Anticancer Peptide Therapeutics targeting the Epidermal Growth Factor Receptor
Disciplines
Biochemistry | Bioinformatics | Computational Chemistry | Medicinal-Pharmaceutical Chemistry
Abstract (300 words maximum)
Epidermal Growth Factor Receptor (EGFR), one of the most studied signal transduction systems, is a member of the receptor tyrosine kinase family. The receptor is located at the cell interface, where the binding of several ligands activates and promotes cell growth, proliferation, and survival. However, the genetic variations by non-synonymous single nucleotide polymorphism (nsSNP) can change the structure and function of the EGFR gene that causes development and progression of various cancers. Several small molecules drug showed promising results targeting the EGFR, however, no study has been performed for anticancer peptide therapeutics. Peptide therapeutics has many benefits over small-molecule medications, as they are highly selective, well-tolerated, have less adverse effects and undergo quicker clinical development and FDA approval period, despite challenges associated to short half-lives, rapid clearance, cost, and intravenous administration. In this study, we aim to identify novel peptide candidates against the EGFR mutants employing computer-aided drug design, and native mass spectrometry. For peptide modelling, Pepfold server was used, and subsequently molecular docking was conducted by PatchDock and FireDock. Our preliminary computational screening data showed that three peptides include Alloferon-1, Anti-cancerous Peptide 1 (Cr-ACP1), and Chaxapeptin showed the binding affinities of -54.26, -53.4, and -51.7 Kcal/mol respectively. The best candidate peptides will be synthesized, and their performance will be tested by native mass spectrometry.
Academic department under which the project should be listed
CSM - Chemistry and Biochemistry
Primary Investigator (PI) Name
Mohammad A. Halim
Anticancer Peptide Therapeutics targeting the Epidermal Growth Factor Receptor
Epidermal Growth Factor Receptor (EGFR), one of the most studied signal transduction systems, is a member of the receptor tyrosine kinase family. The receptor is located at the cell interface, where the binding of several ligands activates and promotes cell growth, proliferation, and survival. However, the genetic variations by non-synonymous single nucleotide polymorphism (nsSNP) can change the structure and function of the EGFR gene that causes development and progression of various cancers. Several small molecules drug showed promising results targeting the EGFR, however, no study has been performed for anticancer peptide therapeutics. Peptide therapeutics has many benefits over small-molecule medications, as they are highly selective, well-tolerated, have less adverse effects and undergo quicker clinical development and FDA approval period, despite challenges associated to short half-lives, rapid clearance, cost, and intravenous administration. In this study, we aim to identify novel peptide candidates against the EGFR mutants employing computer-aided drug design, and native mass spectrometry. For peptide modelling, Pepfold server was used, and subsequently molecular docking was conducted by PatchDock and FireDock. Our preliminary computational screening data showed that three peptides include Alloferon-1, Anti-cancerous Peptide 1 (Cr-ACP1), and Chaxapeptin showed the binding affinities of -54.26, -53.4, and -51.7 Kcal/mol respectively. The best candidate peptides will be synthesized, and their performance will be tested by native mass spectrometry.