Mycophenolic acid for COVID-19

Abstract The prediction of virus–drug associations (VDAs) is crucial for drug repositioning, contributing to the identification of latent antiviral drugs. In this study, we developed a graph-based integrated Gaussian kernel similarity (GiGs) method for predicting potential VDAs in drug repositioning. The GiGs model comprises three components: (i) collection of experimentally validated VDA information and calculation virus sequence, drug chemical structure, and drug side effect similarity; (ii) integration of viruses and drugs similarity based on the above information and Gaussian interaction profile kernel (GIPK); and (iii) utilization of similarity-constrained weight graph normalization matrix factorization to predict antiviral drugs. The GiGs model enhances correlation matrix quality through the integration of multiple biological data, improves performance via similarity constraints, and prevents overfitting and predicts missing data more accurately through graph regularization. Extensive experimental results indicated that the GiGs model outperforms five other advanced association prediction methods. A case study identified broad-spectrum drugs for treating highly pathogenic human coronavirus infections, with molecular docking experiments confirming the model’s accuracy.

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) caused an outbreak in 2002-2003, spreading to 29 countries with a mortality rate of about 10%. Strict quarantine and infection control methods quickly stopped the spread of the disease. Later research showed that SARS-CoV came from animals (zoonosis) and stressed the possibility of a similar spread from host to human, which was clearly shown by the COVID-19 outbreak. The COVID-19 pandemic, instigated by SARS-CoV-2, has affected 776 million confirmed cases and more than seven million deaths globally as of Sept 15, 2024. The existence of animal reservoirs of coronaviruses continues to pose a risk of re-emergence with improved fitness and virulence. Given the high death rate (up to 70 percent) and the high rate of severe sickness (up to 68.7 percent in long-COVID patients), it is even more critical to identify new therapies as soon as possible. This study combines research on antivirals that target SARS coronaviruses that have been conducted over the course of more than twenty years. It is a beneficial resource that might be useful in directing future studies.

Background:The development and roll-out of vaccines, and the use of various drugs have contributed to controlling the COVID-19 pandemic. Nevertheless, challenges such as the inequitable distribution of vaccines, the influence of emerging viral lineages and immune evasive variants on vaccine efficacy, and the inadequate immune defense in subgroups of the population continue to motivate the development of new drugs to combat the disease. Aim:In this study, we sought to identify, prioritize, and characterize drug repurposing candidates appropriate for treating mild, moderate, or severe COVID-19 using a network-based integrative approach that systematically integrates drug-related data and multi-omics datasets. Methods: We leveraged drug data, and multi-omics data, and used a random walk restart algorithm to explore an integrated knowledge graph comprised of three sub-graphs: (i) a COVID-19 knowledge graph, (ii) a drug repurposing knowledge graph, and (iii) a COVID-19 disease-state specific omics graph. Results:We prioritized twenty FDA-approved agents as potential candidate drugs for mild, moderate, and severe COVID-19 disease phases. Specifically, drugs that could stimulate immune cell recruitment and activation including histamine, curcumin, and paclitaxel have potential utility in mild disease states to mitigate disease progression. Drugs like omacetaxine, crizotinib, and vorinostat that exhibit antiviral properties and have the potential to inhibit viral replication can be considered for mild to moderate COVID-19 disease states. Also, given the association between antioxidant deficiency and high inflammatory factors that trigger cytokine storms, antioxidants like glutathione can be considered for moderate disease states. Drugs that exhibit potent anti-inflammatory effects like (i) anti-inflammatory drugs (sarilumab and tocilizumab), (ii) corticosteroids (dexamethasone and hydrocortisone), and (iii) immunosuppressives (sirolimus and cyclosporine) are potential candidates for moderate to severe disease states that trigger a hyperinflammatory cascade of COVID-19. Conclusion:Our study demonstrates that the multi-omics data-driven integrative analysis within the drug data enables prioritizing drug candidates for COVID-19 disease phases, offering a comprehensive basis for therapeutic strategies that can be brought to market quickly given their established safety profiles. Importantly, the multi-omics data-driven integrative analysis within the drug data approach implemented here can be used to prioritize drug repurposing candidates appropriate for other diseases.

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.

