4.7 Article

Discovery of potential WEE1 inhibitors via hybrid virtual screening

Journal

FRONTIERS IN PHARMACOLOGY
Volume 14, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fphar.2023.1298245

Keywords

virtual screening; WEE1; molecular dynamics; geometric deep learning; cell cycle

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This study successfully identified potential WEE1 inhibitors through virtual screening, and compound 4 exhibited excellent inhibitory activity and anti-proliferative effects, indicating its potential as a WEE1 inhibitor.
G2/M cell cycle checkpoint protein WEE1 kinase is a promising target for inhibiting tumor growth. Although various WEE1 inhibitors have entered clinical investigations, their therapeutic efficacy and safety profile remain unsatisfactory. In this study, we employed a comprehensive virtual screening workflow, which included Schrodinger-Glide molecular docking at different precision levels, as well as the utilization of tools such as MM/GBSA and Deepdock to predict the binding affinity between targets and ligands, in order to identify potential WEE1 inhibitors. Out of ten molecules screened, 50% of these molecules exhibited strong inhibitory activity against WEE1. Among them, compounds 4 and 5 showed excellent inhibitory activity with IC50 values of 1.069 and 3.77 nM respectively, which was comparable to AZD1775. Further investigations revealed that compound 4 displayed significant anti-proliferative effects in A549, PC9, and HuH-7 cells and could also induce apoptosis and G1 phase arrest in PC9 cells. Additionally, molecular dynamics simulations unveiled the binding details of compound 4 with WEE1, notably the crucial hydrogen bond interactions formed with Cys379. In summary, this comprehensive virtual screening workflow, combined with in vitro testing and computational modeling, holds significant importance in the development of promising WEE1 inhibitors.

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