Bioinformatic modeling, cloning and expression of AntiVEGF disulfid –rich peptide

Abstract

ntroduction: A variety of key human physiological processes rely on angiogenesis. Furthermore, this process significantly contributes to tumor progression, invasion and metastasis. As the strongest inducer of angiogenesis, VEGF and its receptor are targets of therapeutic research for blocking pathological angiogenesis. Preventing the interaction between VEGF and VEGFR2 by a peptide is a promising strategy for the development of novel anti-cancer therapeutics. This study was conducted with the aim of designing and evaluating the anti-VEGF peptides using bioinformatics and laboratory methods. Materials and Methods: The effective amino acid sequences in the interaction of VEGF-A and VEGFR-2 were investigated using Chimera, SPDBV and PyMOL software. The VEGF binding sites on the receptor were determined and used as the basis for peptide design. The binding affinity of the resulting peptides was analyzed by Hex 8.0.0 and ClusPro software. Then, GROMACS v5.0.6 has been used for Molecular Dynamics (MD) simulation and assessing the stability of target-ligand complexes. The gene coding for the selected peptide was cloned and expressed in E. coli BL21. The bacterial cells were cultured and the expressed recombinant peptide was purified using Ni-NTA chromatography. The reactivity of the peptide with VEGF was confirmed using western blotting and ELISA assays. Finally, the inhibition potency of the peptide on human umbilical vein endothelial cells was assessed using the MTT assay. Results: Among the three peptides (PepA, SFTI-1- PepA-L1 and Pep1) derived from VEGFR2, the Pep1 with the best ELISA result and the highest reactivity with VEGF was selected for further in vitro analysis. Western blot analysis confirmed the specific reactivity of the selected peptide with VEGF. The MTT assay revealed