Web resources facilitate drug discovery in treatment of COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Mei LC
PROVIDER: S-EPMC8056987 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the COVID-19 pandemic, drug repositioning has presented itself as an alternative to the time-consuming process of generating new drugs. This review describes a drug repurposing process that is based on a new data-driven approach: we put forward five information paths that associate COVID-19-related genes and COVID-19 symptoms with drugs that directly target these gene products, that target the symptoms or that treat diseases that are symptomatically or genetically similar to COVID-19. The intersection of the five information paths results in a list of 13 drugs that we suggest as potential candidates against COVID-19. In addition, we have found information in published studies and in clinical trials that support the therapeutic potential of the drugs in our final list.
| S-EPMC8520166 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) started as an epidemic in Wuhan in 2019, and has since become a pandemic. Groups from China identified and sequenced the virus responsible for COVID-19, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and determined that it was a novel coronavirus sharing high sequence identity with bat- and pangolin-derived SARS-like coronaviruses, suggesting a zoonotic origin. SARS-CoV-2 is a member of the Coronaviridae family of enveloped, positive-sense, single-stranded RNA viruses that infect a broad range of vertebrates. The rapid release of the sequence of the virus has enabled the development of diagnostic tools. Additionally, serological tests can now identify individuals who have been infected. SARS-CoV-2 infection is associated with a fatality rate of around 1-3%, which is commonly linked to the development of acute respiratory distress syndrome (ARDS), likely resulting from uncontrolled immune activation, the so called "cytokine storm". Risk factors for mortality include advanced age, obesity, diabetes, and hypertension. Drug repurposing has been used to rapidly identify potential treatments for COVID-19, which could move quickly to phase III. Better knowledge of the virus and its enzymes will aid the development of more potent and specific direct-acting antivirals. In the long term, a vaccine to prevent infection is crucial; however, even if successful, it might not be available before 2021-22. To date, except for intravenous remdesivir and dexamethasone, which have modest effects in moderate to severe COVID-19, no strong clinical evidence supports the efficacy of any other drugs against SARS-CoV-2. The aim of this review is to provide insights on the discovery of SARS-CoV-2, its virology, diagnostic tools, and the ongoing drug discovery effort.
| S-EPMC7543767 | biostudies-literature
Project description:BackgroundSince the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in finding a potential therapeutic agent for the disease. Considering the matter of time, the computational methods of drug repurposing offer the best chance of selecting one drug from a list of approved drugs for the life-threatening condition of COVID-19. The present systematic review aims to provide an overview of studies that have used computational methods for drug repurposing in COVID-19.MethodsWe undertook a systematic search in five databases and included original articles in English that applied computational methods for drug repurposing in COVID-19.ResultsTwenty-one original articles utilizing computational drug methods for COVID-19 drug repurposing were included in the systematic review. Regarding the quality of eligible studies, high-quality items including the use of two or more approved drug databases, analysis of molecular dynamic simulation, multi-target assessment, the use of crystal structure for the generation of the target sequence, and the use of AutoDock Vina combined with other docking tools occurred in about 52%, 38%, 24%, 48%, and 19% of included studies. Studies included repurposed drugs mainly against non-structural proteins of SARS-CoV2: the main 3C-like protease (Lopinavir, Ritonavir, Indinavir, Atazanavir, Nelfinavir, and Clocortolone), RNA-dependent RNA polymerase (Remdesivir and Ribavirin), and the papain-like protease (Mycophenolic acid, Telaprevir, Boceprevir, Grazoprevir, Darunavir, Chloroquine, and Formoterol). The review revealed the best-documented multi-target drugs repurposed by computational methods for COVID-19 therapy as follows: antiviral drugs commonly used to treat AIDS/HIV (Atazanavir, Efavirenz, and Dolutegravir Ritonavir, Raltegravir, and Darunavir, Lopinavir, Saquinavir, Nelfinavir, and Indinavir), HCV (Grazoprevir, Lomibuvir, Asunaprevir, Ribavirin, and Simeprevir), HBV (Entecavir), HSV (Penciclovir), CMV (Ganciclovir), and Ebola (Remdesivir), anticoagulant drug (Dabigatran), and an antifungal drug (Itraconazole).ConclusionsThe present systematic review provides a list of existing drugs that have the potential to influence SARS-CoV2 through different mechanisms of action. For the majority of these drugs, direct clinical evidence on their efficacy for the treatment of COVID-19 is lacking. Future clinical studies examining these drugs might come to conclude, which can be more useful to inhibit COVID-19 progression.
