Dataset Information

A connectivity map-based drug repurposing study and integrative analysis of transcriptomic profiling of SARS-CoV-2 infection.

ABSTRACT:

Aims

The recent outbreak of COVID-19 has become a global health concern. There are currently no effective treatment strategies and vaccines for the treatment or prevention of this fatal disease. The current study aims to determine promising treatment options for the COVID-19 through a computational drug repurposing approach.

Materials and methods

In this study, we focus on differentially expressed genes (DEGs), detected in SARS-CoV-2 infected cell lines including "the primary human lung epithelial cell line NHBE" and "the transformed lung alveolar cell line A549". Next, the identified DEGs are used in the connectivity map (CMap) analysis to identify similarly acting therapeutic candidates. Furthermore, to interpret lists of DEGs, pathway enrichment and protein network analysis are performed. Genes are categorized into easily interpretable pathways based on their biological functions, and overrepresentation of each pathway is tested in comparison to what is expected randomly.

Key findings

The results suggest the effectiveness of lansoprazole, folic acid, sulfamonomethoxine, tolnaftate, diclofenamide, halcinonide, saquinavir, metronidazole, ebselen, lidocaine and benzocaine, histone deacetylase (HDAC) inhibitors, heat shock protein 90 (HSP90) inhibitors, and many other clinically approved drugs as potent drugs against COVID-19 outbreak.

Significance

Making new drugs remain a lengthy process, so the drug repurposing approach provides an insight into the therapeutics that might be helpful in this pandemic. In this study, pathway enrichment and protein network analysis are also performed, and the effectiveness of some drugs obtained from the CMap analysis has been investigated according to previous researches.

SUBMITTER: Mousavi SZ

PROVIDER: S-EPMC7598903 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A connectivity map-based drug repurposing study and integrative analysis of transcriptomic profiling of SARS-CoV-2 infection.

Mousavi Seyedeh Zahra SZ Rahmanian Mojdeh M Sami Ashkan A

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 20201029

<h4>Aims</h4>The recent outbreak of COVID-19 has become a global health concern. There are currently no effective treatment strategies and vaccines for the treatment or prevention of this fatal disease. The current study aims to determine promising treatment options for the COVID-19 through a computational drug repurposing approach.<h4>Materials and methods</h4>In this study, we focus on differentially expressed genes (DEGs), detected in SARS-CoV-2 infected cell lines including "the primary huma ...[more]

PMID: 33130005

Similar Datasets

Project description:Drug repositioning (also referred to as drug repurposing) is the method of exploring novel therapeutic indications for Food and Drug Administration-approved clinically implemented drugs. The unique strategy of drug repositioning is used to boost the drug development process since drug discovery is an expensive, arduous, cumbersome, and high-risk procedure. Recently, several pharmaceutical firms have used the drug repositioning technique in their drug discovery and development programs to develop new medications based on the identification of new therapeutic targets. This technique is extremely effective, saves time, is comparatively economical, and has a low chance of failure. Developing appropriate treatment measures to inhibit the spread of Coronavirus disease-2019 (COVID-19) is currently a top priority. As a result, several studies were conducted to build novel therapeutic molecules using diverse strategies of drug repurposing to discover drug candidates against COVID-19 infection that can act as substantial inhibitors against virus particles. By implementing virtual screening of drug libraries, it is possible to identify potential drugs through drug repurposing. A molecular docking approach and calculation of binding free energy are used to estimate binding affinity and drug–receptor interactions. Drug-repurposing methodologies can be divided into three categories: target-oriented, drug-oriented, and disease-oriented, based on the gathered data about the various physicochemical, pharmacokinetic and pharmacological features of a drug candidate. Using computational methods such as homology modeling and molecular similarity, this methodology aids in determining the binding interaction of drug molecules with the target protein of the virus. In this book chapter, we explore a typical set of currently utilized computational techniques for identifying repurposable drug molecules for COVID-19, as well as their supporting databases. We also assess promising drugs anticipated by computational approaches to drugs currently being evaluated in clinical trials. Moreover, we also examine the takeaways from the evaluated research efforts, such as how to competently combine bioinformatics tools with experimental work and suggest a fully integrated drug-repurposing approach to combat the deadly COVID-19 infection.

Dataset Information

A connectivity map-based drug repurposing study and integrative analysis of transcriptomic profiling of SARS-CoV-2 infection.

Aims

Materials and methods

Key findings

Significance

Publications

A connectivity map-based drug repurposing study and integrative analysis of transcriptomic profiling of SARS-CoV-2 infection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets