L1000 connectivity map interrogation identifies candidate drugs for repurposing as SARS-CoV-2 antiviral therapies.
Ontology highlight
ABSTRACT:
SUBMITTER: Sendama W
PROVIDER: S-EPMC7719280 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Drug repurposing aims to find novel indications of clinically used or experimental drugs. Because drug data already exist, drug repurposing may save time and cost, and bypass safety concerns. Polypharmacology, one drug with multiple targets, serves as a basis for drug repurposing. Large-scale databases have been accumulated in recent years, and utilization and integration of these databases would be highly helpful for polypharmacology and drug repurposing. The Connectivity Map (CMap) is a database collecting gene-expression profiles of drug-treated human cancer cells, which has been widely used for investigation of polypharmacology and drug repurposing. In this study, we integrated the next-generation L1000-based CMap and an analytic Web tool, the L1000FWD, for systematic analyses of polypharmacology and drug repurposing. Two different types of anti-cancer drugs were used as proof-of-concept examples, including histone deacetylase (HDAC) inhibitors and topoisomerase inhibitors. We identified KM-00927 and BRD-K75081836 as novel HDAC inhibitors and mitomycin C as a topoisomerase IIB inhibitor. Our study provides a prime example of utilization and integration of the freely available public resources for systematic polypharmacology analysis and drug repurposing.
| S-EPMC6281908 | biostudies-literature
Project description:BackgroundDrug repurposing, the process of identifying additional therapeutic uses for existing drugs, has attracted increasing attention from both the pharmaceutical industry and the research community. Many existing computational drug repurposing methods rely on preclinical data (e.g., chemical structures, drug targets), resulting in translational problems for clinical trials.ResultsIn this study, we propose a novel framework based on clinical connectivity mapping for drug repurposing to analyze therapeutic effects of drugs on diseases. We firstly establish clinical drug effect vectors (i.e., drug-laboratory results associations) by applying a continuous self-controlled case series model on a longitudinal electronic health record data, then establish clinical disease sign vectors (i.e., disease-laboratory results associations) by applying a Wilcoxon rank sum test on a large-scale national survey data. Eventually, a repurposing possibility score for each drug-disease pair is computed by applying a dot product-based scoring function on clinical disease sign vectors and clinical drug effect vectors. During the experiment, we comprehensively evaluate 392 drugs for 6 important chronic diseases (include asthma, coronary heart disease, congestive heart failure, heart attack, type 2 diabetes, and stroke). The experiment results not only reflect known associations between diseases and drugs, but also include some hidden drug-disease associations. The code for this paper is available at: https://github.com/HoytWen/CCMDR CONCLUSIONS: The proposed clinical connectivity map framework uses laboratory results found from electronic clinical information to bridge drugs and diseases, which make their relations explainable and has better translational power than existing computational methods. Experimental results demonstrate the effectiveness of our proposed framework, further case analysis also proves our method can be used to repurposing existing drugs opportunities.
| S-EPMC8461864 | biostudies-literature
Project description:We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.
| S-EPMC5990023 | biostudies-literature
Project description:Background:The coronavirus disease 2019 (COVID-19) has become a worldwide public health crisis. At present, there are no effective antiviral drugs to treat COVID-19. Although some vaccines have been developed, late-stage clinical trials that allow licensure by regulatory agencies are still needed. Previous reports have indicated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV are highly homologous and both use angiotensin-converting enzyme 2 (ACE2) as the receptor to enter cells, and SARS-CoV infection reduces the ACE2 expression in the lung. Therefore, the analysis of genes co-expressed with ACE2 in the lung may uncover the underlying mechanism of COVID-19. Finally, we used the Connectivity map (Cmap) database to search for candidate drugs using transcriptome profiles of patients with COVID-19. Method:Based on the differentially expressed genes (DEGs), indicated by the expression of RNAs isolated from bronchoalveolar lavage fluid (BALF) cells of patients with COVID-19, we performed functional enrichment analysis and hub gene cluster analysis. Furthermore, we identified genes co-expressed with ACE2 in healthy lung samples and analyzed the significant genes. Additionally, to identify several candidate drugs for the treatment of COVID-19, we queried Cmap using DEGs and genes co-expressed with ACE2. Results and Conclusion:The up-regulated genes in the BALF cells of patients with COVID-19 are related to viral mRNA translation. The down-regulated genes are related to immune response functions. Genes positively correlated with ACE2 are related to immune defense and those negatively correlated are enriched in synaptic transmission functions. The results reflected prosperous viral proliferation and immune dysfunction in patients. Furthermore, ACE2 may not only mediate viral entrance, but also play an important role in immune defense. By using Cmap with transcriptome profiles of patients with COVID-19, we identified candidate drugs for the treatment of COVID-19, such as amantadine and acyclovir.
