Dengue is the most prevalent arthropod-borne disease globally and affects approximately 2.5 billion people living in over 100 countries. The increasing geographic expansion of Aedes aegypti mosquitoes which transmit the virus has made dengue fever a global health concern. There are currently no approved antivirals available to treat dengue, and the only approved vaccine used in some countries is limited to seropositive patients. Treatment of dengue therefore remains largely supportive to date; hence research efforts are being intensified for the development of antivirals against dengue. The NS3 and NS5 nonstructural proteins have been the major targets for dengue antiviral development due to their indispensable enzymatic and biological functions in the viral replication process. NS5 is the largest and most conserved nonstructural protein encoded by flaviviruses including dengue. Its multifunctionality makes it an attractive target for antiviral development against dengue, but research efforts are hindered due to its limited structural characterization compared to the NS5 of other flaviviruses like the Zika virus. Increase in structural insights into the dengue NS5 protein will accelerate drug discovery efforts focused on NS5 as an antiviral target. In this review, we will give an overview of the current state of therapeutic development against dengue.

Many ligands directly target adenosine receptors (ARs). Here we review the effects of noncanonical AR drugs on adenosinergic signaling. Non-AR mechanisms include raising adenosine levels by inhibiting adenosine transport (e.g. ticagrelor, ethanol, cannabidiol), affecting intracellular metabolic pathways (e.g. methotrexate, nicotinamide riboside, salicylate, 5‐aminoimidazole‐4‐carboxamide riboside), or undetermined means (e.g. acupuncture). Yet other compounds bind ARs in addition to their canonical ‘on-target’ activity (e.g. mefloquine). The strength of experimental support for an adenosine-related role in a drug’s effects varies widely. AR knockout mice are the ‘gold standard’ method for investigating an AR role, but few drugs have been tested in these mice. Given the interest in AR modulation for treatment of cancer, CNS, immune, metabolic, cardiovascular, and musculoskeletal conditions, it is informative to consider AR and non-AR adenosinergic effects of approved drugs and conventional treatments.

Considering Cu(tda) chelate is a receptor for adenine and related 6-aminopurines, now we report the synthesis, molecular and crystal structures, thermal stability, spectral properties and DFT calculations on the [Cu(tda)(9heade)(H2O)]•2H2O (1). N7 is found to be the preferred donor atom of 9heade, that can favor the cooperation of a Cu-N7(9heade) bond and an (9heade)N6-H•••O(tda) interligand interaction. But unprecedentedly, the Cu(tda)-9heade molecular recognition in 1 is essentially featured the Cu-N1(9heade), without any N6-H•••O(carboxyl tda) interligand interaction. Nevertheless, being N1 the most basic donor for N9-substituted adenines, this Cu-N1 bond is now assisted by an O2-water mediated interaction (N6-H•••O2 and O2•••Cu weak contact). Also in the crystal packing, the O-H(ol) of 9heade interacts with its own adenine moiety by an O3-water mediated interaction (O(ol)-H•••O3 plus O3-H36•••π(adenine moiety). In turn these water-mediated interactions seems to be responsible to serious alterations on the physical properties of crystalline or grounded samples. Density functional theory calculations were used to evaluate the interactions energetically. Moreover, the quantum theory of atoms-in-molecules (QTAIM) in combination with the noncovalent interaction plot (NCIPlot) were used to analyze the interactions and rationalize the existence and relative importance of hydrogen bonding, chalcogen bonding and π-stacking interactions.

The central dogma of molecular biology dictates that, with only a few exceptions, information proceeds from DNA to protein through an RNA intermediate. Examining the enigmatic steps from prebiotic to biological chemistry, we take another road suggesting that primordial peptides acted as template for the self-assembly of the first nucleic acids polymers. Arguing in favour of a sort of archaic “reverse translation” from proteins to RNA, our basic premise is a Hadean Hearth where key biomolecules such as amino acids, polypeptides, purines, pyrimidines, nucleosides and nucleotides were available under different prebiotically plausible conditions, including meteorites delivery, shallow ponds and hydrothermal vents scenarios. Supporting a protein-first scenario alternative to the RNA world hypothesis, we propose the primeval occurrence of short peptides termed “selective amino acid- and nucleotide-matching oligopeptides” (henceforward SANMAOs) that noncovalently bind at the same time the polymerized amino acids and the single nucleotides dispersed in the prebiotic milieu. We describe the chemical features of this hypothetical oligopeptide, its biological plausibility and its virtues from an evolutionary perspective. We provide a theoretical example of SANMAO’s selective pairing between amino acids and nucleosides, simulating a poly-Glycine peptide that acts as a template to build a purinic chain corresponding to the glycine’s extant triplet codon GGG. Further, we discuss how SANMAO might have endorsed the formation of low-fidelity RNA’s polymerized strains, well before the appearance of the accurate genetic material’s transmission ensured by the current translation apparatus.

