Rational design of potent sialidase-based inhibitors of influenza virus replication

Natural autophagy activators: A promising strategy for combating photoaging

BACKGROUND

Photodamage to the skin stands out as one of the most widespread epidermal challenges globally. Prolonged exposure to sunlight containing ultraviolet radiation (UVR) instigates stress, thereby compromising the skin's functionality and culminating in photoaging. Recent investigations have shed light on the importance of autophagy in shielding the skin from photodamage. Despite the acknowledgment of numerous phytochemicals possessing photoprotective attributes, their potential to induce autophagy remains relatively unexplored.

PURPOSE

Diminished autophagy activity in photoaged skin underscores the potential benefits of restoring autophagy through natural compounds to enhance photoprotection. Consequently, this study aims to highlight the role of natural compounds in safeguarding against photodamage and to assess their potential to induce autophagy via an in-silico approach.

METHODS

A thorough search of the literature was done using several databases, including PUBMED, Science Direct, and Google Scholar, to gather relevant studies. Several keywords such as Phytochemical, Photoprotection, mTOR, Ultraviolet Radiation, Reactive oxygen species, Photoaging, and Autophagy were utilized to ensure thorough exploration. To assess the autophagy potential of phytochemicals through virtual screening, computational methodologies such as molecular docking were employed, utilizing tools like AutoDock Vina. Receptor preparation for docking was facilitated using MGLTools.

RESULTS

The initiation of structural and functional deterioration in the skin due to ultraviolet radiation (UVR) or sunlight-induced reactive oxygen species/reactive nitrogen species (ROS/RNS) involves the modulation of various pathways. Natural compounds like phenolics, flavonoids, flavones, and anthocyanins, among others, possess chromophores capable of absorbing light, thereby offering photoprotection by modulating these pathways. In our molecular docking study, these phytochemicals have shown binding affinity with mTOR, a negative regulator of autophagy, indicating their potential as autophagy modulators.

CONCLUSION

This integrated review underscores the photoprotective characteristics of natural compounds, while the in-silico analysis reveals their potential to modulate autophagy, which could significantly contribute to their anti-photoaging properties. The findings of this study hold promise for the advancement of cosmeceuticals and therapeutics containing natural compounds aimed at addressing photoaging and various skin-related diseases. By leveraging their dual benefits of photoprotection and autophagy modulation, these natural compounds offer a multifaceted approach to combatting skin aging and related conditions.

Bioisosteres at C9 of 2-Deoxy-2,3-didehydro-N-acetyl Neuraminic Acid Identify Selective Inhibitors of NEU3

Human neuraminidases play critical roles in many physiological and pathological processes. Humans have four isoenzymes of NEU, making selective inhibitors important tools to investigate the function of individual isoenzymes. A typical scaffold for NEU inhibitors is 2-deoxy-2,3-didehydro-N-acetylneuraminic acid (DANA) where C9 modifications can be critical for potency and selectivity against human NEU. To design improved DANA analogues, we generated a library of compounds with either a short alkyl chain or a biphenyl substituent linked to the C9 position through one of six amide bioisosteres. Bioisostere linkers included triazole, urea, thiourea, carbamate, thiocarbamate, and sulfonamide groups. Within this library, we identified a C9 biphenyl carbamate derivative (963) that showed high selectivity and potency for NEU3 (Ki = 0.12 ± 0.01 μM). In contrast, NEU1 and NEU4 isoenzymes preferred amide and triazole linkers, respectively. Finally, analogues with urea, sulfonamide, and amide linkers showed enhanced inhibitory activity for a bacterial NEU, NanI from Clostridium perfringens.

Glycopolymer with Sulfated Fucose and 6'-Sialyllactose as a Dual-Targeted Inhibitor on Resistant Influenza A Virus Strains

The frequent mutations of influenza A virus (IAV) have led to an urgent need for the development of innovative antiviral drugs. Glycopolymers offer significant advantages in biomedical applications owing to their biocompatibility and structural diversity. However, the primary challenge lies in the design and synthesis of well-defined glycopolymers to precisely control their biological functionalities. In this study, functional glycopolymers with sulfated fucose and 6'-sialyllactose were successfully synthesized through ring-opening metathesis polymerization and a postmodification strategy. The optimized heteropolymer exhibited simultaneous targeting of hemagglutinin and neuraminidase on the surface of IAV, as evidenced by MU-NANA assay and hemagglutination inhibition data. Antiviral experiments demonstrated that the glycopolymer displayed broad and efficient inhibitory activity against wild-type and mutant strains of H1N1 and H3N2 subtypes in vitro, thereby establishing its potential as a dual-targeted inhibitor for combating IAV resistance.

Bridging the gap between target-based and phenotypic-based drug discovery

INTRODUCTION

The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed.

AREAS COVERED

This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process.

EXPERT OPINION

The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.

Lomitapide repurposing for treatment of malignancies: A promising direction

The development of novel drugs from basic science to clinical practice requires several years, much effort, and cost. Drug repurposing can promote the utilization of clinical drugs in cancer therapy. Recent studies have shown the potential effects of lomitapide on treating malignancies, which is currently used for the treatment of familial hypercholesterolemia. We systematically review possible functions and mechanisms of lomitapide as an anti-tumor compound, regarding the aspects of apoptosis, autophagy, and metabolism of tumor cells, to support repurposing lomitapide for the clinical treatment of tumors.

Retracted and republished from: "The current state of research on influenza antiviral drug development: drugs in clinical trial and licensed drugs"

Influenza viruses (IVs) threaten global human health due to the high morbidity, infection, and mortality rates. Currently, the influenza drugs recommended by the Food and Drug Administration are oseltamivir, zanamivir, peramivir, and baloxavir marboxil. These recommended antivirals are currently effective for major subtypes of IVs as the compounds target conserved domains in neuraminidase or polymerase acidic (PA) protein. However, this trend may gradually change due to the selection of antiviral drugs and the natural evolution of IVs. Therefore, there is an urgent need to develop drugs related to the treatment of influenza to deal with the next pandemic. Here, we summarized the cutting-edge research in mechanism of action, inhibitory activity, and clinical efficacy of drugs that have been approved and drugs that are still in clinical trials for influenza treatment. We hope this review will provide up-to-date and comprehensive information on influenza antivirals and generate hypotheses for screens and development of new broad-spectrum influenza drugs in the near future.

The essential malaria protein PfCyRPA targets glycans to invade erythrocytes

Plasmodium falciparum is a human-adapted apicomplexan parasite that causes the most dangerous form of malaria. P. falciparum cysteine-rich protective antigen (PfCyRPA) is an invasion complex protein essential for erythrocyte invasion. The precise role of PfCyRPA in this process has not been resolved. Here, we show that PfCyRPA is a lectin targeting glycans terminating with α2-6-linked N-acetylneuraminic acid (Neu5Ac). PfCyRPA has a >50-fold binding preference for human, α2-6-linked Neu5Ac over non-human, α2-6-linked N-glycolylneuraminic acid. PfCyRPA lectin sites were predicted by molecular modeling and validated by mutagenesis studies. Transgenic parasite lines expressing endogenous PfCyRPA with single amino acid exchange mutants indicated that the lectin activity of PfCyRPA has an important role in parasite invasion. Blocking PfCyRPA lectin activity with small molecules or with lectin-site-specific monoclonal antibodies can inhibit blood-stage parasite multiplication. Therefore, targeting PfCyRPA lectin activity with drugs, immunotherapy, or a vaccine-primed immune response is a promising strategy to prevent and treat malaria.

