Computational Modeling of DYRK1A Inhibitors as Potential Anti-Alzheimer Agents

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a promising target for the treatment of different neurodegenerative diseases, especially Alzheimer’s disease (AD). In this chapter, different ligand-based and structure-based computational approaches were explored to develop a workflow for the selection of potential candidates as inhibitors of DYRK1A. The NuBBE database—comprising different compounds from the Brazilian biodiversity landscape—was screened with the designed workflow allowing to search for potential inhibitors. Five different compounds from this database were identified as candidates, and one of them presented not only a good interaction profile with the ATP binding site of DYRK1A but also a great synthesizable accessibility score and an optimal predicted toxicological profile. These results show the capability of the developed in silico workflow to screen large databases to find hit compounds from natural sources, therefore representing a good starting point for future further studies.