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Prediction of membrane protein types and subcellular locations

跨膜蛋白 伪氨基酸组成 膜蛋白 高尔基体 生物 蛋白质靶向 生物化学 内质网 计算生物学 跨膜结构域 亚细胞定位 细胞质 受体
作者
Kuo‐Chen Chou,David W. Elrod
出处
期刊:Proteins [Wiley]
卷期号:34 (1): 137-153 被引量:239
标识
DOI:10.1002/(sici)1097-0134(19990101)34:1<137::aid-prot11>3.0.co;2-o
摘要

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.
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