Discovery of a Novel DCAF1 Ligand Using a Drug–Target Interaction Prediction Model: Generalizing Machine Learning to New Drug Targets

• DOI: 10.1021/acs.jcim.3c00082
• Publication Date: 2023-06-23T22:42:16Z
• Authors: Serah W. Kimani; Julie Owen; Stuart R. Green; Fengling Li; Yanjun Li; Aiping Dong; Peter J. Brown; Suzanne Ackloo; David Kuter; Cindy Yang; Miranda MacAskill; Stephen Scott Mac...; Cheryl H. Arrowsmith; Matthieu Schapira; Vijay Shahani; Levon Halabelian
• Keywords: Cheminformatics; Docking (animal)

DCAF1 functions as a substrate recruitment subunit for the RING-type CRL4DCAF1 and HECT family EDVPDCAF1 E3 ubiquitin ligases. The WDR domain of serves binding platform proteins is also targeted by HIV SIV lentiviral adaptors to induce ubiquitination proteasomal degradation antiviral host factors. It therefore attractive both potential therapeutic target development chemical inhibitors an ligase that could be recruited novel PROTACs protein degradation. In this study, we used proteome-scale drug–target interaction prediction model, MatchMaker, combined with cheminformatics filtering docking identify ligands domain. Biophysical screening X-ray crystallographic studies predicted binders confirmed selective ligand occupying central cavity This study shows artificial intelligence-enabled virtual methods can successfully applied in absence previously known ligands.