Microb Pathog. 2021 Jul 29:105114. doi: 10.1016/j.micpath.2021.105114. Online ahead of print.

ABSTRACT

Understanding the pathogenesis of SARS-CoV-2 is essential for developing effective treatment strategies. Viruses hijack the host metabolism to redirect the resources for their replication and survival. The influence of SARS-CoV-2 on host metabolism is yet to be fully understood. In this study, we analyzed the transcriptomic data obtained from different human respiratory cell lines and patient samples (nasopharyngeal swab, peripheral blood mononuclear cells, lung biopsy, bronchoalveolar lavage fluid) to understand metabolic alterations in response to SARS-CoV-2 infection. We explored the expression pattern of metabolic genes in the comprehensive genome-scale network model of human metabolism, Recon3D, to extract key metabolic genes, pathways, and reporter metabolites under each SARS-CoV-2-infected condition. A SARS-CoV-2 core metabolic interactome was constructed for network-based drug repurposing. Our analysis revealed the host-dependent dysregulation of glycolysis, mitochondrial metabolism, amino acid metabolism, nucleotide metabolism, glutathione metabolism, polyamine synthesis, and lipid metabolism. We observed different pro- and antiviral metabolic changes and generated hypotheses on how the host metabolism can be targeted for reducing viral titers and immunomodulation. These findings warrant further exploration with more samples and in vitro studies to test predictions.

PMID:34333072 | DOI:10.1016/j.micpath.2021.105114

Comput Biol Med. 2021 Jul 23;136:104677. doi: 10.1016/j.compbiomed.2021.104677. Online ahead of print.

ABSTRACT

Viral epidemics and pandemics are considered public health emergencies. However, traditional and novel antiviral discovery approaches are unable to mitigate them in a timely manner. Notably, drug repurposing emerged as an alternative strategy to provide antiviral solutions in a timely and cost-effective manner. In the literature, many FDA-approved drugs have been repurposed to inhibit viruses, while a few among them have also entered clinical trials. Using experimental data, we identified repurposed drugs against 14 viruses responsible for causing epidemics and pandemics such as SARS-CoV-2, SARS, Middle East respiratory syndrome, influenza H1N1, Ebola, Zika, Nipah, chikungunya, and others. We developed a novel computational "drug-target-drug" approach that uses the drug-targets extracted for specific drugs, which are experimentally validated in vitro or in vivo for antiviral activity. Furthermore, these extracted drug-targets were used to fetch the novel FDA-approved drugs for each virus and prioritize them by calculating their confidence scores. Pathway analysis showed that the majority of the extracted targets are involved in cancer and signaling pathways. For SARS-CoV-2, our method identified 21 potential repurposed drugs, of which 7 (e.g., baricitinib, ramipril, chlorpromazine, enalaprilat, etc.) have already entered clinical trials. The prioritized drug candidates were further validated using a molecular docking approach. Therefore, we anticipate success during the experimental validation of our predicted FDA-approved repurposed drugs against 14 viruses. This study will assist the scientific community in hastening research aimed at the development of antiviral therapeutics.

PMID:34332351 | DOI:10.1016/j.compbiomed.2021.104677

Biomed Pharmacother. 2021 Jul 22;141:111916. doi: 10.1016/j.biopha.2021.111916. Online ahead of print.

ABSTRACT

Naodesheng (NDS) tablets have been widely used to treat ischemic stroke clinically. NDS relieves neurological function impairment and improve learning and memory in rats with focal cerebral ischemia, suggesting that NDS has potential for Alzheimer's disease (AD) treatment. However, there are no studies about its effective material basis and possible mechanisms. In this study, a systems pharmacology method was applied to reveal the potential molecular mechanism of NDS in the treatment of AD. First, we obtained 360 NDS candidate constituents through ADMET filter analysis. Then, 115 AD-related targets were uncovered by pharmacophore model prediction via mapping the predicted targets against AD-related proteins. In addition, compound-target and target-function networks were established to suggest potential synergistic effects among the candidate constituents. Furthermore, potential targets regulated by NDS were integrated into AD-related pathways to demonstrate the therapeutic mechanism of NDS in AD treatment. Subsequently, a validation experiment proved the therapeutic effect of NDS on cognitive dysfunction in rats with intracerebroventricular injection of Aβ. We found that administration of NDS tablets regulates β-amyloid metabolism, improves synaptic plasticity, inhibits neuroinflammation and improves learning and memory function. In conclusion, this is the first study to provide a comprehensive systems pharmacology approach to elucidate the potential therapeutic mechanism of NDS tablets for AD treatment. We suggest that the protective effects of NDS in neurodegenerative conditions could be partly attributed to its role in improving synaptic plasticity and inhibiting neuroinflammation via NF-κB signaling pathway inhibition and cAMP/PKA/CREB signaling pathway activation.