ABSTRACTAn outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

Summary ParagraphThe SARS-CoV-2 virus has caused already over 3.5 million COVID-19 cases and 250,000 deaths globally. There is an urgent need to create novel models to study SARS-CoV-2 using human disease-relevant cells to understand key features of virus biology and facilitate drug screening. As primary SARS-CoV-2 infection is respiratory-based, we developed a lung organoid model using human pluripotent stem cells (hPSCs) that could be adapted for drug screens. The lung organoids, particularly aveolar type II cells, express ACE2 and are permissive to SARS-CoV-2 infection. Transcriptomic analysis following SARS-CoV-2 infection revealed a robust induction of chemokines and cytokines with little type I/III interferon signaling, similar to that observed amongst human COVID-19 pulmonary infections. We performed a high throughput screen using hPSC-derived lung organoids and identified FDA-approved drug candidates, including imatinib and mycophenolic acid, as inhibitors of SARS-CoV-2 entry. Pre- or post-treatment with these drugs at physiologically relevant levels decreased SARS-CoV-2 infection of hPSC-derived lung organoids. Together, these data demonstrate that hPSC-derived lung cells infected by SARS-CoV-2 can model human COVID-19 disease and provide a valuable resource to screen for FDA-approved drugs that might be repurposed and should be considered for COVID-19 clinical trials.

Summary ParagraphThe current COVID-19 pandemic is caused by SARS-coronavirus 2 (SARS-CoV-2). There are currently no therapeutic options for mitigating this disease due to lack of a vaccine and limited knowledge of SARS-CoV-2 biology. As a result, there is an urgent need to create new disease models to study SARS-CoV-2 biology and to screen for therapeutics using human disease-relevant tissues. COVID-19 patients typically present with respiratory symptoms including cough, dyspnea, and respiratory distress, but nearly 25% of patients have gastrointestinal indications including anorexia, diarrhea, vomiting, and abdominal pain. Moreover, these symptoms are associated with worse COVID-19 outcomes1. Here, we report using human pluripotent stem cell-derived colonic organoids (hPSC-COs) to explore the permissiveness of colonic cell types to SARS-CoV-2 infection. Single cell RNA-seq and immunostaining showed that the putative viral entry receptor ACE2 is expressed in multiple hESC-derived colonic cell types, but highly enriched in enterocytes. Multiple cell types in the COs can be infected by a SARS-CoV-2 pseudo-entry virus, which was further validated in vivo using a humanized mouse model. We used hPSC-derived COs in a high throughput platform to screen 1280 FDA-approved drugs against viral infection. Mycophenolic acid and quinacrine dihydrochloride were found to block the infection of SARS-CoV-2 pseudo-entry virus in COs both in vitro and in vivo, and confirmed to block infection of SARS-CoV-2 virus. This study established both in vitro and in vivo organoid models to investigate infection of SARS-CoV-2 disease-relevant human colonic cell types and identified drugs that blocks SARS-CoV-2 infection, suitable for rapid clinical testing.

AbstractCoronaviruses (CoVs) circulate in humans and animals, and expand their host range by zoonotic and anthroponotic transmissions. Endemic human CoVs, such as 229E and OC43 cause limited respiratory disease, and elicit short term anti-viral immunity favoring recurrent infections. Yet, severe acute respir-atory syndrome (SARS)-CoV-2 spreads across the globe with unprecedented impact on societies and economics. The world lacks broadly effective and affordable anti-viral agents to fight the pandemic and reduce the death toll. Here, we developed an image-based multicycle replication assay for focus for-mation of α-coronavirus hCoV-229E-eGFP infected cells for screening with a chemical library of 5440 compounds arrayed in 384 well format. The library contained about 39% clinically used compounds, 26% in phase I, II or III clinical trials, and 34% in preclinical development. Hits were counter-selected against toxicity, and challenged with hCoV-OC43 and SARS-CoV-2 in tissue culture and human bronchial and nasal epithelial explant cultures from healthy donors. Fifty three compounds inhibited hCoV-229E-GFP, 39 of which at 50% effective concentrations (EC50) < 2μM, and were at least 2-fold separated from toxicity. Thirty nine of the 53 compounds inhibited the replication of hCoV-OC43, while SARS-CoV-2 was inhibited by 11 compounds in at least two of four tested cell lines. Six of the 11 compounds are FDA-approved, one of which is used in mouth wash formulations, and five are systemic and orally available. Here, we demonstrate that methylene blue (MB) and mycophenolic acid (MPA), two broadly available low cost compounds, strongly inhibited shedding of infectious SARS-CoV-2 at the apical side of the cultures, in either pre- or post-exposure regimens, with somewhat weaker effects on viral RNA release indicated by RT-qPCR measurements. Our study illustrates the power of full cycle screens in repurposing clinical compounds against SARS-CoV-2. Importantly, both MB and MPA reportedly act as immunosuppressants, making them interesting candidates to counteract the cytokine storms affecting COVID-19 patients.

