In Silico Methods for Identifying Organellar and Suborganellar Targeting Peptides in Arabidopsis Chloroplast Proteins and for Predicting the Topology of Membrane Proteins

  • Sandra K. Tanz
  • Ian SmallEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 774)


Numerous experimental and in silico approaches have been developed for attempting to identify the ­subcellular localisation of proteins. Approximately 2,000–4,000 proteins are thought to be targeted to plastids in plants, but a complete and unambiguous catalogue has yet to be drawn up. This article reviews the various prediction methods that identify plastid targeting sequences, and those that can help estimate location and topology within the plastid or plastid membranes. The most successful approaches are described in detail, with detailed notes to help avoid common pitfalls and advice on interpreting conflicting or ambiguous results. In most cases, it is best to try multiple approaches, and we also cover the powerful new integrated databases that provide a selected blend of experimental data and predictions.

Key words

Chloroplast proteins Transit peptide Protein import Targeting predictions Protein topology Transmembrane helices 


  1. 1.
    Heazlewood, J. L., Tonti-Filippini, J., Verboom, R. E., and Millar, A. H. (2005) Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis. Plant Physiol. 139, 598–609.PubMedGoogle Scholar
  2. 2.
    Soll, J., and Schleiff, E. (2004) Protein import into chloroplasts. Nat. Rev. Mol. Cell Biol. 5, 198–208.PubMedGoogle Scholar
  3. 3.
    Hörmann, F., Soll, J., and Bölter, B. (2007) The chloroplast protein import machinery: a review. Methods Mol. Biol. 390, 179–193.PubMedGoogle Scholar
  4. 4.
    Inaba, T., and Schnell, D. J. (2008) Protein trafficking to plastids: one theme, many variations. Biochem. J. 413, 15–28.PubMedGoogle Scholar
  5. 5.
    Jarvis, P. (2008) Targeting of nucleus-encoded proteins to chloroplasts in plants. New Phytol. 179, 257–285.PubMedGoogle Scholar
  6. 6.
    Li, H. M., and Chiu, C. C. (2010) Protein transport into chloroplasts. Annu. Rev. Plant Biol. 61, 157–180.PubMedGoogle Scholar
  7. 7.
    Gould, S. B., Waller, R. F., and McFadden, G. I. (2008) Plastid evolution. Annu. Rev. Plant Biol. 59, 491–517.Google Scholar
  8. 8.
    Martin, W., Rujan, T., Richly, E., Hansen, A., Cornelsen, S., Lins, T., Leister, D., Stoebe, B., Hasegawa, M., and Penny, D. (2002) Evolutionary analysis of Arabidopsis, cyanobacterial, and chloroplast genomes reveals plastid phylogeny and thousands of cyanobacterial genes in the nucleus. Proc. Natl. Acad. Sci. USA 99, 12246–12251.PubMedGoogle Scholar
  9. 9.
    Cavalier-Smith, T. (2000) Membrane heredity and early chloroplast evolution. Trends Plant Sci. 5, 174–182.PubMedGoogle Scholar
  10. 10.
    von Heijne, G., Steppuhn, J., and Herrmann, R. G. (1989) Domain structure of mitochondrial and chloroplast targeting peptides. Eur. J. Biochem. 180, 535–545.Google Scholar
  11. 11.
    Bruce, B. D. (2000) Chloroplast transit peptides: structure, function and evolution. Trends Cell. Biol. 10, 440–447.PubMedGoogle Scholar
  12. 12.
    Schnell, D. J., Blobel, G., Keegstra, K., Kessler, F., Ko, K., and Soll, J. (1997) A consensus nomenclature for the protein-import components of the chloroplast envelope. Trends Cell. Biol. 7, 303–304.PubMedGoogle Scholar
  13. 13.
    Sommer, M. S., and Schleiff, E. (2009) Molecular interactions within the plant TOC complex. Biol. Chem. 390, 739–744.PubMedGoogle Scholar
  14. 14.
    Benz, J. P., Soll, J., and Bolter, B. (2009) Protein transport in organelles: the composition, function and regulation of the Tic complex in chloroplast protein import. FEBS J.   276, 1166–1176.PubMedGoogle Scholar
  15. 15.
    Richter, S., Zhong, R., and Lamppa, G. (2005) Function of the stromal processing peptidase in the chloroplast import pathway. Physiol. Plant. 123, 362–368.Google Scholar
  16. 16.
    Zhang, X. P., and Glaser, E. (2002) Interaction of plant mitochondrial and chloroplast signal peptides with the Hsp70 molecular chaperone. Trends Plant. Sci. 7, 14–21.PubMedGoogle Scholar
  17. 17.