PMID:34328103 | DOI:10.1016/j.biopha.2021.111916

Science. 2021 Jul 30;373(6554):541-547. doi: 10.1126/science.abi4708. Epub 2021 Jun 22.

ABSTRACT

Repurposing drugs as treatments for COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has drawn much attention. Beginning with sigma receptor ligands and expanding to other drugs from screening in the field, we became concerned that phospholipidosis was a shared mechanism underlying the antiviral activity of many repurposed drugs. For all of the 23 cationic amphiphilic drugs we tested, including hydroxychloroquine, azithromycin, amiodarone, and four others already in clinical trials, phospholipidosis was monotonically correlated with antiviral efficacy. Conversely, drugs active against the same targets that did not induce phospholipidosis were not antiviral. Phospholipidosis depends on the physicochemical properties of drugs and does not reflect specific target-based activities-rather, it may be considered a toxic confound in early drug discovery. Early detection of phospholipidosis could eliminate these artifacts, enabling a focus on molecules with therapeutic potential.

PMID:34326236 | DOI:10.1126/science.abi4708

BMC Bioinformatics. 2021 Jul 29;22(Suppl 10):387. doi: 10.1186/s12859-021-04292-4.

ABSTRACT

BACKGROUND: Stroke has an acute onset and a high mortality rate, making it one of the most fatal diseases worldwide. Its underlying biology and treatments have been widely studied both in the "Western" biomedicine and the Traditional Chinese Medicine (TCM). However, these two approaches are often studied and reported in insolation, both in the literature and associated databases.

RESULTS: To aid research in finding effective prevention methods and treatments, we integrated knowledge from the literature and a number of databases (e.g. CID, TCMID, ETCM). We employed a suite of biomedical text mining (i.e. named-entity) approaches to identify mentions of genes, diseases, drugs, chemicals, symptoms, Chinese herbs and patent medicines, etc. in a large set of stroke papers from both biomedical and TCM domains. Then, using a combination of a rule-based approach with a pre-trained BioBERT model, we extracted and classified links and relationships among stroke-related entities as expressed in the literature. We construct StrokeKG, a knowledge graph includes almost 46 k nodes of nine types, and 157 k links of 30 types, connecting diseases, genes, symptoms, drugs, pathways, herbs, chemical, ingredients and patent medicine.

CONCLUSIONS: Our Stroke-KG can provide practical and reliable stroke-related knowledge to help with stroke-related research like exploring new directions for stroke research and ideas for drug repurposing and discovery. We make StrokeKG freely available at http://114.115.208.144:7474/browser/ (Please click "Connect" directly) and the source structured data for stroke at https://github.com/yangxi1016/Stroke.

PMID:34325669 | DOI:10.1186/s12859-021-04292-4

Curr Neuropharmacol. 2021 Jul 29. doi: 10.2174/1570159X19666210729123734. Online ahead of print.

ABSTRACT

BACKGROUND: Whereas the World faces an unprecedented pandemic caused by the SARS-CoV-2 virus, repositioning existing drugs to treat COVID-19 disease is urgently awaited, provided that high-quality scientific evidence supporting safety and efficacy in this new indication is gathered. Efforts concerning drug repositioning to COVID-19 were mostly focused on antiviral drugs or drugs targeting the late phase of the disease.

METHODS: Based on published research, the pharmacological activities of fluvoxamine and amantadine, two well-known drugs widely used in clinical practice for psychiatric and neurological diseases, respectively, have been reviewed, focusing on their potential therapeutic importance in the treatment of COVID-19.

RESULTS: Several preclinical and clinical reports were identified suggesting that these two drugs might exert protective effects in the early phases of COVID-19.

