COVID19db: a comprehensive database platform to discover potential drugs and targets of COVID-19 at whole transcriptomic scale

Abstract

Many open access transcriptomic data of coronavirus disease 2019 (COVID-19) were generated, they have great heterogeneity and are difficult to analyze. To utilize these invaluable data for better understanding of COVID-19, additional software should be developed. Especially for researchers without bioinformatic skills, a user-friendly platform is mandatory. We developed the COVID19db platform (http://hpcc.siat.ac.cn/covid19db & http://www.biomedical-web.com/covid19db) that provides 39 930 drug–target–pathway interactions and 95 COVID-19 related datasets, which include transcriptomes of 4127 human samples across 13 body sites associated with the exposure of 33 microbes and 33 drugs/agents. To facilitate data application, each dataset was standardized and annotated with rich clinical information. The platform further provides 14 different analytical applications to analyze various mechanisms underlying COVID-19. Moreover, the 14 applications enable researchers to customize grouping and setting for different analyses and allow them to perform analyses using their own data. Furthermore, a Drug Discovery tool is designed to identify potential drugs and targets at whole transcriptomic scale. For proof of concept, we used COVID19db and identified multiple potential drugs and targets for COVID-19. In summary, COVID19db provides user-friendly web interfaces to freely analyze, download data, and submit new data for further integration, it can accelerate the identification of effective strategies against COVID-19.

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

“…Elsewhere the Ensembl COVID-19 resource ( 5 ) places the SARS-CoV-2 genome in the familiar Ensembl framework, providing evolutionary insights and integrating information regarding non-coding RNA structures (from Rfam ( 6 )) and variants. Other COVID-19 databases cover transcriptomics of infected cells, both in SCovid ( 7 ) from a single cell perspective that allows a tissue-specific view of infection and in COVID19db ( 8 ) with an emphasis on network analysis and opportunities for drug discovery. The final three databases consider the immune response to infection and the potential impact of viral genomic variants on its effectiveness.…”

Epigenetic activation of antiviral sensors and effectors of interferon response pathways during SARS-CoV-2 infection

“…4 b). To assess the association between methylation and expression of the genes in this gene set, we first compared their expression levels between COVID-19 patients (n=62) and healthy blood samples (n=24) [48] . This analysis showed that nine of the genes including MX1 , CMPK2 , PARP9 , TRIM22 , AIM2 , IFI44L , IFIT3 , IRF7, and EPSTI1 were significantly upregulated in blood of COVID-19 patients (p ≤ 0.05, ANOVA; |log 2 (FC)| ≥ 1) ( Fig.…”

Structures of the SARS-CoV-2 spike glycoprotein and applications for novel drug development

“…Several user-defined rules (e.g., Lipinski’s rule of five, synthetic accessibility) are also introduced for filtering out undesired hits. (6) COVID19 db ( http://hpcc.siat.ac.cn/covid19db or http://www.biomedicalweb.com/covid19db ) is a user-friendly and open-access platform that integrates 95 COVID-19-related human transcriptomic datasets of 4,127 human samples across 13 body sites associated with exposure to 33 microbes and 33 drugs/agents in GEO and 39, 930 drug–target–pathway interactions among 2,037 drugs, 1,116 targets, and 207 pathways in DrugCentral and KEGG ( Zhang et al, 2022 ). In addition, 14 different analytical applications (included in the differential expression and coexpression modules) and a web service tool are designed and integrated to analyse the integrated data or the obtained human transcriptomic data.…”

“…(3) CovidExpress (https://stjudecab.github.io/covidexpress) is an open-access database and interactive visualization tool for intuitive investigation of SARS-CoV-2-related transcriptomes, and we collected approximately 1,500 human bulk RNA-seq datasets from publicly available resources (Djekidel et al, 2021) (Zhang et al, 2022). In addition, 14 different analytical applications (included in the differential expression and coexpression modules) and a web service tool are designed and integrated to analyse the integrated data or the obtained human transcriptomic data.…”