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Bioinformatics Analysis of Physichemical Properties of Protein Sorting Signals

Subcellular localization of proteins is usually guided by their sorting signals encoded by subsequences of amino acids at the N-terminal or C-terminal ends. These signals are usually composed of a set of physichemically conserved amino acid groups such as the hydrophoblic cores of secretory signal peptides. Using experimentally determined sorting signals, biologists have identified the physichemical models of several categories of sorting motifs. Here we proposed a bioinformatics algorithm for de novo identification of physichemical groups enriched within a set of proteins without knowing the sorting signals themselves. Experiments showed that our binominal distribution based enrichment test algorithm have successfully identified the known sorting signal properties of secretory signal peptides, nuclear localization signals, and mitochondrial sorting signals.