A path-based analysis of infected cell line and COVID-19 patient transcriptome reveals novel potential targets and drugs against SARS-CoV-2

Agrawal, Piyush; Sambaturu, Narmada; Olgun, Gulden; Hannenhalli, Sridhar

doi:10.21203/rs.3.rs-1474136/v1

Cited by 2 publications

(3 citation statements)

References 117 publications

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“…Most hits were identified among inhibitors that target dehydrogenases, CaMK, mTOR, ULK, CLK-1, TOPK, CSF-1R, and PAK (Figure 5D). CaMK, mTOR, ULK, TOPK (also known as PBK), and PAK had already been proposed as antiviral drug targets for SARS-CoV-2 [Shahinozzaman et al, 2020; Jamaly et al, 2021; Shang et al, 2021; Agrawal et al, 2022; Basile et al, 2022]. However, we could not find any information on potential anti-SARS-CoV-2 effects caused by CLK-1 or CSF-1R inhibition.…”

Section: Resultsmentioning

confidence: 77%

“…Next, we used the caspase 3/7 activity assay in Caco-2-F03 cells to screen the Kinase Inhibitor Library (96-well)-L1200 (Selleck) for anti-SARS-CoV-2 drug candidates, which resulted in 81 hits that reduced SARS-CoV-2-induced caspase 3/7 activity by ≥ 90%. These hits included inhibitors of known potential anti-SARS-CoV-2 drug targets (CaMK, mTOR, ULK, TOPK, PAK, ROCK, CDK) [Shahinozzaman et al, 2020; Jamaly et al, 2021; Ellinger et al, 2021; Shang et al, 2021; Zhang et al, 2021b; Agrawal et al, 2022; Basile et al, 2022] and those that interfere with drug targets that had not previously been identified to be relevant during SARS-CoV-2 replication (CLK-1, CSF-1R). We determined dose response curves for 21 out of these 81 hit compounds using immunostaining for the viral S protein, which confirmed their anti-SARS-CoV-2 activities.…”

Section: Discussionmentioning

confidence: 99%

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Identification of novel antiviral drug candidates using an optimized SARS-CoV-2 phenotypic screening platform

Bojkova

Reus

Panosch

et al. 2022

Preprint

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Reliable, easy-to-handle phenotypic screening platforms are needed for the identification of anti-SARS-CoV-2 compounds. Here, we present caspase 3/7 activity as a read-out for monitoring the replication of SARS-CoV-2 isolates from different variants, including a remdesivir-resistant strain, and of other coronaviruses in a broad range of cell culture models, independently of cytopathogenic effect formation. Compared to other cell culture models, the Caco-2 subline Caco-2-F03 displayed superior performance, as it possesses a stable SARS-CoV-2 susceptible phenotype and does not produce false-positive hits due to drug-induced phospholipidosis. A proof-of-concept screen of 1796 kinase inhibitors identified known and novel antiviral drug candidates including inhibitors of PHGDH, CLK-1, and CSF1R. The activity of the PHGDH inhibitor NCT-503 was further increased in combination with the HK2 inhibitor 2-deoxy-D-glucose, which is in clinical development for COVID-19. In conclusion, caspase 3/7 activity detection in SARS-CoV-2-infected Caco-2F03 cells provides a simple phenotypic high-throughput screening platform for SARS-CoV-2 drug candidates that reduces false positive hits.

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Section: Resultsmentioning

confidence: 77%

Section: Discussionmentioning

confidence: 99%

Identification of novel antiviral drug candidates using an optimized SARS-CoV-2 phenotypic screening platform

Bojkova

Reus

Panosch

et al. 2022

Preprint

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“…PBK (PDZ Binding Kinase) plays a regulatory role in cell cycle regulation and cell mitosis. It was reported that using the PathExt tool was able to identify PBK as the most common central gene target in activated TopNets to suppress SARS-CoV-2 [58]. Ekaterina et al showed that genes such as PBK regulated myofibril formation and thus caused cardiac hypertrophy [59].…”

Section: Plos Onementioning

confidence: 99%

Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis

Zhang

et al. 2022

PLoS ONE

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Background There is growing evidence of a strong relationship between COVID-19 and myocarditis. However, there are few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 Myocarditis. This study aimed to identify critical genes related to COVID-19 Myocarditis by bioinformatic methods, explore the biological mechanisms and gene regulatory networks, and probe related drugs. Methods The gene expression data of GSE150392 and GSE167028 were obtained from the Gene Expression Omnibus (GEO), including cardiomyocytes derived from human induced pluripotent stem cells infected with SARS-CoV-2 in vitro and GSE150392 from patients with myocarditis infected with SARS-CoV-2 and the GSE167028 gene expression dataset. Differentially expressed genes (DEGs) (adjusted P-Value <0.01 and |Log2 Fold Change| ≥2) in GSE150392 were assessed by NetworkAnalyst 3.0. Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes. Functional enrichment analyses were performed by using the "clusterProfiler" package in the R software, and protein-protein interaction (PPI) networks were constructed on the STRING website (https://cn.string-db.org/). Critical genes were identified by the CytoHubba plugin of Cytoscape by 5 algorithms. Transcription factor-gene (TF-gene) and Transcription factor-microRibonucleic acid (TF-miRNA) coregulatory networks construction were performed by NetworkAnalyst 3.0 and displayed in Cytoscape. Finally, Drug Signatures Database (DSigDB) was used to probe drugs associated with COVID-19 Myocarditis. Results Totally 850 DEGs (including 449 up-regulated and 401 down-regulated genes) and 159 significant genes in turquoise modules were identified from GSE150392 and GSE167028, respectively. Functional enrichment analysis indicated that common genes were mainly enriched in biological processes such as cell cycle and ubiquitin-protein hydrolysis. 6 genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) were identified as critical genes. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Etoposide, Methotrexate, Troglitazone, etc) were considered as target drugs for COVID-19 Myocarditis. Conclusions Through bioinformatics method analysis, this study provides a new perspective to explore the pathogenesis, gene regulatory networks and provide drug compounds as a reference for COVID-19 Myocarditis. It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.

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A path-based analysis of infected cell line and COVID-19 patient transcriptome reveals novel potential targets and drugs against SARS-CoV-2

Cited by 2 publications

References 117 publications

Identification of novel antiviral drug candidates using an optimized SARS-CoV-2 phenotypic screening platform

Identification of novel antiviral drug candidates using an optimized SARS-CoV-2 phenotypic screening platform

Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis

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