Protein Annotation by Secondary Structure Based Alignments (PASSTA)

Most software tools in homology recognition on proteins answer only a few specific questions, often leaving not much room for the interpretation of the results. We develop a software Passta that helps to decide whether a protein sequence is related to a protein with known structure. Our approach may indicate rearrangements and duplications, and it displays information from different sources in an integrated fashion. Our approach is to first break each sequence of the Protein Data Bank (PDB) into Secondary Structure Elements (SSEs). Given a query sequence, our goal is then to ‘explain’ it by SSE sequences as good as possible. Therefore, we use the Waterman-Eggert algorithm to compute pairwise alignments of SSE sequences with the query. In a graph-based approach, we then select those alignments that reproduce the query in an optimal way. We discuss two examples to illustrate the potential (and possible pitfalls) of the method.