L1000 connectivity map interrogation identifies candidate drugs for repurposing as SARS-CoV-2 antiviral therapies | Zendy

Wezi Sendama | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

L1000 connectivity map interrogation identifies candidate drugs for repurposing as SARS-CoV-2 antiviral therapies

Author(s) -

Wezi Sendama

Publication year - 2020

Publication title -

computational and structural biotechnology journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.908

H-Index - 45

ISSN - 2001-0370

DOI - 10.1016/j.csbj.2020.11.054

Subject(s) - repurposing , drug repositioning , computational biology , in silico , covid-19 , transcriptome , drug discovery , bioinformatics , biology , medicine , gene expression , gene , pharmacology , drug , genetics , disease , infectious disease (medical specialty) , ecology , pathology

Adaptive clinical trials are underway to determine the efficacy of potential therapies for COVID-19, with flexibility to include emerging therapies if there is sufficient preclinical evidence for their potential utility. In silico screening of connectivity maps, which link gene expression profiles to libraries of perturbagens, may facilitate the identification of such emerging therapies. The L1000 Connectivity Map is built from samples of transcripts taken from gene expression profiles of cells in various experimental conditions followed by computational inferences of the remainder of the transcriptome. Searching the L1000 Connectivity Map for modulators of a protease that facilitates coronavirus infection identifies plausible candidate drugs for repurposing as antiviral agents against SARS-CoV-2 following further investigation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research