In silico identification of EGFR tyrosine kinase inhibitors for glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults and is characterized by rapid progression, limited therapeutic options and poor survival outcomes. Aberrant activation of receptor tyrosine kinases (RTKs), particularly epidermal growth factor receptor (EGFR), results in persistent activation of oncogenic signalling pathways promoting tumorigenesis, disease progression and therapeutic resistance. Although several RTK inhibitors have been evaluated in clinical trials for GBM, their therapeutic efficacy remains limited by challenges such as the development of drug resistance and low blood-brain barrier (BBB) penetration. This study aimed to identify potential EGFR tyrosine kinase inhibitors using various in silico methods. Ligand-based virtual screening of chemical databases was performed using the SwissSimilarity web tool, applying a combined 2D-fingerprint and 3D-shape similarity search algorithm. Lapatinib, a dual EGFR/HER2 tyrosine kinase inhibitor that binds to the inactive-like conformation of EGFR kinase domain, was used as the reference ligand for similarity searching. A total of 688 structural analogs of lapatinib were subsequently retrieved and evaluated for physicochemical properties, pharmacokinetic parameters, drug-likeness and toxicity using SwissADME and ProTox 3.0 web servers. A subset of 16 compounds exhibiting favorable predicted pharmacokinetic and safety profiles, BBB penetration and drug-like characteristics were prioritized for molecular docking. Molecular docking was performed using AutoDock Vina to estimate the binding affinities of selected compounds to the target protein. Predicted binding poses and molecular interactions were visualized using PyMOL. Molecular docking revealed several compounds with favorable binding affinities to the target protein and key molecular interactions within the EGFR tyrosine kinase domain. The compounds identified and evaluated through this computational approach represent promising candidates for further structural optimization and in vitro experimental validation.