Skip to main content
  • Mini Review
  • Published:

The interactome: Predicting the protein-protein interactions in cells

Abstract

The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy.

Abbreviations

3D:

three dimensional

BIND:

Biomolecular Interaction Network Database

BLAST:

Basic Local Alignment Search Tool

CAPRI:

Critical Assessment of PRediction of Interactions

DBID:

database of interacting domains

DIP:

Database of Interacting Proteins

DNA:

deoxyribonucleic acid

GO:

Gene Ontology

HPRD:

Human Protein Reference Database

KEGG:

Kyoto Encyclopedia of Genes and Genomes

KO:

KEGG Orthology

MetaBASIC:

Bilaterally Amplified Sequence Information Comparison

MINT:

Molecular Interaction Database

OPHID:

Online Predicted Human Interaction Database

PDB:

Protein Data Bank

RNA:

ribonucleic acid

References

  1. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N. and Bourne, P.E. The Protein Data Bank. Nucleic Acids Res. 28 (2000) 235–242.

    PubMed  CAS  Google Scholar 

  2. Ginalski, K., von Grotthuss, M., Grishin, N.V. and Rychlewski, L. Detecting distant homology with Meta-BASIC. Nucleic Acids Res. 32 (2004) W576–W581.

    PubMed  CAS  Google Scholar 

  3. Sprinzak, E., Sattath, S. and Margalit, H. How reliable are experimental protein-protein interaction data? J. Mol. Biol. 327 (2003) 919–923.

    PubMed  CAS  Google Scholar 

  4. von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S.G., Fields, S. and Bork, P. Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417 (2002) 399–403.

    Google Scholar 

  5. Carter, P., Lesk, V.I., Islam, S.A. and Sternberg, M.J. Protein-protein docking using 3D-Dock in rounds 3, 4, and 5 of CAPRI. Proteins 60 (2005) 281–288.

    PubMed  CAS  Google Scholar 

  6. Fariselli, P., Pazos, F., Valencia, A. and Casadio, R. Prediction of protein-protein interaction sites in heterocomplexes with neural networks. Eur. J. Biochem. 269 (2002) 1356–1361.

    PubMed  CAS  Google Scholar 

  7. Hoskins, J., Lovell, S. and Blundell, T.L. An algorithm for predicting protein-protein interaction sites: Abnormally exposed amino acid residues and secondary structure elements. Protein Sci. 15 (2006) 1017–1029.

    PubMed  CAS  Google Scholar 

  8. Jothi, R., Cherukuri, P.F., Tasneem, A. and Przytycka, T.M. Coevolutionary analysis of domains in interacting proteins reveals insights into domain-domain interactions mediating protein-protein interactions. J. Mol. Biol. 362 (2006) 861–875.

    PubMed  CAS  Google Scholar 

  9. Tan, K., Shlomi, T., Feizi, H., Ideker, T. and Sharan, R. Transcriptional regulation of protein complexes within and across species. Proc. Natl. Acad. Sci. USA 104 (2007) 1283–1288.

    PubMed  CAS  Google Scholar 

  10. Teichmann, S.A. Principles of protein-protein interactions. Bioinformatics 18 Suppl 2 (2002) S249.

    PubMed  Google Scholar 

  11. Cusick, M.E., Klitgord, N., Vidal, M. and Hill, D.E. Interactome: gateway into systems biology. Hum. Mol. Genet. 14 Spec No. 2 (2005) R171–R181.

    PubMed  CAS  Google Scholar 

  12. Goh, C.S. and Cohen, F.E. Co-evolutionary analysis reveals insights into protein-protein interactions. J. Mol. Biol. 324 (2002) 177–192.

    PubMed  CAS  Google Scholar 

  13. Sharan, R., Ideker, T., Kelley, B., Shamir, R. and Karp, R.M. Identification of protein complexes by comparative analysis of yeast and bacterial protein interaction data. J. Comput. Biol. 12 (2005) 835–846.

    PubMed  CAS  Google Scholar 

  14. Barash, Y., Elidan, G., Kaplan, T. and Friedman, N. CIS: compound importance sampling method for protein-DNA binding site p-value estimation. Bioinformatics 21 (2005) 596–600.

    PubMed  CAS  Google Scholar 

  15. Sharan, R., Suthram, S., Kelley, R.M., Kuhn, T., McCuine, S., Uetz, P., Sittler, T., Karp, R.M. and Ideker, T. Conserved patterns of protein interaction in multiple species. Proc. Natl. Acad. Sci. USA 102 (2005) 1974–1979.

    PubMed  CAS  Google Scholar 

  16. Kelley, B.P., Sharan, R., Karp, R.M., Sittler, T., Root, D.E., Stockwell, B.R. and Ideker, T. Conserved pathways within bacteria and yeast as revealed by global protein network alignment. Proc. Natl. Acad. Sci. USA 100 (2003) 11394–11399.

    PubMed  CAS  Google Scholar 

  17. Salwinski, L., Miller, C.S., Smith, A.J., Pettit, F.K., Bowie, J.U. and Eisenberg, D. The Database of Interacting Proteins: 2004 update. Nucleic Acids Res. 32 (2004) D449–D451.

    PubMed  CAS  Google Scholar 

  18. Alfarano, C., Andrade, C.E., Anthony, K., Bahroos, N., Bajec, M., Bantoft, K., Betel, D., Bobechko, B., Boutilier, K., Burgess, E., Buzadzija, K., Cavero, R., D’Abreo, C., Donaldson, I., Dorairajoo, D., Dumontier, M.J., Dumontier, M.R., Earles, V., Farrall, R., Feldman, H., Garderman, E., Gong, Y., Gonzaga, R., Grytsan, V., Gryz, E., Gu, V., Haldorsen, E., Halupa, A., Haw, R., Hrvojic, A., Hurrell, L., Isserlin, R., Jack, F., Juma, F., Khan, A., Kon, T., Konopinsky, S., Le, V., Lee, E., Ling, S., Magidin, M., Moniakis, J., Montojo, J., Moore, S., Muskat, B., Ng, I., Paraiso, J.P., Parker, B., Pintilie, G., Pirone, R., Salama, J.J., Sgro, S., Shan, T., Shu, Y., Siew, J., Skinner, D., Snyder, K., Stasiuk, R., Strumpf, D., Tuekam, B., Tao, S., Wang, Z., White, M., Willis, R., Wolting, C., Wong, S., Wrong, A., Xin, C., Yao, R., Yates, B., Zhang, S., Zheng, K., Pawson, T., Ouellette, B.F. and Hogue, C.W. The Biomolecular Interaction Network Database and related tools 2005 update. Nucleic Acids Res. 33 (2005) D418–D424.