Surface-Controlled Sialoside-Based Biosensing of Viral and Bacterial Neuraminidases

Neuraminidases (NA) are sialic acid-cleaving enzymes that are used by both bacteria and viruses. These enzymes have sialoside structure-related binding and cleaving preferences. Differentiating between these enzymes requires using a large array of hard-to-access sialosides. In this work, we used electrochemical impedimetric biosensing to differentiate among several pathogene-related NAs. We used a limited set of sialosides and tailored the surface properties. Various sialosides were grafted on two different surfaces with unique properties. Electrografting on glassy carbon electrodes provided low-density sialoside-functionalized surfaces with a hydrophobic submonolayer. A two-step assembly on gold electrodes provided a denser sialoside layer on a negatively charged submonolayer. The synthesis of each sialoside required dozens of laborious steps. Utilizing the unique protein-electrode interaction modes resulted in richer biodata without increasing the synthetic load. These principles allowed for profiling NAs and determining the efficacy of various antiviral inhibitors.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Theoretical models of staurosporine and analogs uncover detailed structural information in biological solution

Staurosporine and its analogs (STA-analogs) are indolocarbazoles (ICZs) compounds able to inhibit kinase proteins in a non-specific way, while present antimicrobial and cytostatic properties. The knowledge of molecular features associated to the complexation, including the ligand shape in solution and thermodynamics of complexation, is substantial to the development of new bioactive ICZs with improved therapeutic properties. In this context, the empirical approach of GROMOS force field is able to accurately reproduce condensed phase physicochemical properties of molecular systems after parameterization. Hence, through parameterization under GROMOS force field and molecular simulations, we assessed STA-analogs dynamics in aqueous solution, as well as its interaction with water to probe conformational and structural features involved in complexation to therapeutic targets. The coexistence of multiple conformers observed in simulations, and confirmed by metadynamics calculations, expanding the conformational space knowledge of these ligands with potential implications in understanding the ligand conformational selection during complexation. Also, changes in availability to H-bonding concerning the different substituents and water can reflect on effects at complexation free energy due to variation at the desolvation energetic costs. Based on these results, we expect the obtained structural data provide systemic framework for rational chemical modification of STA-analogs.

Automation of Drug Discovery through Cutting-edge In-silico Research in Pharmaceuticals: Challenges and Future Scope

The rapidity and high-throughput nature of in silico technologies make them advantageous for predicting the properties of a large array of substances. In silico approaches can be used for compounds intended for synthesis at the beginning of drug development when there is either no or very little compound available. In silico approaches can be used for impurities or degradation products. Quantifying drugs and related substances (RS) with pharmaceutical drug analysis (PDA) can also improve drug discovery (DD) by providing additional avenues to pursue. Potential future applications of PDA include combining it with other methods to make insilico predictions about drugs and RS. One possible outcome of this is a determination of the drug potential of nontoxic RS. ADME estimation, QSAR research, molecular docking, bioactivity prediction, and toxicity testing all involve impurity profiling. Before committing to DD, RS with minimal toxicity can be utilised in silico. The efficacy of molecular docking in getting a medication to market is still debated despite its refinement and improvement. Biomedical labs and pharmaceutical companies were hesitant to adopt molecular docking algorithms for drug screening despite their decades of development and improvement. Despite the widespread use of "force fields" to represent the energy exerted within and between molecules, it has been impossible to reliably predict or compute the binding affinities between proteins and potential binding medications.

Antiviral options and therapeutics against influenza: history, latest developments and future prospects

Drugs and chemotherapeutics have helped to manage devastating impacts of infectious diseases since the concept of 'magic bullet'. The World Health Organization estimates about 650,000 deaths due to respiratory diseases linked to seasonal influenza each year. Pandemic influenza, on the other hand, is the most feared health disaster and probably would have greater and immediate impact on humanity than climate change. While countermeasures, biosecurity and vaccination remain the most effective preventive strategies against this highly infectious and communicable disease, antivirals are nonetheless essential to mitigate clinical manifestations following infection and to reduce devastating complications and mortality. Continuous emergence of the novel strains of rapidly evolving influenza viruses, some of which are intractable, require new approaches towards influenza chemotherapeutics including optimization of existing anti-infectives and search for novel therapies. Effective management of influenza infections depend on the safety and efficacy of selected anti-infective in-vitro studies and their clinical applications. The outcomes of therapies are also dependent on understanding diversity in patient groups, co-morbidities, co-infections and combination therapies. In this extensive review, we have discussed the challenges of influenza epidemics and pandemics and discoursed the options for anti-viral chemotherapies for effective management of influenza virus infections.

Lignocellulosic biomass-based glycoconjugates for diverse biotechnological applications

Glycoconjugates are the ubiquitous components of mammalian cells, mainly synthesized by covalent bonds of carbohydrates to other biomolecules such as proteins and lipids, with a wide range of potential applications in novel vaccines, therapeutic peptides and antibodies (Ab). Considering the emerging developments in glycoscience, renewable production of glycoconjugates is of importance and lignocellulosic biomass (LCB) is a potential source of carbohydrates to produce synthetic glycoconjugates in a sustainable pathway. In this review, recent advances in glycobiology aiming on glycoconjugates production is presented together with the recent and cutting-edge advances in the therapeutic properties and application of glycoconjugates, including therapeutic glycoproteins, glycosaminoglycans (GAGs), and nutraceuticals, emphasizing the integral role of glycosylation in their function and efficacy. Special emphasis is given towards the potential exploration of carbon neutral feedstocks, in which LCB has an emerging role. Techniques for extraction and recovery of mono- and oligosaccharides from LCB are critically discussed and influence of the heterogeneous nature of the feedstocks and different methods for recovery of these sugars in the development of the customized glycoconjugates is explored. Although reports on the use of LCB for the production of glycoconjugates are scarce, this review sets clear that the potential of LCB as a source for the production of valuable glycoconjugates cannot be underestimated and encourages that future research should focus on refining the existing methodologies and exploring new approaches to fully realize the potential of LCB in glycoconjugate production.

The current state of research on influenza antiviral drug development: drugs in clinical trial and licensed drugs

Influenza viruses (IVs) threaten global human health due to the high morbidity, infection, and mortality rates. Currently, the influenza drugs recommended by the FDA are oseltamivir, zanamivir, peramivir, and baloxavir marboxil. Notably, owing to the high variability of IVs, no drug exists that can effectively treat all types and subtypes of IVs. Moreover, the current trend of drug resistance is likely to continue as the viral genome is constantly mutating. Therefore, there is an urgent need to develop drugs related to the treatment of influenza to deal with the next pandemic. Here, we summarized the cutting-edge research in mechanism of action, inhibitory activity, and clinical efficacy of drugs that have been approved and drugs that are still in clinical trials for influenza treatment. We hope this review will provide up-to-date and comprehensive information on influenza antivirals and generate hypotheses for screens and development of new broad-spectrum influenza drugs in the near future.

