Molecules (Nov 2016)

Unraveling the Roots of Selectivity of Peptide Affinity Reagents for Structurally Similar Ribosomal Inactivating Protein Derivatives

  • Deborah A. Sarkes,
  • Margaret M. Hurley,
  • Dimitra N. Stratis-Cullum

DOI
https://doi.org/10.3390/molecules21111504
Journal volume & issue
Vol. 21, no. 11
p. 1504

Abstract

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Peptide capture agents have become increasingly useful tools for a variety of sensing applications due to their ease of discovery, stability, and robustness. Despite the ability to rapidly discover candidates through biopanning bacterial display libraries and easily mature them to Protein Catalyzed Capture (PCC) agents with even higher affinity and selectivity, an ongoing challenge and critical selection criteria is that the peptide candidates and final reagent be selective enough to replace antibodies, the gold-standard across immunoassay platforms. Here, we have discovered peptide affinity reagents against abrax, a derivative of abrin with reduced toxicity. Using on-cell Fluorescence Activated Cell Sorting (FACS) assays, we show that the peptides are highly selective for abrax over RiVax, a similar derivative of ricin originally designed as a vaccine, with significant structural homology to abrax. We rank the newly discovered peptides for strongest affinity and analyze three observed consensus sequences with varying affinity and specificity. The strongest (Tier 1) consensus was FWDTWF, which is highly aromatic and hydrophobic. To better understand the observed selectivity, we use the XPairIt peptide–protein docking protocol to analyze binding location predictions of the individual Tier 1 peptides and consensus on abrax and RiVax. The binding location profiles on the two proteins are quite distinct, which we determine is due to differences in pocket size, pocket environment (including hydrophobicity and electronegativity), and steric hindrance. This study provides a model system to show that peptide capture candidates can be quite selective for a structurally similar protein system, even without further maturation, and offers an in silico method of analysis for understanding binding and down-selecting candidates.

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