    PubMed  CAS  Google Scholar 

  19. Chatr-Aryamontri, A., Ceol, A., Palazzi, L.M., Nardelli, G., Schneider, M.V., Castagnoli, L. and Cesareni, G. MINT: the Molecular INTeraction database. Nucleic Acids Res. 35 (2007) D572–574.

    PubMed  CAS  Google Scholar 

  20. Hermjakob, H., Montecchi-Palazzi, L., Lewington, C., Mudali, S., Kerrien, S., Orchard, S., Vingron, M., Roechert, B., Roepstorff, P., Valencia, A., Margalit, H., Armstrong, J., Bairoch, A., Cesareni, G., Sherman, D. and Apweiler, R. IntAct: an open source molecular interaction database. Nucleic Acids Res. 32 (2004) D452–D455.

    PubMed  CAS  Google Scholar 

  21. Kerrien, S., Alam-Faruque, Y., Aranda, B., Bancarz, I., Bridge, A., Derow, C., Dimmer, E., Feuermann, M., Friedrichsen, A., Huntley, R., Kohler, C., Khadake, J., Leroy, C., Liban, A., Lieftink, C., Montecchi-Palazzi, L., Orchard, S., Risse, J., Robbe, K., Roechert, B., Thorneycroft, D., Zhang, Y., Apweiler, R. and Hermjakob, H. IntAct - open source resource for molecular interaction data. Nucleic Acids Res. 35 (2007) D561–565.

    PubMed  CAS  Google Scholar 

  22. Peri, S., Navarro, J.D., Amanchy, R., Kristiansen, T.Z., Jonnalagadda, C.K., Surendranath, V., Niranjan, V., Muthusamy, B., Gandhi, T.K., Gronborg, M., Ibarrola, N., Deshpande, N., Shanker, K., Shivashankar, H.N., Rashmi, B.P., Ramya, M.A., Zhao, Z., Chandrika, K.N., Padma, N., Harsha, H.C., Yatish, A.J., Kavitha, M.P., Menezes, M., Choudhury, D.R., Suresh, S., Ghosh, N., Saravana, R., Chandran, S., Krishna, S., Joy, M., Anand, S.K., Madavan, V., Joseph, A., Wong, G.W., Schiemann, W.P., Constantinescu, S.N., Huang, L., Khosravi-Far, R., Steen, H., Tewari, M., Ghaffari, S., Blobe, G.C., Dang, C.V., Garcia, J.G., Pevsner, J., Jensen, O.N., Roepstorff, P., Deshpande, K.S., Chinnaiyan, A.M., Hamosh, A., Chakravarti, A. and Pandey, A. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res. 13 (2003) 2363–2371.

    PubMed  CAS  Google Scholar 

  23. Hoffmann, R. and Valencia, A. Implementing the iHOP concept for navigation of biomedical literature. Bioinformatics 21 Suppl 2 (2005) ii252–ii258.

    PubMed  CAS  Google Scholar 

  24. von Mering, C., Jensen, L.J., Snel, B., Hooper, S.D., Krupp, M., Foglierini, M., Jouffre, N., Huynen, M.A. and Bork, P. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 33 (2005) D433–D437.

    Google Scholar 

  25. Finn, R.D., Mistry, J., Schuster-Bockler, B., Griffiths-Jones, S., Hollich, V., Lassmann, T., Moxon, S., Marshall, M., Khanna, A., Durbin, R., Eddy, S.R., Sonnhammer, E.L. and Bateman, A. Pfam: clans, web tools and services. Nucleic Acids Res. 34 (2006) D247–D251.

    PubMed  CAS  Google Scholar 

  26. Altschul, S.F., Madden, T.L., Schaffer, A.A., Zhang, J., Zhang, Z., Miller, W. and Lipman, D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25 (1997) 3389–3402.

    PubMed  CAS  Google Scholar 

  27. Jones, D.T. Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol. 292 (1999) 195–202.

    PubMed  CAS  Google Scholar 

  28. Tatusov, R.L., Fedorova, N.D., Jackson, J.D., Jacobs, A.R., Kiryutin, B., Koonin, E.V., Krylov, D.M., Mazumder, R., Mekhedov, S.L., Nikolskaya, A.N., Rao, B.S., Smirnov, S., Sverdlov, A.V., Vasudevan, S., Wolf, Y.I., Yin, J.J. and Natale, D.A. The COG database: an updated version includes eukaryotes. BMC Bioinformatics 4 (2003) 41.

    PubMed  Google Scholar 

  29. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M. and Sherlock, G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25 (2000) 25–29.

    PubMed  CAS  Google Scholar 

  30. Camon, E., Barrell, D., Lee, V., Dimmer, E. and Apweiler, R. The Gene Ontology Annotation (GOA) Database - an integrated resource of GO annotations to the UniProt Knowledgebase. In Silico Biol 4 (2004) 5–6.

    PubMed  Google Scholar 

  31. Camon, E., Magrane, M., Barrell, D., Binns, D., Fleischmann, W., Kersey, P., Mulder, N., Oinn, T., Maslen, J., Cox, A. and Apweiler, R. The Gene Ontology Annotation (GOA) project: implementation of GO in SWISS-PROT, TrEMBL, and InterPro. Genome Res. 13 (2003) 662–672.

    PubMed  CAS  Google Scholar 

  32. Mao, X., Cai, T., Olyarchuk, J.G. and Wei, L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 21 (2005) 3787–3793.

    PubMed  CAS  Google Scholar 

  33. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y. and Hattori, M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 32 (2004) D277–D280.

