T-cell cellular stress and reticulocyte signatures, but not loss of naïve T lymphocytes, characterize severe COVID-19 in older adults.

In children and younger adults up to 39 years of age, SARS-CoV-2 usually elicits mild symptoms that resemble the common cold. Disease severity increases with age starting at 30 and reaches astounding mortality rates that are ~330 fold higher in persons above 85 years of age compared to those 18-39 years old. To understand age-specific immune pathobiology of COVID-19, we have analyzed soluble mediators, cellular phenotypes, and transcriptome from over 80 COVID-19 patients of varying ages and disease severity, carefully controlling for age as a variable. We found that reticulocyte numbers and peripheral blood transcriptional signatures robustly correlated with disease severity. By contrast, decreased numbers and proportion of naïve T-cells, reported previously as a COVID-19 severity risk factor, were found to be general features of aging and not of COVID-19 severity, as they readily occurred in older participants experiencing only mild or no disease at all. Single-cell transcriptional signatures across age and severity groups showed that severe but not moderate/mild COVID-19 causes cell stress response in different T-cell populations, and some of that stress was unique to old severe participants, suggesting that in severe disease of older adults, these defenders of the organism may be disabled from performing immune protection. These findings shed new light on interactions between age and disease severity in COVID-19.

A small molecule targeting hepatitis B surface antigen inhibits clinically relevant drug-resistant hepatitis B virus.

BACKGROUND: Currently approved oral antivirals for chronic HBV infection target the reverse transcriptase (RT) domain of the HBV polymerase. Emergence of drug resistance has been reported in a small proportion of chronic HBV patients on prolonged treatment with antivirals. We recently reported ZINC20451377, a small molecule targeting hepatitis B surface antigen (HBsAg) that effectively inhibits both WT HBV and tenofovir-resistant HBV. Due to the partial overlap between the RT domain and HBsAg, drug-resistant mutants are associated with corresponding mutations in HBsAg. OBJECTIVES: To evaluate the efficacy of ZINC20451377 against nine clinically relevant drug-resistant HBV mutants that lead to simultaneous mutations in the overlapping HBsAg gene. METHODS: Huh7 cells were transfected with 1.2× HBV replicons corresponding to WT HBV or drug-resistant HBV mutants and treated with different concentrations of ZINC20451377. We assessed the IC50 values of ZINC20451377 for HBsAg levels in the culture supernatants using ELISAs. HBV secretion was measured by immunocapture of secreted virions followed by real-time PCR quantitation of virion-associated DNA. RESULTS: ZINC20451377 led to a dose-dependent inhibition of secreted HBsAg encoded by WT HBV and all nine drug-resistant mutants tested and the IC50 values were in the low micromolar range. ZINC20451377 inhibited HBV secretion from drug-resistant mutants except for mutants harbouring the rtL180M + rtM204V (MV) mutation. CONCLUSIONS: The small molecule ZINC20451377 inhibits HBsAg and virion secretion in some of the clinically relevant drug-resistant HBV mutants. ZINC20451377 has a modest overall effect, and it was not effective against the MV mutants (lamivudine- and entecavir-resistant mutants).

Insights of ligand binding in modeled h5-HT1A receptor: homology modeling, docking, MM-GBSA, screening and molecular dynamics.

The pharmacologically characterized receptor subtype of the serotonin family, the 5HT1A receptor is implicated in the pathophysiology and treatment of depression and anxiety-related disorders. Being the most extensively targeted receptor for developing novel antidepressants and anxiolytics, a near-ideal theoretical model can aid in high-throughput screening of promising drug candidates. However, the design of potential drug candidates suffers owing to a lack of complete structural information. In this work, homology models of 5-HT1A receptor are generated using two distinct alignments (CW and PSTA) and model building methods (KB and EB). The developed models are validated for virtual screening using a ligand dataset of agonists and antagonists. The best-suited model was efficient in discriminating agonist/antagonist binding. Correlation plots between pKi and docking (R2agonist≥ 0.6, R2antagonist≥ 0.7) and MM-GBSA dG bind values (R2agonist≥ 0.5, R2antagonist≥ 0.7) revealed optimum corroboration between in vitro and in silico outcomes, which further suggested the usefulness of the developed model for the design of high-affinity probes for the neurological disorders.Communicated by Ramaswamy H. Sarma.

