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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
Structure-based virtual screening, pharmacokinetic prediction, molecular dynamics studies for the identification of
Mohan Anbuselvam1, Murugesh Easwaran2, Arun Meyyazhagan3
1Department of Biotechnology, Selvamm College of Arts and Science (Autonomous), Namakkal, India.
Abstract:
Breast cancer is one of the most prevalent malignancy cancer types especially affecting women globally. EGFR is a proto onco gene as well as the first identified tyrosine kinase receptor. It plays a dynamic role in many biological tasks such as apoptosis, cell cycle progression, differentiation, development and transcription. Somatic mutation in the EGFR kinase domain derails the normal kinase activity and over expression leads to the progression of cancer especially breast cancer. EGFR is one of the well-known therapeutic targets for breast cancer. In this scenario, we attempt to identify novel potent inhibitors of EGFR. Initially, we performed structure-based virtual screening and identified four potential compounds effective against EGFR. Further, the compounds were subjected to ADME prediction as part of evaluation of the druggability and all the four compounds found to fall under satisfactory range with predicted pharmacokinetic properties. Eventually, the conformational stability of protein-ligand complex was analyzed at different time scale by using Gromacs software. Molecular dynamics simulation run of 20 ns is carried out and results were analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF) to signify the stability of protein-igand complex. The stability of the protein-ligand complex is more stable throughout entire simulation. From the results obtained from in silico studies, we propose that these compounds are exceptionally useful for further lead optimization and drug development.Communicated by Ramaswamy H. Sarma.
Insights
Researchers identified novel potent inhibitors for the Epidermal Growth Factor Receptor (EGFR) in breast cancer. In silico studies confirmed the stability and druggability of four promising compounds for further drug development.
Area of Science:
- Oncology
- Molecular Biology
- Pharmacology
Background:
- Breast cancer is a leading global malignancy, disproportionately affecting women.
- Epidermal Growth Factor Receptor (EGFR) is a key proto-oncogene implicated in cancer progression.
- EGFR mutations and overexpression drive breast cancer development, making it a critical therapeutic target.
Purpose of the Study:
- To identify novel potent inhibitors targeting the Epidermal Growth Factor Receptor (EGFR) for breast cancer treatment.
- To evaluate the druggability and pharmacokinetic properties of identified compounds.
- To assess the conformational stability of protein-ligand complexes using molecular dynamics simulations.
Main Methods:
- Structure-based virtual screening was employed to identify potential EGFR inhibitors.
- ADME (Absorption, Distribution, Metabolism, Excretion) predictions were performed to assess druggability.
- Molecular dynamics simulations (20 ns) using Gromacs analyzed protein-ligand complex stability via RMSD and RMSF.
Main Results:
- Four potential compounds demonstrating efficacy against EGFR were identified through virtual screening.
- All four compounds exhibited satisfactory pharmacokinetic properties based on ADME predictions.
- Molecular dynamics simulations confirmed the conformational stability of the protein-ligand complexes throughout the simulation period.
Conclusions:
- The identified compounds show significant potential as novel EGFR inhibitors for breast cancer.
- These compounds possess favorable druggability and stability profiles, suitable for further optimization.
- The in silico findings support the advancement of these compounds for lead optimization and drug development.
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