Jul 2026· Journal of King Saud University: Science· 0 citations
TL;DR
The pharmacophore-based screening and docking analysis identified eleven promising EGFR-binding compounds, of which eight demonstrated optimal ADMET characteristics and stable interactions within the active site during molecular dynamics simulations, suggesting their potential efficacy as EGFR inhibitors.
Abstract
Glioblastoma (GB) is an aggressive and lethal brain tumor characterized by high mortality and poor prognosis. Amplification and mutation of the epidermal growth factor receptor (EGFR) gene are key drivers of GB progression, highlighting EGFR as a promising therapeutic target. This study aimed to identify novel small-molecule EGFR inhibitors through a pharmacophore-guided computational screening approach. A pharmacophore model was generated using the co-crystal ligand (PDB: HYZ) as a template. This model was employed to screen the Specs database comprising approximately 280,000 compounds. Ligand-based virtual screening yielded 323 hits that matched the pharmacophore query. These compounds were subjected to molecular docking against the EGFR active site using the Glide standard precision protocol, applying a binding affinity threshold of -9 kcal/mol. Eleven compounds with favorable docking scores were further evaluated through ADMET (adsorption, distribution, metabolism, excretion, toxicity) profiling, and eight top candidates were subjected to molecular dynamics simulations to assess binding stability. The pharmacophore-based screening and docking analysis identified eleven promising EGFR-binding compounds, of which eight demonstrated optimal ADMET characteristics and stable interactions within the active site during molecular dynamics simulations. The selected molecules exhibited strong binding affinities and favorable conformational stability, suggesting their potential efficacy as EGFR inhibitors. This study identified and characterized novel small molecules with high potential for EGFR inhibition in glioblastoma. These findings provide a foundation for further experimental validation and may contribute to the development of targeted therapies for GB.
Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Fibroblast growth factor 2 (FGF2) is essential in normal neurodevelopment and promotes glioma growth and vascularization. This study aims to identify the binding sites of FGF2 protein receptors using molecular docking and virtual screening with natural compounds, and to determine the free binding energy between FGF2 protein and herbal active compounds from Indonesian plants. This research includes virtual screening with molecular docking using Vina on 1496 Indonesian herbal compounds, docking with Autodock4.2.6, and analysis of the Autodock4.2.6 docking results using Ligplot+. The amino acids derived from the FGF2 protein bind well to each of the FGFR 1-4 receptors. In the virtual screening, the synthetic compound Temozolomide had docking scores in the range (-4.4) to (-5.0), while compounds from Indonesian herbal plants had docking scores in the range (-6.8) to (-8.1). Hydrogen and hydrophobic interactions occur between the FGF2 receptor and selected herbal compounds. This shows the interaction is stable. These natural compounds will inhibit FGF2 binding to other receptors, thereby inducing apoptosis in FGF2. The results of blind docking show that the binding sites are similar, indicating good accuracy. In summary, Pyranoamentoflavone compounds found in nyamplung (Calophyllum Inophyllum), 5,3',5'-Trihydroxy-6,7,4'-trimethoxyflavone in kemuning (Murura Paniculata), and Sotetsuflavone in jamb antidote (Cycas Revoluta) have good potential as an FGF2 inhibitor as an anti-cancer drug for Glioblastoma.
N. Fernando, Agus Kartono, S. T. Wahyudi· Jurnal Ilmiah Berkala Sains...· 0 citations
This research developed a promising lead molecule (HIT1) as a therapeutic approach for ER-positive breast cancer through pharmacophore model-based drug design of thiazine derivative targeting ERα via pharmacophore model-based drug design.