CONCLUSION: Preclinical and early clinical evidence are presented indicating that these drugs hold promise to prevent COVID-19 progression when administered early during infection.

PMID:34325642 | DOI:10.2174/1570159X19666210729123734

PLoS One. 2021 Jul 29;16(7):e0255270. doi: 10.1371/journal.pone.0255270. eCollection 2021.

ABSTRACT

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become the current health concern and threat to the entire world. Thus, the world needs the fast recognition of appropriate drugs to restrict the spread of this disease. The global effort started to identify the best drug compounds to treat COVID-19, but going through a series of clinical trials and our lack of information about the details of the virus's performance has slowed down the time to reach this goal. In this work, we try to select the subset of human proteins as candidate sets that can bind to approved drugs. Our method is based on the information on human-virus protein interaction and their effect on the biological processes of the host cells. We also define some informative topological and statistical features for proteins in the protein-protein interaction network. We evaluate our selected sets with two groups of drugs. The first group contains the experimental unapproved treatments for COVID-19, and we show that from 17 drugs in this group, 15 drugs are approved by our selected sets. The second group contains the external clinical trials for COVID-19, and we show that 85% of drugs in this group, target at least one protein of our selected sets. We also study COVID-19 associated protein sets and identify proteins that are essential to disease pathology. For this analysis, we use DAVID tools to show and compare disease-associated genes that are contributed between the COVID-19 comorbidities. Our results for shared genes show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. In the last part of this work, we recommend 56 potential effective drugs for further research and investigation for COVID-19 treatment. Materials and implementations are available at: https://github.com/MahnazHabibi/Drug-repurposing.

PMID:34324563 | DOI:10.1371/journal.pone.0255270

Mol Cell Biochem. 2021 Jul 29. doi: 10.1007/s11010-021-04230-1. Online ahead of print.

ABSTRACT

Despite the existing therapies and lack of receptors such as HER-2, estrogen receptor and progesterone receptor, triple-negative breast cancer is one of the most aggressive subtypes of breast cancer. TNBCs are known for their highly aggressive metastatic behavior and typically migrate to brain and bone for secondary site propagation. Many diseases share similar molecular pathology exposing new avenues in molecular signaling for engendering innovative therapies. Generation of newer therapies and novel drugs are time consuming associated with very high resources. In order to provide personalized or precision medicine, drug repositioning will contribute in a cost-effective manner. In our study, we have repurposed and used a neoteric combination of two drug molecules namely, fluvoxamine and tivozanib, to target triple-negative breast cancer growth and progression. Our combination regime significantly targets two diverse but significant pathways in TNBCs. Subsequent analysis on migratory, invasive, and angiogenic properties showed the significance of our repurposed drug combination. Molecular array data resulted in identifying the specific and key players participating in cancer progression when the drug combination was used. The innovative combination of fluvoxamine and tivozanib reiterates the use of drug repositioning for precision medicine and subsequent companion diagnostic development.

PMID:34324118 | DOI:10.1007/s11010-021-04230-1

Recent Pat Anticancer Drug Discov. 2021 Jul 28. doi: 10.2174/1574892816666210728123758. Online ahead of print.

ABSTRACT

BACKGROUND: The development of cancer drugs is among the most focused "bench to bedside activities" to improve human health. Because of the amount of data publicly available to cancer research, drug development for cancers has significantly benefited from big data and AI. In the meantime, challenges, like curating the data of low quality, remain to be resolved.

OBJECTIVE: This review focused on the recent advancements in and challenges of AI in developing cancer drugs.

METHOD: We discussed target validation, drug repositioning, de novo design, and compounds' synthetic strategies.

RESULTS AND CONCLUSION: AI can be applied to all stages during drug development, and some excellent reviews detailing the applications of AI in specific stages are available.

PMID:34323201 | DOI:10.2174/1574892816666210728123758

Recent Pat Anticancer Drug Discov. 2021 Jul 27. doi: 10.2174/1574892816666210728115605. Online ahead of print.

