In Silico Design and Analysis of a Novel Ranibizumab-derived Peptide against the Vascular Endothelial Growth Factor.

Abstract

Purpose: Blocking the interaction between vascular endothelial growth factor (VEGF) and vascular endothelial growth factor receptor-2 (VEGFR2) is recognized as an effective strategy for treating neovascular age-related macular degeneration (nAMD). The present research aimed at designing and modelling an anti-VEGF peptide based on ranibizumab for potential application in inhibiting the VEGF/VEGFR2 interaction.

Methods: Effective amino acids in the interaction between VEGF and ranibizumab were analyzed using Swiss-PdbViewer (SPDBV), PyMOL, and Chimera software. The effective area in this interaction was determined and applied as a basis to design a peptide. Then, this sequence (containing 25 amino acids) was subjected to random mutagenesis, and the binding affinity of the resulting peptides was analyzed using the ClusPro software. Subsequently, GROMACS v5.0.6 was employed for molecular dynamics (MD) simulations to evaluate the stability of target-ligand complexes. Ultimately, the peptide exhibiting the highest affinity was grafted into the kB1 and MCoTI-II frameworks to enhance the stability.

Results: This modification resulted in improved peptide-VEGF binding affinity, demonstrating the potential of in silico design for creating effective anti-angiogenic peptides in antiangiogenic therapies.

Conclusion: The findings from this study provide a basis for designing and validating peptide inhibitors against VEGF.