A multi-stage computational pipeline for repurposing FDA-approved drugs: application to EGFR C797S–mutant NSCLC
Background/Objectives: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death globally. Resistance to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors, particularly due to the C797S mutation, poses a significant clinical challenge. This study utilized a comprehensive multiphase computational drug repurposing approach to discover FDA-approved medications that may be effective against the EGFR C797S mutation. Methods: A library of 1,650 compounds from the ZINC15 database was subjected to shape-based screening, followed by hierarchical molecular docking using high-throughput, standard precision, and extra-precision methods. The top candidates were further analyzed using MM-GBSA binding free-energy calculations, covalent docking simulations, and three 300-ns molecular dynamics simulations to evaluate the binding stability and interaction persistence under dynamic conditions. Results: Among the evaluated compounds, doripenem, norgestrel, oxymetholone, norethisterone, and ertapenem exhibited high docking scores and consistent interactions with crucial hinge-region residues, such as MET-793 and mutant SER-797, within the ATP-binding site. Through molecular dynamics analyses, ertapenem and oxymetholone were identified as the most stable complexes, exhibiting minimal root-mean-square deviation fluctuations and maintaining hydrogen-bond networks similar to that of the reference inhibitor osimertinib. Conclusion: These findings suggest that ertapenem and oxymetholone are promising structurally unique scaffolds for targeting osimertinib-resistant EGFR C797S-driven NSCLC. While experimental validation is necessary, this study provides a computational framework for swift drug repurposing and lays a rational foundation for future biochemical evaluation and structure-guided optimization of next-generation EGFR inhibitors.
Authors
- Mansour S. Alturki (ORCID: https://orcid.org/0000-0001-7702-9379)
- Mohammed F. Aldawsari (ORCID: https://orcid.org/0000-0003-1298-4863)
- Reem A. Alkhodier (ORCID: https://orcid.org/0000-0002-3946-6145)
- Mohamed Gomaa (ORCID: https://orcid.org/0000-0003-1544-3042)
- Abdulaziz Halawi
- Saad M. Wali (ORCID: https://orcid.org/0009-0006-0080-4799)
- Ohood K. Almuzaini
- Wajin R. Alruwili
- Abdulaziz H. Al Khzem
- Khalid N. Aldosarry
Institutions
- Prince Sattam Bin Abdulaziz University (SA)
- King Saud bin Abdulaziz University for Health Sciences (SA)
- Umm al-Qura University (SA)
- King Abdullah International Medical Research Center (SA)
- Imam Abdulrahman Bin Faisal University (SA)
Publication Details
- Journal
- Frontiers in Chemistry
- Published
- 2026-03-31
- DOI
- https://doi.org/10.3389/fchem.2026.1753911
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00