Management of influenza - updated Swedish guidelines for antiviral treatment

Influenza causes seasonal epidemics of respiratory infection in all parts of the world. Manifestations of influenza range from mild upper to severe lower respiratory tract infection. Medical risk groups are defined by factors predisposing for development of severe disease and are recommended annual vaccination as a protective measure. The previous Swedish treatment guidelines for influenza were issued in 2011, and a review of current evidence was deemed relevant. An important reason to revisit the guidelines is the recent approval of a novel drug for influenza treatment, baloxavir. Updated Swedish evidence-based guidelines created by a group of experts from various research areas, for the management of influenza are presented here. The work has been made in collaboration with the Public Health Agency of Sweden and the Swedish Reference Group for AntiViral therapy (RAV). The updated guidelines include guidelines for diagnostics, treatment and prophylaxis in special groups, including management of pregnant women and children with influenza. A new section about infection control has been added. Pharmacological treatment is covered in detail with regards to indication and dosage. Additionally, drug resistance and environmental aspects are discussed.

DeepGRID: Deep Learning Using GRID Descriptors for BBB Prediction

Deep Learning approaches are able to automatically extract relevant features from the input data and capture nonlinear relationships between the input and output. In this work, we present the GRID-derived AI (GrAId) descriptors, a simple modification to GRID MIFs that facilitate their use in combination with Convolutional Neural Networks (CNNs) to build Deep Learning models in a rotationally, conformationally, and alignment-independent approach we are calling DeepGRID. To our knowledge, this is the first time that GRID MIFs have been combined with CNNs in a Deep Learning approach. We applied the approach to build regression and classification models for blood-brain barrier permeation, an important factor when designing CNS drugs and conversely when designing to avoid off-target effects for CNS-inactive drugs. The VolSurf approach was one of the first to successfully model this property from three-dimensional structures, using descriptors derived from their GRID Molecular Interaction Fields (MIFs) in combination with PLS. We compared the DeepGRID models with others built using the hand-crafted VolSurf descriptors in combination with both PLS and Random Forest (RF). Both the DeepGRID and RF regression models performed best according to the % of compounds with a Geometric Mean Fold Error (GMFE) within 2-fold of the experimental data. Applying these regression models as classifiers, for the smaller 332 and 416 compound data sets all models performed well with ROC AUC values of ∼0.9 on the external test set. For the larger 2105 compound data set, the DeepGRID classifier performed the best with an AUC of 0.87 on the external test set with the RF model having an AUC of 0.84 and the original VolSurf lgBB model having an AUC of 0.83.

Rational multivalency construction enables bactericidal effect amplification and dynamic biomaterial design

The multivalency of bioligands in living systems brings inspiration for not only the discovery of biological mechanisms but also the design of extracellular matrix (ECM)-mimicking biomaterials. However, designing controllable multivalency construction strategies is still challenging. Herein, we synthesized a series of well-defined multivalent antimicrobial peptide polymers (mAMPs) by clicking ligand molecules onto polymers prepared by reversible addition-fragmentation chain transfer polymerization. The multiple cationic ligands in the mAMPs could enhance the local disturbance of the anionic phospholipid layer of the bacterial membrane through multivalent binding, leading to amplification of the bactericidal effect. In addition to multivalency-enhanced antibacterial activity, mAMPs also enable multivalency-assisted hydrogel fabrication with an ECM-like dynamic structure. The resultant hydrogel with self-healing and injectable properties could be successfully employed as an antibacterial biomaterial scaffold to treat infected skin wounds. The multivalency construction strategy presented in this work provides new ideas for the biomimetic design of highly active and dynamic biomaterials for tissue repair and regeneration.

Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology

Using high-throughput microfluidic enzyme kinetics (HT-MEK), we measured over 9,000 inhibition curves detailing impacts of 1,004 single-site mutations throughout the alkaline phosphatase PafA on binding affinity for two transition state analogs (TSAs), vanadate and tungstate. As predicted by catalytic models invoking transition state complementary, mutations to active site and active-site-contacting residues had highly similar impacts on catalysis and TSA binding. Unexpectedly, most mutations to more distal residues that reduced catalysis had little or no impact on TSA binding and many even increased tungstate affinity. These disparate effects can be accounted for by a model in which distal mutations alter the enzyme's conformational landscape, increasing the occupancy of microstates that are catalytically less effective but better able to accommodate larger transition state analogs. In support of this ensemble model, glycine substitutions (rather than valine) were more likely to increase tungstate affinity (but not more likely to impact catalysis), presumably due to increased conformational flexibility that allows previously disfavored microstates to increase in occupancy. These results indicate that residues throughout an enzyme provide specificity for the transition state and discriminate against analogs that are larger only by tenths of an Ångström. Thus, engineering enzymes that rival the most powerful natural enzymes will likely require consideration of distal residues that shape the enzyme's conformational landscape and fine-tune active-site residues. Biologically, the evolution of extensive communication between the active site and remote residues to aid catalysis may have provided the foundation for allostery to make it a highly evolvable trait.

6D-QSAR for predicting biological activity of human aldose reductase inhibitors using quasar receptor surface modeling

The application of QSAR analysis dates back a half-century ago and is currently continuously employed in any rational drug design. The multi-dimensional QSAR modeling can be a promising tool for researchers to develop reliable predictive QSAR models for designing novel compounds. In the present work, we studied inhibitors of human aldose reductase (AR) to generate multi-dimensional QSAR models using 3D- and 6D-QSAR methods. For this purpose, Pentacle and Quasar's programs were used to produce the QSAR models using corresponding dissociation constant (K_d) values. By inspecting the performance metrics of the generated models, we achieved similar results with comparable internal validation statistics. However, considering the externally validated values, 6D-QSAR models provide significantly better prediction of endpoint values. The obtained results suggest that the higher the dimension of the QSAR model, the higher the performance of the generated model. However, more studies are required to verify these outcomes.

Sialidase facilitates Porphyromonas gingivalis immune evasion by reducing M1 polarization, antigen presentation, and phagocytosis of infected macrophages

Background

Porphyromonas gingivalis (P. gingivalis), a major pathogen of periodontitis, can evade host immune defenses. Previously, we found that P. gingivalis W83 sialidase gene mutant strain (ΔPG0352) was more easily cleared by macrophages. The aims of this study were to investigate the effects of sialidase in P. gingivalis on the polarization, antigen presentation, and phagocytosis of infected macrophages and to clarify the mechanism of P. gingivalis immune evasion.

Methods

Human monocytes U937 were differentiated to macrophages and infected with P. gingivalis W83, ΔPG0352, comΔPG0352, and Escherichia coli (E. coli). The phagocytosis of macrophages was observed by transmission electron microscopy and flow cytometry. ELISA or Griess reaction were used to examine the levels of interleukin-12 (IL-12), inducible nitric oxide synthase (iNOS) and interleukin-10 (IL-10), and the expressions of CD68, CD80 and CD206 were determined by flow cytometry. The expression of major histocompatibility complex-II (MHC-II) was detected by immunofluorescence. A rat periodontitis model was established to determine the M1 and M2 polarization of macrophages.

Results

Compare with P. gingivalis W83, ΔPG0352 increased the levels of IL-12, iNOS, CD80, and MHC-II and inhibited the levels of IL-10 and CD206. Macrophages phagocytosed 75.4% of ΔPG0352 and 59.5% of P. gingivalis W83. In the rat periodontitis model, the levels of M1 and M2 macrophages in P. gingivalis W83 group were both higher than those in ΔPG0352 group, while the ratio of M1/M2 was higher in the ΔPG0352 group. Alveolar bone absorption was lower in ΔPG0352 group.

Conclusion

Sialidase facilitates P. gingivalis immune evasion by reducing M1 polarization, antigen presentation, and phagocytosis of infected macrophages.

