Design of a Peptide-Based Model Leads for Scavenging Anions.

Among several peptide-based anion recognition motifs, the "CNN" motif containing C , N, and N of three consecutive residues is unique in its mode of interaction. Having a spatial geometry of βαα or βαβ, this motif occurs in the N terminus of a helix and often found at the functional interface of a protein, mediating crucial biological significance upon interaction with anion(s). The interaction of anion(s) with chimeric peptide sequences containing the naturally occurring "CNN" motif (CPS224Ac, CPS226, and CPS228) reported in our previous attempts strongly confirms that the information regarding the interaction is embedded within the local sequences of the motif segment. At these prevailing circumstances, an effort has been pursued to design novel scaffolds based on the "CNN" motif for achieving better recognition of anion(s). Exploring the existing data set of the "CNN" motif available in the FSSP database, four novel peptide-based scaffolds have been designed (DS1, DS2, DS3, and DS4), and preliminary screenings have been performed using computational approaches. Our initial work suggests that two (DS1 and DS3) out of the four scaffolds are potential candidates for better anion recognition. By employing biophysical characterization using both qualitative and quantitative measures, in this present study, we report the interaction of sulfate and phosphate ions with these two designed scaffolds, in which there is much better recognition of anions by these scaffolds than the natural sequences, justifying their logical engineering. Our observation strongly suggests that these designed scaffolds are better potential candidates than those of the naturally occurring "CNN" motif in terms of anion recognition and could be utilized for the scavenging of anion(s) for different purposes.