Discovery of novel small-molecule ligands targeting the WD40 repeat proteins using AI-driven hit finding technologies

WD40 Repeat (WDR) proteins comprise one of the largest protein families in the human genome with strong genetic links to diseases. WDRs are scaffolding proteins involved in a wide variety of cellular processes including epigenetics, ubiquitin signaling, DNA repair, RNA splicing, and immune system signaling (Schapira et al, Nat Rev Drug Disc. 2017). This family harbors more ‘essential genes’ in cancer than any other protein family (Wang et al, Drug Discov Today 2020), and yet, it is largely unexplored with respect to drug discovery. Here, we employed several hit finding technologies to discover small-molecule ligands targeting the WDR protein family, including DNA-encoded library (DEL) selection combined with Machine Learning (ML), as well as Artificial Intelligence (AI)-driven virtual screening, which resulted in the identification of several hits. Experimental validation of the identified hits was performed using a suite of biophysical methods, and the compound binding modes were elucidated structurally using X-ray crystallography. Structure-guided hit optimization led to the development of potent and selective compounds for several WDR proteins.