, protein stability, protein expression and protein-protein interactions. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds (auPRC=0.759) and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By structural modeling, we found that E2-accessible ubiquitination sites, but not lysine residues in general, are particularly associated with kinase degradability. Finally, we extended MAPD predictions to the entire proteome to find 964 disease-causing proteins, including 278 cancer genes, that may be tractable to TPD drug development.

Mining chemical information in Swedish wastewaters for simultaneous assessment of population consumption, treatment efficiency and environmental discharge of illicit drugs

Consumption of illicit drugs poses health risks to the public and environment. Knowledge on their usage helps better implementations of intervention strategies to reduce drug-related harms in the society and also policies to limit their releases as emerging contaminants to recipient environments. This study aimed to investigate from the daily consumption to treatment efficiency and subsequent discharge of illicit drugs by the Swedish urban populations based on simultaneous collection and analysis of influent and effluent wastewater. Two different weekly monitoring campaigns showed similar drug prevalence in Stockholm and Uppsala, with amphetamine as the most popular drug. Almost all target drug residues were still measurable in effluent wastewater. High removal efficiencies (> 94%) were observed for amphetamine, cocaine and benzoylecgonine, whereas ketamine, 3,4-methylenedioxymethamphetamine (MDMA), mephedrone and methamphetamine were the least removed substances (< 64%), with the highest discharge observed for MDMA in both catchments (~ 3.0 g/day in Uppsala; ~ 18 g/day in Stockholm). Our study provides new insights into short-term changes in the use and related discharge of illicit drugs by urban populations. Such wastewater monitoring can provide useful information to public health, forensic and environmental authorities in planning future intervention and regulation policies.

Nifedipine, Niclosamide and Furosemid Release of A Biocompatible and Protective Hydrogel for Cancer Therapy

In this work, biocompatible and protective pure HEMA hydrogel structures and drug loaded HEMA hydrogel have been successfully synthesized. The hydrogel was prepared using HEMA, MBA, APS and TEMED. The structural and morphological characterization of pure hydrogel and drug-loaded hydrogels were characterized using Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM), respectively. The pH affinity, morphology, structure, drug release, swelling and cytotoxic effect of the resulting materials were studied in detail. Drug releases of drug-loaded hydrogel structures were measured at certain time intervals and recorded as cumulatively (%). In addition, cytotoxicity tests were performed by Alamar blue method on MCF-7, MIA PaCa-2 and HEK 293 cell lines of released drug molecules. This HEMA hydrogel was suggested to be materials of biological attention and of large pharmacological potential as support material in drug release of nifedipine, furosemide, niclosamide and similar drug molecules.

Development and Characterization of Stingless Bee Propolis Properties for the Development of Solid Lipid Nanoparticles for Loading Lipophilic Substances

Stingless bees are insects which are popularly bred by agriculturists in the eastern region of Thailand for the pollination of their orchards. The products from stingless bee breeding include bee honey and bee propolis. The objective of this experiment is to study the possibility of developing stingless bee propolis wax into solid lipid nanoparticles (SLN) by the comparison of five surfactants (Brij 721, Cremophor WO 7, Myrj 52, Poloxamer 188, and Tween 80). Each surfactant is used at three concentrations: 10%, 20%, and 30%. A master formula is selected according to the following: physical features, particle size, zeta potential, and entrapment. The results showed that Brij 721 and Myri 52 at 20% can be used in preparing SLN and have good preservation properties for vitamin E (size: 451.2 nm and 416.8 nm, zeta potential: - 24.0 and - 32.7; % EE: 92.32% and 92.00%, resp.). Therefore, they are further developed by adding the following drugs at low solubility: curcumin, ibuprofen, and astaxanthin. It is found that a formula using the surfactants Brij 721 and Myrj 52 at 20% have similar drug entrapment. The entrapment study involves curcumin 82%, ibuprofen 40%, and astaxanthin 67%. Moreover, the cytotoxicity test of blank solid lipid nanoparticle found no toxicty in fibroblast cell line (CRL-2522). Therefore, from this study, it is determined that stingless bee propolis wax has the potential to be developed to provide more efficient SLN in the future.