In silico analysis of the effect of mutation on epidermal growth factor receptor in non-small-cell lung carcinoma: from mutational analysis to drug designing

• Published in: Journal of biomolecular structure & dynamics Vol. 35; no. 2; pp. 427 - 434
• Main Authors: Zhao, Fu-Li, Yang, Guang-Hua, Xiang, Sen, Gao, Dong-Dong, Zeng, Chen
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 25.01.2017
• Subjects: Amino Acid Sequence; Carcinoma, Non-Small-Cell Lung - genetics; docking; Drug Design; Drug Resistance, Neoplasm; Humans; Hydrogen Bonding; lung cancer; Lung Neoplasms - genetics; MM-PBSA; Models, Molecular; Molecular Docking Simulation; Molecular Dynamics Simulation; Mutation; NSCLC; Protein Conformation; Protein Kinase Inhibitors - chemistry; Receptor, Epidermal Growth Factor - chemistry; Receptor, Epidermal Growth Factor - genetics; simulations; lung cancer; docking; mutation; MM-PBSA; NSCLC; simulations
• ISSN: 0739-1102; 1538-0254
• DOI: 10.1080/07391102.2016.1146165

Tyrosine kinase inhibitors (TKI)-resistant mutation in epidermal growth factor receptor's (EGFR) kinase domain is an important anomaly to look into. Studying the mutations at atomic level using molecular dynamics simulations gave us an insight into the architectural changes happening at the microscopic level. The knowledge was used to design new TKI whose function is devoid of the affect of the mutations in kinase domain. Traditional Chinese medicinal library was used for structure-based drug designing, where virtual screening was followed by ADME/Tox analysis and the shortlisted compounds were docked into the kinase domain of EGFR and simulated there using atomic-level selection of the grid. The shortlisted compounds from molecular docking analysis were subjected to MM-PBSA calculations. The in silico data generated is giving a strong lead compound for further in vitro and in vivo analysis.