Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS.
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ABSTRACT:
SUBMITTER: O'Donovan SM
PROVIDER: S-EPMC7336712 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. Identification of effective therapeutics is a crucial tool to treat those infected with SARS-CoV-2 and limit the spread of this novel disease globally. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and publicly available SARS-CoV-2 infected cell lines to identify novel therapeutics. We identified a shortlist of 20 candidate drugs: 8 are already under trial for the treatment of COVID-19, the remaining 12 have antiviral properties and 6 have antiviral efficacy against coronaviruses specifically, in vitro. All candidate drugs are either FDA approved or are under investigation. Our candidate drug findings are discordant with (i.e., reverse) SARS-CoV-2 transcriptome signatures generated in vitro, and a subset are also identified in transcriptome signatures generated from COVID-19 patient samples, like the MEK inhibitor selumetinib. Overall, our findings provide additional support for drugs that are already being explored as therapeutic agents for the treatment of COVID-19 and identify promising novel targets that are worthy of further investigation.
| S-EPMC7904823 | biostudies-literature
Project description:Cancer is a disease that affects and kills millions of people worldwide. Breast cancer, especially, has a high incidence and mortality, and is challenging to treat. Due to its high impact on the health sector, oncological therapy is the subject of an intense and very expensive research. To improve this therapy and reduce its costs, strategies such as drug repurposing and drug combinations have been extensively studied. Drug repurposing means giving new usefulness to drugs which are approved for the therapy of various diseases, but, in this case, are not approved for cancer therapy. On the other hand, the purpose of combining drugs is that the response that is obtained is more advantageous than the response obtained by the single drugs. Using drugs with potential to be repurposed, combined with 5-fluorouracil, the aim of this project was to investigate whether this combination led to therapeutic benefits, comparing with the isolated drugs. We started with a screening of the most promising drugs, with verapamil and itraconazole being chosen. Several cellular viability studies, cell death and proliferation studies, mainly in MCF-7 cells (Michigan Cancer Foundation-7, human breast adenocarcinoma cells) were performed. Studies were also carried out to understand the effect of the drugs at the level of possible therapeutic resistance, evaluating the epithelial-mesenchymal transition. Combining all the results, the conclusion is that the combination of verapamil and itraconazole with 5-fluorouracil had benefits, mainly by decreasing cell viability and proliferation. Furthermore, the combination of itraconazole and 5-fluorouracil seemed to be the most effective, being an interesting focus in future studies.
| S-EPMC6315516 | biostudies-other
Project description:Drug repositioning research using transcriptome data has recently attracted attention. In this study, we attempted to identify new target proteins of the urotensin-II receptor antagonist, KR-37524 (4-(3-bromo-4-(piperidin-4-yloxy)benzyl)-N-(3-(dimethylamino)phenyl)piperazine-1-carboxamide dihydrochloride), using a transcriptome-based drug repositioning approach. To do this, we obtained KR-37524-induced gene expression profile changes in four cell lines (A375, A549, MCF7, and PC3), and compared them with the approved drug-induced gene expression profile changes available in the LINCS L1000 database to identify approved drugs with similar gene expression profile changes. Here, the similarity between the two gene expression profile changes was calculated using the connectivity score. We then selected proteins that are known targets of the top three approved drugs with the highest connectivity score in each cell line (12 drugs in total) as potential targets of KR-37524. Seven potential target proteins were experimentally confirmed using an in vitro binding assay. Through this analysis, we identified that neurologically regulated serotonin transporter proteins are new target proteins of KR-37524. These results indicate that the transcriptome-based drug repositioning approach can be used to identify new target proteins of a given compound, and we provide a standalone software developed in this study that will serve as a useful tool for drug repositioning.
| S-EPMC8384862 | biostudies-literature
Project description:A depleted antimicrobial drug pipeline combined with an increasing prevalence of Gram-negative 'superbugs' has increased interest in nano therapies to treat antibiotic resistance. As cubosomes and polymyxins disrupt the outer membrane of Gram-negative bacteria via different mechanisms, we herein examine the antimicrobial activity of polymyxin-loaded cubosomes and explore an alternative strategy via the polytherapy treatment of pathogens with cubosomes in combination with polymyxin. The polytherapy treatment substantially increases antimicrobial activity compared to polymyxin B-loaded cubosomes or polymyxin and cubosomes alone. Confocal microscopy and neutron reflectometry suggest the superior polytherapy activity is achieved via a two-step process. Firstly, electrostatic interactions between polymyxin and lipid A initially destabilize the outer membrane. Subsequently, an influx of cubosomes results in further membrane disruption via a lipid exchange process. These findings demonstrate that nanoparticle-based polytherapy treatments may potentially serve as improved alternatives to the conventional use of drug-loaded lipid nanoparticles for the treatment of "superbugs".