ABSTRACT

The heterogeneous tumor microenvironment is exceptionally perplexing and not wholly comprehended. Different multifaceted alignments lead to the generation of oxygen destitute situations within the tumor niche that modulate numerous intrinsic tumor microenvironments. Disentangling these communications is vital for scheming practical therapeutic approaches that can successfully decrease tumor allied chemotherapy resistance by utilizing the innate capability of the immune system. Several research groups have concerned with a protruding role for oxygen metabolism along with hypoxia in the immunity of healthy tissue. Hypoxia in addition to hypoxia-inducible factors (HIFs) in the tumor microenvironment plays an important part in tumor progression and endurance. Although numerous hypoxia-focused therapies have shown promising outcomes both in vitro and in vivo these outcomes have not effectively translated into clinical preliminaries. Distinctive cell culture techniques have utilized as an in vitro model for tumor niche along with tumor microenvironment and proficient in more precisely recreating tumor genomic profiles as well as envisaging therapeutic response. To study the dynamics of tumor immune evasion, three-dimensional (3D) cell cultures are more physiologically important to the hypoxic tumor microenvironment. Recent research has revealed new information and insights into our fundamental understanding of immune systems, as well as novel results that have been established as potential therapeutic targets. There are a lot of patented 3D cell culture techniques which will be highlighted in this review. At present notable 3D cell culture procedures in the hypoxic tumor microenvironment, discourse open doors to accommodate both drug repurposing, advancement, and divulgence of new medications and will deliberate the 3D cell culture methods into standard prescription disclosure especially in the field of cancer biology which will be discussing here.

PMID:34323197 | DOI:10.2174/1574892816666210728115605

World J Gastrointest Oncol. 2021 Jul 15;13(7):638-661. doi: 10.4251/wjgo.v13.i7.638.

ABSTRACT

Colorectal cancer (CRC) is the most commonly diagnosed fatal cancer in both women and men worldwide. CRC ranked second in mortality and third in incidence in 2020. It is difficult to diagnose CRC at an early stage as there are no clinical symptoms. Despite advances in molecular biology, only a limited number of biomarkers have been translated into routine clinical practice to predict risk, prognosis and response to treatment. In the last decades, systems biology approaches at the omics level have gained importance. Over the years, several biomarkers for CRC have been discovered in terms of disease diagnosis and prognosis. On the other hand, a few drugs are being developed and used in clinics for the treatment of CRC. However, the development of new drugs is very costly and time-consuming as the research and development takes about 10 years and more than $1 billion. Therefore, drug repositioning (DR) could save time and money by establishing new indications for existing drugs. In this review, we aim to provide an overview of biomarkers for the diagnosis and prognosis of CRC from the systems biology perspective and insights into DR approaches for the prevention or treatment of CRC.

PMID:34322194 | PMC:PMC8299930 | DOI:10.4251/wjgo.v13.i7.638

J Inflamm Res. 2021 Jul 20;14:3419-3428. doi: 10.2147/JIR.S322831. eCollection 2021.

ABSTRACT

In the first year of its appearance, the 2019 coronavirus disease (COVID-19) has affected more than 150 million individuals and killed 3 million people worldwide. The pandemic has also triggered numerous global initiatives to tackle the newly emerging disease, including the development of SARS-CoV-2 vaccines and the attempt to discover potential pharmacological therapies. Nonetheless, despite the success of SARS-CoV-2 vaccine development, COVID-19 therapy remains challenging. Several repurposed drugs that were documented to be useful in small clinical trials have been shown to be ineffective in larger studies. Additionally, the pathophysiology of SARS-CoV-2 infection displayed the predominance of hyperinflammation and immune dysregulation in inducing multiorgan damage. Therefore, the potential benefits of both immune modulation and suppression in COVID-19 have been extensively discussed. Here, we reviewed the roles of immunomodulation as potential COVID-19 pharmacological modalities based on the existing data and proposed several new immunologic targets to be tested in the foreseeable future.

PMID:34321903 | PMC:PMC8312605 | DOI:10.2147/JIR.S322831

J Immunother Cancer. 2021 Jul;9(7):e001587. doi: 10.1136/jitc-2020-001587.

ABSTRACT

BACKGROUND: Modified vaccinia virus Ankara (MVA) are genetically engineered non-replicating viral vectors. Intratumoral administration of MVA induces a cyclic GMP-AMP synthase-mediated type I interferon (IFN) response and the production of high levels of the transgenes engineered into the viral genome such as tumor antigens to construct cancer vaccines. Although type I IFNs are essential for establishing CD8-mediated antitumor responses, this cytokine family may also give rise to immunosuppressive mechanisms.