    Zybailov, B., Rutschow, H., Friso, G., Rudella, A., Emanuelsson, O., Sun, Q., and van Wijk, K. J. (2008) Sorting signals, N-terminal modifications and abundance of the chloroplast proteome. PLoS One 3, e1994.PubMedGoogle Scholar
  18. 18.
    Carrie, C., Kuhn, K., Murcha, M. W., Duncan, O., Small, I. D., O’Toole, N., and Whelan, J. (2009) Approaches to defining dual-targeted proteins in Arabidopsis. Plant J. 57, 1128–1139.PubMedGoogle Scholar
  19. 19.
    Morgante, C. V., Rodrigues, R. A., Marbach, P. A., Borgonovi, C. M., Moura, D. S., and Silva-Filho, M. C. (2009) Conservation of dual-targeted proteins in Arabidopsis and rice points to a similar pattern of gene-family evolution. Mol. Genet. Genomics 281, 525–538.PubMedGoogle Scholar
  20. 20.
    Carrie, C., Giraud, E., and Whelan, J. (2009) Protein transport in organelles: Dual targeting of proteins to mitochondria and chloroplasts. FEBS J. 276, 1187–1195.PubMedGoogle Scholar
  21. 21.
    Duchene, A. M., Giritch, A., Hoffmann, B., Cognat, V., Lancelin, D., Peeters, N. M., Zaepfel, M., Marechal-Drouard, L., and Small, I. D. (2005) Dual targeting is the rule for organellar aminoacyl-tRNA synthetases in Arabidopsis thaliana. Proc. Natl. Acad. Sci. USA 102, 16484–16489.PubMedGoogle Scholar
  22. 22.
    Berglund, A. K., Spanning, E., Biverstahl, H., Maddalo, G., Tellgren-Roth, C., Maler, L., and Glaser, E. (2009) Dual targeting to mitochondria and chloroplasts: characterization of Thr-tRNA synthetase targeting peptide. Mol. Plant 2, 1298–1309.PubMedGoogle Scholar
  23. 23.
    Silva-Filho, M. C. (2003) One ticket for multiple destinations: dual targeting of proteins to distinct subcellular locations. Curr. Opin. Plant Biol. 6, 589–595.PubMedGoogle Scholar
  24. 24.
    Peeters, N., and Small, I. (2001) Dual targeting to mitochondria and chloroplasts. Biochim. Biophys. Acta 1541, 54–63.PubMedGoogle Scholar
  25. 25.
    Mackenzie, S. A. (2005) Plant organellar protein targeting: a traffic plan still under construction. Trends Cell. Biol. 15, 548–554.PubMedGoogle Scholar
  26. 26.
    Pujol, C., Marechal-Drouard, L., and Duchene, A. M. (2007) How can organellar protein N-terminal sequences be dual targeting signals? In silico analysis and mutagenesis approach. J. Mol. Biol. 369, 356–367.PubMedGoogle Scholar
  27. 27.
    Chen, M. H., Huang, L. F., Li, H. M., Chen, Y. R., and Yu, S. M. (2004) Signal peptide-dependent targeting of a rice alpha-amylase and cargo proteins to plastids and extracellular compartments of plant cells. Plant Physiol. 135, 1367–1377.PubMedGoogle Scholar
  28. 28.
    Nanjo, Y., Oka, H., Ikarashi, N., Kaneko, K., Kitajima, A., Mitsui, T., Munoz, F. J., Rodriguez-Lopez, M., Baroja-Fernandez, E., and Pozueta-Romero, J. (2006) Rice plastidial N-glycosylated nucleotide pyrophosphatase/phosphodiesterase is transported from the ER-golgi to the chloroplast through the secretory pathway. Plant Cell 18, 2582–2592.PubMedGoogle Scholar
  29. 29.
    Villarejo, A., Buren, S., Larsson, S., Dejardin, A., Monne, M., Rudhe, C., Karlsson, J., Jansson, S., Lerouge, P., Rolland, N., von Heijne, G., Grebe, M., Bako, L., and Samuelsson, G. (2005) Evidence for a protein transported through the secretory pathway en route to the higher plant chloroplast. Nat. Cell Biol. 7, 1224–1231.PubMedGoogle Scholar
  30. 30.
    Lee, Y. J., Kim, D. H., Kim, Y. W., and Hwang, I. (2001) Identification of a signal that distinguishes between the chloroplast outer envelope membrane and the endomembrane system in vivo. Plant Cell 13, 2175–2190.PubMedGoogle Scholar
  31. 31.
    Hofmann, N. R., and Theg, S. M. (2005) Chloroplast outer membrane protein targeting and insertion. Trends Plant Sci. 10, 450–457.PubMedGoogle Scholar
  32. 32.
