Protein subcellular location prediction.

The function of a protein is closely correlated with its subcellular location. With the rapid increase in new protein sequences entering into data banks, we are confronted with a challenge: is it possible to utilize a bioinformatic approach to help expedite the determination of protein subcellular locations? To explore this problem, proteins were classified, according to their subcellular locations, into the following 12 groups: (1) chloroplast, (2) cytoplasm, (3) cytoskeleton, (4) endoplasmic reticulum, (5) extracell, (6) Golgi apparatus, (7) lysosome, (8) mitochondria, (9) nucleus, (10) peroxisome, (11) plasma membrane and (12) vacuole. Based on the classification scheme that has covered almost all the organelles and subcellular compartments in an animal or plant cell, a covariant discriminant algorithm was proposed to predict the subcellular location of a query protein according to its amino acid composition. Results obtained through self-consistency, jackknife and independent dataset tests indicated that the rates of correct prediction by the current algorithm are significantly higher than those by the existing methods. It is anticipated that the classification scheme and concept and also the prediction algorithm can expedite the functionality determination of new proteins, which can also be of use in the prioritization of genes and proteins identified by genomic efforts as potential molecular targets for drug design.

[1]  P. Aloy,et al.  Relation between amino acid composition and cellular location of proteins. , 1997, Journal of molecular biology.

[2]  H. Blanch,et al.  Economics of sugar production with Trichoderma reesei Rutgers C-30. [Paper] presented at the Second Chemical Congress of the North American Continent, Las Vegas, NV, August 25-27, 1980. , 1980 .

[3]  K Nishikawa,et al.  The folding type of a protein is relevant to the amino acid composition. , 1986, Journal of biochemistry.

[4]  Patrick Argos,et al.  [10] Prediction of protein structure , 1986 .

[5]  M. Kanehisa,et al.  A knowledge base for predicting protein localization sites in eukaryotic cells , 1992, Genomics.

[6]  R. Jernigan,et al.  Understanding the recognition of protein structural classes by amino acid composition , 1997, Proteins.

[7]  K Nishikawa,et al.  Discrimination of intracellular and extracellular proteins using amino acid composition and residue-pair frequencies. , 1994, Journal of molecular biology.

[8]  Rolf Apweiler,et al.  The SWISS-PROT protein sequence data bank and its supplement TrEMBL , 1997, Nucleic Acids Res..

[9]  G. Fasman.  Prediction of Protein Structure and the Principles of Protein Conformation , 2012, Springer US.

[10]  K. Chou,et al.  Using discriminant function for prediction of subcellular location of prokaryotic proteins. , 1998, Biochemical and biophysical research communications.

[11]  G M Maggiora,et al.  Domain structural class prediction. , 1998, Protein engineering.

[12]  B. Rost,et al.  Adaptation of protein surfaces to subcellular location. , 1998, Journal of molecular biology.

[13]  A. V. Grimstone.  Molecular biology of the cell (3rd edn) , 1995 .

[14]  H. Lodish.  Molecular Cell Biology , 1986 .

[15]  K. Chou,et al.  Prediction of protein structural classes. , 1995, Critical reviews in biochemistry and molecular biology.

[16]  K. Chou,et al.  Prediction and classification of domain structural classes , 1998, Proteins.

[17]  P. Y. Chou,et al.  Prediction of Protein Structural Classes from Amino Acid Compositions , 1989 .

[18]  C. DeLisi,et al.  Prediction of protein structural class from the amino acid sequence , 1986, Biopolymers.

[19]  T. Hubbard,et al.  Using neural networks for prediction of the subcellular location of proteins. , 1998, Nucleic acids research.

[20]  K. Chou.  A novel approach to predicting protein structural classes in a (20–1)‐D amino acid composition space , 1995, Proteins.

[21]  K. Chou,et al.  Prediction of Protein Structural Classes by Modified Mahalanobis Discriminant Algorithm , 1998, Journal of protein chemistry.

[22]  M. Kanehisa,et al.  Expert system for predicting protein localization sites in gram‐negative bacteria , 1991, Proteins.

[23]  S. Brunak,et al.  Prediction of N-terminal protein sorting signals. , 1997, Current opinion in structural biology.

[24]  R. Quatrano.  Genomics , 1998, Plant Cell.