METHODS: In vitro assays were performed to evaluate the activity of simvastatin and atorvastatin on type I IFN signaling and on antigen presentation. Surface levels of IFN α/β receptor 1, endocytosis of bovine serum albumin-fluorescein 5 (6)-isothiocyanate, signal transducer and activator of transcription (STAT) phosphorylation, and real-time PCR of IFN-stimulated genes were assessed in the murine fibroblast cell line L929. In vivo experiments were performed to characterize the effect of simvastatin on the MVA-induced innate immune response and on the antitumor effect of MVA-based antitumor vaccines in B16 melanoma expressing ovalbumin (OVA) and Lewis lung carcinoma (LLC)-OVA tumor models. RNAseq analysis, depleting monoclonal antibodies, and flow cytometry were used to evaluate the MVA-mediated immune response.

RESULTS: In this work, we identified commonly prescribed statins as potent IFNα pharmacological inhibitors due to their ability to reduce surface expression levels of IFN-α/β receptor 1 and to reduce clathrin-mediated endocytosis. Simvastatin and atorvastatin efficiently abrogated for 8 hours the transcriptomic response to IFNα and enhanced the number of dendritic cells presenting an OVA-derived peptide bound to major histocompatibility complex (MHC) class I. In vivo, intraperitoneal or intramuscular administration of simvastatin reduced the inflammatory response mediated by peritumoral administration of MVA and enhanced the antitumor activity of MVA encoding tumor-associated antigens. The synergistic antitumor effects critically depend on CD8+ cells, whereas they were markedly improved by depletion of CD4+ lymphocytes, T regulatory cells, or NK cells. Either MVA-OVA alone or combined with simvastatin augmented B cells, CD4+ lymphocytes, CD8+ lymphocytes, and tumor-specific CD8+ in the tumor-draining lymph nodes. However, only the treatment combination increased the numbers of these lymphocyte populations in the tumor microenvironment and in the spleen.

CONCLUSION: In conclusion, blockade of IFNα functions by simvastatin markedly enhances lymphocyte infiltration and the antitumor activity of MVA, prompting a feasible drug repurposing.

PMID:34321273 | DOI:10.1136/jitc-2020-001587

Bioinformatics. 2021 Jul 28:btab548. doi: 10.1093/bioinformatics/btab548. Online ahead of print.

ABSTRACT

MOTIVATION: In silico drug-target interaction (DTI) prediction is important for drug discovery and drug repurposing. Approaches to predict DTIs can proceed indirectly, top-down, using phenotypic effects of drugs to identify potential drug targets, or they can be direct, bottom-up and use molecular information to directly predict binding affinities. Both approaches can be combined with information about interaction networks.

RESULTS: We developed DTI-Voodoo as a computational method that combines molecular features and ontology-encoded phenotypic effects of drugs with protein-protein interaction networks, and uses a graph convolutional neural network to predict DTIs. We demonstrate that drug effect features can exploit information in the interaction network whereas molecular features do not. DTI-Voodoo is designed to predict candidate drugs for a given protein; we use this formulation to show that common DTI datasets contain intrinsic biases with major effects on performance evaluation and comparison of DTI prediction methods. Using a modified evaluation scheme, we demonstrate that DTI-Voodoo improves significantly over state of the art DTI prediction methods.

AVAILABILITY: DTI-Voodoo source code and data necessary to reproduce results are freely available at https://github.com/THinnerichs/DTI-VOODOO.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34320178 | DOI:10.1093/bioinformatics/btab548

J Pharm Pharm Sci. 2021;24:390-399. doi: 10.18433/jpps31931.

ABSTRACT

PURPOSE: SARS-CoV-2 infection is associated with substantial mortality and high morbidity. This study tested the effect of angiotensin II type I receptor blocker, losartan, on SARS-CoV-2 replication and inhibition of the papain-like protease of the virus.

