title: Prediction of protein signal sequences and their cleavage sites.
abstract: Protein signal sequences play a central role in the targeting and translocation of nearly all secreted proteins and many integral membrane proteins in both prokaryotes and eukaryotes. The knowledge of signal sequences has become a crucial tool for pharmaceutical scientists who genetically modify bacteria, plants, and animals to produce effective drugs. However, to effectively use such a tool, the first important thing is to find a fast and effective method to identify the "zipcode" entity; this is also evoked by both the huge amount of unprocessed data available and the industrial need to find more effective vehicles for the production of proteins in recombinant systems. In view of this, a sequence-encoded algorithm was developed to identify the signal sequences and predict their cleavage sites. The rate of correct prediction for 1,939 secretory proteins and 1,440 nonsecretory proteins by self-consistency test is 90.14% and that by jackknife test is 90.13%. The encouraging results indicate that the signal sequences share some common features although they lack similarity in sequence, length, and even composition and that they are predictable to a considerably accurate extent.
authors.affiliation: Computer-Aided Drug Discovery, Pharmacia, Kalamazoo, Michigan 49007-4940, USA. kuo-chen.chou@am.pnu.com
authors.forename: K C
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D001665:Binding Sites; D006801:Humans; D008956:Models, Chemical; D021382:Protein Sorting Signals
chemical_list: D021382:Protein Sorting Signals