    PubMed  CAS  Google Scholar 

  34. Jeong, H., Mason, S.P., Barabasi, A.L. and Oltvai, Z.N. Lethality and centrality in protein networks. Nature 411 (2001) 41–42.

    PubMed  CAS  Google Scholar 

  35. Sprinzak, E., Altuvia, Y. and Margalit, H. Characterization and prediction of protein-protein interactions within and between complexes. Proc. Natl. Acad. Sci. USA 103 (2006) 14718–14723.

    PubMed  CAS  Google Scholar 

  36. Brown, K.R. and Jurisica, I. Online predicted human interaction database. Bioinformatics 21 (2005) 2076–2082.

    PubMed  CAS  Google Scholar 

  37. Cagney, G., Uetz, P. and Fields, S. High-throughput screening for protein-protein interactions using two-hybrid assay. Methods Enzymol. 328 (2000) 3–14.

    PubMed  CAS  Google Scholar 

  38. Uetz, P., Giot, L., Cagney, G., Mansfield, T.A., Judson, R.S., Knight, J.R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., Qureshi-Emili, A., Li, Y., Godwin, B., Conover, D., Kalbfleisch, T., Vijayadamodar, G., Yang, M., Johnston, M., Fields, S. and Rothberg, J.M. A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403 (2000) 623–627.

    PubMed  CAS  Google Scholar 

  39. Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M. and Sakaki, Y. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. USA 98 (2001) 4569–4574.

    PubMed  CAS  Google Scholar 

  40. Ito, T., Chiba, T. and Yoshida, M. Exploring the protein interactome using comprehensive two-hybrid projects. Trends Biotechnol. 19 (2001) S23–S27.

    PubMed  CAS  Google Scholar 

  41. Rigaut, G., Shevchenko, A., Rutz, B., Wilm, M., Mann, M. and Seraphin, B. A generic protein purification method for protein complex characterization and proteome exploration. Nat. Biotechnol. 17 (1999) 1030–1032.

    PubMed  CAS  Google Scholar 

  42. Bader, G.D. and Hogue, C.W. Analyzing yeast protein-protein interaction data obtained from different sources. Nat. Biotechnol. 20 (2002) 991–997

    PubMed  CAS  Google Scholar 

  43. Chen, T., Jaffe, J.D. and Church, G.M. Algorithms for identifying protein cross-links via tandem mass spectrometry. J. Comput. Biol. 8 (2001) 571–583.

    PubMed  CAS  Google Scholar 

  44. Ito, T., Ota, K., Kubota, H., Yamaguchi, Y., Chiba, T., Sakuraba, K. and Yoshida, M. Roles for the two-hybrid system in exploration of the yeast protein interactome. Mol. Cell. Proteomics 1 (2002) 561–566.

    PubMed  CAS  Google Scholar 

  45. McDermott, J., Bumgarner, R. and Samudrala, R. Functional annotation from predicted protein interaction networks. Bioinformatics 21 (2005) 3217–3226.

    PubMed  CAS  Google Scholar 

  46. Morrison, J.L., Breitling, R., Higham, D.J. and Gilbert, D.R. A lock-and-key model for protein-protein interactions. Bioinformatics 22 (2006) 2012–2019.

    PubMed  CAS  Google Scholar 

  47. Schweitzer, B., Predki, P. and Snyder, M. Microarrays to characterize protein interactions on a whole-proteome scale. Proteomics 3 (2003) 2190–2199.

    PubMed  CAS  Google Scholar 

  48. Tong, A.H., Drees, B., Nardelli, G., Bader, G.D., Brannetti, B., Castagnoli, L., Evangelista, M., Ferracuti, S., Nelson, B., Paoluzi, S., Quondam, M., Zucconi, A., Hogue, C.W., Fields, S., Boone, C. and Cesareni, G. A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science 295 (2002) 321–324.

    PubMed  CAS  Google Scholar 

  49. Walhout, A.J., Boulton, S.J. and Vidal, M. Yeast two-hybrid systems and protein interaction mapping projects for yeast and worm. Yeast 17 (2000) 88–94.

    PubMed  CAS  Google Scholar 

  50. Wehr, M.C., Laage, R., Bolz, U., Fischer, T.M., Grunewald, S., Scheek, S., Bach, A., Nave, K.A. and Rossner, M.J. Monitoring regulated protein-protein interactions using split TEV. Nat. Methods 3 (2006) 985–993.

    PubMed  CAS  Google Scholar 

  51. Wu, X., Zhu, L., Guo, J., Zhang, D.Y. and Lin, K. Prediction of yeast protein-protein interaction network: insights from the Gene Ontology and annotations. Nucleic Acids Res. 34 (2006) 2137–2150.

    PubMed  CAS  Google Scholar 

  52. Yarmush, M.L. and Jayaraman, A. Advances in proteomic technologies. Annu. Rev. Biomed. Eng. 4 (2002) 349–373.

    PubMed  CAS  Google Scholar 

  53. Marcotte, E.M., Pellegrini, M., Ng, H.L., Rice, D.W., Yeates, T.O. and Eisenberg, D. Detecting protein function and protein-protein interactions from genome sequences. Science 285 (1999) 751–753.

    PubMed  CAS  Google Scholar 

  54. Troyanskaya, O.G., Dolinski, K., Owen, A.B., Altman, R.B. and Botstein, D. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). Proc. Natl. Acad. Sci. USA 100 (2003) 8348–8353.

    PubMed  CAS  Google Scholar 

  55. Lu, L., Lu, H. and Skolnick, J. MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading. Proteins 49 (2002) 350–364.

    PubMed  CAS  Google Scholar 

  56. Smith, G.R. and Sternberg, M.J. Prediction of protein-protein interactions by docking methods. Curr. Opin. Struct. Biol. 12 (2002) 28–35.

    PubMed  Google Scholar 

  57. Wodak, S.J. and Mendez, R. Prediction of protein-protein interactions: the CAPRI experiment, its evaluation and implications. Curr. Opin. Struct. Biol. 14 (2004) 242–249.

