A surrogate-based approach for post-genomic partner identification

Abstract

Background: Modern drug discovery is concerned with identification and validation of novel protein targets from among the 30,000 genes or more postulated to be present in the human genome. While protein-protein interactions may be central to many disease indications, it has been difficult to identify new chemical entities capable of regulating these interactions as either agonists or antagonists.

Results: In this paper, we show that peptide complements (or surrogates) derived from highly diverse random phage display libraries can be used for the identification of the expected natural biological partners for protein and non-protein targets. Our examples include surrogates isolated against both an extracellular secreted protein (TNFbeta) and intracellular disease related mRNAs. In each case, surrogates binding to these targets were obtained and found to contain partner information embedded in their amino acid sequences. Furthermore, this information was able to identify the correct biological partners from large human genome databases by rapid and integrated computer based searches.

Conclusions: Modified versions of these surrogates should provide agents capable of modifying the activity of these targets and enable one to study their involvement in specific biological processes as a means of target validation for downstream drug discovery.

Figure 1a

Peptide surrogates with RGG Box Sequences. Random peptide libraries were panned on four different mRNA targets. Isolated phage binders from rounds three and four of each pan, were sequenced. Several peptides from each pan showed the presence of the RGG box, a well-defined RNA-binding motif [8,9]. RGG sequences in each surrogate is in bold and underlined. Peptide surrogate with KH Domain. Panning of the 20-mer random peptide library on target M1 isolated a phage clone containing the sequence VIGxxGxxF which is similar to an RNA-binding motif, the KH motif [8,9]. The surrogate motif corresponding to the KH domain is in bold and underlined.

Figure 2

RRE Binding Motif. Alignment of Rev peptide with surrogate peptides containing the (K/R)LRRRP motif. surrogates were obtained by panning a portion of the RRE mRNA using the 40 mer random peptide library. Consensus motifs are in bold and underlined.

Figure 3

surrogate Maturation. One clone for each of the three targets – APP, HCV, and IGF was identified for generation of secondary libraries. Residues that were selected for after four rounds of panning are indicated in bold and underlined.

Figure 4

HCV-eIF3 Binding Motif. Alignment of eIF3 with surrogate peptides containing the TxRLL motif. surrogate peptides were obtained by panning a portion of the 5'UTR of HCV mRNA using both the 20 mer and 40 mer random libraries. Peptides HCV-3-F5 and HCV-3-H8 were obtained from the 40-mer library from the same pan. Peptide HCV-NG-D9 was obtained from the 40 mer library using modified experimental conditions. Peptide HCV-3-C3 was obtained from the 20 mer library. Consensus sequences are in bold and underlined. Sequences outside the motif that are conserved between the surrogates and eIF3 are in Italics and underlined.

Figure 5

Alignment of the TNFβ surrogate peptide KcB7 with its cognate receptor TNFR1 (p55). Peptide KcB7 was isolated by panning TNFβ. The peptide has the sequence RKEMGGGGGPGWSENLFQ and a BLASTp search revealed identity to amino acids 77–81 (RKEMG) and amino acids 107–113 (WSENLFQ) on TNFR1 (p55). RKEMG is involved in binding of TNFR1 to the A subunit of TNFβ while WSENL binds to several amino acids in the C subunit of TNFβ