COMPARE analysis as an efficient bioinformatic approach to accelerate
repurposing of existing drugs against Covid-19 and other emerging
epidemics
Abstract
A novel bioinformatic approach for drug repurposing against emerging
viral epidemics like Covid-19 is described. It exploits the COMPARE
algorithm, a public program from the NCI to sort drugs according to
their patterns of growth inhibitory profiles from a diverse panel of
human cancer cell lines. The data repository of the NCI includes the
growth inhibitory patterns of more than 55000 molecules. When drugs with
purported anti-SARS-CoV-2 activities were used as seeds (e.g.,
hydroxychloroquine and ritonavir) in COMPARE, the analysis uncovered
several drugs with fingerprints similar to the seeded drugs.
Interestingly, the uncovered drugs were all reportedly known to exert
antiviral activities, confirming that COMPARE analysis is valuable for
predicting antiviral drug repurposing. Unlike pure in-silico approaches,
this approach is biologically more relevant and able to
pharmacologically correlate compounds regard-less of their structures.
This is an untapped resource, reliable and readily exploitable for drug
repurposing against surprising viral outbreaks.