    PubMed  CAS  Google Scholar 

  58. Jones, S. and Thornton, J.M. Analysis of protein-protein interaction sites using surface patches. J. Mol. Biol. 272 (1997) 121–132.

    PubMed  CAS  Google Scholar 

  59. Lo Conte, L., Chothia, C. and Janin, J. The atomic structure of protein-protein recognition sites. J. Mol. Biol. 285 (1999) 2177–2198.

    PubMed  Google Scholar 

  60. Glaser, F., Steinberg, D.M., Vakser, I.A. and Ben-Tal, N. Residue frequencies and pairing preferences at protein-protein interfaces. Proteins 43 (2001) 89–102.

    PubMed  CAS  Google Scholar 

  61. Hu, Z., Ma, B., Wolfson, H. and Nussinov, R. Conservation of polar residues as hot spots at protein interfaces. Proteins 39 (2000) 331–342.

    PubMed  CAS  Google Scholar 

  62. DeLano, W.L. Unraveling hot spots in binding interfaces: progress and challenges. Curr. Opin. Struct. Biol. 12 (2002) 14–20.

    PubMed  CAS  Google Scholar 

  63. Pellegrini, M., Marcotte, E.M. and Yeates, T.O. A fast algorithm for genome-wide analysis of proteins with repeated sequences. Proteins 35 (1999) 440–446.

    PubMed  CAS  Google Scholar 

  64. Eisen, M.B., Spellman, P.T., Brown, P.O. and Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95 (1998) 14863–14868.

    PubMed  CAS  Google Scholar 

  65. Sprinzak, E. and Margalit, H. Correlated sequence-signatures as markers of protein-protein interaction. J. Mol. Biol. 311 (2001) 681–692.

    PubMed  CAS  Google Scholar 

  66. Bock, J.R. and Gough, D.A. Predicting protein-protein interactions from primary structure. Bioinformatics 17 (2001) 455–460.

    PubMed  CAS  Google Scholar 

  67. Gallet, X., Charloteaux, B., Thomas, A. and Brasseur, R. A fast method to predict protein interaction sites from sequences. J. Mol. Biol. 302 (2000) 917–926.

    PubMed  CAS  Google Scholar 

  68. Ofran, Y. and Rost, B. Predicted protein-protein interaction sites from local sequence information. FEBS Lett. 544 (2003) 236–239.

    PubMed  CAS  Google Scholar 

  69. Jones, S. and Thornton, J.M. Principles of protein-protein interactions. Proc. Natl. Acad. Sci. USA 93 (1996) 13–20.

    PubMed  CAS  Google Scholar 

  70. Nooren, I.M. and Thornton, J.M. Diversity of protein-protein interactions. Embo J. 22 (2003) 3486–3492.

    PubMed  CAS  Google Scholar 

  71. Nooren, I.M. and Thornton, J.M. Structural characterisation and functional significance of transient protein-protein interactions. J. Mol. Biol. 325 (2003) 991–1018.

    PubMed  CAS  Google Scholar 

  72. Bahadur, R.P., Chakrabarti, P., Rodier, F. and Janin, J. A dissection of specific and non-specific protein-protein interfaces. J. Mol. Biol. 336 (2004) 943–955.

    PubMed  CAS  Google Scholar 

  73. Ofran, Y. and Rost, B. Analysing six types of protein-protein interfaces. J. Mol. Biol. 325 (2003) 377–387.

    PubMed  CAS  Google Scholar 

  74. Saha, R.P., Bahadur, R.P. and Chakrabarti, P. Interresidue contacts in proteins and protein-protein interfaces and their use in characterizing the homodimeric interface. J. Proteome Res. 4 (2005) 1600–1609.

    PubMed  CAS  Google Scholar 

  75. Bordner, A.J. and Abagyan, R. Statistical analysis and prediction of protein-protein interfaces. Proteins 60 (2005) 353–366.

    PubMed  CAS  Google Scholar 

  76. Neuvirth, H., Raz, R. and Schreiber, G. ProMate: a structure based prediction program to identify the location of protein-protein binding sites. J. Mol. Biol. 338 (2004) 181–199.

    PubMed  CAS  Google Scholar 

  77. Chung, J.L., Wang, W. and Bourne, P.E. Exploiting sequence and structure homologs to identify protein-protein binding sites. Proteins 62 (2006) 630–640.

    PubMed  CAS  Google Scholar 

  78. Valdar, W.S. and Thornton, J.M. Protein-protein interfaces: analysis of amino acid conservation in homodimers. Proteins 42 (2001) 108–124.

    PubMed  CAS  Google Scholar 

  79. Yao, H., Kristensen, D.M., Mihalek, I., Sowa, M.E., Shaw, C., Kimmel, M., Kavraki, L. and Lichtarge, O. An accurate, sensitive, and scalable method to identify functional sites in protein structures. J. Mol. Biol. 326 (2003) 255–261.

    PubMed  CAS  Google Scholar 

  80. Aloy, P., Querol, E., Aviles, F.X. and Sternberg, M.J. Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking. J. Mol. Biol. 311 (2001) 395–408.

    PubMed  CAS  Google Scholar 

  81. Berezin, C., Glaser, F., Rosenberg, J., Paz, I., Pupko, T., Fariselli, P., Casadio, R. and Ben-Tal, N. ConSeq: the identification of functionally and structurally important residues in protein sequences. Bioinformatics 20 (2004) 1322–1324.

    PubMed  CAS  Google Scholar 

  82. Caffrey, D.R., Somaroo, S., Hughes, J.D., Mintseris, J. and Huang, E.S. Are protein-protein interfaces more conserved in sequence than the rest of the protein surface? Protein Sci. 13 (2004) 190–202.

    PubMed  CAS  Google Scholar 

  83. Yan, C., Dobbs, D. and Honavar, V. A two-stage classifier for identification of protein-protein interface residues. Bioinformatics 20 Suppl 1 (2004) I371–I378.

    PubMed  CAS  Google Scholar 

  84. Porollo, A. and Meller, J. Prediction-based fingerprints of protein-protein interactions. Proteins 66 (2006) 630–645.

