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High-throughput identification of putative receptors for cancer-binding peptides using biopanning and microarray analysis.
Ferraro DJ, Bhave SR, Kotipatruni RP, Hunn JC, Wildman SA, Hong C, Dadey DY, Muhoro LK, Jaboin JJ, Thotala D, Hallahan DE., Integr Biol (Camb). 2012 Nov 13. doi: 10.1039/C2IB20187A [Epub ahead of print]

Phage-display peptide biopanning has been successfully used to identify cancer-targeting peptides in multiple models. For cancer-binding peptides, identification of the peptide receptor is necessary to demonstrate the mechanism of action and to further optimize specificity and target binding. The process of receptor identification can be slow and some peptides may turn out to bind ubiquitous proteins not suitable for further drug development. In this report, we describe a high-throughput method for screening a large number of peptides in parallel to identify peptide receptors, which we have termed “reverse biopanning.” Peptides can then be selected for further development based on their receptor. To demonstrate this method, we screened a library of 39 peptides previously identified in our laboratory to bind specifically to cancers after irradiation. The reverse biopanning process identified 2 peptides, RKFLMTTRYSRV and KTAKKNVFFCSV, as candidate ligands for the protein tax interacting protein 1 (TIP-1), a protein previously identified in our laboratory to be expressed in tumors and upregulated after exposure to ionizing radiation. We used computational modeling as the initial method for rapid validation of peptide–TIP-1 binding. Pseudo-binding energies were calculated to be −360.645 kcal mol−1, −487.239 kcal mol−1, and −595.328 kcal mol−1 for HVGGSSV, TTRYSRV, and NVFFCSV respectively, suggesting that the peptides would have at least similar, if not stronger, binding to TIP-1 compared to the known TIP-1 binding peptide HVGGSSV. We validated peptide binding in vitro using electrophoretic mobility shift assay, which showed strong binding of RKFLMTTRYSRV and the truncated form TTRYSRV. This method allows for the identification of many peptide receptors and subsequent selection of peptides for further drug development based on the peptide receptor.