Predicting in vivo protein peptide interactions with random phage display

Binding sites in protein complexes occasionally map to small peptides within one or more proteins. Random peptide display methods simulate binding interactions by providing all possible peptide combinations with an equal opportunity to bind a protein of interest. The natural substrates for the protein are typically known in advance. However, it is often the case that such substrates are identified as putative partner proteins by using in vivo methods such as yeast two hybrid screening. Unfortunately, such methods often produce lengthy datasets of protein sequences and offer little mechanistic insight into how such interactions might take place in vivo. Here, we review an approach that addresses this problem. First, sequence alignment tools identify and characterize blocks of conserved sequences among peptides recovered during random peptide display. Next, searching programs detect similar blocks of conserved sequences within naturally occurring proteins to predict partner proteins. Finally, the significance of an interaction is tested using site specific mutagenesis, binding competition or co-immunoprecipitation experiments. This strategy should become increasingly powerful with the growing popularity of interaction studies, sequencing projects and microarray analyses in modern biology.