    Google Scholar 

  85. Koike, A. and Takagi, T. Prediction of protein-protein interaction sites using support vector machines. Protein Eng. Des. Sel. 17 (2004) 165–173.

    PubMed  CAS  Google Scholar 

  86. Jansen, R., Yu, H., Greenbaum, D., Kluger, Y., Krogan, N.J., Chung, S., Emili, A., Snyder, M., Greenblatt, J.F. and Gerstein, M. A Bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302 (2003) 449–453.

    PubMed  CAS  Google Scholar 

  87. Liu, X., Zhang, L.M. and Zheng, W.M. Prediction of protein secondary structure based on residue pairs. J. Bioinform. Comput. Biol. 2 (2004) 343–352.

    PubMed  CAS  Google Scholar 

  88. Zhang, L.V., Wong, S.L., King, O.D. and Roth, F.P. Predicting co-complexed protein pairs using genomic and proteomic data integration. BMC Bioinformatics 5 (2004) 38.

    PubMed  Google Scholar 

  89. Zhou, H.X. and Shan, Y. Prediction of protein interaction sites from sequence profile and residue neighbor list. Proteins 44 (2001) 336–343

    PubMed  CAS  Google Scholar 

  90. Hesse, H. and Hoefgen, R. On the way to understand biological complexity in plants: S-nutrition as a case study for systems biology. Cell. Mol. Biol. Lett. 11 (2006) 37–56.

    PubMed  CAS  Google Scholar 

  91. Hsieh, C.J., Chen, M.J., Liao, Y.L. and Liao, T.N. Polymorphisms of the uridine-diphosphoglucuronosyltransferase 1A1 gene and coronary artery disease. Cell. Mol. Biol. Lett. 13 (2008) 1–10.

    PubMed  CAS  Google Scholar 

  92. Huang, B., Chu, C.H., Chen, S.L., Juan, H.F. and Chen, Y.M. A proteomics study of the mung bean epicotyl regulated by brassinosteroids under conditions of chilling stress. Cell. Mol. Biol. Lett. 11 (2006) 264–278.

    PubMed  CAS  Google Scholar 

  93. Knizewski, L., Steczkiewicz, K., Kuchta, K., Wyrwicz, L., Plewczynski, D., Kolinski, A., Rychlewski, L. and Ginalski, K. Uncharacterized DUF1574 leptospira proteins are SGNH hydrolases. Cell Cycle 7 (2008) 542–544.

    PubMed  CAS  Google Scholar 

  94. Korohoda, W. and Wilk, A. Cell electrophoresis - a method for cell separation and research into cell surface properties. Cell. Mol. Biol. Lett. 13 (2008) 312–326.

    PubMed  CAS  Google Scholar 

  95. Li, J., Ji, C., Zheng, H., Fei, X., Zheng, M., Dai, J., Gu, S., Xie, Y. and Mao, Y. Molecular cloning and characterization of a novel human gene containing 4 ankyrin repeat domains. Cell. Mol. Biol. Lett. 10 (2005) 185–193.

    PubMed  CAS  Google Scholar 

  96. Liu, S.J., Zhang, D.Q., Sui, X.M., Zhang, L., Cai, Z.W., Sun, L.Q., Liu, Y.J., Xue, Y. and Hu, G.F. The inhibition of in vivo tumorigenesis of osteosarcoma (OS)-732 cells by antisense human osteopontin RNA. Cell. Mol. Biol. Lett. 13 (2008) 11–19.

    PubMed  CAS  Google Scholar 

  97. Miyamato, T., Sato, H., Yogev, L., Kleiman, S., Namiki, M., Koh, E., Sakugawa, N., Hayashi, H., Ishikawa, M., Lamb, D.J. and Sengoku, K. Is a genetic defect in Fkbp6 a common cause of azoospermia in humans? Cell. Mol. Biol. Lett. 11 (2006) 557–569.

    PubMed  CAS  Google Scholar 

  98. Wisniewska, A., Draus, J. and Subczynski, W.K. Is a fluid-mosaic model of biological membranes fully relevant? Studies on lipid organization in model and biological membranes. Cell. Mol. Biol. Lett. 8 (2003) 147–159.

    PubMed  CAS  Google Scholar 

  99. Wladyka, B. and Pustelny, K. Regulation of bacterial protease activity. Cell. Mol. Biol. Lett. 13 (2008) 212–229.

    PubMed  CAS  Google Scholar 

  100. Cottage, A., Mullan, L., Portela, M.B., Hellen, E., Carver, T., Patel, S., Vavouri, T., Elgar, G. and Edwards, Y.J. Molecular characterisation of the SAND protein family: a study based on comparative genomics, structural bioinformatics and phylogeny. Cell. Mol. Biol. Lett. 9 (2004) 739–753

    PubMed  CAS  Google Scholar 

  101. Gronemeyer, H. and Miturski, R. Molecular mechanisms of retinoid action. Cell. Mol. Biol. Lett. 6 (2001) 3–52.

    PubMed  CAS  Google Scholar 

  102. Agoston, V., Cemazar, M., Kajan, L. and Pongor, S. Graph-representation of oxidative folding pathways. BMC Bioinformatics 6 (2005) 19.

    PubMed  Google Scholar 

  103. Kajan, L., Kertesz-Farkas, A., Franklin, D., Ivanova, N., Kocsor, A. and Pongor, S. Application of a simple likelihood ratio approximant to protein sequence classification. Bioinformatics 22 (2006) 2865–2869.

    PubMed  CAS  Google Scholar 

  104. Kocsor, A., Kertesz-Farkas, A., Kajan, L. and Pongor, S. Application of compression-based distance measures to protein sequence classification: a methodological study. Bioinformatics 22 (2006) 407–412.

    PubMed  CAS  Google Scholar 

  105. Vlahovicek, K., Kajan, L., Agoston, V. and Pongor, S. The SBASE domain sequence resource, release 12: prediction of protein domain-architecture using support vector machines. Nucleic Acids Res. 33 (2005) D223–D225.

