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Updated: Jul 17, 2025
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Computer-aided anti-cancer drug discovery of EGFR protein based on virtual screening of drug bank, ADMET, docking,
Miah Roney1,2, Amit Dubey3,4, Muhammad Hassan Nasir5
1Faculty of Industrial Sciences and Technology, Universiti Malafysia Pahang Al-Sultan Abdullah, Lebuhraya Tun Razak, Pahang, Darul Makmur, Malaysia.
Abstract:
Numerous malignancies, including breast cancer, non-small cell lung cancer, and chronic myeloid leukemia, are brought on by aberrant tyrosine kinase signaling. Since the current chemotherapeutic medicines are toxic, there is a great need and demand from cancer patients to find novel chemicals that are toxic-free or have low toxicity and that can kill tumor cells and stop their growth. This work describes the in-silico examination of substances from the drug bank as EGFR inhibitors. Firstly, drug-bank was screened using the pharmacophore technique to select the ligands and Erlotinib (DB00530) was used as matrix compound. The selected ligands were screened using ADMET and the hit compounds were subjected to docking. The lead compound from the docking was subjected to DFT and MD simulation study. Using the pharmacophore technique, 23 compounds were found through virtual drug bank screening. One hit molecule from the ADMET prediction was the subject of docking study. According to the findings, DB03365 molecule fits to the EGFR active site by several hydrogen bonding interactions with amino acids. Furthermore, DFT analysis revealed high reactivity for DB03365 compound in the binding pocket of the target protein, based on ELUMO, EHOMO and band energy gap. Furthermore, MD simulations for 100 ns revealed that the ligand interactions with the residues of EGFR protein were part of the essential residues for structural stability and functionality. However, DB03365 was a promising lead molecule that outperformed the reference compound in terms of performance and in-vitro and in-vivo experiments needs to validate the study.Communicated by Ramaswamy H. Sarma.
Insights
This study identified DB03365 as a promising, low-toxicity EGFR inhibitor candidate for cancer therapy. Computational analysis showed its strong binding to EGFR, suggesting potential for new drug development against various malignancies.
Area of Science:
- Computational chemistry
- Drug discovery
- Molecular modeling
Background:
- Aberrant tyrosine kinase signaling drives numerous cancers, including breast cancer and lung cancer.
- Existing chemotherapy drugs exhibit significant toxicity, necessitating the development of safer alternatives.
- Targeting epidermal growth factor receptor (EGFR) is a key strategy in cancer treatment.
Purpose of the Study:
- To identify novel, low-toxicity EGFR inhibitors from a drug bank using in-silico methods.
- To evaluate the binding potential and molecular interactions of candidate compounds with EGFR.
- To assess the suitability of identified compounds for further preclinical development.
Main Methods:
- Pharmacophore screening of a drug bank to identify potential EGFR inhibitors.
- ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) prediction for selected ligands.
- Molecular docking to assess binding affinity and interactions within the EGFR active site.
- Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations for lead compound analysis.
Main Results:
- Pharmacophore screening yielded 23 potential inhibitor compounds.
- One hit molecule, DB03365, demonstrated favorable ADMET properties and docked effectively into the EGFR active site via hydrogen bonding.
- DFT analysis indicated high reactivity of DB03365 within the EGFR binding pocket.
- 100 ns MD simulations confirmed stable interactions between DB03365 and essential EGFR residues.
Conclusions:
- DB03365 emerged as a promising lead molecule for EGFR inhibition, showing superior predicted performance compared to the reference compound.
- Further in vitro and in vivo validation is required to confirm the therapeutic potential of DB03365.
- This in-silico approach provides a foundation for developing novel, safer anti-cancer therapeutics targeting EGFR.
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