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
HIGHLIGHTS
Employed the t-SNE algorithm and ECFP4 fingerprints to discern molecular similarities between FDA-approved drugs and known clinical trial inhibitors, identifying 11 key drugs.
Leveraged the DrugSpaceX platform to generate analogues for these selected FDA-approved drugs, yielding a massive collection of 68,640 refined analogues based on Lipinski’s Rule of Five and Synthetic Accessibility scores.
Derivatives of Palbociclib and Ribociclib emerged as the most promising WEE1 inhibitors, supported by their docking scores and interaction patterns.
Validated protein-ligand interactions through molecular dynamics simulations, spotlighting DE50607359, a superior Palbociclib analogue, meeting critical pharmacokinetic parameters.
Acknowledgements
Authors thank Sri Ramachandra Institute of Higher Education and Research (Deemed to be University) for providing the infrastructure facility. We also thank PSGCP and R. C. Patel Institute for Schrodinger and simulation support, respectively.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Author contributions
Jaikanth Chandrasekaran: Conception and design of the study, Analysis and interpretation of data, Supervision, Writing—original draft, review & editing, Final approval.
Rajesh Muthuraj: Acquisition of data, Analysis, Visualization and interpretation of data, Performed- ECFP4 fingerprinting, t-SNE similarity sorting, Analogue generation, Drug likeliness filtration, Writing—original draft, review & editing, Prepared Graphical abstract.
Dhanushya Gopal: Writing—review, Visualization and interpretation of data
Iqrar Ahmed: Performed MD simulations
Data availability statement
The data that support the findings of this study are available in the Supporting Information Material of this paper.