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Updated: Jun 26, 2026
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Computational studies of epidermal growth factor receptor: docking reliability, three-dimensional quantitative
Concettina La Motta1, Stefania Sartini, Tiziano Tuccinardi
1Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.
Abstract:
An aberrant activity of the epidermal growth factor receptor (EGFR) has been shown to be related to many human cancers, such as breast and liver cancers, thus making EGFR an attractive target for antitumor drug discovery. In this study we evaluated the reliability of various kinds of docking software and procedures to predict the binding disposition of EGFR inhibitors. By application of the best procedure and use of more than 200 compounds, a receptor-based 3D-QSAR model for EGFR inhibition was developed. On the basis of the results obtained, the possibility of developing virtual screening studies was also evaluated. The VS procedure that proved to be the most reliable from a computational point of view was then used to filter the Maybridge database in order to identify new EGFR inhibitors. Enzymatic assays revealed that among the eight top-scoring compounds, seven proved to inhibit EGFR activity at a concentration of 100 microM, two of them exhibiting IC(50) values in the low micromolar range and one in the nanomolar range. These results demonstrate the validity of the methodologies followed. Furthermore, the two low micromolar compounds may be considered as very interesting leads for the development of new EGFR inhibitors.
Insights
Researchers developed a reliable computational model to discover new epidermal growth factor receptor (EGFR) inhibitors for cancer drug discovery. This method identified promising compounds with low micromolar and nanomolar activity against EGFR.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Drug Discovery
Background:
- Aberrant epidermal growth factor receptor (EGFR) activity is linked to various human cancers, including breast and liver cancers.
- EGFR is a key target for developing novel antitumor drugs.
Purpose of the Study:
- To assess the reliability of different docking software and procedures for predicting EGFR inhibitor binding.
- To develop a robust 3D-QSAR model for EGFR inhibition using validated computational methods.
Main Methods:
- Evaluation and selection of optimal docking procedures for predicting ligand-receptor interactions.
- Development of a receptor-based 3D-QSAR model using over 200 compounds.
- Virtual screening of the Maybridge database using the validated virtual screening (VS) procedure.
Main Results:
- Seven out of eight top-scoring compounds identified via virtual screening inhibited EGFR activity at 100 microM.
- Two compounds showed low micromolar IC50 values, and one exhibited nanomolar IC50 values.
- The developed computational methodology proved effective in identifying novel EGFR inhibitors.
Conclusions:
- The study validates a reliable computational approach for identifying potential EGFR inhibitors.
- The identified compounds, particularly those with low micromolar activity, represent promising leads for new anticancer drug development targeting EGFR.
