Bioactivity Profile Similarities to Expand the Repertoire of COVID-19 Drugs
semanticscholar(2020)
摘要
We
present an online resource, based on small-molecule bioactivity signatures and
natural language processing, to expand the portfolio of compounds with
potential to treat COVID-19. By comparing the set of drugs reported to be
potentially active against SARS-CoV-2 to a universe of 1M bioactive molecules,
we identify compounds that display analogous chemical and functional features to the
current COVID-19 candidates. Searches can be filtered by level of evidence and
mechanism of action, and results can be restricted to drug molecules or include
the much broader space of bioactive compounds. Moreover, we allow users to contribute COVID-19 drug candidates,
which are automatically incorporated
to the pipeline once per day. The computational platform, as well as the source
code, is available at https://sbnb.irbbarcelona.org/covid19.
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