Abstract

In the era of targeted therapeutics, protein kinases like WEE1 have become pivotal drug targets, especially for cancer therapy. Utilizing a multi-faceted approach, our study adds fresh insights to this endeavour. We employed the t-SNE algorithm, combined with ECFP4 fingerprints, to analyse the molecular similarity between FDA-approved drugs and known clinical trial inhibitors. Our t-SNE analysis identified the closest clusters to known inhibitors and selected 11 FDA-approved drugs for further study. Using the DrugSpaceX platform, we generated analogues for these 11 FDA-approved drugs. These analogues were refined according to Lipinski’s Rule of Five and Synthetic Accessibility scores, yielding 68,640 analogues for additional scrutiny. Among these, derivatives of Palbociclib and Ribociclib stood out as the most promising WEE1 inhibitors, based on docking scores and interaction patterns. Molecular dynamics simulations validated the stability of these protein-ligand interactions, particularly for DE50607359, a top-ranked Palbociclib analogue, which also met most pharmacokinetic parameters within acceptable limits. Our study uncovers new candidates for WEE1 inhibition not previously reported. With our multi-layered computational strategy, we provide a solid foundation for future experimental validation and targeted drug development in cancer therapeutics. Communicated by Ramaswamy H. Sarma

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