WaterKit: Thermodynamic Profiling of Protein Hydration Sites

Water desolvation is one of the key components of the free energy of binding of small molecules to their receptors. Thus, understanding the energetic balance of solvation and desolvation resulting from individual water molecules can be crucial when estimating ligand binding, especially when evaluating different molecules and poses as done in High-Throughput Virtual Screening (HTVS). Over the most recent decades, several methods were developed to tackle this problem, ranging from fast approximate methods (usually empirical functions using either discrete atom-atom pairwise interactions or continuum solvent models) to more computationally expensive and accurate ones, mostly based on Molecular Dynamics (MD) simulations, such as Grid Inhomogeneous Solvation Theory (GIST) or Double Decoupling. On one hand, MD-based methods are prohibitive to use in HTVS to estimate the role of waters on the fly for each ligand. On the other hand, fast and approximate methods show an unsatisfactory level of accuracy, with low agreement with results obtained with the more expensive methods. Here we introduce WaterKit, a new grid-based sampling method with explicit water molecules to calculate thermodynamic properties using the GIST method. Our results show that the discrete placement of water molecules is successful in reproducing the position of crystallographic waters with very high accuracy, as well as providing thermodynamic estimates with accuracy comparable to more expensive MD simulations. Unlike these methods, WaterKit can be used to analyze specific regions on the protein surface, (such as the binding site of a receptor), without having to hydrate and simulate the whole receptor structure. The results show the feasibility of a general and fast method to compute thermodynamic properties of water molecules, making it well-suited to be integrated in high-throughput pipelines such as molecular docking.

Real-time monitoring of enzyme-catalyzed phosphoribosylation of anti-influenza prodrug favipiravir by time-lapse nuclear magnetic resonance spectroscopy

Favipiravir (brand name Avigan), a widely known anti-influenza prodrug, is metabolized by endogenous enzymes of host cells to generate the active form, which exerts inhibition of viral RNA-dependent RNA polymerase activity; first, favipiravir is converted to its phosphoribosylated form, favipiravir-ribofuranosyl-5'-monophosphate (favipiravir-RMP), by hypoxanthine-guanine phosphoribosyltransferase (HGPRT). Because this phosphoribosylation reaction is the rate-determining step in the generation of the active metabolite, quantitative and real-time monitoring of the HGPRT-catalyzed reaction is essential to understanding the pharmacokinetics of favipiravir. However, assay methods enabling such monitoring have not been established. ¹⁹ F- or ³¹ P-based nuclear magnetic resonance (NMR) are powerful techniques for observation of intermolecular interactions, chemical reactions, and metabolism of molecules of interest, given that NMR signals of the heteronuclei sensitively reflect changes in the chemical environment of these moieties. Here, we demonstrated direct, sensitive, target-selective, nondestructive, and real-time observation of HGPRT-catalyzed conversion of favipiravir to favipiravir-RMP by performing time-lapse ¹⁹ F-NMR monitoring of the fluorine atom of favipiravir. In addition, we showed that ³¹ P-NMR can be used for real-time observation of the identical reaction by monitoring phosphorus atoms of the phosphoribosyl group of favipiravir-RMP and of the pyrophosphate product of that reaction. Furthermore, we demonstrated that NMR approaches permit the determination of general parameters of enzymatic activity such as V_max and K_m . This method not only can be widely employed in enzyme assays, but also may be of use in the screening and development of new favipiravir-analog antiviral prodrugs that can be phosphoribosylated more efficiently by HGPRT, which would increase the intracellular concentration of the drug's active form. The techniques demonstrated in this study would allow more detailed investigation of the pharmacokinetics of fluorinated drugs, and might significantly contribute to opening new avenues for widespread pharmaceutical studies.

Antiviral Approaches against Influenza Virus

Preventing and controlling influenza virus infection remains a global public health challenge, as it causes seasonal epidemics to unexpected pandemics. These infections are responsible for high morbidity, mortality, and substantial economic impact. Vaccines are the prophylaxis mainstay in the fight against influenza. However, vaccination fails to confer complete protection due to inadequate vaccination coverages, vaccine shortages, and mismatches with circulating strains. Antivirals represent an important prophylactic and therapeutic measure to reduce influenza-associated morbidity and mortality, particularly in high-risk populations. Here, we review current FDA-approved influenza antivirals with their mechanisms of action, and different viral- and host-directed influenza antiviral approaches, including immunomodulatory interventions in clinical development. Furthermore, we also illustrate the potential utility of machine learning in developing next-generation antivirals against influenza.

Biocatalysis versus Molecular Recognition in Sialoside-Selective Neuraminidase Biosensing

Sialic acid recognition and hydrolysis are essential parts of cellular function and pathogen infectivity. Neuraminidases are enzymes that detach sialic acid from sialosides, and their inhibition is a prime target for viral infection treatment. The connectivity and type of sialic acid influence the recognition and hydrolysis activity of the many different neuraminidases. The common strategies to evaluate neuraminidase activity, recognition, and inhibition rely on extensive labeling and require a large amount of sialylated glycans. The above limitations make the effort of finding viral inhibitors extremely difficult. We used synthetic sialylated glycans and developed a label-free electrochemical method to show that sialoside structural features lead to selective neuraminidase biosensing. We compared Neu5Ac to Neu5Gc sialosides to evaluate the organism-dependent neuraminidase selectivity-sensitivity relationship. We demonstrated that the type of surface and the glycan monolayer density direct the response to either binding or enzymatic activity. We proved that while the hydrophobic glassy carbon surface increases the interaction with the enzyme hydrophobic interface, the negatively charged interface of the lipoic acid monolayer on gold repels the protein and enables biocatalysis. We showed that the sialoside monolayers can serve as tools to evaluate the inhibition of neuraminidases both by biocatalysis and molecular recognition.

Exploring cooperative molecular contacts using a PostgreSQL database system

Cooperative molecular contacts play an important role in protein structure and ligand binding. Here, we constructed a PostgreSQL database that stores structural information in the form of atomic environments and allows flexible mining of molecular contacts. Taking the Ser-His-Asp/Glu catalytic triad as a first test case, we demonstrate that the presence of a carboxylate oxygen atom in the vicinity of a His is associated with shorter Ser-OH..N-His bond in the PDB30 subset. We prospectively mine catalytic triads in unannotated proteins, suggesting catalytic functions for unannotated proteins. As a second test case, we demonstrate that this database system can include ligand atoms, represented by Sybyl atom types, by evaluating the proportion of counter-ions for ligand carboxylate oxygens.

Influenza Treatment: Limitations of Antiviral Therapy and Advantages of Drug Combination Therapy

Influenza infection is serious and debilitating for humans and animals. The influenza virus undergoes incessant mutation, segment recombination, and genome reassortment. As a result, new epidemics and pandemics are expected to emerge, making the elimination challenging of the disease. Antiviral therapy has been used for the treatment of influenza since the development of amantadine in the 1960s; however, its use is hampered by the emergence of novel strains and the development of drug resistance. Thus, combinational therapy with two or more antivirals or immunomodulators with different modes of action is the optimal strategy for the effective treatment of influenza infection. In this review, we describe current options for combination therapy, their performance, and constraints imposed by resistance, calling attention to the advantages of combination therapy against severe influenza infections. We also discuss the challenges of influenza therapy and the limitations of approved antiviral drugs.