| S-EPMC7652993 | biostudies-literature
Project description:Drug repurposing is an appealing method to address the Coronavirus 2019 (COVID-19) pandemic because of the low cost and efficiency. We analyzed our in-house database of approved drug screens and compared their activity profiles with results from a severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) cytopathic effect (CPE) assay. The activity profiles of the human ether-à-go-go-related gene (hERG), phospholipidosis (PLD), and many cytotoxicity screens were found significantly correlated with anti-SARS-CoV-2 activity. hERG inhibition is a nonspecific off-target effect that has contributed to promiscuous drug interactions, whereas drug-induced PLD is an undesirable effect linked to hERG blockers. Thus, this study identifies preferred drug candidates as well as chemical structures that should be avoided because of their potential to induce toxicity. Lastly, we highlight the hERG liability of anti-SARS-CoV-2 drugs currently enrolled in clinical trials.
| S-EPMC8983078 | biostudies-literature
Project description:The time and cost of developing new drugs have led many groups to limit their search for therapeutics to compounds that have previously been approved for human use. Many "repurposed" drugs, such as derivatives of thalidomide, antibiotics, and antivirals have had clinical success in treatment areas well beyond their original approved use. These include applications in treating antibiotic-resistant organisms, viruses, cancers and to prevent burn scarring. The major theoretical justification for reusing approved drugs is that they have known modes of action and controllable side effects. Coadministering antibiotics with inhibitors of bacterial toxins or enzymes that mediate multidrug resistance can greatly enhance their activity. Drugs that control host cell pathways, including inflammation, tumor necrosis factor, interferons, and autophagy, can reduce the "cytokine storm" response to injury, control infection, and aid in cancer therapy. An active compound, even if previously approved for human use, will be a poor clinical candidate if it lacks specificity for the new target, has poor solubility or can cause serious side effects. Synergistic combinations can reduce the dosages of the individual components to lower reactivity. Preclinical analysis should take into account that severely ill patients with comorbidities will be more sensitive to side effects than healthy trial subjects. Once an active, approved drug has been identified, collaboration with medicinal chemists can aid in finding derivatives with better physicochemical properties, specificity, and efficacy, to provide novel therapies for cancers, emerging and rare diseases.
| S-EPMC7018532 | biostudies-literature
Project description:The high cost of drug development and the narrow spectrum of coverage typically provided by direct-acting antivirals limit the scalability of this antiviral approach. This review summarizes progress and challenges in the repurposing of approved kinase inhibitors as host-targeted broad-spectrum antiviral therapies.
| S-EPMC5804095 | biostudies-literature
Project description:In vitro selected ribozymes are promising tools for site-specific labeling of RNA. Previously known nucleic acid catalysts attached fluorescently labeled adenosine or guanosine derivatives through 2',5'-branched phosphodiester bonds to the RNA of interest. Herein, we report new ribozymes that use orthogonal substrates, derived from the antiviral drug tenofovir, and attach bioorthogonal functional groups, as well as affinity handles and fluorescent reporter units through a hydrolytically more stable phosphonate ester linkage. The tenofovir transferase ribozymes were identified by in vitro selection and are orthogonal to nucleotide transferase ribozymes. As genetically encodable functional RNAs, these ribozymes may be developed for potential cellular applications. The orthogonal ribozymes addressed desired target sites in large RNAs in vitro, as shown by fluorescent labeling of E. coli 16S and 23S rRNAs in total cellular RNA.
| S-EPMC7318677 | biostudies-literature
Project description:The usage of fluconazole and amphotericin B in clinical settings is often limited by, among other things, drug resistance development and undesired side effects. Thus, there is a constant need to find new drugs to better manage fungal infections. Toward this end, the study described in this paper considered the repurposing of aspirin (acetylsalicylic acid) and ibuprofen as alternative drugs to control the growth of cryptococcal cells. In vitro susceptibility tests, including a checkerboard assay, were performed to assess the response of Cryptococcus neoformans and Cryptococcus gattii to the above-mentioned anti-inflammatory drugs. Next, the capacity of these two drugs to induce stress as well as their mode of action in the killing of cryptococcal cells was determined. The studied fungal strains revealed a response to both aspirin and ibuprofen that was dose dependent, with ibuprofen exerting greater antimicrobial action. More importantly, the MICs of these drugs did not negatively (i) affect growth or (ii) impair the functioning of macrophages; rather, they enhanced the ability of these immune cells to phagocytose cryptococcal cells. Ibuprofen was also shown to act in synergy with fluconazole and amphotericin B. The treatment of cryptococcal cells with aspirin or ibuprofen led to stress induction via activation of the high-osmolarity glycerol (HOG) pathway, and cell death was eventually achieved through reactive oxygen species (ROS)-mediated membrane damage. The presented data highlight the potential clinical application of aspirin and ibuprofen as candidate anti-Cryptococcus drugs.
| S-EPMC4958236 | biostudies-literature
Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to profile a range of cellular models and perturbations of cellular state. These data relate to using RNA-Seq datasets from the GTEx consortium (http://www.gtexportal.org/) to validate the L1000 assay and to improve the statistical model used in imputing the transcriptome. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org
2017-03-03 | GSE92743 | GEO