    Tu, S. L., Chen, L. J., Smith, M. D., Su, Y. S., Schnell, D. J., and Li, H. M. (2004) Import pathways of chloroplast interior proteins and the outer-membrane protein OEP14 converge at Toc75. Plant Cell 16, 2078–2088.PubMedGoogle Scholar
  33. 33.
    Kouranov, A., Wang, H., and Schnell, D. J. (1999) Tic22 is targeted to the intermembrane space of chloroplasts by a novel pathway. J. Biol. Chem. 274, 25181–25186.PubMedGoogle Scholar
  34. 34.
    Vojta, L., Soll, J., and Bolter, B. (2007) Protein transport in chloroplasts – targeting to the intermembrane space. FEBS J. 274, 5043–5054.PubMedGoogle Scholar
  35. 35.
    Knight, J. S., and Gray, J. C. (1995) The N-terminal hydrophobic region of the mature phosphate translocator is sufficient for targeting to the chloroplast inner envelope membrane. Plant Cell 7, 1421–1432.PubMedGoogle Scholar
  36. 36.
    Lubeck, J., Heins, L., and Soll, J. (1997) A nuclear-coded chloroplastic inner envelope membrane protein uses a soluble sorting intermediate upon import into the organelle. J. Cell Biol. 137, 1279–1286.PubMedGoogle Scholar
  37. 37.
    Li, M., and Schnell, D. J. (2006) Reconstitution of protein targeting to the inner envelope membrane of chloroplasts. J. Cell Biol. 175, 249–259.PubMedGoogle Scholar
  38. 38.
    Tripp, J., Inoue, K., Keegstra, K., and Froehlich, J. E. (2007) A novel serine/proline-rich domain in combination with a transmembrane domain is required for the insertion of AtTic40 into the inner envelope membrane of chloroplasts. Plant J. 52, 824–838.PubMedGoogle Scholar
  39. 39.
    Bonen, L., and Doolittle, W. F. (1975) On the prokaryotic nature of red algal chloroplasts. Proc. Natl. Acad. Sci. USA 72, 2310–2314.PubMedGoogle Scholar
  40. 40.
    Moreira, D., Le Guyader, H., and Philippe, H. (2000) The origin of red algae and the evolution of chloroplasts. Nature 405, 69–72.PubMedGoogle Scholar
  41. 41.
    Aldridge, C., Cain, P., and Robinson, C. (2009) Protein transport in organelles: Protein transport into and across the thylakoid membrane. FEBS J. 276, 1177–1186.PubMedGoogle Scholar
  42. 42.
    Robinson, C., Thompson, S. J., and Woolhead, C. (2001) Multiple pathways used for the targeting of thylakoid proteins in chloroplasts. Traffic 2, 245–251.PubMedGoogle Scholar
  43. 43.
    Shackleton, J. B., and Robinson, C. (1991) Transport of proteins into chloroplasts. The thylakoidal processing peptidase is a signal-type peptidase with stringent substrate requirements at the −3 and −1 positions. J. Biol. Chem. 266, 12152–12156.PubMedGoogle Scholar
  44. 44.
    von Heijne, G. (1990) The signal peptide. J. Membr. Biol. 115, 195–201.Google Scholar
  45. 45.
    Yuan, J., Henry, R., McCaffery, M., and Cline, K. (1994) SecA homolog in protein transport within chloroplasts: evidence for endosymbiont-derived sorting. Science 266, 796–798.PubMedGoogle Scholar
  46. 46.
    Schuenemann, D., Amin, P., Hartmann, E., and Hoffman, N. E. (1999) Chloroplast SecY is complexed to SecE and involved in the translocation of the 33-kDa but not the 23-kDa subunit of the oxygen-evolving complex. J. Biol. Chem. 274, 12177–12182.PubMedGoogle Scholar
  47. 47.
    Dalbey, R. E., and Chen, M. (2004) Sec-translocase mediated membrane protein biogenesis. Biochim. Biophys. Acta 1694, 37–53.PubMedGoogle Scholar
  48. 48.
    Mould, R. M., and Robinson, C. (1991) A proton gradient is required for the transport of two lumenal oxygen-evolving proteins across the thylakoid membrane. J. Biol. Chem. 266, 12189–12193.PubMedGoogle Scholar
  49. 49.
    Cline, K., Ettinger, W. F., and Theg, S. M. (1992) Protein-specific energy requirements for protein transport across or into thylakoid membranes. Two lumenal proteins are transported in the absence of ATP. J. Biol. Chem. 267, 2688–2696.Google Scholar
  50. 50.
    Chaddock, A. M., Mant, A., Karnauchov, I., Brink, S., Herrmann, R. G., Klosgen, R. B., and Robinson, C. (1995) A new type of signal peptide: central role of a twin-arginine motif in transfer signals for the delta pH-dependent thylakoidal protein translocase. EMBO J. 14, 2715–2722.PubMedGoogle Scholar
  51. 51.