METHODS: The dose-dependent inhibitory effect of losartan, in concentrations from 1μM to 100μM as determined by quantitative cell analysis combining fluorescence microscopy, image processing, and cellular measurements (Cellomics analysis) on SARS-CoV-2 replication was investigated in Vero E6 cells. The impact of losartan on deubiquitination and deISGylation of SARS-CoV-2 papain-like protease (PLpro) were also evaluated. Results: Losartan reduced PLpro cleavage of tetraUbiquitin to diUbiquitin. It was less effective in inhibiting PLpro's cleavage of ISG15-AMC than Ubiquitin-AMC. To determine if losartan inhibited SARS-CoV-2 replication, losartan treatment of SARS-CoV-2 infected Vero E6 was examined. Losartan treatment one hour prior to SARS-CoV-2 infection reduced levels of SARS-CoV-2 nuclear protein, an indicator of virus replication, by 80% and treatment one-hour post-infection decreased viral replication by 70%.

CONCLUSION: Losartan was not an effective inhibitor of deubiquitinase or deISGylase activity of the PLpro but affected the SARS-CoV-2 replication of Vero E6 cells in vitro. As losartan has a favorable safety profile and is currently available it has features necessary for efficacious drug repurposing and treatment of COVID-19.

PMID:34319871 | DOI:10.18433/jpps31931

Clin Microbiol Rev. 2021 Jul 28:e0010921. doi: 10.1128/CMR.00109-21. Online ahead of print.

ABSTRACT

The development of effective antiviral therapy for COVID-19 is critical for those awaiting vaccination, as well as for those who do not respond robustly to vaccination. This review summarizes 1 year of progress in the race to develop antiviral therapies for COVID-19, including research spanning preclinical and clinical drug development efforts, with an emphasis on antiviral compounds that are in clinical development or that are high priorities for clinical development. The review is divided into sections on compounds that inhibit SARS-CoV-2 enzymes, including its polymerase and proteases; compounds that inhibit virus entry, including monoclonal antibodies; interferons; and repurposed drugs that inhibit host processes required for SARS-CoV-2 replication. The review concludes with a summary of the lessons to be learned from SARS-CoV-2 drug development efforts and the challenges to continued progress.

PMID:34319150 | DOI:10.1128/CMR.00109-21

J Phys Chem B. 2021 Jul 28. doi: 10.1021/acs.jpcb.1c04556. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.

PMID:34319118 | DOI:10.1021/acs.jpcb.1c04556

JACC Case Rep. 2021 Feb 24;3(3):392-396. doi: 10.1016/j.jaccas.2020.11.043. eCollection 2021 Mar.

ABSTRACT

Coronary spasm is a frequent cause of angina despite unobstructed coronary arteries, and symptom control with recommended drugs is limited. We report the case of a 77-year-old woman who had refractory angina despite conventional antianginal treatment. Repurposing riociguat, a soluble guanylate cyclase stimulator, resulted in improvement of symptoms and prevention of spasm. (Level of Difficulty: Intermediate.).

PMID:34317544 | PMC:PMC8311038 | DOI:10.1016/j.jaccas.2020.11.043

Clin Pharmacol Ther. 2021 Jul 27. doi: 10.1002/cpt.2376. Online ahead of print.

ABSTRACT

This study aimed to systematically investigate if any of the available drugs in Electronic Health Record (EHR) can be repurposed as potential treatment for COVID-19. Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on 9,748 COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Patient exposure to a drug between 3-months prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. All-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes. Overall, 17 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to two types of 13-valent pneumococcal conjugate vaccines, PCV13, (OR, 0.31; 95% CI, 0.12-0.81 and OR, 0.33; 95% CI, 0.15-0.73), diphtheria toxoid and tetanus toxoid vaccine (OR, 0.38; 95% CI, 0.15-0.93) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: acellular pertussis vaccine, 23-valent pneumococcal polysaccharide vaccine (PPSV23), flaxseed extract, ethinyl estradiol, estradiol, turmeric extract, ubidecarenone, azelastine, pseudoephedrine, dextromethorphan, omega-3 fatty acids, fluticasone, and ibuprofen. In conclusion, this cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

PMID:34314511 | DOI:10.1002/cpt.2376

J Chem Inf Model. 2021 Jul 27. doi: 10.1021/acs.jcim.1c00384. Online ahead of print.

ABSTRACT

The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices-including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.

PMID:34313439 | DOI:10.1021/acs.jcim.1c00384