| S-EPMC8763928 | biostudies-literature
Project description:By utilizing Optum Life Sciences Claims Data, we constructed Real World Data (RWD) cohorts comprising over 3 million patients and simulated a clinical trial observational study design to evaluate over 200 FDA-approved drugs with COVID-19 repurposing potential, and identified a dozen candidates exhibiting significant reduction in the odds of severe COVID-19 outcomes such as death, intensive care unit (ICU) admission, hospitalization and pneumonia. Notably, certain drug combinations demonstrated effects comparable to those of COVID-19 vaccines. Furthermore, our study revealed a novel finding: a quantitative linear relationship between COVID-19 outcomes and overall patient health risks. This discovery enabled a more precise estimation of drug efficacy using the risk adjustment. The top performing drugs identified include emtricitabine, tenofovir, folic acid, progesterone, estradiol, epinephrine, disulfiram, nitazoxanide and some drug combinations including aspirin-celecoxib.
| S-EPMC10477169 | biostudies-literature
Project description:ObjectivesTo date, no immunomodulatory drug has demonstrated its efficacy in primary SS (pSS). We sought to analyse potential commonalities between pSS transcriptomic signatures and signatures of various drugs or specific knock-in or knock-down genes.MethodsGene expression from peripheral blood samples of patients with pSS was compared with that of healthy controls in two cohorts and three public databases. In each of the five datasets, we analysed the 150 most up- and downregulated genes between pSS patients and controls with regard to the differentially expressed genes resulting from the biological action on nine cell lines of 2837 drugs, 2160 knock-in and 3799 knock-down genes in the Connectivity Map database.ResultsWe analysed 1008 peripheral blood transcriptomes from five independent studies (868 patients with pSS and 140 healthy controls). Eleven drugs could represent potential candidate drugs, with histone deacetylases and PI3K inhibitors among the most significantly associated. Twelve knock-in genes were associated with a pSS-like profile and 23 knock-down genes were associated with a pSS-revert profile. Most of those genes (28/35, 80%) were interferon-regulated.ConclusionThis first drug repositioning transcriptomic approach in SS confirms the interest of targeting interferons and identifies histone deacetylases and PI3K inhibitors as potential therapeutic targets.
| S-EPMC10629788 | biostudies-literature
Project description:Mycobacterium tuberculosis (Mtb) is a deadly tuberculosis (TB)-causing pathogen. The proteasome is vital to the survival of Mtb and is therefore validated as a potential target for anti-TB therapy. Mtb resistance to existing antibacterial agents has enhanced drastically, becoming a worldwide health issue. Therefore, new potential therapeutic agents need to be developed that can overcome the complications of TB. With this purpose, in the present study, 224,205 natural compounds from the ZINC database have been screened against the catalytic site of Mtb proteasome by the computational approach. The best scoring hits, ZINC3875469, ZINC4076131, and ZINC1883067, demonstrated robust interaction with Mtb proteasome with binding energy values of -7.19, -7.95, and -7.21 kcal/mol for the monomer (K-chain) and -8.05, -9.10, and -7.07 kcal/mol for the dimer (both K and L chains) of the beta subunit, which is relatively higher than that of reference compound HT1171 (-5.83 kcal/mol (monomer) and -5.97 kcal/mol (dimer)). In-depth molecular docking of top-scoring compounds with Mtb proteasome reveals that amino acid residues Thr1, Arg19, Ser20, Thr21, Gln22, Gly23, Asn24, Lys33, Gly47, Asp124, Ala126, Trp129, and Ala180 are crucial in binding. Furthermore, a molecular dynamics study showed steady-state interaction of hit compounds with Mtb proteasome. Computational prediction of physicochemical property assessment showed that these hits are non-toxic and possess good drug-likeness properties. This study proposed that these compounds could be utilized as potential inhibitors of Mtb proteasome to combat TB infection. However, there is a need for further bench work experiments for their validation as inhibitors of Mtb proteasome.
