Computational assessment of pigment epithelium-derived factor as an anti-cancer protein during its interaction with the receptors

Pigment epithelium-derived factor (PEDF) is a member of the serine proteinase inhibitor (serpin) with antiangiogenic, anti-tumorigenic, antioxidant, anti-atherosclerosis, antithrombotic, anti-inflammatory, and neuroprotective properties. The PEDF can bind to low-density lipoprotein receptor-related protein 6 (LRP6), laminin (LR), vascular endothelial growth factor receptor 1 (VEGFR1), vascular endothelial growth factor receptor 2 (VEGFR2), and ATP synthase beta-subunit receptors. In this study, we aimed to investigate the structural basis of the interaction between PEDF and its receptors using bioinformatics approaches to identify the critical amino acids for designing anticancer peptides. The human ATP synthase beta-subunit was predicted by homology modeling. The molecular docking, molecular dynamics (MD) simulation, and Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) were used to study this protein-receptor complex. The molecular docking showed PEDF could bind to the Laminin and VEGFR2 much stronger than ATP synthase beta-subunit, VEGFR1, and LRP6. The PEDF could effectively interact with various receptors during the simulation. The N-terminal of PEDF has an important role in the interaction with the receptors. The MM/PBSA showed the electrostatic (Delta E-Elec) and van der Waals interactions (Delta E-VdW) contributed positively to the binding process of the complexes. The critical amino acids in the binding interaction of PEDF to its receptors in the MD simulation were determined. The interaction mode of 34-mer PEDF to laminin, VEGFR2, and LRP6 were different from VEGFR1, ATP synthase beta-subunit. The 34-mer PEDF has an important role in the interaction with different receptors and these critical amino acids can be used for designing peptides for future therapeutic aims. Communicated by Ramaswamy H. Sarma

Automated summary

This study aimed to investigate the structural basis of the interaction between PEDF and its receptors using bioinformatics approaches, in order to identify the critical amino acids for designing anticancer peptides. The results showed that PEDF could effectively interact with different receptors and its N-terminal played an important role in the interaction with receptors.