Antiviral effects and tissue exposure of tetrandrine against SARS-CoV-2 infection and COVID-19.

Tetrandrine (TET) has been used to treat silicosis in China for decades. The aim of this study was to facilitate rational repurposing of TET against SARS-CoV-2 infection. In this study, we confirmed that TET exhibited antiviral potency against SARS-CoV-2 in the African green monkey kidney (Vero E6), human hepatocarcinoma (Huh7), and human lung adenocarcinoma epithelial (Calu-3) cell lines. TET functioned during the early-entry stage of SARS-CoV-2 and impeded intracellular trafficking of the virus from early endosomes to endolysosomes. An in vivo study that used adenovirus (AdV) 5-human angiotensin-converting enzyme 2 (hACE2)-transduced mice showed that although TET did not reduce pulmonary viral load, it significantly alleviated pathological damage in SARS-CoV-2-infected murine lungs. The systemic preclinical pharmacokinetics were investigated based on in vivo and in vitro models, and the route-dependent biodistribution of TET was explored. TET had a large volume of distribution, which contributed to its high tissue accumulation. Inhaled administration helped TET target the lung and reduced its exposure to other tissues, which mitigated its off-target toxicity. Based on the available human pharmacokinetic data, it appeared feasible to achieve an unbound TET 90% maximal effective concentration (EC90) in human lungs. This study provides insights into the route-dependent pulmonary biodistribution of TET associated with its efficacy.

How does China respond to the agricultural commodities market: A case study in the post COVID-19 era?

COVID-19 pandemic caused different levels of impact across the industries, including agriculture, since it is a food chain reaction from the raw materials to the end product. The main purpose of our review research is to find out how the Chinese government responded to food security and price in the agricultural market in post COVID19 era and then follow with key issues that need to be considered, such as steady agricultural product prices. Also, during the post COVID-19, the conflict between Russia and Ukraine affected the world's agricultural production and market. This review research concluded the strategies of the Chinese government to respond to this global issue from the point of view of agriculture. The paper also proposed some solutions and suggestions that can be applied during this new era. In the end, we concluded effective policies and regulations that have been proven by the Chinese government and can be referred to by other countries or regions.

Disease Progression of Hospitalized Elderly Patients with Omicron BA.2 Treated with Molnupiravir.

INTRODUCTION: The efficacy of molnupiravir (MLN) on Omicron sublineages is limited. We investigated the effectiveness of MLN in older adults diagnosed with Omicron BA.2. METHODS: Data of elderly COVID-19 patients (over 60 years) admitted to Chinghai Hospital (Shanghai, China) from 26 March to 31 May 2022 were reviewed. Study outcomes were a composite of undetectable viral load (VL) and disease progression [all-cause mortality, initiation of oxygen supply through high-flow device or invasive mechanical ventilation (IMV), or intensive care unit (ICU) admission] and their individual outcomes. RESULTS: A total of 42 elderly patients were enrolled: 26 of them received MLN, 17 (40.5%) were males, the median age was 84 years, and 12 were fully vaccinated (31.0%). Among these elderly COVID-19 patients, five (11.90%) experienced obvious dyspnea or were transferred to ICU [three MLN users (11.5%) versus two non-MLN users (12.5%)]. Compared with no MLN use, MLN use was associated with rapid undetectable VL. At day 10, MLN users achieved significantly greater undetectable VL than non-MLN users. Adjusted analysis showed that elderly patients who received MLN were 7.584 times more likely to achieve undetectable VL at day 10 than non-MLN users. Overall, elderly patients experienced a median hospital stay of 13 days. Compared with patients receiving standard care (SC), the median hospital stay of MLN users was reduced by 2.5 days. CONCLUSION: Early initiation of MLN in elderly COVID-19 was associated with fast undetectable VL and short hospital stay.

Antiviral Efficacy and Safety of Molnupiravir Against Omicron Variant Infection: A Randomized Controlled Clinical Trial.