    Creighton, A. M., Hulford, A., Mant, A., Robinson, D., and Robinson, C. (1995) A monomeric, tightly folded stromal intermediate on the delta pH-dependent thylakoidal protein transport pathway. J. Biol. Chem. 270, 1663–1669.PubMedGoogle Scholar
  52. 52.
    Hynds, P. J., Robinson, D., and Robinson, C. (1998) The sec-independent twin-arginine translocation system can transport both tightly folded and malfolded proteins across the thylakoid membrane. J. Biol. Chem. 273, 34868–34874.PubMedGoogle Scholar
  53. 53.
    Sargent, F. (2007) The twin-arginine transport system: moving folded proteins across membranes. Biochem. Soc. Trans. 35, 835–847.PubMedGoogle Scholar
  54. 54.
    Robinson, C., and Bolhuis, A. (2001) Protein targeting by the twin-arginine translocation pathway. Nat. Rev. Mol. Cell Biol. 2, 350–356.PubMedGoogle Scholar
  55. 55.
    Marques, J. P., Schattat, M. H., Hause, G., Dudeck, I., and Klosgen, R. B. (2004) In vivo transport of folded EGFP by the DeltapH/TAT-dependent pathway in chloroplasts of Arabidopsis thaliana. J. Exp. Bot. 55, 1697–1706.PubMedGoogle Scholar
  56. 56.
    Halpin, C., Elderfield, P. D., James, H. E., Zimmermann, R., Dunbar, B., and Robinson, C. (1989) The reaction specificities of the thylakoidal processing peptidase and Escherichia coli leader peptidase are identical. EMBO J. 8, 3917–3921.PubMedGoogle Scholar
  57. 57.
    Schuenemann, D., Gupta, S., Persello-Cartieaux, F., Klimyuk, V. I., Jones, J. D., Nussaume, L., and Hoffman, N. E. (1998) A novel signal recognition particle targets light-harvesting proteins to the thylakoid membranes. Proc. Natl. Acad. Sci. USA 95, 10312–10316.PubMedGoogle Scholar
  58. 58.
    Tu, C. J., Schuenemann, D., and Hoffman, N. E. (1999) Chloroplast FtsY, chloroplast signal recognition particle, and GTP are required to reconstitute the soluble phase of light-harvesting chlorophyll protein transport into thylakoid membranes. J. Biol. Chem. 274, 27219–27224.PubMedGoogle Scholar
  59. 59.
    Grudnik, P., Bange, G., and Sinning, I. (2009) Protein targeting by the signal recognition particle. Biol. Chem. 390, 775–782.PubMedGoogle Scholar
  60. 60.
    Moore, M., Harrison, M. S., Peterson, E. C., and Henry, R. (2000) Chloroplast Oxa1p homolog albino3 is required for post-translational integration of the light harvesting chlorophyll-binding protein into thylakoid membranes. J. Biol. Chem. 275, 1529–1532.PubMedGoogle Scholar
  61. 61.
    Lorkovic, Z. J., Schroder, W. P., Pakrasi, H. B., Irrgang, K. D., Herrmann, R. G., and Oelmuller, R. (1995) Molecular characterization of PsbW, a nuclear-encoded component of the photosystem II reaction center complex in spinach. Proc. Natl. Acad. Sci. USA 92, 8930–8934.PubMedGoogle Scholar
  62. 62.
    Kim, S. J., Robinson, C., and Mant, A. (1998) Sec/SRP-independent insertion of two thylakoid membrane proteins bearing cleavable signal peptides. FEBS Lett. 424, 105–108.PubMedGoogle Scholar
  63. 63.
    Tissier, C., Woolhead, C. A., and Robinson, C. (2002) Unique structural determinants in the signal peptides of “spontaneously” inserting thylakoid membrane proteins. Eur. J. Biochem. 269, 3131–3141.PubMedGoogle Scholar
  64. 64.
    Mant, A., Woolhead, C. A., Moore, M., Henry, R., and Robinson, C. (2001) Insertion of PsaK into the thylakoid membrane in a “Horseshoe” conformation occurs in the absence of signal recognition particle, nucleoside triphosphates, or functional albino3. J. Biol. Chem. 276, 36200–36206.PubMedGoogle Scholar
  65. 65.
    Zygadlo, A., Robinson, C., Scheller, H. V., Mant, A., and Jensen, P. E. (2006) The properties of the positively charged loop region in PSI-G are essential for its “spontaneous” insertion into thylakoids and rapid assembly into the photosystem I complex. J. Biol. Chem. 281, 10548–10554.PubMedGoogle Scholar
  66. 66.
