In addition to general
challenges in drug discovery such as the
identification of lead compounds in time- and cost-effective ways,
specific challenges also exist. Particularly, it is necessary to develop
pharmacological inhibitors that effectively discriminate between closely
related molecular targets. DYRK1B kinase is considered a valuable
target for cancer-specific mono- or combination chemotherapy; however,
the inhibition of its closely related DYRK1A kinase is not beneficial.
Existing inhibitors target both kinases with essentially the same
efficiency, and the unavailability of the DYRK1B crystal structure
makes the discovery of DYRK1B-specific inhibitors even more challenging.
Here, we propose a novel multi-stage compound discovery pipeline aimed
at in silico identification of both potent and selective
small molecules from a large set of initial candidates. The method
uses structure-based docking and ligand-based quantitative structure–activity
relationship modeling. This approach allowed us to identify lead and
runner-up small-molecule compounds targeting DYRK1B with high efficiency
and specificity.