    PubMed  CAS  Google Scholar 

  106. Vlahovicek, K., Kajan, L., Murvai, J., Hegedus, Z. and Pongor, S. The SBASE domain sequence library, release 10: domain architecture prediction. Nucleic Acids Res. 31 (2003) 403–405.

    PubMed  CAS  Google Scholar 

  107. von Grotthuss, M., Plewczynski, D., Ginalski, K., Rychlewski, L. and Shakhnovich, E.I. PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics. BMC Bioinformatics 7 (2006) 53.

    Google Scholar 

  108. Wyrwicz, L.S., Koczyk, G., Rychlewski, L. and Plewczynski, D. ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics. J. Phys. Condens. Matter 19 (2007) 285222.

    Google Scholar 

  109. Grabarkiewicz, T., Grobelny, P., Hoffmann, M. and Mielcarek, J. DFT study on hydroxy acid-lactone interconversion of statins: The case of fluvastatin. Org. Biomol. Chem. 4 (2006) 4299–4306.

    PubMed  CAS  Google Scholar 

  110. Grabarkiewicz, T. and Hoffmann, M. Syn- and anti-conformations of 5′- deoxy- and 5′-O-methyl-uridine 2′,3′-cyclic monophosphate. J. Mol. Model. 12 (2006) 205–212.

    PubMed  CAS  Google Scholar 

  111. Hoffmann, M., Chrzanowska, M., Hermann, T. and Rychlewski, J. Modeling of purine derivatives transport across cell membranes based on their partition coefficient determination and quantum chemical calculations. J. Med. Chem. 48 (2005) 4482–4486.

    PubMed  CAS  Google Scholar 

  112. Hoffmann, M. and Marciniec, B. Quantum chemical study of the mechanism of ethylene elimination in silylative coupling of olefins. J. Mol. Model. 13 (2007) 477–483.

    PubMed  CAS  Google Scholar 

  113. Hoffmann, M., Plutecka, A., Rychlewska, U., Kucybala, Z., Paczkowski, J. and Pyszka, I. New type of bonding formed from an overlap between pi aromatic and pi C=O molecular orbitals stabilizes the coexistence in one molecule of the ionic and neutral meso-ionic forms of imidazopyridine. J. Phys. Chem. A Mol. Spectrosc. Kinet. Environ. Gen. Theory 109 (2005) 4568–4574.

    PubMed  CAS  Google Scholar 

  114. Hoffmann, M. and Rychlewski, J. Effects of substituting a OH group by a F atom in D-glucose. Ab initio and DFT analysis. J. Am. Chem. Soc. 123 (2001) 2308–2316.

    PubMed  CAS  Google Scholar 

  115. Hoffmann, M., Rychlewski, J., Chrzanowska, M. and Hermann, T. Mechanism of activation of an immunosuppressive drug: azathioprine. Quantum chemical study on the reaction of azathioprine with cysteine. J. Am. Chem. Soc. 123 (2001) 6404–6409.

    PubMed  CAS  Google Scholar 

  116. Plutecka, A., Hoffmann, M., Rychlewska, U., Kucybala, Z., Paczkowski, J. and Pyszka, I. Relationship between structure and photoinitiating abilities of selected bromide salts of 2-oxo-2,3-dihydro-1H-imidazo[1,2-a]pyridine (IMP): influence of the solvent and the substitution in benzaldehyde on the course of its reaction with IMP. Acta Crystallogr. B 62 (2006) 135–142.

    PubMed  Google Scholar 

  117. Hoffmann, M., Eitner, K., von Grotthuss, M., Rychlewski, L., Banachowicz, E., Grabarkiewicz, T., Szkoda, T. and Kolinski, A. Three dimensional model of severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain and molecular design of severe acute respiratory syndrome coronavirus helicase inhibitors. J. Comput. Aided Mol. Des. 20 (2006) 305–319.

    PubMed  CAS  Google Scholar 

  118. Ostrowski, J., Rubel, T., Wyrwicz, L.S., Mikula, M., Bielasik, A., Butruk, E. and Regula, J. Three clinical variants of gastroesophageal reflux disease form two distinct gene expression signatures. J. Mol. Med. 84 (2006) 872–882.

    PubMed  Google Scholar 

  119. Paziewska, A., Wyrwicz, L.S., Bujnicki, J.M., Bomsztyk, K. and Ostrowski, J. Cooperative binding of the hnRNP K three KH domains to mRNA targets. FEBS Lett. 577 (2004) 134–140.

    PubMed  CAS  Google Scholar 

  120. Paziewska, A., Wyrwicz, L.S. and Ostrowski, J. The binding activity of yeast RNAs to yeast Hek2p and mammalian hnRNP K proteins, determined using the three-hybrid system. Cell. Mol. Biol. Lett. 10 (2005) 227–235.

    PubMed  CAS  Google Scholar 

  121. von Grotthuss, M., Koczyk, G., Pas, J., Wyrwicz, L.S. and Rychlewski, L. Ligand-Info small-molecule Meta-Database. Comb. Chem. High. Throughput Screen. 7 (2004) 757–761.

    Google Scholar 

  122. von Grotthuss, M., Pas, J. and Rychlewski, L. Ligand-Info, searching for similar small compounds using index profiles. Bioinformatics 19 (2003) 1041–1042.

    Google Scholar 

  123. von Grotthuss, M., Wyrwicz, L.S. and Rychlewski, L. mRNA cap-1 methyltransferase in the SARS genome. Cell 113 (2003) 701–702.

    Google Scholar 

  124. Wyrwicz, L.S. and Rychlewski, L. Herpes glycoprotein gL is distantly related to chemokine receptor ligands. Antiviral Res. 75 (2007) 83–86.

    PubMed  CAS  Google Scholar 

  125. Zemojtel, T., Frohlich, A., Palmieri, M.C., Kolanczyk, M., Mikula, I., Wyrwicz, L.S., Wanker, E.E., Mundlos, S., Vingron, M., Martasek, P. and Durner, J. Plant nitric oxide synthase: a never-ending story? Trends Plant Sci. 11 (2006) 524–525; author reply 526-528.