    Woolhead, C. A., Thompson, S. J., Moore, M., Tissier, C., Mant, A., Rodger, A., Henry, R., and Robinson, C. (2001) Distinct Albino3-dependent and -independent pathways for thylakoid membrane protein insertion. J. Biol. Chem. 276, 40841–40846.PubMedGoogle Scholar
  67. 67.
    Jarvis, P., and Robinson, C. (2004) Mechanisms of protein import and routing in chloroplasts. Curr. Biol. 14, R1064-1077.PubMedGoogle Scholar
  68. 68.
    Emanuelsson, O., Nielsen, H., and von Heijne, G. (1999) ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci. 8, 978–984.PubMedGoogle Scholar
  69. 69.
    Emanuelsson, O., Nielsen, H., Brunak, S., and von Heijne, G. (2000) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 300, 1005–1016.PubMedGoogle Scholar
  70. 70.
    Emanuelsson, O., Brunak, S., von Heijne, G., and Nielsen, H. (2007) Locating proteins in the cell using TargetP, SignalP and related tools. Nat. Protoc. 2, 953–971.PubMedGoogle Scholar
  71. 71.
    Small, I., Peeters, N., Legeai, F., and Lurin, C. (2004) Predotar: a tool for rapidly screening proteomes for N-terminal targeting sequences. Proteomics 4, 1581–1590.PubMedGoogle Scholar
  72. 72.
    Millar, A. H., Whelan, J., and Small, I. (2006) Recent surprises in protein targeting to mitochondria and plastids. Curr. Opin. Plant Biol. 9, 610–615.PubMedGoogle Scholar
  73. 73.
    Petsalaki, E. I., Bagos, P. G., Litou, Z. I., and Hamodrakas, S. J. (2006) PredSL: a tool for the N-terminal sequence-based prediction of protein subcellular localization. Genomics Proteomics Bioinformatics 4, 48–55.PubMedGoogle Scholar
  74. 74.
    Rastogi, S., and Rost, B. (2010) Bioinformatics predictions of localization and targeting. Methods Mol. Biol. 619, 285–305.PubMedGoogle Scholar
  75. 75.
    Emanuelsson, O., and von Heijne, G. (2001) Prediction of organellar targeting signals. Biochim. Biophys. Acta 1541, 114–119.PubMedGoogle Scholar
  76. 76.
    Gomez, S. M., Bil, K. Y., Aguilera, R., Nishio, J. N., Faull, K. F., and Whitelegge, J. P. (2003) Transit peptide cleavage sites of integral thylakoid membrane proteins. Mol. Cell. Proteomics 2, 1068–1085.PubMedGoogle Scholar
  77. 77.
    Bendtsen, J. D., Nielsen, H., von Heijne, G., and Brunak, S. (2004) Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 340, 783–795.PubMedGoogle Scholar
  78. 78.
    Jarvis, P. (2004) Organellar proteomics: chloroplasts in the spotlight. Curr. Biol. 14, R317-319.PubMedGoogle Scholar
  79. 79.
    Westerlund, I., Von Heijne, G., and Emanuelsson, O. (2003) LumenP – a neural network predictor for protein localization in the thylakoid lumen. Protein Sci. 12, 2360–2366.PubMedGoogle Scholar
  80. 80.
    Bannai, H., Tamada, Y., Maruyama, O., Nakai, K., and Miyano, S. (2002) Extensive feature detection of N-terminal protein sorting signals. Bioinformatics 18, 298–305.PubMedGoogle Scholar
  81. 81.
    Bendtsen, J. D., Nielsen, H., Widdick, D., Palmer, T., and Brunak, S. (2005) Prediction of twin-arginine signal peptides. BMC Bioinformatics 6, 167.PubMedGoogle Scholar
  82. 82.
    Heazlewood, J. L., Verboom, R. E., Tonti-Filippini, J., Small, I., and Millar, A. H. (2007) SUBA: the Arabidopsis Subcellular Database. Nucleic Acids Res. 35, D213–218.PubMedGoogle Scholar
  83. 83.
    Consortium, T. U. (2010) The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res. 38, D142-148.Google Scholar
  84. 84.
    Jain, E., Bairoch, A., Duvaud, S., Phan, I., Redaschi, N., Suzek, B. E., Martin, M. J., McGarvey, P., and Gasteiger, E. (2009) Infrastructure for the life sciences: design and implementation of the UniProt website. BMC Bioinformatics 10, 136.PubMedGoogle Scholar
  85. 85.
    Carbon, S., Ireland, A., Mungall, C. J., Shu, S., Marshall, B., and Lewis, S. (2009) AmiGO: online access to ontology and annotation data. Bioinformatics 25, 288–289.PubMedGoogle Scholar
  86. 86.
