Development of a Cationic Amphiphilic Helical Peptidomimetic (B18L) As A Novel Anti-Cancer Drug Lead.
Yuan LyuSteven KopchoFolnetti A AlvarezBryson C OkeomaChioma M OkeomaPublished in: Cancers (2020)
BST-2 is a novel driver of cancer progression whose expression confers oncogenic properties to breast cancer cells. As such, targeting BST-2 in tumors may be an effective therapeutic approach against breast cancer. Here, we sought to develop potent cytotoxic anti-cancer agent using the second-generation BST-2-based anti-adhesion peptide, B18, as backbone. To this end, we designed a series of five B18-derived peptidomimetics. Among these, B18L, a cationic amphiphilic α-helical peptidomimetic, was selected as the drug lead because it displayed superior anti-cancer activity against both drug-resistant and drug-sensitive cancer cells, with minimal toxicity on normal cells. Probing mechanism of action using molecular dynamics simulations, biochemical and membrane biophysics studies, we observed that B18L binds BST-2 and possesses membranolytic characteristics. Furthermore, molecular biology studies show that B18L dysregulates cancer signaling pathways resulting in decreased Src and Erk1/2 phosphorylation, increased expression of pro-apoptotic Bcl2 proteins, caspase 3 cleavage products, as well as processing of the caspase substrate, poly (ADP-ribose) polymerase-1 (PARP-1), to the characteristic apoptotic fragment. These data indicate that through the coordinated regulation of membrane, mitochondrial and signaling events, B18L executes cancer cell death and thus has the potential to be developed into a potent and selective anti-cancer compound.
Keyphrases
- cell death
- drug resistant
- molecular dynamics simulations
- papillary thyroid
- cell cycle arrest
- induced apoptosis
- poor prognosis
- squamous cell
- anti inflammatory
- multidrug resistant
- oxidative stress
- breast cancer cells
- squamous cell carcinoma
- childhood cancer
- pi k akt
- binding protein
- cell proliferation
- emergency department
- lymph node metastasis
- escherichia coli
- dna repair
- machine learning
- big data
- adverse drug
- epithelial mesenchymal transition
- staphylococcus aureus
- tyrosine kinase
- drug induced
- artificial intelligence