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Originally published In Press as doi:10.1074/jbc.M204161200 on August 16, 2002

J. Biol. Chem., Vol. 277, Issue 48, 45765-45769, November 29, 2002
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Using Functional Domain Composition and Support Vector Machines for Prediction of Protein Subcellular Location*

Kuo-Chen ChouDagger and Yu-Dong Cai§

From Dagger  Upjohn Laboratories, Pharmacia, Kalamazoo, Michigan 49001-4940 and § Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China

Proteins are generally classified into the following 12 subcellular locations: 1) chloroplast, 2) cytoplasm, 3) cytoskeleton, 4) endoplasmic reticulum, 5) extracellular, 6) Golgi apparatus, 7) lysosome, 8) mitochondria, 9) nucleus, 10) peroxisome, 11) plasma membrane, and 12) vacuole. Because the function of a protein is closely correlated with its subcellular location, with the rapid increase in new protein sequences entering into databanks, it is vitally important for both basic research and pharmaceutical industry to establish a high throughput tool for predicting protein subcellular location. In this paper, a new concept, the so-called "functional domain composition" is introduced. Based on the novel concept, the representation for a protein can be defined as a vector in a high-dimensional space, where each of the clustered functional domains derived from the protein universe serves as a vector base. With such a novel representation for a protein, the support vector machine (SVM) algorithm is introduced for predicting protein subcellular location. High success rates are obtained by the self-consistency test, jackknife test, and independent dataset test, respectively. The current approach not only can play an important complementary role to the powerful covariant discriminant algorithm based on the pseudo amino acid composition representation (Chou, K. C. (2001) Proteins Struct. Funct. Genet. 43, 246-255; Correction (2001) Proteins Struct. Funct. Genet. 44, 60), but also may greatly stimulate the development of this area.

* The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Current address and to whom correspondence should be addressed: Biomolecular Sciences Dept., UMIST, P. O. Box 88, Manchester, M60 1QD, United Kingdom. Tel.: 44-161-2008936; Fax: 44-161-2360409; E-mail: y.cai@umist.ac.uk.

Copyright © 2002 by The American Society for Biochemistry and Molecular Biology, Inc.
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