Water Networks in Complexes between Proteins and FDA-Approved Drugs

Water molecules at protein-ligand interfaces are often of significant pharmaceutical interest, owing in part to the entropy which can be released upon the displacement of an ordered water by a therapeutic compound. Protein structures may not, however, completely resolve all critical bound water molecules, or there may be no experimental data available. As such, predicting the location of water molecules in the absence of a crystal structure is important in the context of rational drug design. Grand canonical Monte Carlo (GCMC) is a computational technique that is gaining popularity for the simulation of buried water sites. In this work, we assess the ability of GCMC to accurately predict water binding locations, using a dataset that we have curated, containing 108 unique structures of complexes between proteins and Food and Drug Administration (FDA)-approved small-molecule drugs. We show that GCMC correctly predicts 81.4% of nonbulk crystallographic water sites to within 1.4 Å. However, our analysis demonstrates that the reported performance of water prediction methods is highly sensitive to the way in which the performance is measured. We also find that crystallographic water sites with more protein/ligand hydrogen bonds and stronger electron density are more reliably predicted by GCMC. An analysis of water networks revealed that more than half of the structures contain at least one ligand-contacting water network. In these cases, displacement of a water site by a ligand modification might yield unexpected results if the larger network is destabilized. Cooperative effects between waters should therefore be explicitly considered in structure-based drug design.

Screening and identification of 3-aryl-quinolin-2-one derivatives as antiviral agents against influenza A

Quinolin-2-one represents an important and valuable chemical motif that possesses a wide variety of biological activities; however, the anti-influenza activities of quinolin-2-one-containing compounds were rarely reported. Herein, we describe the screening and identification of 3-aryl-quinolin-2-one derivatives as a novel class of antiviral agents. The 3-aryl-quinolinone derivatives were synthesized via an efficient copper-catalyzed reaction cascade that we previously developed. Using this synthetic method, preliminary structure-activity relationships of this scaffold against the influenza A virus infection were systematically explored. The most potent compound 34 displayed IC₅₀ values of 2.14 and 4.88 μM against the replication of H3N2 (A/HK/8/68) and H1N1 (A/WSN/33) strains, respectively, without apparent cytotoxicity on MDCK cells. We further demonstrated that 27 and 34 potently inhibited the plaque formation of the IAV, rendering this scaffold attractive for pursuing novel anti-influenza agents.

N1 neuraminidase of H5N1 avian influenza A virus complexed with sialic acid and zanamivir - A study by molecular docking and molecular dynamics simulation

Development of antiviral drugs is an urgent need to control and prevent the presently circulating H5N1 avian influenza virus which is affects the human respiratory tract. The complex crystal structure of N1-N-acetylneuranamic acid (sialic acid, SIA) is not available as complex and hence SIA and zanamivir (ZMR) are docked into the binding site of N1 neuraminidase. Based on the analysis, the initial complex structures have been simulated for 120 ns to get insight into the binding modes and interaction between protein-ligand complex systems. NAMD pair interaction energy and MM-PBSA binding free energy are calculated and show that there are two possible binding modes (BM1 and BM2) for N1-SIA and a single binding mode (BM1) for and N1-ZMR complex structures respectively. BM1 of N1-SIA is the most preferred binding mode. On contrary to the currently available drugs in which the chair conformation is distorted, in both the binding modes of N1-SIA, the binding pocket of N1 neuraminidase is able to accommodate SIA in ²C₅ chair conformation which is the preferred conformation of SIA in solution state. In N1-ZMR complex, ZMR is bind in a distorted chair conformation. The neuraminidase binding pocket is also able to accommodate galactose of SIAα(2→3)GAL and SIAα(2→6)GAL. RMSD, RMSF and hydrogen bonding analyses have been carried out to identify the conformational flexibility and structural stability of each complex system. All the analyses show that SIA can be used as an inhibitor for N1 neuraminidase of H5N1 influenza viral infection. Communicated by Ramaswamy H. Sarma.

Screening and characterization of inhibitory vNAR targeting nanodisc-assembled influenza M2 proteins

Influenza A virus poses a constant challenge to human health. The highly conserved influenza matrix-2 (M2) protein is an attractive target for the development of a universal antibody-based drug. However, screening using antigens with subphysiological conformation in a nonmembrane environment significantly reduces the generation of efficient antibodies. Here, M2(1-46) was incorporated into nanodiscs (M2-nanodiscs) with M2 in a membrane-embedded tetrameric conformation, closely resembling its natural physiological state in the influenza viral envelope. M2-nanodisc generation, an antigen, was followed by Chiloscyllium plagiosum immunization. The functional vNARs were selected by phage display panning strategy from the shark immune library. One of the isolated vNARs, AM2H10, could specifically bind to tetrameric M2 instead of monomeric M2e (the ectodomain of M2 protein). Furthermore, AM2H10 blocked ion influx through amantadine-sensitive and resistant M2 channels. Our findings indicated the possibility of developing functional shark nanobodies against various influenza viruses by targeting the M2 protein.

Emerging antiviral therapies and drugs for the treatment of influenza

INTRODUCTION

Both vaccines and antiviral drugs represent the mainstay for preventing and treating influenza. However, approved M2 ion channel inhibitors, neuraminidase inhibitors, polymerase inhibitors, and various vaccines cannot meet therapeutic needs because of viral resistance. Thus, the discovery of new targets for the virus or host and the development of more effective inhibitors are essential to protect humans from the influenza virus.

AREAS COVERED

This review summarizes the latest progress in vaccines and antiviral drug research to prevent and treat influenza, providing the foothold for developing novel antiviral inhibitors.

EXPERT OPINION

Vaccines embody the most effective approach to preventing influenza virus infection, and recombinant protein vaccines show promising prospects in developing next-generation vaccines. Compounds targeting the viral components of RNA polymerase, hemagglutinin and nucleoprotein, and the modification of trusted neuraminidase inhibitors are future research directions for anti-influenza virus drugs. In addition, some host factors affect the replication of virus in vivo, which can be used to develop antiviral drugs.

pH Regulates Ligand Binding to an Enzyme Active Site by Modulating Intermediate Populations

Understanding the mechanism of ligands binding to their protein targets and the influence of various factors governing the binding thermodynamics is essential for rational drug design. The solution pH is one of the critical factors that can influence ligand binding to a protein cavity, especially in enzymes whose function is sensitive to the pH. Using computer simulations, we studied the pH effect on the binding of a guanidinium ion (Gdm⁺) to the active site of hen egg-white lysozyme (HEWL). HEWL serves as a model system for enzymes with two acidic residues in the active site and ligands with Gdm⁺ moieties, which can bind to the active sites of such enzymes and are present in several approved drugs treating various disorders. The computed free energy surface (FES) shows that Gdm⁺ binds to the HEWL active site using two dominant binding pathways populating multiple intermediates. We show that the residues close to the active site that can anchor the ligand could play a critical role in ligand binding. Using a Markov state model, we quantified the lifetimes and kinetic pathways connecting the different states in the FES. The protonation and deprotonation of the acidic residues in the active site in response to the pH change strongly influence the Gdm⁺ binding. There is a sharp jump in the ligand-binding rate constant when the pH approaches the largest pK_a of the acidic residue present in the active site. The simulations reveal that, at most, three Gdm⁺ can bind at the active site, with the Gdm⁺ bound in the cavity of the active site acting as a scaffold for the other two Gdm⁺ ions binding. These results can aid in providing greater insights into designing novel molecules containing Gdm⁺ moieties that can have high binding affinities to inhibit the function of enzymes with acidic residues in their active site.

