HYDROPHOBIC NEIGHBORING HOMOLOGY (HNH) DOTPLOT - AN APPROACH FOR ASSESSING STRUCTURALLY SIMILAR MOTIFS IN PROTEINS

Structural biology needs sensitive tools to detect homology between pr oteins of low sequence identity, but with closely related 3-D structur es. Using a conventional dotplot method, we therefore introduced 2 con cepts to improve the search for similarities between secondary structu res of analyzed proteins: 'hydrophobic neighboring homology' (HNH) and 'amino acid degeneracy classes'. The amino acids are grouped into 3 s ubsets: hydrophobic, hydrophilic and mimetic, A 'Neighboring Similarit y Index' (NSI) is calculated for every residue pair and quantifies its neighbor homology. By thresholding the homology matrix and filtering the dotplot, the homologous patterns are extracted. We have evaluated the efficiency and limits of the method using 21 protein pairs extract ed from the Protein Data Bank (PDB), or selected from the recent liter ature. Globally, we again find the homologous structures (alpha-helice s and beta-strands) of these pair proteins, The introduction of neighb or residue hydrophobicity in the conventional dotplot improves the ali gnment of proteins with low sequence identity (< 25%). HNH, written in standard ANSI C with the graphic library X11, under UNIX, is availabl e on request.