Nucleoside analogs are commonly used drugs for the treatment of cancer and viral infections. Nucleoside deoxyribosyltransferase (NDT) is one of the key enzymes required for the biosynthesis of deoxynucleotides. The feasibility of biochemical transformation processes is usually greatly dependent on the cost of biocatalysts. Therefore, immobilizing and reusing biocatalysts is an approach to be considered to bring biotransformations closer to industrial feasibility, since it not only allows enzymes to be reused but can also improve their stability under several reaction conditions. In this work, histidine tags have been successfully fused to a Nucleoside deoxyribosyltransferase from Lactobacillus reuteri (LrDNT), which has been produced in a bench-scale reactor using a facile araBAD promoter-based protein expression system in an industrial microorganism, the E. coli BL21(DE3) strain. The overexpressed LrNDT was bound to a nickel-chelating agarose affinity chromatography medium via a one-step purification and immobilization process with a 99% yield, retaining about 97% of its initial activity. The optimal conditions for the immobilized LrNDT maintain high enzyme activity within the range of 20-45°C and pH 6.0-7.5. Finally, the immobilized enzyme reactor (IMER) of LrNDT was applied for the continuous-flow biosynthesis of 2'-deoxyadenosine and retained 90% of its activity after 16 hours, providing a theoretical basis for the industrial production of nucleoside analogs.

Chronic hepatitis B virus (HBV) infection is the largest global cause of hepatocellular carcinoma (HCC). Current HBV treatment options include pegylated interferon-alpha and nucleos(t)ide analogues (NAs), which have been shown to be effective in reducing HBV DNA levels to become undetectable. However, literature has shown that some patients have persistent risk of developing HCC. The mechanism in which this occurs is not fully elucidated, however it has been discovered that HBV covalently closed circular DNA (cccDNA) integrates into critical HCC driver genes in hepatocytes upon initial infection and are not targets of current NA therapy. Some studies suggest that HBV undergoes compartmentalization in peripheral blood mononuclear cells that serve as a sanctuary for replication during antiviral therapy. The aim of this review is to expand on how patients with HBV may develop HCC despite years of HBV viral suppression and carry worse prognosis than treatment-naive HBV patients who develop HCC. Furthermore, HCC recurrence after initial surgical or locoregional treatment in this setting may cause carcinogenic cells to be-have more aggressively in the treatment experienced. Curative novel therapies targeting the life cycle of HBV, modulating the host immune response, and inhibiting HBV RNA translation are being investigated.

The vascular endothelium is key target for immune, and thrombotic responses that has to be controlled in successful xenotransplantation. Several genes were identified that if induced or overexpressed help to regulate the inflammatory response and preserve the transplanted organ function and metabolism. However, few studies addressed combined expression of such genes. The aim of this work was to evaluate in vivo the effects of the simultaneous expression of a three human genes in a mouse generated using the multi-cistronic F2A technology. Male 3-month-old mice that express human heme oxygenase 1 (hHO-1), ecto-5’-nucleotidase (hE5NT), and ecto-nucleoside triphosphate diphosphohydrolase 1 (hENTPD1) (Transgenic) were compared to wild-type FVB mice (Control). Background analysis include extracellular nucleotide catabolism enzymes profile on the aortic surface, blood nucleotide concentration and serum L-arginine metabolites. Furthermore, inflammatory stress induced by LPS in transgenic and control mice was used to characterize interleukin 6 (IL-6) and adhesion molecules endothelium permeabil-ity responses. Transgenic mice had significantly higher rates of extracellular adenosine triphosphate and adenosine monophosphate hydrolysis on the aortic surface in comparison to control. Increased levels of blood AMP and adenosine were also noticed in transgenics. Moreover, transgenic ani-mals demonstrated the decrease in serum monomethyl-L-arginine level and a higher L-arginine/ monomethyl-L-arginine ratio. Importantly, significantly decreased serum IL-6, and adhesion mol-ecule levels were observed in transgenic mice in comparison to control after LPS treatment. Fur-thermore, reduced endothelial permeability in the LPS-treated transgenic mice was noted as com-pared to LPS-treated control. The human enzymes (hHO-1, hE5NT, hENTPD1) simultaneously encoded in transgenic mice demonstrated benefits in sev-eral biochemical and functional aspects of endothelium. This is consistent in use of this approach in the context of xenotransplantation.

The effective treatment of human immunodeficiency virus (HIV), also known as acquired immunodeficiency syndrome (AIDS), has transformed a highly lethal disease into a chronic and manageable condition. However, better methods need to be developed for eliminating the virus from reservoirs, enhancing patient access and adherence to therapy, and improving treatment in the long term to reduce adverse effects. From the perspective of drug discovery, one promising strategy is the development of anti-HIV prodrugs. This approach aims to enhance the efficacy and safety of treatment, promoting the development of more appropriate and convenient systems for patients. In this review, we discussed the use of the prodrug approach for HIV antiviral agents and emphasized nucleoside reverse transcriptase inhibitors. We comprehensively described various strategies that are used to enhance factors such as water solubility, bioavailability, pharmacokinetic parameters, permeability across biological membranes, chemical stability, drug delivery to specific sites/organs, and tolerability. These strategies might help researchers conduct better studies in this field. We also reported successful examples from the primary therapeutic classes while discussing the advantages and limitations. In this review, we highlighted the key trends in the application of the prodrug approach for treating HIV/AIDS..