Oral mitis group streptococci reduce infectivity of influenza A virus via acidification and H2O2 production

Members of the mitis group streptococci are the most abundant inhabitants of the oral cavity and dental plaque. Influenza A virus (IAV), the causative agent of influenza, infects the upper respiratory tract, and co-infection with Streptococcus pneumoniae is a major cause of morbidity during influenza epidemics. S. pneumoniae is a member of mitis group streptococci and shares many features with oral mitis group streptococci. In this study, we investigated the effect of viable Streptococcus oralis, a representative member of oral mitis group, on the infectivity of H1N1 IAV. The infectivity of IAV was measured by a plaque assay using Madin-Darby canine kidney cells. When IAV was incubated in growing culture of S. oralis, the IAV titer decreased in a time- and dose-dependent manner and became less than 100-fold, whereas heat-inactivated S. oralis had no effect. Other oral streptococci such as Streptococcus mutans and Streptococcus salivarius also reduced the viral infectivity to a lesser extent compared to S. oralis and Streptococcus gordonii, another member of the oral mitis group. S. oralis produces hydrogen peroxide (H2O2) at a concentration of 1–2 mM, and its mutant deficient in H2O2 production showed a weaker effect on the inactivation of IAV, suggesting that H2O2 contributes to viral inactivation. The contribution of H2O2 was confirmed by an inhibition assay using catalase, an H2O2-decomposing enzyme. These oral streptococci produce short chain fatty acids (SCFA) such as acetic acid as a by-product of sugar metabolism, and we also found that the inactivation of IAV was dependent on the mildly acidic pH (around pH 5.0) of these streptococcal cultures. Although inactivation of IAV in buffers of pH 5.0 was limited, incubation in the same buffer containing 2 mM H2O2 resulted in marked inactivation of IAV, which was similar to the effect of growing S. oralis culture. Taken together, these results reveal that viable S. oralis can inactivate IAV via the production of SCFAs and H2O2. This finding also suggests that the combination of mildly acidic pH and H2O2 at low concentrations could be an effective method to inactivate IAV.

Sialidase Inhibitors with Different Mechanisms

Sialidases, or neuraminidases, are enzymes that catalyze the hydrolysis of sialic acid (Sia)-containing molecules, mostly removal of the terminal Sia (desialylation). By desialylation, sialidase can modulate the functionality of the target compound and is thus often involved in biological pathways. Inhibition of sialidases with inhibitors is an important approach for understanding sialidase function and the underlying mechanisms and could serve as a therapeutic approach as well. Transition-state analogues, such as anti-influenza drugs oseltamivir and zanamivir, are major sialidase inhibitors. In addition, difluoro-sialic acids were developed as mechanism-based sialidase inhibitors. Further, fluorinated quinone methide-based suicide substrates were reported. Sialidase product analogue inhibitors were also explored. Finally, natural products have shown competitive inhibiton against viral, bacterial, and human sialidases. This Perspective describes sialidase inhibitors with different mechanisms and their activities and future potential, which include transition-state analogue inhibitors, mechanism-based inhibitors, suicide substrate inhibitors, product analogue inhibitors, and natural product inhibitors.

Glycoconjugates: Synthesis, Functional Studies, and Therapeutic Developments

Glycoconjugates are major constituents of mammalian cells that are formed via covalent conjugation of carbohydrates to other biomolecules like proteins and lipids and often expressed on the cell surfaces. Among the three major classes of glycoconjugates, proteoglycans and glycoproteins contain glycans linked to the protein backbone via amino acid residues such as Asn for N-linked glycans and Ser/Thr for O-linked glycans. In glycolipids, glycans are linked to a lipid component such as glycerol, polyisoprenyl pyrophosphate, fatty acid ester, or sphingolipid. Recently, glycoconjugates have become better structurally defined and biosynthetically understood, especially those associated with human diseases, and are accessible to new drug, diagnostic, and therapeutic developments. This review describes the status and new advances in the biological study and therapeutic applications of natural and synthetic glycoconjugates, including proteoglycans, glycoproteins, and glycolipids. The scope, limitations, and novel methodologies in the synthesis and clinical development of glycoconjugates including vaccines, glyco-remodeled antibodies, glycan-based adjuvants, glycan-specific receptor-mediated drug delivery platforms, etc., and their future prospectus are discussed.

Structural and inhibitor sensitivity analysis of influenza B-like viral neuraminidases derived from Asiatic toad and spiny eel

Influenza virus neuraminidase (NA) is an important target for antiviral development because it plays a crucial role in releasing newly assembled viruses. Two unique influenza-like virus genomes were recently reported in the Wuhan Asiatic toad and Wuhan spiny eel. Their NA genes appear to be highly divergent from all known influenza NAs, raising key questions as to whether the Asiatic toad influenza-like virus NA (tNA) and spiny eel NA (eNA) have canonical NA activities and structures and whether they show sensitivity to NA inhibitors (NAIs). Here, we found that both tNA and eNA have neuraminidase activities. A detailed structural analysis revealed that tNA and eNA present similar overall structures to currently known NAs, with a conserved calcium binding site. Inhibition assays indicated that tNA is resistant to NAIs, while eNA is still sensitive to NAIs. E119 is conserved in canonical NAs. The P119E substitution in tNA can restore sensitivity to NAIs, and, in contrast, the E119P substitution in eNA decreased its sensitivity to NAIs. The structures of NA-inhibitor complexes further provide a detailed insight into NA-inhibitor interactions at the atomic level. Moreover, tNA and eNA have unique N-glycosylation sites compared with canonical NAs. Collectively, the structural features, NA activities, and sensitivities to NAIs suggest that fish- and amphibian-derived influenza-like viruses may circulate in these vertebrates. More attention should be paid to these influenza-like viruses because their NA molecules may play roles in the emergence of NAI resistance.

The arrival of highly pathogenic avian influenza viruses H5N8 in Iran through two windows, 2016

The highly pathogenic avian influenza (HPAI) H5N1 virus has received considerable attention during the past 2 decades due to its zoonotic and mutative features. This Virus is of special importance due to to the possibility of causing infection in human populations. According to it's geographical location, Iran hosts a large number of aquatic migratory birds every year, and since these birds can be considered as the host of the H5 HPAI, the country is significantly at risk of this virus. the In this study, the molecular characteristics of hemagglutinin (HA) and neuraminidase (NA) genes of the H5N8 strain were identified in Malard county of Tehran province and Meighan wetland of Arak city, Markazi province were investigated. Based on the analysis of the amino acid sequence of the HA genes, the cleavage site of the gene includes the PLREKRRKR/GLF polybasic amino acid motif, which is a characteristic of highly pathogenic influenza viruses. The HA gene of two viruses had T156A, S123P, S133A mutations associated with the increased mammalian sialic acid-binding, and the NA gene of two viruses had H253Y mutations associated with the resistance to antiviral drugs. Phylogenetic analysis of the HA genes indicated the classification of these viruses in the 2.3.4.4 b subclade. Although the A/Goose/Iran/180/2016 virus was also an H5N8 2.3.4.4 b virus, its cluster was separated from the A/Chicken/Iran/162/2016 virus. This means that the entry of these viruses in to the country happened through more than one window. Furthermore, it seems that the introduction of these H5N8 HPAI strains in Iran probably occurred through the West Asia-East African flyway by wild migratory aquatic birds.