    PubMed  CAS  Google Scholar 

  126. Plewczynski, D., Hoffmann, M., von Grotthuss, M., Ginalski, K. and Rychewski, L. In silico prediction of SARS protease inhibitors by virtual high throughput screening. Chem. Biol. Drug Design 69 (2007) 269–279.

    CAS  Google Scholar 

  127. Plewczynski, D., Hoffmann, M., von Grotthuss, M., Knizewski, L., Rychewski, L., Eitner, K. and Ginalski, K. Modelling of potentially promising SARS protease inhibitors. J. Phys. Condens. Matter 19 (2007) 285207.

    Google Scholar 

  128. Feder, M., Pas, J., Wyrwicz, L.S. and Bujnicki, J.M. Molecular phylogenetics of the RrmJ/fibrillarin superfamily of ribose 2′-Omethyltransferases. Gene 302 (2003) 129–138.

    PubMed  CAS  Google Scholar 

  129. Ginalski, K., Pas, J., Wyrwicz, L.S., von Grotthuss, M., Bujnicki, J.M. and Rychlewski, L. ORFeus: Detection of distant homology using sequence profiles and predicted secondary structure. Nucleic Acids Res. 31 (2003) 3804–3807.

    PubMed  CAS  Google Scholar 

  130. Klimek-Tomczak, K., Mikula, M., Dzwonek, A., Paziewska, A., Wyrwicz, L.S., Hennig, E.E. and Ostrowski, J. Mitochondria-associated satellite I RNA binds to hnRNP K protein. Acta Biochim. Pol. 53 (2006) 169–178.

    PubMed  CAS  Google Scholar 

  131. Klimek-Tomczak, K., Wyrwicz, L.S., Jain, S., Bomsztyk, K. and Ostrowski, J. Characterization of hnRNP K protein-RNA interactions. J. Mol. Biol. 342 (2004) 1131–1141.

    PubMed  CAS  Google Scholar 

  132. Pas, J., von Grotthuss, M., Wyrwicz, L.S., Rychlewski, L. and Barciszewski, J. Structure prediction, evolution and ligand interaction of CHASE domain. FEBS Lett. 576 (2004) 287–290.

    PubMed  CAS  Google Scholar 

  133. von Grotthuss, M., Pas, J., Wyrwicz, L., Ginalski, K. and Rychlewski, L. Application of 3D-Jury, GRDB, and Verify3D in fold recognition. Proteins 53 Suppl 6 (2003) 418–423.

    Google Scholar 

  134. von Grotthuss, M., Plewczynski, D., Ginalski, K., Rychlewski, L. and Shakhnovich, E.I. PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics. BMC Bioinformatics 7 (2006) 53.

    Google Scholar 

  135. von Grotthuss, M., Wyrwicz, L.S., Pas, J. and Rychlewski, L. Predicting protein structures accurately. Science 304 (2004) 1597–1599; author reply 1597–1599.

    Google Scholar 

  136. Wyrwicz, L.S., von Grotthuss, M., Pas, J. and Rychlewski, L. How unique is the rice transcriptome? Science 303 (2004) 168; author reply 168.

    PubMed  CAS  Google Scholar 

  137. Plewczynski, D., Jaroszewski, L., Godzik, A., Kloczkowski, A. and Rychlewski, L. Molecular modeling of phosphorylation sites in proteins using a database of local structure segments. J. Mol. Mod. 11 (2005) 431–438.

    CAS  Google Scholar 

  138. Plewczynski, D., Tkacz, A., Godzik, A. and Rychlewski, L. A support vector machine approach to the identification of phosphorylation sites. Cell. Mol. Biol. Lett. 10 (2005) 73–89.

    PubMed  CAS  Google Scholar 

  139. Plewczynski, D., Tkacz, A., Wyrwicz, L., Godzik, A., Kloczkowski, A. and Rychlewski, L. Support-vector-machine classification of linear functional motifs in proteins. J. Mol. Mod. 12 (2006) 453–461.

    CAS  Google Scholar 

  140. Plewczynski, D., Tkacz, A., Wyrwicz, L.S. and Rychlewski, L. AutoMotif server: prediction of single residue post-translational modifications in proteins. Bioinformatics 21 (2005) 2525–2527.

    PubMed  CAS  Google Scholar 

  141. Plewczynski, D., Tkacz, A., Wyrwicz, L.S., Rychlewski, L. and Ginalski, K. AutoMotif Server for prediction of phosphorylation sites in proteins using support vector machine: 2007 update. J. Mol. Mod. 14 (2008) 69–76.

    CAS  Google Scholar 

  142. Plewczynski, D., Slabinski, L., Tkacz, A., Kajan, L., Holm, L., Ginalski, K. and Rychlewski, L. The RPSP: Web server for prediction of signal peptides. Polymer 48 (2007) 5493–5496.

    CAS  Google Scholar 

  143. Fernandez-Ballester, G. and Serrano, L. Prediction of protein-protein interaction based on structure. Methods Mol. Biol. 340 (2006) 207–234

    PubMed  CAS  Google Scholar 

  144. Plewczynski, D., Pas, J., von Grotthuss, M. and Rychlewski, L. Comparison of proteins based on segments structural similarity). Acta Bioch. Pol. 51 (2004) 161–172.

    CAS  Google Scholar 

  145. Plewczynski, D., Rychlewski, L., Ye, Y.Z., Jaroszewski, L. and Godzik, A. Integrated web service for improving alignment quality based on segments comparison. BMC Bioinformatics 5 (2004) 98.

    PubMed  Google Scholar 

  146. Kinch, L.N., Ginalski, K., Rychlewski, L. and Grishin, N.V. Identification of novel restriction endonuclease-like fold families among hypothetical proteins. Nucleic Acids Res. 33 (2005) 3598–3605.

    PubMed  CAS  Google Scholar 

  147. Ginalski, K., Elofsson, A., Fischer, D. and Rychlewski, L. 3D-Jury: a simple approach to improve protein structure predictions. Bioinformatics 19 (2003) 1015–1018.