    Swarbreck, D., Wilks, C., Lamesch, P., Berardini, T. Z., Garcia-Hernandez, M., Foerster, H., Li, D., Meyer, T., Muller, R., Ploetz, L., Radenbaugh, A., Singh, S., Swing, V., Tissier, C., Zhang, P., and Huala, E. (2008) The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res. 36, D1009–1014.PubMedGoogle Scholar
  87. 87.
    von Heijne, G. (1988) Transcending the impenetrable: how proteins come to terms with membranes. Biochim. Biophys. Acta 947, 307–333.Google Scholar
  88. 88.
    Krogh, A., Larsson, B., von Heijne, G., and Sonnhammer, E. L. (2001) Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567–580.PubMedGoogle Scholar
  89. 89.
    Moller, S., Croning, M. D., and Apweiler, R. (2001) Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics 17, 646–653.PubMedGoogle Scholar
  90. 90.
    Cuthbertson, J. M., Doyle, D. A., and Sansom, M. S. (2005) Transmembrane helix prediction: a comparative evaluation and analysis. Protein Eng. Des. Sel. 18, 295–308.PubMedGoogle Scholar
  91. 91.
    Schulz, G. E. (2000) beta-Barrel membrane proteins. Curr. Opin. Struct. Biol. 10, 443–447.PubMedGoogle Scholar
  92. 92.
    Sun, Q., Zybailov, B., Majeran, W., Friso, G., Olinares, P. D., and van Wijk, K. J. (2009) PPDB, the Plant Proteomics Database at Cornell. Nucleic Acids Res. 37, D969–974.PubMedGoogle Scholar
  93. 93.
    Schwacke, R., Schneider, A., van der Graaff, E., Fischer, K., Catoni, E., Desimone, M., Frommer, W. B., Flugge, U. I., and Kunze, R. (2003) ARAMEMNON, a novel database for Arabidopsis integral membrane proteins. Plant Physiol. 131, 16–26.PubMedGoogle Scholar
  94. 94.
    Nair, R., and Rost, B. (2008) Protein subcellular localization prediction using artificial intelligence technology. Methods Mol. Biol. 484, 435–463.PubMedGoogle Scholar
  95. 95.
    Ferro, M., Brugiere, S., Salvi, D., Seigneurin-Berny, D., Court, M., Moyet, L., Ramus, C., Miras, S., Mellal, M., Le Gall, S., Kieffer-Jaquinod, S., Bruley, C., Garin, J., Joyard, J., Masselon, C., and Rolland, N. (2010) AT_CHLORO, a comprehensive chloroplast proteome database with subplastidial localization and curated information on envelope proteins. Mol. Cell. Proteomics 9, 1063–1084.PubMedGoogle Scholar
  96. 96.
    Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., and Madden, T. L. (2009) BLAST+: architecture and applications. BMC Bioinformatics 10, 421.PubMedGoogle Scholar
  97. 97.
    Schwacke, R., Fischer, K., Ketelsen, B., Krupinska, K., and Krause, K. (2007) Comparative survey of plastid and mitochondrial targeting properties of transcription factors in Arabidopsis and rice. Mol. Genet. Genomics 277, 631–646.PubMedGoogle Scholar
  98. 98.
    Tantoso, E., and Li, K. B. (2008) AAIndexLoc: predicting subcellular localization of proteins based on a new representation of sequences using amino acid indices. Amino Acids 35, 345–353.PubMedGoogle Scholar
  99. 99.
    Jin, Y. H., Niu, B., Feng, K. Y., Lu, W. C., Cai, Y. D., and Li, G. Z. (2008) Predicting subcellular localization with AdaBoost Learner. Protein Pept. Lett. 15, 286–289.PubMedGoogle Scholar
  100. 100.
    Mitschke, J., Fuss, J., Blum, T., Hoglund, A., Reski, R., Kohlbacher, O., and Rensing, S. A. (2009) Prediction of dual protein targeting to plant organelles. New Phytol. 183, 224–235.PubMedGoogle Scholar
  101. 101.
    Pierleoni, A., Martelli, P. L., Fariselli, P., and Casadio, R. (2006) BaCelLo: a balanced subcellular localization predictor. Bioinformatics 22, e408-416.PubMedGoogle Scholar
  102. 102.
    Brady, S., and Shatkay, H. (2008) EpiLoc: a (working) text-based system for predicting protein subcellular location. Pac. Symp. Biocomput. 13, 604–615.Google Scholar
  103. 103.
    Nair, R., and Rost, B. (2005) Mimicking cellular sorting improves prediction of subcellular localization. J. Mol. Biol. 348, 85–100.PubMedGoogle Scholar
  104. 104.
    Blum, T., Briesemeister, S., and Kohlbacher, O. (2009) MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction. BMC Bioinformatics 10, 274.PubMedGoogle Scholar
  105. 105.