SARS-CoV-2 virulence is known to increase with lowering of environmental temperature and solar ultraviolet radiation; therefore, we have focused our real-world nationwide study concerning with COVID-19 trends and dynamics on the coldest seasons of the year in Italy, the Western country hardest hit at the onset of the pandemic, comparing the autumn-winter of 2020 (before mass vaccination but when the emergency machinery was fully operative in terms of tracing and swabs) with the autumn-winter of 2021 (after mass vaccination), and analyzing the mortality burden by age groups and life stages in the years 2019 (pre-COVID-19), 2020 (before mass vaccination) and 2021 (after mass vaccination). Methods: During the state of national health emergency, the Civil Defense Department released the aggregate data coming from the Higher Institute of Health, the Ministry of Health, the Italian Regions, and the Independent Provinces, to inform the population (58.85 million people) about the pandemic situation, daily. Among these data there were the number of contagions, performed swabs, hospitalizations in Intensive Care Units (ICU), non-ICU patients, and deaths. By means of a team effort, we have collected and elaborated all these data, comparing the COVID-19 pandemic in Italy during the autumn-winter of 2020 with the autumn-winter of 2021. Moreover, we have extracted from the database of the National Institute of Statistics the total number of annual deaths in Italy during the years 2019, 2020 and 2021, comparing them to each other in order to evaluate the mortality burden attributable to COVID-19. Results: From the autumn-winter of 2020 to the autumn-winter of 2021, the contagions increased by ≈285%, however against a ≈290% increase in the performed swabs; therefore, the mean positivity rate passed from 8.74% before mass vaccination to 8.59% after mass vaccination. The unprecedent vaccination campaign allowed a ≈251% abatement in COVID-19 deaths, and a reduction of ≈224% and ≈228% in daily ICU and non-ICU hospitalizations due to COVID-19, respectively. Regarding COVID-19 deaths, in 2020 there was a mortality excess of ≈14.3% quantifiable in 105,900 more deaths compared to 2019, the pre-COVID-19 year; 103,183 out of 105,900 deaths occurred in older adults (≥60 years), which is equivalent to ≈97.4%, while in adults over 50, the segment of population just below older adults, in 2020 there were 2807 more deaths than in 2019. Surprisingly, from the analysis of our data, it is emerged that under the age of 40 in the years 2019, 2020 and 2021 there were 7103, 6808 and 7165 deaths, respectively. This means that in subjects under 40 during 2020 there were 295 fewer deaths than in 2019, while during 2021 there were 357 more deaths than in 2020, equivalent to ≈5.2% more. Conclusions: COVID-19 is a potential life-threatening disease mainly in older adults, as they are the most vulnerable due to inherent immunosenescence and inflammaging. Extensive vaccination in this segment of population with up-to-date vaccines is the means to reduce deaths, hospitalizations, and ICU pressure in the public interest. In the event of future threats, a new mass vaccination campaign must not be implemented without taking into account the individual age; it should primarily be aimed at people over 60 and at patients of any age with immune deficits, and secondly at people over 50. COVID-19 vaccination shows a favorable benefit-risk balance in older adults, while this balance falls under the age of 40; this younger segment of population should be therefore exempt from any mandatory vaccination.

COVID-19 has been characterized as one of the deadliest respiratory diseases, and the emergence of SARS-CoV-2 caught the pharmaceutical industry and the drug development communities off guard. Identifying potential antiviral targets is of great concern, and one way to detect them is by analyzing metabolic changes in infected cells. In this study, we present a novel workflow to predict robust druggable targets against emerging RNA viruses using metabolic networks and information of the viral structure and its genome sequence. For this purpose, we implemented pymCADRE, a tool to create metabolic models using gene expression data, and used this to reconstruct a metabolic network of the human bronchial epithelial cells. We observed that pymCADRE reduces the computational time when flux variability analysis is employed for internal optimizations. Subsequently, we created a fully automated computational tool, named PREDICATE, which analyses one or more nucleotide sequences, introduces given amino acid mutations, and simulates in silico viral infections. Moreover, it predicts a set of host reactions, which, when constrained, inhibit the virus production while preserving the host’s optimal state. In the context of SARS-CoV-2, we applied this tool to our metabolic network of bronchial epithelial cells and identified enzymatic reactions with inhibitory effects. From the list of the reported targets, the most promising one was the Nucleoside Diphosphate Kinase, whose inhibitors have already been reported in the literature. Finally, we computationally tested the robustness of our targets in all currently known variants of concern, verifying the inhibitory effect of our target enzyme against SARS-CoV-2. Focusing on the metabolic fluxes of infected cells, we aim at applying our workflow and methods for rapid hypothesis-driven identification of potentially exploitable antivirals to efficiently prevent future pandemics concerning various viruses and host cell types.