T-cell cellular stress and reticulocyte signatures, but not loss of naïve T lymphocytes, characterize severe COVID-19 in older adults.

In children and younger adults up to 39 years of age, SARS-CoV-2 usually elicits mild symptoms that resemble the common cold. Disease severity increases with age starting at 30 and reaches astounding mortality rates that are ~330 fold higher in persons above 85 years of age compared to those 18-39 years old. To understand age-specific immune pathobiology of COVID-19 we have analyzed soluble mediators, cellular phenotypes, and transcriptome from over 80 COVID-19 patients of varying ages and disease severity, carefully controlling for age as a variable. We found that reticulocyte numbers and peripheral blood transcriptional signatures robustly correlated with disease severity. By contrast, decreased numbers and proportion of naïve T-cells, reported previously as a COVID-19 severity risk factor, were found to be general features of aging and not of COVID-19 severity, as they readily occurred in older participants experiencing only mild or no disease at all. Single-cell transcriptional signatures across age and severity groups showed that severe but not moderate/mild COVID-19 causes cell stress response in different T-cell populations, and some of that stress was unique to old severe participants, suggesting that in severe disease of older adults, these defenders of the organism may be disabled from performing immune protection. These findings shed new light on interactions between age and disease severity in COVID-19.

A novel piperazine derivative that targets hepatitis B surface antigen effectively inhibits tenofovir resistant hepatitis B virus.

Chronic hepatitis B virus (HBV) infection is a global problem. The loss of hepatitis B surface antigen (HBsAg) in serum is a therapeutic end point. Prolonged therapy with nucleoside/nucleotide analogues targeting the HBV-polymerase may lead to resistance and rarely results in the loss of HBsAg. Therefore, inhibitors targeting HBsAg may have potential therapeutic applications. Here, we used computational virtual screening, docking, and molecular dynamics simulations to identify potential small molecule inhibitors against HBsAg. After screening a million molecules from ZINC database, we identified small molecules with potential anti-HBV activity. Subsequently, cytotoxicity profiles and anti-HBV activities of these small molecules were tested using a widely used cell culture model for HBV. We identified a small molecule (ZINC20451377) which binds to HBsAg with high affinity, with a KD of 65.3 nM, as determined by Surface Plasmon Resonance spectroscopy. Notably, the small molecule inhibited HBsAg production and hepatitis B virion secretion (10 µM) at low micromolar concentrations and was also efficacious against a HBV quadruple mutant (CYEI mutant) resistant to tenofovir. We conclude that this small molecule exhibits strong anti-HBV properties and merits further testing.

Epidemiology and molecular characterization of chikungunya virus from human cases in North India, 2016.

Chikungunya virus (CHIKV), an arthropod-borne Alphavirus is responsible for chikungunya disease. Arthralgia and arthritis are the major symptom. Some patients recover early while others for a very long time. This study provides, epidemiology and molecular characterization of three whole-genome sequences of CHIKV and assessed phylogenetic analysis, physiological properties, antigenicity, and B-cell epitope prediction by in silico. We report the clinical epidemiology of 325 suspected patients. Of these, 118 (36.30%) were confirmed CHIKV positive by either PCR or ELISA. Clinical analysis showed joint pain, joint swelling and headache were frequent and significant features. Phylogenie analysis showed the currently circulating strain is in close clustring to Africa, Uganda, and Singapore CHIKV strains. Molecular characterization by WGS was done. Thirty eight amino acid changes in the nonstructural proteins were found with respect to the S27 (ECSA) strain. Of these five located in nsP2. Similarly, 34 amino acid changes in structural proteins were observed. The major change was notice; in E3 protein hydropathicity -0.281 to -0.362, in E2 isoelectric point (pI) 8.24 to 8.37, instability index 66.08 to 71.062, aliphatic index varied from 74.69 to 68.59 and E3 75.79 to 70.05. In nsP1 protein pI varies from 6.62 to 8.04, while no other change was observed in structural and nonstructural protein. The linear B-cell epitopes, position, and number varied with the mutation. The molecular characterizations of WGS demonstrate the observation of protein, antigenicity with respect to the mutation.