Background: The rapid worldwide spread of the Omicron variant of SARS-CoV-2 has unleashed a new wave of COVID-19 outbreaks. The efficacy of molnupiravir, an approved drug, is still unknown in patients infected with the Omicron variant. Objective: Evaluated the antiviral efficacy and safety of molnupiravir in patients infected with SARS-CoV-2 Omicron variant, with symptom duration within 5 days. Methods: We conducted a randomized, controlled trial involving patients with mild or moderate COVID-19. Patients were randomized to orally receive molnupiravir (800 mg) plus basic treatment or only basic treatment for 5 days (BID). The antiviral efficacy of the drug was evaluated using reverse transcriptase polymerase chain reaction. Results: Results showed that the time of viral RNA clearance (primary endpoint) was significantly decreased in the molnupiravir group (median, 9 days) compared to the control group (median, 10 days) (Log-Rank p = 0.0092). Of patients receiving molnupiravir, 18.42% achieved viral RNA clearance on day 5 of treatment, compared to the control group (0%) (p = 0.0092). On day 7, 40.79%, and 6.45% of patients in the molnupiravir and control groups, respectively, achieved viral RNA clearance (p = 0.0004). In addition, molnupiravir has a good safety profile, and no serious adverse events were reported. Conclusion: Molnupiravir significantly accelerated the SARS-CoV-2 Omicron RNA clearance in patients with COVID-19. Clinical Trial Registration: [chictr.org.cn], identifier [ChiCTR2200056817].

Molnupiravir and Its Active Form, EIDD-1931, Show Potent Antiviral Activity against Enterovirus Infections In Vitro and In Vivo.

Enterovirus infections can cause hand, foot, and mouth disease (HFDM), aseptic meningitis, encephalitis, myocarditis, and acute flaccid myelitis, leading to death of infants and young children. However, no specific antiviral drug is currently available for the treatment of this type of infection. The Unites States and United Kingdom health authorities recently approved a new antiviral drug, molnupiravir, for the treatment of COVID-19. In this study, we reported that molnupiravir (EIDD-2801) and its active form, EIDD-1931, have broad-spectrum anti-enterovirus potential. Our data showed that EIDD-1931 could significantly reduce the production of EV-A71 progeny virus and the expression of EV-A71 viral protein at non-cytotoxic concentrations. The results of the time-of-addition assay suggest that EIDD-1931 acts at the post-entry step, which is in accordance with its antiviral mechanism. The intraperitoneal administration of EIDD-1931 and EIDD-2801 protected 1-day-old ICR suckling mice from lethal EV-A71 challenge by reducing the viral load in various tissues of the infected mice. The pharmacokinetics analysis indicated that the plasma drug concentration overwhelmed the EC50 for enteroviruses, suggesting the clinical potential of molnupiravir against enteroviruses. Thus, molnupiravir along with its active form, EIDD-1931, may be a promising drug candidate against enterovirus infections.

Mechanism of Action of Small-Molecule Agents in Ongoing Clinical Trials for SARS-CoV-2: A Review.

Since the first reports from December 2019, COVID-19 caused an overwhelming global pandemic that has affected 223 countries, seriously endangering public health and creating an urgent need for effective drugs to treat SARS-CoV-2 infection. Currently, there is a lack of safe, effective, and specific therapeutic drugs for COVID-19, with mainly supportive and symptomatic treatments being administered to patients. The preferred option for responding to an outbreak of acute infectious disease is through drug repurposing, saving valuable time that would otherwise be lost in preclinical and clinical research, hastening clinical introduction, and lowering treatment costs. Alternatively, researchers seek to design and discover novel small-molecule candidate drugs targeting the key proteins in the life cycle of SARS-CoV-2 through an in-depth study of the infection mechanism, thus obtaining a number of candidate compounds with favorable antiviral effects in preclinical and clinical settings. There is an urgent need to further elucidate the efficacy and mechanism of action of potential anti-SARS-CoV-2 small-molecule drugs. Herein, we review the candidate small-molecule anti-SARS-CoV-2 drugs in ongoing clinical trials, with a major focus on their mechanisms of action in an attempt to provide useful insight for further research and development of small-molecule compounds against SARS-CoV-2 infection.

Therapeutic prospect of tetrandrine against SARS-CoV-2 based on its pulmonary pharmacology and exposure character

As the main active compound of Stephania tetrandra S. Moore, tetrandrine (TET) has been used to treat silicosis for nearly 50 years. TET has clear therapeutic effect on pulmonary fibrosis and lung cancer. A recent study suggests that TET may inhibit the replication of SARS-CoV-2 by blocking the two-pore channel 2 (TPC2), revealing its potential as a natural medicine to treat COVID-19. To explore the material basis of TET targeting lung efficacy and its potential toxicity, available literatures related to the pharmacological activity on pulmonary, dosage, toxicity and pharmacokinetics of TET are systemically reviewed. The prospect and current problems of TET to be a therapeutic agent for COVID-19 are further investigated on this basis.

