id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-342456-5gp3cry0	Hoagland, Daisy A.	Modulating the transcriptional landscape of SARS-CoV-2 as an effective method for developing antiviral compounds	2020-07-13		.txt	text/plain	4511	240	48	Utilizing expression patterns of SARS-CoV-2-infected cells, we identified a region in gene expression space that was unique to virus infection and inversely proportional to the transcriptional footprint of known compounds characterized in the Library of Integrated Network-based Cellular Signatures. These signatures were then used as queries against the LINCS L1000 dataset, a collection of gene expression profiles generated following the administration of >20,000 bioactive compounds including >1,000 FDA-approved drugs to human cell lines at a variety of different times and concentrations (Subramanian et al., 2017) With L1000FWD , we could identify reciprocal transcriptional signatures generated between SARS-CoV-2 infection and a given compound. Overall, based on the L1000 data, these seven compounds influence the same pharmacological high-dimensional gene expression signature space and are predicted to disrupt key cellular processes that are modulated in response to SARS-CoV-2 infection.	./cache/cord-342456-5gp3cry0.txt	./txt/cord-342456-5gp3cry0.txt