    Schein, A. I., Kissinger, J. C., and Ungar, L. H. (2001) Chloroplast transit peptide prediction: a peek inside the black box. Nucleic Acids Res. 29, E82.PubMedGoogle Scholar
  106. 106.
    Chou, K. C., and Shen, H. B. (2007) Large-scale plant protein subcellular location prediction. J. Cell. Biochem. 100, 665–678.PubMedGoogle Scholar
  107. 107.
    Chou, K. C., and Shen, H. B. (2008) Cell-PLoc: a package of web servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 3, 153–162.PubMedGoogle Scholar
  108. 108.
    Chou, K. C., and Shen, H. B. (2010) Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization. PLoS One 5, e11335.PubMedGoogle Scholar
  109. 109.
    Huang, W. L., Tung, C. W., Ho, S. W., Hwang, S. F., and Ho, S. Y. (2008) ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. BMC Bioinformatics 9, 80.PubMedGoogle Scholar
  110. 110.
    Boden, M., and Hawkins, J. (2005) Prediction of subcellular localization using sequence-biased recurrent networks. Bioinformatics 21, 2279–2286.PubMedGoogle Scholar
  111. 111.
    Hawkins, J., and Boden, M. (2006) Detecting and sorting targeting peptides with neural networks and support vector machines. J. Bioinform. Comput. Biol. 4, 1–18.PubMedGoogle Scholar
  112. 112.
    Nakai, K., and Horton, P. (1999) PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization. Trends Biochem. Sci. 24, 34–36.PubMedGoogle Scholar
  113. 113.
    Nakai, K., and Kanehisa, M. (1991) Expert system for predicting protein localization sites in gram-negative bacteria. Proteins 11, 95–110.PubMedGoogle Scholar
  114. 114.
    Briesemeister, S., Blum, T., Brady, S., Lam, Y., Kohlbacher, O., and Shatkay, H. (2009) SherLoc2: a high-accuracy hybrid method for predicting subcellular localization of proteins. J. Proteome Res. 8, 5363–5366.PubMedGoogle Scholar
  115. 115.
    Matsuda, S., Vert, J. P., Saigo, H., Ueda, N., Toh, H., and Akutsu, T. (2005) A novel ­representation of protein sequences for prediction of subcellular location using sup­port vector machines. Protein Sci. 14, 2804–2813.PubMedGoogle Scholar
  116. 116.
    Tamura, T., and Akutsu, T. (2007) Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition. BMC Bioinformatics 8, 466.PubMedGoogle Scholar
  117. 117.
    Jia, P., Qian, Z., Zeng, Z., Cai, Y., and Li, Y. (2007) Prediction of subcellular protein localization based on functional domain composition. Biochem. Biophys. Res. Commun. 357, 366–370.PubMedGoogle Scholar
  118. 118.
    Garg, P., Sharma, V., Chaudhari, P., and Roy, N. (2009) SubCellProt: predicting protein subcellular localization using machine learning approaches. In Silico Biol. 9, 35–44.PubMedGoogle Scholar
  119. 119.
    Horton, P., Park, K. J., Obayashi, T., Fujita, N., Harada, H., Adams-Collier, C. J., and Nakai, K. (2007) WoLF PSORT: protein localization predictor. Nucleic Acids Res. 35, W585–587.PubMedGoogle Scholar
  120. 120.
    Briesemeister, S., Rahnenfuhrer, J., and Kohlbacher, O. (2010) Going from where to why – interpretable prediction of protein subcellular localization. Bioinformatics 26, 1232–1238.PubMedGoogle Scholar
  121. 121.
    Nakai, K., and Kanehisa, M. (1992) A knowledge base for predicting protein localization sites in eukaryotic cells. Genomics 14, 897–911.PubMedGoogle Scholar
  122. 122.
    Cserzo, M., Eisenhaber, F., Eisenhaber, B., and Simon, I. (2002) On filtering false positive transmembrane protein predictions. Protein Eng. 15, 745–752.PubMedGoogle Scholar
  123. 123.
    Bagos, P. G., Liakopoulos, T. D., and Hamodrakas, S. J. (2006) Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins. BMC Bioinformatics 7, 189.PubMedGoogle Scholar
  124. 124.
    Tusnady, G. E., and Simon, I. (1998) Principles governing amino acid composition of integral membrane proteins: application to topology prediction. J. Mol. Biol. 283, 489–506.PubMedGoogle Scholar
  125. 125.
    Tusnady, G. E., and Simon, I. (2001) The HMMTOP transmembrane topology prediction server. Bioinformatics 17, 849–850.PubMedGoogle Scholar
  126. 126.
    Adamian, L., and Liang, J. (2006) Prediction of transmembrane helix orientation in polytopic membrane proteins. BMC Struct. Biol. 6, 13.PubMedGoogle Scholar
  127. 127.
