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Expert system for predicting protein localization sites in gram‐negative bacteria
Author(s) -
Nakai Kenta,
Kanehisa Minoru
Publication year - 1991
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.340110203
Subject(s) - periplasmic space , bacterial outer membrane , cytoplasm , signal peptide , bacteria , peptide sequence , inner membrane , outer membrane efflux proteins , biochemistry , amino acid , gram negative bacteria , membrane , biology , amino acid residue , membrane protein , subcellular localization , sequence (biology) , escherichia coli , genetics , gene
We have developed an expert system that makes use of various kinds of knowledge organized as “if‐then” rules for predicting protein localization sites in Gram‐negative bacteria, given the amino acid sequence information alone. We considered four localization sites: the cytoplasm, the inner (cytoplasmic) membrane, the periplasm, and the outer membrane. Most rules were derived from experimental observations. For example, the rule to recognize an inner membrane protein is the presence of either a hydrophobic stretch in the predicted mature protein or an uncleavable N‐terminal signal sequence. Lipoproteins are first recognized by a consensus pattern and then assumed present at either the inner or outer membrane. These two possibilities are further discriminated by examining an acidic residue in the mature N‐terminal portion. Furthermore, we found an empirical rule that periplasmic and outer membrane proteins were successfully discriminated by their different amino acid composition. Overall, our system could predict 83% of the localization sites of proteins in our database.