<p><b>Objective:</b> The COVID-19
pandemic has catalyzed a widespread effort to identify drug candidates and
biological targets of relevance to SARS-COV-2 infection, which resulted in
large numbers of publications on this subject. We have built the <b><u>CO</u></b>VID-19
<b><u>K</u></b>nowledge <b><u>E</u></b>xtractor (COKE), a web application to
extract, curate, and annotate essential drug-target relationships from the
research literature on COVID-19 to assist drug repurposing efforts.</p>
<p><b>Materials and Methods:</b> SciBiteAI
ontological tagging of the COVID Open Research Dataset (CORD-19), a repository
of COVID-19 scientific publications, was employed to identify drug-target
relationships. Entity identifiers were resolved through lookup routines using
UniProt and DrugBank. A custom algorithm was used to identify co-occurrences of
protein and drug terms, and confidence scores were calculated for each entity
pair.</p>
<p><b>Results:</b> COKE processing of
the current CORD-19 database identified about 3,000 drug-protein pairs, including
29 unique proteins and 500 investigational, experimental, and approved drugs. Some of these drugs are presently undergoing clinical
trials for COVID-19.</p>
<p><b>Discussion:</b> The rapidly
evolving situation concerning the COVID-19 pandemic has resulted in a dramatic growth
of publications on this subject in a short period. These circumstances call for
methods that can condense the literature into the key concepts and
relationships necessary for insights into SARS-CoV-2 drug repurposing. </p>
<p><b>Conclusion:</b> The COKE
repository and web application deliver key drug - target protein relationships
to researchers studying SARS-CoV-2. COKE
portal may provide comprehensive and critical information on studies concerning
drug repurposing against COVID-19. COKE is freely available at <a href="https://coke.mml.unc.edu/">https://coke.mml.unc.edu/</a> and the code is
available at <a href="https://github.com/DnlRKorn/CoKE">https://github.com/DnlRKorn/CoKE</a>.
</p>