| S-EPMC8074214 | biostudies-literature
Project description:PurposeTo facilitate the demonstration of the prognostic value of radiomics, multicenter radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis is however challenging, as they are sensitive to the variability in scanner models, acquisition protocols and reconstruction settings, which is often unavoidable in a multicentre retrospective analysis. A statistical harmonization strategy called ComBat was utilized in radiomics studies to deal with the "center-effect". The goal of the present work was to integrate a transfer learning (TL) technique within ComBat-and recently developed alternate versions of ComBat with improved flexibility (M-ComBat) and robustness (B-ComBat)-to allow the use of a previously determined harmonization transform to the radiomic feature values of new patients from an already known center.Material and methodsThe proposed TL approach were incorporated in the four versions of ComBat (standard, B, M, and B-M ComBat). The proposed approach was evaluated using a dataset of 189 locally advanced cervical cancer patients from 3 centers, with magnetic resonance imaging (MRI) and positron emission tomography (PET) images, with the clinical endpoint of predicting local failure. The impact performance of the TL approach was evaluated by comparing the harmonization achieved using only parts of the data to the reference (harmonization achieved using all the available data). It was performed through three different machine learning pipelines.ResultsThe proposed TL technique was successful in harmonizing features of new patients from a known center in all versions of ComBat, leading to predictive models reaching similar performance as the ones developed using the features harmonized with all the data available.ConclusionThe proposed TL approach enables applying a previously determined ComBat transform to new, previously unseen data.
| S-EPMC8248970 | biostudies-literature
Project description:Cancer cells have a very different metabolism from that of normal cells from which they are derived. Their metabolism is elevated, which allows them to sustain higher proliferative rate and resist some cell death signals. This phenomenon, known as the "Warburg effect", has become the focus of intensive efforts in the discovery of new therapeutic targets and new cancer drugs. Both glycolysis and glutaminolysis pathways are enhanced in cancer cells. While glycolysis is enhanced to satisfy the increasing energy demand of cancer cells, glutaminolysis is enhanced to provide biosynthetic precursors for cancer cells. It was recently discovered that there is a tyrosine phosphorylation of a specific isoform of pyruvate kinase, the M2 isoform, that is preferentially expressed in all cancer cells, which results in the generation of pyruvate through a unique enzymatic mechanism that is uncoupled from ATP production. Pyruvate produced through this unique enzymatic mechanism is converted primarily into lactic acid, rather than acetyl-CoA for the synthesis of citrate, which would normally then enter the citric acid cycle. Inhibition of key enzymes in glycolysis and glutaminolysis pathways with small molecules has provided a novel but emerging area of cancer research and has been proven effective in slowing the proliferation of cancer cells, with several inhibitors being in clinical trials. This review paper will cover recent advances in the development of chemotherapeutic agents against several metabolic targets for cancer therapy, including glucose transporters, hexokinase, pyruvate kinase M2, glutaminase, and isocitrate dehydrogenase.
| S-EPMC6110043 | biostudies-other
Project description:Abscisic acid (ABA) is the main phytohormone involved in abiotic stress response and its adaptation, and is a candidate agrichemical. Consequently, several agonists of ABA have been developed using the yeast two-hybrid system. Here, we describe a novel cell-free-based drug screening approach for the development and validation of ABA receptor agonists. Biochemical validation of this approach between 14 ABA receptors (PYR/PYL/RCARs) and 7 type 2C-A protein phosphatases (PP2CAs) revealed the same interactions as those of previous proteome data, except for nine new interactions. By chemical screening using this approach, we identified two novel ABA receptor agonists, JFA1 (julolidine and fluorine containing ABA receptor activator 1) and JFA2 as its analog. The results of biochemical validation for this approach and biological analysis suggested that JFA1 and JFA2 inhibit seed germination and cotyledon greening of seedlings by activating PYR1 and PYL1, and that JFA2 enhanced drought tolerance without inhibiting root growth by activating not only PYR1 and PYL1 but also PYL5. Thus, our approach was useful for the development of ABA receptor agonists and their validation.
| S-EPMC5844987 | biostudies-literature