Prediction of membrane protein types and subcellular locations.
Membrane proteins are classified according to two different schemes. In scheme 1, they are discriminated among the following five types: (1) type I single-pass transmembrane, (2) type II single-pass transmembrane, (3) multipass transmembrane, (4) lipid chain-anchored membrane, and (5) GPI-anchored membrane proteins. In scheme 2, they are discriminated among the following nine locations: (1) chloroplast, (2) endoplasmic reticulum, (3) Golgi apparatus, (4) lysosome, (5) mitochondria, (6) nucleus, (7) peroxisome, (8) plasma, and (9) vacuole. An algorithm is formulated for predicting the type or location of a given membrane protein based on its amino acid composition. The overall rates of correct prediction thus obtained by both self-consistency and jackknife tests, as well as by an independent dataset test, were around 76-81% for the classification of five types, and 66-70% for the classification of nine cellular locations. Furthermore, classification and prediction were also conducted between inner and outer membrane proteins; the corresponding rates thus obtained were 88-91%. These results imply that the types of membrane proteins, as well as their cellular locations and other attributes, are closely correlated with their amino acid composition. It is anticipated that the classification schemes and prediction algorithm can expedite the functionality determination of new proteins. The concept and method can be also useful in the prioritization of genes and proteins identified by genomics efforts as potential molecular targets for drug design.
Chou
K C
KC
Computer-Aided Drug Discovery, Pharmacia and Upjohn, Kalamazoo, Michigan 49007-4940, USA.
Elrod
D W
DW
D000465:Algorithms; D002736:Chloroplasts / Q000737:chemistry; D015195:Drug Design; D008565:Membrane Proteins / Q000737:chemistry* / Q000145:classification; D008928:Mitochondria / Q000737:chemistry; D008954:Models, Biological; D015233:Models, Statistical
D008565:Membrane Proteins