ABSTRACTVaccines and drugs are two effective medical interventions to mitigate SARS-CoV-2 infection. Three SARS-CoV-2 inhibitors, remdesivir, paxlovid, and molnupiravir, have been approved for treating COVID-19 patients, but more are needed, because each drug has its limitation of usage and SARS-CoV-2 constantly develops drug resistance mutations. In addition, SARS-CoV-2 drugs have the potential to be repurposed to inhibit new human coronaviruses, thus help to prepare for future coronavirus outbreaks. We have screened a library of microbial metabolites to discover new SARS-CoV-2 inhibitors. To facilitate this screening effort, we generated a recombinant SARS-CoV-2 Delta variant carrying the nano luciferase as a reporter for measuring viral infection. Six compounds were found to inhibit SARS-CoV-2 at the half maximal inhibitory concentration (IC50) below 1 μM, including the anthracycline drug aclarubicin that markedly reduced viral RNA-dependent RNA polymerase (RdRp)-mediated gene expression, whereas other anthracyclines inhibited SARS-CoV-2 by activating the expression of interferon and antiviral genes. As the most commonly prescribed anti-cancer drugs, anthracyclines hold the promise of becoming new SARS-CoV-2 inhibitors.IMPORTANCEMicrobial metabolites are a rich source of bioactive molecules. The best examples are antibiotics and immunosuppressants that have transformed the practice of modern medicine and saved millions of lives. Recently, some microbial metabolites were reported to have antiviral activity, including the inhibition of Zika virus and Ebola virus. In this study, we discovered several microbial metabolites that effectively inhibit SARS-CoV-2 infection, including anthracyclines that have also been shown to inhibit other viruses including Ebola virus through enhancing interferon responses, which indicates potentially broad antiviral properties of these microbial metabolites and can lead to the discovery of pan-antiviral molecules.

Abstract The ongoing coronavirus disease 2019 (COVID-19) pandemic has highlighted the need to better understand virus–host interactions. We developed a network-based method that expands the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)–host protein interaction network and identifies host targets that modulate viral infection. To disrupt the SARS-CoV-2 interactome, we systematically probed for potent compounds that selectively target the identified host proteins with high expression in cells relevant to COVID-19. We experimentally tested seven chemical inhibitors of the identified host proteins for modulation of SARS-CoV-2 infection in human cells that express ACE2 and TMPRSS2. Inhibition of the epigenetic regulators bromodomain-containing protein 4 (BRD4) and histone deacetylase 2 (HDAC2), along with ubiquitin-specific peptidase (USP10), enhanced SARS-CoV-2 infection. Such proviral effect was observed upon treatment with compounds JQ1, vorinostat, romidepsin and spautin-1, when measured by cytopathic effect and validated by viral RNA assays, suggesting that the host proteins HDAC2, BRD4 and USP10 have antiviral functions. We observed marked differences in antiviral effects across cell lines, which may have consequences for identification of selective modulators of viral infection or potential antiviral therapeutics. While network-based approaches enable systematic identification of host targets and selective compounds that may modulate the SARS-CoV-2 interactome, further developments are warranted to increase their accuracy and cell-context specificity.

The novel coronavirus pneumonia COVID-19 infected by SARS-CoV-2 has attracted worldwide attention. It is urgent to find effective therapeutic strategies for stopping COVID-19. In this study, a Bounded Nuclear Norm Regularization (BNNR) method is developed to predict anti-SARS-CoV-2 drug candidates. First, three virus-drug association datasets are compiled. Second, a heterogeneous virus-drug network is constructed. Third, complete genomic sequences and Gaussian association profiles are integrated to compute virus similarities; chemical structures and Gaussian association profiles are integrated to calculate drug similarities. Fourth, a BNNR model based on kernel similarity (VDA-GBNNR) is proposed to predict possible anti-SARS-CoV-2 drugs. VDA-GBNNR is compared with four existing advanced methods under fivefold cross-validation. The results show that VDA-GBNNR computes better AUCs of 0.8965, 0.8562, and 0.8803 on the three datasets, respectively. There are 6 anti-SARS-CoV-2 drugs overlapping in any two datasets, that is, remdesivir, favipiravir, ribavirin, mycophenolic acid, niclosamide, and mizoribine. Molecular dockings are conducted for the 6 small molecules and the junction of SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2. In particular, niclosamide and mizoribine show higher binding energy of −8.06 and −7.06 kcal/mol with the junction, respectively. G496 and K353 may be potential key residues between anti-SARS-CoV-2 drugs and the interface junction. We hope that the predicted results can contribute to the treatment of COVID-19.