M. Sanjeev, Bhim Singh, Kailash Jangid et al.· Journal of Molecular Graphic...· 0 citations
In recent years, in the treatment of non-small-cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR) inhibitors have demonstrated ideal clinical efficacy. Unfortunately, a significant obstacle to targeted lung cancer therapy is the unavoidable emergence of acquired resistance to EGFR inhibitors through a variety of pathways during a period of medication. The third-generation EGFR inhibitor Lazertinib, which is potent, irreversible, brain-penetrant, mutant-selective, and wild type-sparing, was used to treat patients with advanced or metastatic NSCLC. Lazertinib can bind to EGFRT790M in different conformations, identified by a 180° rotation of the pyrazole moiety, according to the X-ray co-crystal structure. A molecular modeling study integrating molecular dynamics and free energy calculation was conducted to comprehend the distinct binding manner of Lazertinib binding to EGFR and the structural need for the inhibitory activity. According to binding free energy calculations, Lazertinib has a greater binding affinity with EGFRT790M than EGFRWT, which is in accordance with the experimental observations. Additionally, it confirms that Lazertinib preferentially binds to EGFRT790M with the same conformation as in EGFRWT. The residues that made a greater contribution to the binding of Lazertinib to EGFR were identified using the per-residue energy decomposition. It is anticipated that these findings will be helpful to the rational development of new EGFR inhibitors.
Background: HER2 is a key oncogenic gene in breast cancer, involved in tumor progression, metastasis, and therapeutic resistance. This study aimed to find new HER2 inhibitors using a hybrid of machine learning (ML) and structure-based virtual screening (VS), combined with molecular dynamics (MD) simulations on various scaffolds. Methods: Four supervised molecular fingerprint classification models were trained on a dataset of 10,000 validated compounds from ChEMBL. Random Forest was the top model for screening a large compound library. Selected compounds underwent molecular docking in the HER2 ATP binding site, ADMET, drug likeness, toxicity analysis, and 200 ns MD simulations. Methods like PCA, FEL, hydrogen-bond analysis, DCCM, RDF, salt-bridge analysis, and MM/PBSA were used to assess binding stability. Results: Virtual screening identified three compounds, CHMEBL193865 (Lead-1), CHMEBL46740 (Lead-2), and CHMEBL151318 (Lead-3)—with better binding affinity and interaction profiles than the reference inhibitor. MD simulations showed stable protein–ligand complexes with RMSD values of 2.32–2.76 Å. Among these, Lead-2 was the most structurally stable, and Lead-1 had the most favorable binding free energy. All three compounds showed good drug likeness, ADMET properties, and low predicted toxicity. Conclusions: These findings support further in vitro and in vivo testing for developing new therapeutics against HER2-overexpressing breast cancer, highlighting two scaffolds with promising lead optimization potential.
Alhumaidi B. Alabbas, Safar M. Alqahtani· Pharmaceuticals· 0 citations
Breast cancer (BC), a malignant disease responsible for high fatality worldwide, is characterized by EGFR overexpression or mutation, which contributes to tumor cell survival and progression. The present study explored the efficacy of Genistein in modulating EGFR using an integrated computational approach. Common targets of Genistein (SwissTargetPrediction) and BC (GeneCards) were identified, followed by PPI, GO, and KEGG enrichment analyses using STRING. The Genistein–targets–pathways network was constructed using Cytoscape 3.10.0. Docking, MM/GBSA binding free‐energy calculations, molecular dynamics (MD) simulations, and post‐MD analyses (PCA and FEL) were performed for Genistein and the reference inhibitor Afatinib against EGFR. Docking scores of Genistein (−8.96 kcal/mol) and Afatinib (−10.22 kcal/mol) demonstrated comparable binding within the EGFR ATP‐binding pocket, with Genistein retaining interactions with key catalytic residues. The MM/GBSA binding free‐energy of Genistein (−134.96 kcal/mol) and Afatinib (−137.92 kcal/mol) differed only marginally, indicating comparable binding stability within the EGFR domain. MD simulations, together with RMSD, RMSF, radius of gyration, SASA, PCA, and FEL analyses, confirmed the structural stability of the Genistein‐EGFR complex throughout the simulation. Collectively, these findings suggest that Genistein is a promising multitarget EGFR‐modulating compound that warrants further experimental validation through in vitro and in vivo studies.
N. Lonikar, Sameep Sonvane, N. B. Bavage et al.· ChemistrySelect· 0 citations
A number of lead candidates with strong EGFR inhibitory potential, promising pharmacokinetic profiles, and mutant selectivity were successfully identified by the integrated computational approach.
M. Kendre, Sachin S. Bhusari, Pravin S. Wakte· Journal of Pharmaceutical In...· 0 citations