New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools

Neurodegenerative diseases (NDD) have been of great interest to scientists for a long time due to their multifactorial character. Among these pathologies, Alzheimer’s disease (AD) is of special relevance, and despite the existence of approved drugs for its treatment, there is still no efficient pharmacological therapy to stop, slow, or repair neurodegeneration. Existing drugs have certain disadvantages, such as lack of efficacy and side effects. Therefore, there is a real need to discover new drugs that can deal with this problem. However, as AD is multifactorial in nature with so many physiological pathways involved, the most effective approach to modulate more than one of them in a relevant manner and without undesirable consequences is through polypharmacology. In this field, there has been significant progress in recent years in terms of pharmacoinformatics tools that allow the discovery of bioactive molecules with polypharmacological profiles without the need to spend a long time and excessive resources on complex experimental designs, making the drug design and development pipeline more efficient. In this review, we present from different perspectives how pharmacoinformatics tools can be useful when drug design programs are designed to tackle complex diseases such as AD, highlighting essential concepts, showing the relevance of artificial intelligence and new trends, as well as different databases and software with their main results, emphasizing the importance of coupling wet and dry approaches in drug design and development processes.

Plant Metabolites as SARS-CoV-2 Inhibitors Candidates: In Silico and In Vitro Studies

Since it acquired pandemic status, SARS-CoV-2 has been causing all kinds of damage all over the world. More than 6.3 million people have died, and many cases of sequelae are in survivors. Currently, the only products available to most of the world’s population to fight the pandemic are vaccines, which still need improvement since the number of new cases, admissions into intensive care units, and deaths are again reaching worrying rates, which makes it essential to compounds that can be used during infection, reducing the impacts of the disease. Plant metabolites are recognized sources of diverse biological activities and are the safest way to research anti-SARS-CoV-2 compounds. The present study computationally evaluated 55 plant compounds in five SARS-CoV-2 targets such Main Protease (Mpro or 3CL or MainPro), RNA-dependent RNA polymerase (RdRp), Papain-Like Protease (PLpro), NSP15 Endoribonuclease, Spike Protein (Protein S or Spro) and human Angiotensin-converting enzyme 2 (ACE-2) followed by in vitro evaluation of their potential for the inhibition of the interaction of the SARS-CoV-2 Spro with human ACE-2. The in silico results indicated that, in general, amentoflavone, 7-O-galloylquercetin, kaempferitrin, and gallagic acid were the compounds with the strongest electronic interaction parameters with the selected targets. Through the data obtained, we can demonstrate that although the indication of individual interaction of plant metabolites with both Spro and ACE-2, the metabolites evaluated were not able to inhibit the interaction between these two structures in the in vitro test. Despite this, these molecules still must be considered in the research of therapeutic agents for treatment of patients affected by COVID-19 since the activity on other targets and influence on the dynamics of viral infection during the interaction Spro x ACE-2 should be investigated.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Binding mechanism of oseltamivir and influenza neuraminidase suggests perspectives for the design of new anti-influenza drugs

Oseltamivir is a widely used influenza virus neuraminidase (NA) inhibitor that prevents the release of new virus particles from host cells. However, oseltamivir-resistant strains have emerged, but effective drugs against them have not yet been developed. Elucidating the binding mechanisms between NA and oseltamivir may provide valuable information for the design of new drugs against NA mutants resistant to oseltamivir. Here, we conducted large-scale (353.4 μs) free-binding molecular dynamics simulations, together with a Markov State Model and an importance-sampling algorithm, to reveal the binding process of oseltamivir and NA. Ten metastable states and five major binding pathways were identified that validated and complemented previously discovered binding pathways, including the hypothesis that oseltamivir can be transferred from the secondary sialic acid binding site to the catalytic site. The discovery of multiple new metastable states, especially the stable bound state containing a water-mediated hydrogen bond between Arg118 and oseltamivir, may provide new insights into the improvement of NA inhibitors. We anticipated the findings presented here will facilitate the development of drugs capable of combating NA mutations.

Influenza virus neuraminidase (NA), a viral membrane glycoprotein, plays an important role in the interactions with host cell surface receptors. The emergence and spread of influenza mutants resistant to neuraminidase inhibitors (NAIs), such as oseltamivir, has been of great concern. Despite many improvements to NAIs, no new first-line NAIs are currently in clinical use. Although there have been previous molecular dynamics simulation studies on the binding and dissociation process of oseltamivir-NA, we discovered new binding pathways and states of oseltamivir through larger-scale simulations and more systematic analysis, which may provide new ideas for the improvement of oseltamivir and even a series of NAIs. In our study, we strongly demonstrate that a detailed understanding of the drug−receptor association process is of fundamental importance for drug design and provide methodological references for the improvement of other drugs.

Predicting Permissive Mutations That Improve the Fitness of A(H1N1)pdm09 Viruses Bearing the H275Y Neuraminidase Substitution

Oseltamivir-resistant influenza viruses arise due to amino acid mutations in key residues of the viral neuraminidase (NA). These changes often come at a fitness cost; however, it is known that permissive mutations in the viral NA can overcome this cost. This result was observed in former seasonal A(H1N1) viruses in 2007 which expressed the H275Y substitution (N1 numbering) with no apparent fitness cost and lead to widespread oseltamivir resistance. Therefore, this study aims to predict permissive mutations that may similarly enable fit H275Y variants to arise in currently circulating A(H1N1)pdm09 viruses. The first approach in this study utilized in silico analyses to predict potentially permissive mutations. The second approach involved the generation of a virus library which encompassed all possible NA mutations while keeping H275Y fixed. Fit variants were then selected by serially passaging the virus library either through ferrets by transmission or passaging once in vitro. The fitness impact of selected substitutions was further evaluated experimentally. The computational approach predicted three candidate permissive NA mutations which, in combination with each other, restored the replicative fitness of an H275Y variant. The second approach identified a stringent bottleneck during transmission between ferrets; however, three further substitutions were identified which may improve transmissibility. A comparison of fit H275Y variants in vitro and in experimentally infected animals showed a statistically significant correlation in the variants that were positively selected. Overall, this study provides valuable tools and insights into potential permissive mutations that may facilitate the emergence of a fit H275Y A(H1N1)pdm09 variant.

IMPORTANCE Oseltamivir (Tamiflu) is the most widely used antiviral for the treatment of influenza infections. Therefore, resistance to oseltamivir is a public health concern. This study is important as it explores the different evolutionary pathways available to current circulating influenza viruses that may lead to widespread oseltamivir resistance. Specifically, this study develops valuable experimental and computational tools to evaluate the fitness landscape of circulating A(H1N1)pmd09 influenza viruses bearing the H275Y mutation. The H275Y substitution is most commonly reported to confer oseltamivir resistance but also leads to loss of virus replication and transmission fitness, which limits its spread. However, it is known from previous influenza seasons that influenza viruses can evolve to overcome this loss of fitness. Therefore, this study aims to prospectively predict how contemporary A(H1N1)pmd09 influenza viruses may evolve to overcome the fitness cost of bearing the H275Y NA substitution, which could result in widespread oseltamivir resistance.

