Title:Structure-based Virtual Screening, Molecular Docking, Molecular
Dynamics Simulation, and Metabolic Reactivity Studies of
Quinazoline Derivatives for their Anti-EGFR Activity Against
Tumor Angiogenesis
Volume: 31
Issue: 5
Author(s): Altaf Ahmad Shah, Shaban Ahmad, Manoj Kumar Yadav, Khalid Raza, Mohammad Amjad Kamal and Salman Akhtar*
Affiliation:
- Novel Global Community Educational
Foundation, Hebersham, NSW 2770, Australia
- Department of Bioengineering, Integral University, Lucknow,
Uttar Pradesh, 226026, India
Keywords:
Tumour angiogenesis, T790M mutation, C797S mutation, drug resistance, metabolic reactivity, hERG inhibition.
Abstract:
Background: Epidermal growth factor receptor (EGFR/HER-1) and its role in tumor development
and progression through the mechanism of tumor angiogenesis is prevalent in non-small lung cancer,
head and neck cancer, cholangiocarcinoma & glioblastoma. Previous treatments targeting the oncogenic
activity of EGFR's kinase domain have been hindered by acquired mutational resistance and side
effects from existing drugs like erlotinib, highlighting the need for new EGFR inhibitors through structure-
based drug designing.
Objective: The research aims to develop novel quinazoline derivatives through structure-based virtual
screening, molecular docking, and molecular dynamics simulation to potentially interact with EGFR's kinase
domain and impede tumor angiogenic phenomenon.
Methods: Quinazoline derivatives were retrieved and filtered from the PubChem database using structure-
based virtual screening and the Lipinski rule of five drug-likeness studies. Molecular docking-based
virtual screening methods and molecular dynamics simulation were then carried out to identify top leads.
Results: A total of 1000 quinazoline derivatives were retrieved, with 671 compounds possessing druglike
properties after applying Lipinski filters. Further filtration using ADME and toxicity filters yielded
28 compounds with good pharmacokinetic profiles. Docking-based virtual screening identified seven
compounds with better binding scores than the control drug, dacomitinib. After cross-checking binding
scores, three top compounds QU524, QU571, and QU297 were selected for molecular dynamics simulation
study of 100 ns interval using Desmond module of Schrodinger maestro to understand their conformational
stability.
Conclusion: The research results showed that the selected quinazoline leads exhibited better binding
affinity and conformational stability than the control drug, erlotinib. These compounds also had good
pharmacokinetic and pharmacodynamic profiles and did not violate Lipinski’s rule of five limits. The
findings suggest that these leads have the potential to target EGFR's kinase domain and inhibit the
EGFR-associated phenomenon of tumor angiogenesis.
