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Development of triple mutant T790M/C797S allosteric EGFR inhibitors: a computational approach
Kshipra S Karnik1, Aniket P Sarkate1, Deepak K Lokwani2
1Department of Chemical Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India.
Abstract:
The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. EGFR inhibitors binding allosterically to C797S mutant EGFR enzyme have been developed. Here, database building, library screening performing R-group enumeration and scaffold hopping technique for increasing the EGFR binding affinity of compounds have been carried out. Virtual screening was performed subjecting to HTVS, SP and XP docking protocol along with its relative binding free energy calculations. Molecular docking studies provided the information about binding pockets and interactions of molecules on mutant (PDB: 5D41) as well as wild type (PDB: 4I23) EGFR enzyme. This was supported with ADMET and molecular simulation studies. On the basis of glide score and protein-ligand interactions, highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. The virtually screened molecules can act as potential EGFR inhibitors in the management of drug resistance. Communicated by Ramaswamy H. Sarma.
Insights
Researchers developed novel epidermal growth factor receptor (EGFR) inhibitors to combat non-small cell lung cancer drug resistance. Computational methods identified promising compounds targeting the C797S mutation, offering new therapeutic strategies.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Oncology
Background:
- Non-small cell lung cancer (NSCLC) treatment faces challenges due to drug resistance, particularly involving mutations in the epidermal growth factor receptor (EGFR).
- Targeting the C797S mutation in EGFR is crucial for overcoming resistance to existing EGFR inhibitors.
Purpose of the Study:
- To design and identify novel compounds with enhanced binding affinity to the mutant EGFR enzyme, specifically targeting the C797S mutation.
- To explore structure-based drug design strategies for developing new EGFR inhibitors to manage drug resistance in NSCLC.
Main Methods:
- Database construction, library screening, R-group enumeration, and scaffold hopping were employed to generate potential drug candidates.
- Virtual screening using High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP) docking protocols was performed.
- Molecular docking, binding free energy calculations, ADMET prediction, and molecular dynamic simulations were utilized to assess compound efficacy and stability.
Main Results:
- Molecular docking studies elucidated binding interactions and pockets for both wild-type (PDB: 4I23) and mutant (PDB: 5D41) EGFR enzymes.
- The highest-scoring molecule, selected based on glide score and protein-ligand interactions, underwent molecular dynamic simulation for conformational stability analysis.
- Virtually screened compounds demonstrated potential as effective EGFR inhibitors against drug-resistant forms of NSCLC.
Conclusions:
- The study successfully identified potential EGFR inhibitors through comprehensive computational approaches.
- These findings offer a promising avenue for developing new therapeutic agents to overcome EGFR inhibitor resistance in non-small cell lung cancer patients.
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