Indian Guidelines on Nebulization Therapy

Inhalational therapy, today, happens to be the mainstay of treatment in obstructive airway diseases (OADs), such as asthma, chronic obstructive pulmonary disease (COPD), and is also in the present, used in a variety of other pulmonary and even non-pulmonary disorders. Hand-held inhalation devices may often be difficult to use, particularly for children, elderly, debilitated or distressed patients. Nebulization therapy emerges as a good option in these cases besides being useful in the home care, emergency room and critical care settings. With so many advancements taking place in nebulizer technology; availability of a plethora of drug formulations for its use, and the widening scope of this therapy; medical practitioners, respiratory therapists, and other health care personnel face the challenge of choosing appropriate inhalation devices and drug formulations, besides their rational application and use in different clinical situations. Adequate maintenance of nebulizer equipment including their disinfection and storage are the other relevant issues requiring guidance. Injudicious and improper use of nebulizers and their poor maintenance can sometimes lead to serious health hazards, nosocomial infections, transmission of infection, and other adverse outcomes. Thus, it is imperative to have a proper national guideline on nebulization practices to bridge the knowledge gaps amongst various health care personnel involved in this practice. It will also serve as an educational and scientific resource for healthcare professionals, as well as promote future research by identifying neglected and ignored areas in this field. Such comprehensive guidelines on this subject have not been available in the country and the only available proper international guidelines were released in 1997 which have not been updated for a noticeably long period of over two decades, though many changes and advancements have taken place in this technology in the recent past. Much of nebulization practices in the present may not be evidence-based and even some of these, the way they are currently used, may be ineffective or even harmful. Recognizing the knowledge deficit and paucity of guidelines on the usage of nebulizers in various settings such as inpatient, out-patient, emergency room, critical care, and domiciliary use in India in a wide variety of indications to standardize nebulization practices and to address many other related issues; National College of Chest Physicians (India), commissioned a National task force consisting of eminent experts in the field of Pulmonary Medicine from different backgrounds and different parts of the country to review the available evidence from the medical literature on the scientific principles and clinical practices of nebulization therapy and to formulate evidence-based guidelines on it. The guideline is based on all possible literature that could be explored with the best available evidence and incorporating expert opinions. To support the guideline with high-quality evidence, a systematic search of the electronic databases was performed to identify the relevant studies, position papers, consensus reports, and recommendations published. Rating of the level of the quality of evidence and the strength of recommendation was done using the GRADE system. Six topics were identified, each given to one group of experts comprising of advisors, chairpersons, convenor and members, and such six groups (A-F) were formed and the consensus recommendations of each group was included as a section in the guidelines (Sections I to VI). The topics included were: A. Introduction, basic principles and technical aspects of nebulization, types of equipment, their choice, use, and maintenance B. Nebulization therapy in obstructive airway diseases C. Nebulization therapy in the intensive care unit D. Use of various drugs (other than bronchodilators and inhaled corticosteroids) by nebulized route and miscellaneous uses of nebulization therapy E. Domiciliary/Home/Maintenance nebulization therapy; public & health care workers education, and F. Nebulization therapy in COVID-19 pandemic and in patients of other contagious viral respiratory infections (included later considering the crisis created due to COVID-19 pandemic). Various issues in different sections have been discussed in the form of questions, followed by point-wise evidence statements based on the existing knowledge, and recommendations have been formulated.

Tetrahydropyridines’ Stereoselective Formation, How Lockdown Assisted in the Identification of the Features of Its Mechanism

The multicomponent reaction of aldehydes, cyano-containing C-H acids, esters of 3-oxocarboxylic acid and ammonium acetate led to unexpected results. The boiling of starting materials in methanol for one to two hours resulted in the formation of polysubstituted 1,4,5,6-tetrahydropyridines with two or three stereogenic centers. During the 2020 lockdown, we obtained key intermediates of this six-step domino reaction. A number of fast and slow reactions occurred during the prolonged stirring of the reaction mass at rt. Sequence: 1. Knoevenagel condensation; 2. Michael addition; 3. Mannich reaction; 4. cyclization—fast reactions and cyclization of the product polysubstituted 2-hydroxypiperidine—was isolated after 40 min stirring at rt. Further monitoring proved the slow dehydration of 2-hydroxypiperidine to obtain 3,4,5,6-tetrahydropyridine after 7 days. Then, four-month isomerization occurred with 1,4,5,6-tetrahydropyridine formation. All reactions were stereoselective. Key intermediates and products structures were verified by X-ray diffraction analysis. Additionally, we specified conditions for the selective intermediates’ preparation.

GANAB and N-Glycans Substrates Are Relevant in Human Physiology, Polycystic Pathology and Multiple Sclerosis: A Review

Glycans are one of the four fundamental macromolecular components of living matter, and they are highly regulated in the cell. Their functions are metabolic, structural and modulatory. In particular, ER resident N-glycans participate with the Glc3Man9GlcNAc2 highly conserved sequence, in protein folding process, where the physiological balance between glycosylation/deglycosylation on the innermost glucose residue takes place, according GANAB/UGGT concentration ratio. However, under abnormal conditions, the cell adapts to the glucose availability by adopting an aerobic or anaerobic regimen of glycolysis, or to external stimuli through internal or external recognition patterns, so it responds to pathogenic noxa with unfolded protein response (UPR). UPR can affect Multiple Sclerosis (MS) and several neurological and metabolic diseases via the BiP stress sensor, resulting in ATF6, PERK and IRE1 activation. Furthermore, the abnormal GANAB expression has been observed in MS, systemic lupus erythematous, male germinal epithelium and predisposed highly replicating cells of the kidney tubules and bile ducts. The latter is the case of Polycystic Liver Disease (PCLD) and Polycystic Kidney Disease (PCKD), where genetically induced GANAB loss affects polycystin-1 (PC1) and polycystin-2 (PC2), resulting in altered protein quality control and cyst formation phenomenon. Our topics resume the role of glycans in cell physiology, highlighting the N-glycans one, as a substrate of GANAB, which is an emerging key molecule in MS and other human pathologies.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Machine-Learning- and Knowledge-Based Scoring Functions Incorporating Ligand and Protein Fingerprints

We propose a novel machine-learning-based scoring function for drug discovery that incorporates ligand and protein structural information into a knowledge-based PMF score. Molecular docking, a simulation method for structure-based drug design (SBDD), is expected to reduce the enormous costs associated with conventional experimental methods in terms of rational drug discovery. Molecular docking has two main purposes: to predict ligand-binding structures for target proteins and to predict protein-ligand binding affinity. Currently available programs of molecular docking offer an accurate prediction of ligand binding structures for many systems. However, the accurate prediction of binding affinity remains challenging. In this study, we developed a new scoring function that incorporates fingerprints representing ligand and protein structures as descriptors in the PMF score. Here, regression analysis of the scoring function was performed using the following machine learning techniques: least absolute shrinkage and selection operator (LASSO) and light gradient boosting machine (LightGBM). The results on a test data set showed that the binding affinity delivered by the newly developed scoring function has a Pearson correlation coefficient of 0.79 with the experimental value, which surpasses that of the conventional scoring functions. Further analysis provided a chemical understanding of the descriptors that contributed significantly to the improvement in prediction accuracy. Our approach and findings are useful for rational drug discovery.

Small molecule inhibitors of mammalian glycosylation

Glycans are one of the fundamental biopolymers encountered in living systems. Compared to polynucleotide and polypeptide biosynthesis, polysaccharide biosynthesis is a uniquely combinatorial process to which interdependent enzymes with seemingly broad specificities contribute. The resulting intracellular cell surface, and secreted glycans play key roles in health and disease, from embryogenesis to cancer progression. The study and modulation of glycans in cell and organismal biology is aided by small molecule inhibitors of the enzymes involved in glycan biosynthesis. In this review, we survey the arsenal of currently available inhibitors, focusing on agents which have been independently validated in diverse systems. We highlight the utility of these inhibitors and drawbacks to their use, emphasizing the need for innovation for basic research as well as for therapeutic applications.