  Given the severity of the SARS-CoV-2 pandemic, a major challenge is to
rapidly repurpose existing approved drugs for clinical interventions. While a
number of data-driven and experimental approaches have been suggested in the
context of drug repurposing, a platform that systematically integrates
available transcriptomic, proteomic and structural data is missing. More
importantly, given that SARS-CoV-2 pathogenicity is highly age-dependent, it is
critical to integrate aging signatures into drug discovery platforms. We here
take advantage of large-scale transcriptional drug screens combined with
RNA-seq data of the lung epithelium with SARS-CoV-2 infection as well as the
aging lung. To identify robust druggable protein targets, we propose a
principled causal framework that makes use of multiple data modalities. Our
analysis highlights the importance of serine/threonine and tyrosine kinases as
potential targets that intersect the SARS-CoV-2 and aging pathways. By
integrating transcriptomic, proteomic and structural data that is available for
many diseases, our drug discovery platform is broadly applicable. Rigorous in
vitro experiments as well as clinical trials are needed to validate the
identified candidate drugs.