Application of omics technology to combat the COVID-19 pandemic.

As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID-19 pandemic, multiomics-based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID-19. In order to help researchers and clinicians to keep up with the knowledge of COVID-19, we summarized the most recent progresses reported in omics-based research papers. This review discusses omics-based approaches for studying COVID-19, summarizing newly emerged SARS-CoV-2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID-19. This review can help researchers and clinicians gain insight into COVID-19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression.

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network.

An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it has infected nearly 7 million people and killed more than 400,000, but there is no specific drug. Therefore, there is an urgent need to find or develop more drugs to suppress the virus. Here, we propose a new nonlinear end-to-end model called LUNAR. It uses graph convolutional neural networks to automatically learn the neighborhood information of complex heterogeneous relational networks and combines the attention mechanism to reflect the importance of the sum of different types of neighborhood information to obtain the representation characteristics of each node. Finally, through the topology reconstruction process, the feature representations of drugs and targets are forcibly extracted to match the observed network as much as possible. Through this reconstruction process, we obtain the strength of the relationship between different nodes and predict drug candidates that may affect the treatment of COVID-19 based on the known targets of COVID-19. These selected candidate drugs can be used as a reference for experimental scientists and accelerate the speed of drug development. LUNAR can well integrate various topological structure information in heterogeneous networks, and skillfully combine attention mechanisms to reflect the importance of neighborhood information of different types of nodes, improving the interpretability of the model. The area under the curve(AUC) of the model is 0.949 and the accurate recall curve (AUPR) is 0.866 using 10-fold cross-validation. These two performance indexes show that the model has superior predictive performance. Besides, some of the drugs screened out by our model have appeared in some clinical studies to further illustrate the effectiveness of the model.

DeepR2cov: deep representation learning on heterogeneous drug networks to discover anti-inflammatory agents for COVID-19.

Recent studies have demonstrated that the excessive inflammatory response is an important factor of death in coronavirus disease 2019 (COVID-19) patients. In this study, we propose a deep representation on heterogeneous drug networks, termed DeepR2cov, to discover potential agents for treating the excessive inflammatory response in COVID-19 patients. This work explores the multi-hub characteristic of a heterogeneous drug network integrating eight unique networks. Inspired by the multi-hub characteristic, we design 3 billion special meta paths to train a deep representation model for learning low-dimensional vectors that integrate long-range structure dependency and complex semantic relation among network nodes. Based on the representation vectors and transcriptomics data, we predict 22 drugs that bind to tumor necrosis factor-α or interleukin-6, whose therapeutic associations with the inflammation storm in COVID-19 patients, and molecular binding model are further validated via data from PubMed publications, ongoing clinical trials and a docking program. In addition, the results on five biomedical applications suggest that DeepR2cov significantly outperforms five existing representation approaches. In summary, DeepR2cov is a powerful network representation approach and holds the potential to accelerate treatment of the inflammatory responses in COVID-19 patients. The source code and data can be downloaded from https://github.com/pengsl-lab/DeepR2cov.git.

Comparative Antiviral Efficacy of Viral Protease Inhibitors against the Novel SARS-CoV-2 In Vitro.

The recent outbreak of novel coronavirus pneumonia (COVID-19) caused by a new coronavirus has posed a great threat to public health. Identifying safe and effective antivirals is of urgent demand to cure the huge number of patients. Virus-encoded proteases are considered potential drug targets. The human immunodeficiency virus protease inhibitors (lopinavir/ritonavir) has been recommended in the global Solidarity Trial in March launched by World Health Organization. However, there is currently no experimental evidence to support or against its clinical use. We evaluated the antiviral efficacy of lopinavir/ritonavir along with other two viral protease inhibitors in vitro, and discussed the possible inhibitory mechanism in silico. The in vitro to in vivo extrapolation was carried out to assess whether lopinavir/ritonavir could be effective in clinical. Among the four tested compounds, lopinavir showed the best inhibitory effect against the novel coronavirus infection. However, further in vitro to in vivo extrapolation of pharmacokinetics suggested that lopinavir/ritonavir could not reach effective concentration under standard dosing regimen [marketed as Kaletra®, contained lopinavir/ritonavir (200 mg/50 mg) tablets, recommended dosage is 400 mg/10 mg (2 tablets) twice daily]. This research concluded that lopinavir/ritonavir should be stopped for clinical use due to the huge gap between in vitro IC50 and free plasma concentration. Nevertheless, the structure-activity relationship analysis of the four inhibitors provided further information for de novel design of future viral protease inhibitors of SARS-CoV-2.