    Jones, D. T. (2007) Improving the accuracy of transmembrane protein topology prediction using evolutionary information. Bioinformatics 23, 538–544.PubMedGoogle Scholar
  128. 128.
    Jones, D. T., Taylor, W. R., and Thornton, J. M. (1994) A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry 33, 3038–3049.PubMedGoogle Scholar
  129. 129.
    Cao, B., Porollo, A., Adamczak, R., Jarrell, M., and Meller, J. (2006) Enhanced recognition of protein transmembrane domains with prediction-based structural profiles. Bioinformatics 22, 303–309.PubMedGoogle Scholar
  130. 130.
    Reynolds, S. M., Kall, L., Riffle, M. E., Bilmes, J. A., and Noble, W. S. (2008) Transmembrane topology and signal peptide prediction using dynamic bayesian networks. PLoS Comput. Biol. 4, e1000213.PubMedGoogle Scholar
  131. 131.
    Kall, L., Krogh, A., and Sonnhammer, E. L. (2004) A combined transmembrane topology and signal peptide prediction method. J. Mol. Biol. 338, 1027–1036.PubMedGoogle Scholar
  132. 132.
    Kall, L., Krogh, A., and Sonnhammer, E. L. (2007) Advantages of combined transmembrane topology and signal peptide prediction – the Phobius web server. Nucleic Acids Res. 35, W429-432.PubMedGoogle Scholar
  133. 133.
    Bernsel, A., Viklund, H., Falk, J., Lindahl, E., von Heijne, G., and Elofsson, A. (2008) Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA 105, 7177–7181.PubMedGoogle Scholar
  134. 134.
    Hirokawa, T., Boon-Chieng, S., and Mitaku, S. (1998) SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics 14, 378–379.PubMedGoogle Scholar
  135. 135.
    Mitaku, S., Hirokawa, T., and Tsuji, T. (2002) Amphiphilicity index of polar amino acids as an aid in the characterization of amino acid preference at membrane-water interfaces. Bioinformatics 18, 608–616.PubMedGoogle Scholar
  136. 136.
    Tsuji, T., and Mitaku, S. (2004) Features of transmembrane helices useful for membrane protein prediction. Chem-Bio Informatics Journal 4, 110–120.Google Scholar
  137. 137.
    Viklund, H., Bernsel, A., Skwark, M., and Elofsson, A. (2008) SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology. Bioinformatics 24, 2928–2929.PubMedGoogle Scholar
  138. 138.
    Hofmann, K. P., and Stoffel, W. (1993) TMbase – a database of membrane spanning proteins segments. Biol. Chem. Hoppe-Seyler 374, 166.Google Scholar
  139. 139.
    Jacoboni, I., Martelli, P. L., Fariselli, P., De Pinto, V., and Casadio, R. (2001) Prediction of the transmembrane regions of beta-barrel membrane proteins with a neural network-based predictor. Protein Sci. 10, 779–787.PubMedGoogle Scholar
  140. 140.
    Martelli, P. L., Fariselli, P., Krogh, A., and Casadio, R. (2002) A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins. Bioinformatics 18 (Suppl 1), S46–53.PubMedGoogle Scholar
  141. 141.
    Berven, F. S., Flikka, K., Jensen, H. B., and Eidhammer, I. (2004) BOMP: a program to predict integral beta-barrel outer membrane proteins encoded within genomes of Gram-negative bacteria. Nucleic Acids Res. 32, W394–399.PubMedGoogle Scholar
  142. 142.
    Freeman, T. C., Jr., and Wimley, W. C. (2010) A highly accurate statistical approach for the prediction of transmembrane β-barrels. Bioinformatics 26, 1965–1974.PubMedGoogle Scholar
  143. 143.
    Garrow, A. G., Agnew, A., and Westhead, D. R. (2005) TMB-Hunt: an amino acid composition based method to screen proteomes for beta-barrel transmembrane proteins. BMC Bioinformatics 6, 56.PubMedGoogle Scholar
  144. 144.
    Gromiha, M. M., Yabuki, Y., Kundu, S., Suharnan, S., and Suwa, M. (2007) TMBETA-GENOME: database for annotated beta-barrel membrane proteins in genomic sequences. Nucleic Acids Res. 35, D314–316.PubMedGoogle Scholar
  145. 145.
    Waldispuhl, J., Berger, B., Clote, P., and Steyaert, J. M. (2006) transFold: a web server for predicting the structure and residue contacts of transmembrane beta-barrels. Nucleic Acids Res. 34, W189–193.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Australian Research Council Centre of Excellence in Plant Energy BiologyUniversity of Western AustraliaCrawleyAustralia

Personalised recommendations