Emodin for COVID-19

Several human diseases are caused by viruses, including cancer, Type I diabetes, Alzheimer’s disease, and hepatocellular carcinoma. In the past, people have suffered greatly from viral diseases such as polio, mumps, measles, dengue fever, SARS, MERS, AIDS, chikungunya fever, encephalitis, and influenza. Recently, COVID-19 has become a pandemic in most parts of the world. Although vaccines are available to fight the infection, their safety and clinical trial data are still questionable. Social distancing, isolation, the use of sanitizer, and personal productive strategies have been implemented to prevent the spread of the virus. Moreover, the search for a potential therapeutic molecule is ongoing. Based on experiences with outbreaks of SARS and MERS, many research studies reveal the potential of medicinal herbs/plants or chemical compounds extracted from them to counteract the effects of these viral diseases. COVID-19′s current status includes a decrease in infection rates as a result of large-scale vaccination program implementation by several countries. But it is still very close and needs to boost people’s natural immunity in a cost-effective way through phytomedicines because many underdeveloped countries do not have their own vaccination facilities. In this article, phytomedicines as plant parts or plant-derived metabolites that can affect the entry of a virus or its infectiousness inside hosts are described. Finally, it is concluded that the therapeutic potential of medicinal plants must be analyzed and evaluated entirely in the control of COVID-19 in cases of uncontrollable SARS infection.

The emergence of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected many countries throughout the world. As urgency is a necessity, most efforts have focused on identifying small molecule drugs that can be repurposed for use as anti-SARS-CoV-2 agents. Although several drug candidates have been identified using in silico method and in vitro studies, most of these drugs require the support of in vivo data before they can be considered for clinical trials. Several drugs are considered promising therapeutic agents for COVID-19. In addition to the direct-acting antiviral drugs, supportive therapies including traditional Chinese medicine, immunotherapies, immunomodulators, and nutritional therapy could contribute a major role in treating COVID-19 patients. Some of these drugs have already been included in the treatment guidelines, recommendations, and standard operating procedures. In this article, we comprehensively review the approved and potential therapeutic drugs, immune cells-based therapies, immunomodulatory agents/drugs, herbs and plant metabolites, nutritional and dietary for COVID-19.

Abstract Background The recent outbreak of the Coronavirus pandemic resulted in a successful vaccination program launched by the World Health Organization. However, a large population is still unvaccinated, leading to the emergence of mutated strains like alpha, beta, delta, and B.1.1.529 (Omicron). Recent reports from the World Health Organization raised concerns about the Omicron variant, which emerged in South Africa during a surge in COVID-19 cases in November 2021. Vaccines are not proven completely effective or safe against Omicron, leading to clinical trials for combating infection by the mutated virus. The absence of suitable pharmaceuticals has led scientists and clinicians to search for alternative and supplementary therapies, including dietary patterns, to reduce the effect of mutated strains. Main body This review analyzed Coronavirus aetiology, epidemiology, and natural products for combating Omicron. Although the literature search did not include keywords related to in silico or computational research, in silico investigations were emphasized in this study. Molecular docking was implemented to compare the interaction between natural products and Chloroquine with the ACE2 receptor protein amino acid residues of Omicron. The global Omicron infection proceeding SARS-CoV-2 vaccination was also elucidated. The docking results suggest that DGCG may bind to the ACE2 receptor three times more effectively than standard chloroquine. Conclusion The emergence of the Omicron variant has highlighted the need for alternative therapies to reduce the impact of mutated strains. The current review suggests that natural products such as DGCG may be effective in binding to the ACE2 receptor and combating the Omicron variant, however, further research is required to validate the results of this study and explore the potential of natural products to mitigate COVID-19. Graphical abstract

AbstractHuman coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV–host interactome and drug targets in the human protein–protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the “Complementary Exposure” pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

IntroductionWith the increasingly serious problem of antiviral drug resistance, drug repurposing offers a time-efficient and cost-effective way to find potential therapeutic agents for disease. Computational models have the ability to quickly predict potential reusable drug candidates to treat diseases.MethodsIn this study, two matrix decomposition-based methods, i.e., Matrix Decomposition with Heterogeneous Graph Inference (MDHGI) and Bounded Nuclear Norm Regularization (BNNR), were integrated to predict anti-viral drugs. Moreover, global leave-one-out cross-validation (LOOCV), local LOOCV, and 5-fold cross-validation were implemented to evaluate the performance of the proposed model based on datasets of DrugVirus that consist of 933 known associations between 175 drugs and 95 viruses.ResultsThe results showed that the area under the receiver operating characteristics curve (AUC) of global LOOCV and local LOOCV are 0.9035 and 0.8786, respectively. The average AUC and the standard deviation of the 5-fold cross-validation for DrugVirus datasets are 0.8856 ± 0.0032. We further implemented cross-validation based on MDAD and aBiofilm, respectively, to evaluate the performance of the model. In particle, MDAD (aBiofilm) dataset contains 2,470 (2,884) known associations between 1,373 (1,470) drugs and 173 (140) microbes. In addition, two types of case studies were carried out further to verify the effectiveness of the model based on the DrugVirus and MDAD datasets. The results of the case studies supported the effectiveness of MHBVDA in identifying potential virus-drug associations as well as predicting potential drugs for new microbes.

COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, TMPRSS2, and AP2-associated protein kinase 1. In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of drug candidates to target receptors, providing insight into their potential efficacy. However, it is crucial to consider both the advantages and limitations of these studies and to complement them with experimental validation to ensure the efficacy and safety of identified drug candidates.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible method to address this issue as the traditional Chinese medicine formulae have been shown effective in the treatment of COVID-19. Huashi Baidu decoction (Q-14) is a clinically approved formula for COVID-19 therapy with antiviral and anti-inflammatory effects. Here, an integrative pharmacological strategy was applied to identify the antiviral and anti-inflammatory bioactive compounds from Q-14. Overall, a total of 343 chemical compounds were initially characterized, and 60 prototype compounds in Q-14 were subsequently traced in plasma using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry. Among the 60 compounds, six compounds (magnolol, glycyrrhisoflavone, licoisoflavone A, emodin, echinatin, and quercetin) were identified showing a dose-dependent inhibition effect on the SARS-CoV-2 infection, including two inhibitors (echinatin and quercetin) of the main protease (M pro ), as well as two inhibitors (glycyrrhisoflavone and licoisoflavone A) of the RNA-dependent RNA polymerase (RdRp). Meanwhile, three anti-inflammatory components, including licochalcone B, echinatin, and glycyrrhisoflavone, were identified in a SARS-CoV-2-infected inflammatory cell model. In addition, glycyrrhisoflavone and licoisoflavone A also displayed strong inhibitory activities against cAMP-specific 3′,5′-cyclic phosphodiesterase 4 (PDE4). Crystal structures of PDE4 in complex with glycyrrhisoflavone or licoisoflavone A were determined at resolutions of 1.54 Å and 1.65 Å, respectively, and both compounds bind in the active site of PDE4 with similar interactions. These findings will greatly stimulate the study of TCMT-NDRD against COVID-19.

The highly contagious coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic and public health emergency as it has taken the lives of over 5.7 million in more than 180 different countries. This disease is characterized by respiratory tract symptoms, such as dry cough and shortness of breath, as well as other symptoms, including fever, chills, and fatigue. COVID-19 is also characterized by the excessive release of cytokines causing inflammatory injury to the lungs and other organs. It is advised to undergo precautionary measures, such as vaccination, social distancing, use of masks, hygiene, and a healthy diet. This review is aimed at summarizing the pathophysiology of COVID-19 and potential biologically active compounds (bioactive) found in plants and plant food. We conclude that many plant food bioactive compounds exhibit antiviral and anti-inflammatory properties and support in attenuating organ damage due to reduced cytokine release and improving the recovery process from COVID-19 infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a substantial number of deaths around the world, making it a serious and pressing public health hazard. Phytochemicals could thus provide a rich source of potent and safer anti-SARS-CoV-2 drugs. The absence of approved treatments or vaccinations continues to be an issue, forcing the creation of new medicines. Computer-aided drug design has helped to speed up the drug research and development process by decreasing costs and time. Natural compounds like terpenoids, alkaloids, polyphenols, and flavonoid derivatives have a perfect impact against viral replication and facilitate future studies in novel drug discovery. This would be more effective if collaboration took place between governments, researchers, clinicians, and traditional medicine practitioners’ safe and effective therapeutic research. Through a computational approach, this study aims to contribute to the development of effective treatment methods by examining the mechanisms relating to the binding and subsequent inhibition of SARS-CoV-2 ribonucleic acid (RNA)-dependent RNA polymerase (RdRp). The in silico method has also been employed to determine the most effective drug among the mentioned compound and their aquatic, nonaquatic, and pharmacokinetics’ data have been analyzed. The highest binding energy has been reported -11.4 kcal/mol against SARS-CoV-2 main protease (7MBG) in L05. Besides, all the ligands are non-carcinogenic, excluding L04, and have good water solubility and no AMES toxicity. The discovery of preclinical drug candidate molecules and the structural elucidation of pharmacological therapeutic targets have expedited both structure-based and ligand-based drug design. This review article will assist physicians and researchers in realizing the enormous potential of computer-aided drug design in the design and discovery of therapeutic molecules, and hence in the treatment of deadly diseases.

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.

Significance Recent spread of SARS-CoV-2 has sparked significant health concerns of emerging infectious viruses. Drug repurposing is a tangible strategy for developing antiviral agents within a short period. In general, drug repurposing starts with virtual screening of approved drugs employing docking simulations. However, the actual hit rate is low, and most of the predicted compounds are false positives. To tackle the challenges, we report advanced virtual screening with pre- and postdocking pharmacophore filtering of 6,218 drugs for COVID-19. Notably, 7 out of 38 compounds showed efficacies in inhibiting SARS-CoV-2 in Vero cells. Three of these were also found to inhibit SARS-CoV-2 in human Calu-3 cells. Furthermore, three drug combinations showed strong synergistic effects in SARS-CoV-2 inhibition at their clinically achievable concentrations.