Discovery of small molecule inhibitors of chikungunya virus proteins (nsP2 and E1) using in silico approaches.

Chikungunya virus (CHIKV) has emerged as a major viral threat, affecting over a million people worldwide per year. It is a vector borne disease transmitted to the human by Ades mosquitoes and primarily affect people by causing viral fever, severe joint pain and other symptoms, like rash, joint swelling, muscle pain and in rare cases can be fatal. CHIKV is a deadly virus, with its mutation rate found to be significantly higher as compared to other viruses. To date, there has been no reported FDA approved drug against this virus. Thus, keeping in mind the urgent need to scrutinize potential therapies against CHIKV, the present study identified twenty plant bioactive compounds that are available at low price and do not have associated adverse effect. For identification of active potentials molecules the pharmacoinformatics-based perspective was applied against CHIKV structural (E1) and non-structural (nsP2) proteins using molecular docking and scoring. The selected compounds were further studied for pharmacokinetics (PK) and pharmacodynamics (PD) associated parameters such as initial absorption, then distribution and later on metabolism excretion and toxicity (ADMET) profiles based on in silico study. The results reveal five potential lead compounds having high binding energy that can help in the development of commercial drugs with favorable ADMET characteristic.Communicated by Ramaswamy H. Sarma.

Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-metallo and metallo PL complexes. Bappl+ outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient of up to ~ 0.76 with low standard deviations. The biggest contributors to the increased performance are the use of a machine-learning model and the enlarged training dataset. We have also evaluated the performance of Bappl+ on target-specific proteins, which highlighted the limitations of our function and provides a way for further improvements. We believe that Bappl+ methodology could prove valuable in ranking candidate molecules against a target metallo or non-metallo protein by reliably predicting their binding affinities, thus helping in the drug discovery process.

Structure-Guided Approach to Identify Potential Inhibitors of Large Envelope Protein to Prevent Hepatitis B Virus Infection.

Hepatitis B virus (HBV) infection is one of the major causes of liver diseases, which can lead to hepatocellular carcinoma. The role of HBV envelope proteins is crucial in viral morphogenesis, infection, and propagation. Thus, blocking the pleiotropic functions of these proteins especially the PreS1 and PreS2 domains of the large surface protein (LHBs) is a promising strategy for designing efficient antivirals against HBV infection. Unfortunately, the structure of the LHBs protein has not been elucidated yet, and it seems that any structure-based drug discovery is critically dependent on this. To find effective inhibitors of LHBs, we have modeled and validated its three-dimensional structure and subsequently performed a virtual high-throughput screening against the ZINC database using RASPD and ParDOCK tools. We have identified four compounds, ZINC11882026, ZINC19741044, ZINC00653293, and ZINC15000762, showing appreciable binding affinity with the LHBs protein. The drug likeness was further validated using ADME screening and toxicity analysis. Interestingly, three of the four compounds showed the formation of hydrogen bonds with amino acid residues lying in the capsid binding region of the PreS1 domain of LHBs, suggesting the possibility of inhibiting the viral assembly and maturation process. The identification of potential lead molecules will help to discover more potent inhibitors with significant antiviral activities.

Toward development of generic inhibitors against the 3C proteases of picornaviruses.

Development of novel antivirals, which requires knowledge of the viral life cycle in molecular detail, is a daunting task, involving extensive investments, and frequently resulting in failure. As there exist significant commonalities among virus families in the manner of host interaction, identifying and targeting common rather than specific features may lead to the development of broadly useful antivirals. Here, we have targeted the 3C protease of Hepatitis A Virus (HAV), a feco-orally transmitted virus of the family Picornaviridae, for identification of potential antivirals. The 3C protease is a viable drug target as it is required by HAV, as well as by other picornaviruses, for post-translational proteolysis of viral polyproteins and for inhibiting host innate immune pathways. Computational screening, followed by chemical synthesis and experimental validation resulted in identification of a few compounds which, at low micromolar concentrations, could inhibit HAV 3C activity. These compounds were further tested experimentally against the 3C protease of Human Rhinovirus, another member of the Picornaviridae family, with comparable results. Computational studies on 3C proteases from other members of the picornavirus family have indicated that the compounds identified could potentially be generic inhibitors for picornavirus 3C proteases.