Molecular Docking, Molecular Dynamics Simulation, and Analysis of EGFR-derived Peptides against the EGF

Abstract

Background: The epidermal growth factor receptor (EGFR) is a member of the tyrosine kinase receptor family known as ErbB. The EGFR signaling pathway is an important regulator of cell proliferation, differentiation, division, and survival, as well as cancer development in humans. Epidermal growth factor, betacellulin, amphiregulin, transforming growth factor and heparin-binding EGF-like growth factor are high-affinity ligands of EGFR. Objective: Tumor progression can be effectively prevented by inhibiting EGF/EGFR interactions. In this study, many anti-EGF peptides targeting EGFR binding regions were designed, modeled, and evaluated. After selecting the peptides with the highest binding energy to the EGF, the interactions between the candidate peptides and all of the key EGFR ligands were investigated. Methods: To identify an EGF-binding peptide capable of blocking EGFR-EGF interactions, large-scale peptide mutation screening was performed. Using the AntiCP server, several possible peptides with anti-cancer properties were identified. The ClusPro analysis was performed in order to analyze the interactions between EGF and all of the library peptides. A total of five peptides with favorable docking scores were identified. The stability of three peptides with the best docking scores in complex with EGF was verified, applying molecular dynamics simulation with the help of the GROMACS software package. Finally, the interaction of candidate peptides with transforming growth factor-alpha, heparin-binding EGF-like growth factor, and betacellulin was investigated using the ClusPro server. Results: After the screening of modeled peptides by the ClusPro server and GROMACS software, two anti-EGF peptides of Pep4 and Pep5 with 31 residues were developed. Then, we demonstrate that both of these peptides can bind to the other high-affinity ligands of EGFR and block TGFA/EGFR, HBEGF/EGFR, and BTC/EGFR interactions. result: After screening of modeled peptides by the ClusPro server and GROMACS software, two anti-EGF peptides of Pep4 and Pep5 with 31 residues were developed. Then, we demonstrate that both of these peptides can bind to the other high-affinity ligands of EGFR and block TGFA/EGFR, HBEGF/EGFR, and BTC/EGFR interactions. Conclusion: The findings suggest novel insights for developing therapies based on peptides for inhibiting the EGF, TGFA, HBEGF, and BTC signaling cascade in cancer cells. Pep4 and Pep5 designed in this work, are recommended as potentially promising anticancer peptides for further experimental evaluation. other: Running title: Anti- EGF Peptides for Cancer Therapeutics