    PubMed  CAS  Google Scholar 

  148. Ginalski, K. and Rychlewski, L. Detection of reliable and unexpected protein fold predictions using 3D-Jury. Nucleic Acids Res. 31 (2003) 3291–3292.

    PubMed  CAS  Google Scholar 

  149. Bu, D., Zhao, Y., Cai, L., Xue, H., Zhu, X., Lu, H., Zhang, J., Sun, S., Ling, L., Zhang, N., Li, G. and Chen, R. Topological structure analysis of the protein-protein interaction network in budding yeast. Nucleic Acids Res. 31 (2003) 2443–2450.

    PubMed  CAS  Google Scholar 

  150. Sen, T.Z., Kloczkowski, A. and Jernigan, R.L. Functional clustering of yeast proteins from the protein-protein interaction network. BMC Bioinformatics 7 (2006) 355.

    PubMed  Google Scholar 

  151. Ogmen, U., Keskin, O., Aytuna, A.S., Nussinov, R. and Gursoy, A. PRISM: protein interactions by structural matching. Nucleic Acids Res. 33 (2005) W331–W336.

    PubMed  CAS  Google Scholar 

  152. Aytuna, A.S., Gursoy, A. and Keskin, O. Prediction of protein-protein interactions by combining structure and sequence conservation in protein interfaces. Bioinformatics 21 (2005) 2850–2855.

    PubMed  CAS  Google Scholar 

  153. Aloy, P., Bottcher, B., Ceulemans, H., Leutwein, C., Mellwig, C., Fischer, S., Gavin, A.C., Bork, P., Superti-Furga, G., Serrano, L. and Russell, R.B. Structure-based assembly of protein complexes in yeast. Science 303 (2004) 2026-2029.

  154. Aloy, P. and Russell, R.B. Interrogating protein interaction networks through structural biology. Proc. Natl. Acad. Sci. USA 99 (2002) 5896–5901.

    PubMed  CAS  Google Scholar 

  155. Aloy, P. and Russell, R.B. InterPreTS: protein interaction prediction through tertiary structure. Bioinformatics 19 (2003) 161–162.

    PubMed  CAS  Google Scholar 

  156. Ben-Hur, A. and Noble, W.S. Kernel methods for predicting protein-protein interactions. Bioinformatics 21 Suppl 1 (2005) i38–46.

    PubMed  CAS  Google Scholar 

  157. Ben-Hur, A. and Noble, W.S. Choosing negative examples for the prediction of protein-protein interactions. BMC Bioinformatics 7 Suppl 1 (2006) S2.

    PubMed  Google Scholar 

  158. Gomez, S.M., Noble, W.S. and Rzhetsky, A. Learning to predict proteinprotein interactions from protein sequences. Bioinformatics 19 (2003) 1875–1881.

    PubMed  CAS  Google Scholar 

  159. Nanni, L. and Lumini, A. An ensemble of K-local hyperplanes for predicting protein-protein interactions. Bioinformatics 22 (2006) 1207–1210.

    PubMed  CAS  Google Scholar 

  160. Sun, S., Zhao, Y., Jiao, Y., Yin, Y., Cai, L., Zhang, Y., Lu, H., Chen, R. and Bu, D. Faster and more accurate global protein function assignment from protein interaction networks using the MFGO algorithm. FEBS Lett. 580 (2006) 1891–1896.

    PubMed  CAS  Google Scholar 

  161. Bordner, A.J. and Abagyan, R.A. Large-scale prediction of protein geometry and stability changes for arbitrary single point mutations. Proteins 57 (2004) 400–413.

    PubMed  CAS  Google Scholar 

  162. Lu, H., Zhu, X., Liu, H., Skogerbo, G., Zhang, J., Zhang, Y., Cai, L., Zhao, Y., Sun, S., Xu, J., Bu, D. and Chen, R. The interactome as a tree-an attempt to visualize the protein-protein interaction network in yeast. Nucleic Acids Res. 32 (2004) 4804–4811.

    PubMed  CAS  Google Scholar 

  163. Plewczynski, D., Spieser, S.A.H. and Koch, U. Assessing different classification methods for virtual screening. J. Chem. Inf. Mod. 46 (2006) 1098–1106.

    CAS  Google Scholar 

  164. Plewczynski, D., von Grotthuss, M., Spieser, S.A.H., Rychlewski, L., Wyrwicz, L.S., Ginalski, K. and Koch, U. Target specific compound identification using a support vector machine. Comb. Chem. High Throughput Screen. 10 (2007) 189–196.

    PubMed  CAS  Google Scholar 

  165. Plewczynski, D., Spieser, S.A. and Koch, U. Assessing different classification methods for virtual screening. J. Chem. Inf. Model. 46 (2006) 1098–1106.

    PubMed  CAS  Google Scholar 

  166. Sen, T.Z., Kloczkowski, A., Jernigan, R.L., Yan, C., Honavar, V., Ho, K.M., Wang, C.Z., Ihm, Y., Cao, H., Gu, X. and Dobbs, D. Predicting binding sites of hydrolase-inhibitor complexes by combining several methods. BMC Bioinformatics 5 (2004) 205.

    PubMed  Google Scholar 

  167. Donald, J.E., Hubner, I.A., Rotemberg, V.M., Shakhnovich, E.I. and Mirny, L.A. CoC: a database of universally conserved residues in protein folds. Bioinformatics 21 (2005) 2539–2540.

    PubMed  CAS  Google Scholar 

  168. Mirny, L.A., Abkevich, V.I. and Shakhnovich, E.I. How evolution makes proteins fold quickly. Proc. Natl. Acad. Sci. USA 95 (1998) 4976–4981.

    PubMed  CAS  Google Scholar 

  169. Mirny, L.A. and Shakhnovich, E.I. Universally conserved positions in protein folds: reading evolutionary signals about stability, folding kinetics and function. J. Mol. Biol. 291 (1999) 177–196.

    PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dariusz Plewczyński.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Plewczyński, D., Ginalski, K. The interactome: Predicting the protein-protein interactions in cells. Cell Mol Biol Lett 14, 1–22 (2009). https://doi.org/10.2478/s11658-008-0024-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2478/s11658-008-0024-7

Key words