Phase 2a, open-label, dose-escalating, multi-center pharmacokinetic study of favipiravir (T-705) in combination with oseltamivir in patients with severe influenza.

BACKGROUND: The pharmacokinetics and appropriate dose regimens of favipiravir are unknown in hospitalized influenza patients; such data are also needed to determine dosage selection for favipiravir trials in COVID-19. METHODS: In this dose-escalating study, favipiravir pharmacokinetics and tolerability were assessed in critically ill influenza patients. Participants received one of two dosing regimens; Japan licensed dose (1600 mg BID on day 1 and 600 mg BID on the following days) and the higher dose (1800 mg/800 mg BID) trialed in uncomplicated influenza. The primary pharmacokinetic endpoint was the proportion of patients with a minimum observed plasma trough concentration (Ctrough) ≥20 mg/L at all measured time points after the second dose. RESULTS: Sixteen patients were enrolled into the low dose group and 19 patients into the high dose group of the study. Favipiravir Ctrough decreased significantly over time in both groups (p <0.01). Relative to day 2 (48 hrs), concentrations were 91.7% and 90.3% lower in the 1600/600 mg group and 79.3% and 89.5% lower in the 1800/800 mg group at day 7 and 10, respectively. In contrast, oseltamivir concentrations did not change significantly over time. A 2-compartment disposition model with first-order absorption and elimination described the observed favipiravir concentration-time data well. Modeling demonstrated that less than 50% of patients achieved Ctrough ≥20 mg/L for >80% of the duration of treatment of the two dose regimens evaluated (18.8% and 42.1% of patients for low and high dose regimen, respectively). Increasing the favipravir dosage predicted a higher proportion of patients reaching this threshold of 20 mg/L, suggesting that dosing regimens of ≥3600/2600 mg might be required for adequate concentrations. The two dosing regimens were well-tolerated in critical ill patients with influenza. CONCLUSION: The two dosing regimens proposed for uncomplicated influenza did not achieve our pre-defined treatment threshold.

Improvement of the C-glycosylation Step for the Synthesis of Remdesivir

The bulk supply of the antiviral C-nucleoside analogue remdesivir is largely hampered by a low-yielding Cglycosylation step in which the base is coupled to the pentose unit. Here, we disclose a significantly improved methodology for this critical transformation. By utilizing diisopropylamine as a cost-effective additive, the addition reaction furnishes an optimal yield of 75% of the desired ribofuranoside adduct, representing the highest yield obtained thus far for this key step. The method proved suitable for hectogram scale synthesis without column chromatographic operations.

Pathological features of COVID-19-associated lung injury: a preliminary proteomics report based on clinical samples.

The COVID-19 pandemic has emerged as a global health emergency due to its association with severe pneumonia and relative high mortality. However, the molecular characteristics and pathological features underlying COVID-19 pneumonia remain largely unknown. To characterize molecular mechanisms underlying COVID-19 pathogenesis in the lung tissue using a proteomic approach, fresh lung tissues were obtained from newly deceased patients with COVID-19 pneumonia. After virus inactivation, a quantitative proteomic approach combined with bioinformatics analysis was used to detect proteomic changes in the SARS-CoV-2-infected lung tissues. We identified significant differentially expressed proteins involved in a variety of fundamental biological processes including cellular metabolism, blood coagulation, immune response, angiogenesis, and cell microenvironment regulation. Several inflammatory factors were upregulated, which was possibly caused by the activation of NF-κB signaling. Extensive dysregulation of the lung proteome in response to SARS-CoV-2 infection was discovered. Our results systematically outlined the molecular pathological features in terms of the lung response to SARS-CoV-2 infection, and provided the scientific basis for the therapeutic target that is urgently needed to control the COVID-19 pandemic.