| S-EPMC7676368 | biostudies-literature
Project description:Importance: There is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19). Objective: To systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19. Design, Setting, and Participants: Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on 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. Exposures: Patient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format. Main Outcomes and Measures: 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. Results: The study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) 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: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone. Conclusions and Relevance: 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.
| S-EPMC7872383 | biostudies-literature
Project description:This review highlights the cutting-edge informatics resources available to explore cancer genomics, biological, and chemical space to facilitate target and therapeutic discovery in cancer. The advances in cancer genomics, chemical biology, high-throughput screening technologies, and synthetic medicinal chemistry have tremendously expanded the biological space of cancer targets and chemical space of bioactive small molecules to interrogate oncogenic signaling. To explore and leverage these exponentially growing cancer-associated data, a great number of computational tools, databases, and algorithms have been developed. This review summarizes recent cancer-related web resources that allow researchers working at the interface of chemical, biological, and cancer genomics fields to integrate clinical and genomics data for specific actionable targets and selective chemical compounds to facilitate cancer therapeutic discovery.
| S-EPMC7429978 | biostudies-literature
Project description:Solid organ transplants (SOTs) are life-saving interventions, recently challenged by coronavirus disease 2019 (COVID-19). SOTs require a multistep process, which can be affected by COVID-19 at several phases.MethodsSOT-specialists, COVID-19-specialists, and medical ethicists designed an international survey according to CHERRIES guidelines. Personal opinions about continuing SOTs, safe managing of donors and recipients, as well as equity of resources' allocation were investigated. The survey was sent by e-mail. Multiple approaches were used (corresponding authors from Scopus, websites of scientific societies, COVID-19 webinars). After the descriptive analysis, univariate and multivariate ordinal regression analysis was performed.ResultsThere were 1819 complete answers from 71 countries. The response rate was 49%. Data were stratified according to region, macrospecialty, and organ of interest. Answers were analyzed using univariate-multivariate ordinal regression analysis and thematic analysis. Overall, 20% of the responders thought SOTs should not stop (continue transplant without restriction); over 70% suggested SOTs should selectively stop, and almost 10% indicated they should completely stop. Furthermore, 82% agreed to shift resources from transplant to COVID-19 temporarily. Briefly, main reason for not stopping was that if the transplant will not proceed, the organ will be wasted. Focusing on SOT from living donors, 61% stated that activity should be restricted only to "urgent" cases. At the multivariate analysis, factors identified in favor of continuing transplant were Italy, ethicist, partially disagreeing on the equity question, a high number of COVID-19-related deaths on the day of the answer, a high IHDI country. Factors predicting to stop SOTs were Europe except-Italy, public university hospital, and strongly agreeing on the equity question.ConclusionsIn conclusion, the majority of responders suggested that transplant activity should be continued through the implementation of isolation measures and the adoption of the COVID-19-free pathways. Differences between professional categories are less strong than supposed.
| S-EPMC8184017 | biostudies-literature
Project description:The emergence of the new coronavirus (nCoV-19) has impacted human health on a global scale, while the interaction between the virus and the host is the foundation of the disease. The viral genome codes a cluster of proteins, each with a unique function in the event of host invasion or viral development. Under the current adverse situation, we employ virtual screening tools in searching for drugs and natural products which have been already deposited in DrugBank in an attempt to accelerate the drug discovery process. This study provides an initial evaluation of current drug candidates from various reports using our systemic in silico drug screening based on structures of viral proteins and human ACE2 receptor. Additionally, we have built an interactive online platform (https://shennongproject.ai/) for browsing these results with the visual display of a small molecule docked on its potential target protein, without installing any specialized structural software. With continuous maintenance and incorporation of data from laboratory work, it may serve not only as the assessment tool for the new drug discovery but also an educational web site for the public.
| S-EPMC7460831 | biostudies-literature
Project description: Not available
| S-EPMC8155633 | biostudies-literature
Project description:The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat.
| S-EPMC7799271 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) is the latest respiratory pandemic resulting from zoonotic transmission of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). Severe symptoms include viral pneumonia secondary to infection and inflammation of the lower respiratory tract, in some cases causing death. We developed primary human lung epithelial infection models to understand responses of proximal and distal lung epithelium to SARS-CoV-2 infection. Differentiated air-liquid interface cultures of proximal airway epithelium and 3D organoid cultures of alveolar epithelium were readily infected by SARS-CoV-2 leading to an epithelial cell-autonomous proinflammatory response. We validated the efficacy of selected candidate COVID-19 drugs confirming that Remdesivir strongly suppressed viral infection/replication. We provide a relevant platform for studying COVID-19 pathobiology and for rapid drug screening against SARS-CoV-2 and future emergent respiratory pathogens.
2020-11-06 | GSE155518 | GEO