One of the central problems in modern biology is to identify the complete set of interactions among proteins in a cell. The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Structural evidence indicates that, interacting pairs of close homologs usually interact in the same way. In this chapter, we make use of both homology and inter-domain linker region knowledge to predict interaction between protein pairs solely by amino acid sequence information. High quality core set of 150 yeast proteins obtained from the Database of Interacting Proteins (DIP) was considered to test the accuracy of the proposed method. The strongest prediction of the method reached over 70% accuracy. These results show great potential for the proposed method.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
I. Donaldson, J. Martin, B. Bruijn, C. Wolting, V. Lay, B. Tuekam, S. Zhang, B. Baskin, G. D. Bader, K. Michalickova, T. Pawson, and C.W. Hogue, PreBIND and Textomy — mining the biomedical literature for protein-protein interactions using a support vector machine, BMC Bioinformatics, 4(11) (2003).
E. Gharakhanian, J. Takahashi, J. Clevr, and H. Kasamatsu, In vitro assay for protein—protein interaction: carboxyl-terminal 40 residues of simian virus 40 structural protein VP3 contain a determinant for interaction with VP1, PNAS, 85(18), 6607–6611 (1998).
P. L. Bartel and S. Fields, The yeast two-hybrid system. In Advances in Molecular Biology, Oxford University Press, New York, 1997.
G. Rigaut, A. Shevchenko, B. Rutz, M. Wilm, M. Mann, and B. Seraphin, A generic protein purification method for protein complex characterization and proteome exploration, Nature Biotechnology, 17, 1030–1032 (1999).
M. Selbach and M. Mann, Protein interaction screening by quantitative immunoprecipitation combined with knockdown (QUICK), Nature Methods, 3, 981–983 (2006).
L. Salwinski, C. S. Miller, A. J. Smith, F. K. Pettit, J. U. Bowie, and D. Eisenberg, The Database of Interacting Proteins: 2004 update, Nucleic Acids Research, 1(32), 449–51 (2004).
H. W. Mewes, MIPS: analysis and annotation of proteins from whole genomes, Nucleic Acids Research, 32, 41–44 (2004).
S. Peri, Human protein reference database as a discovery resource for proteomics, Nucleic Acids Research, 32, 497–501 (2004).
J. Espadaler, Detecting remotely related proteins by their interactions and sequence similarity, Proceedings of the National Academy of Sciences USA, 102, 7151–7156 (2005).
E. Marcotte, Detecting protein function and protein—protein interactions from genome sequences, Science, 285, 751–753 (1999).
T. Dandekar, Conservation of gene order: a fingerprint of proteins that physically interact, Trends in Biochemical Sciences, 23, 324–328 (1998).
M. Pellegrini, E. M. Marcotte, M. J. Thompson, D. Eisenberg, and T. O. Yeates, Assigning protein functions by comparative genome analysis: protein phylogenetic profiles, Proceedings of National Academy of Sciences USA, 96, 4285–4288 (1999).
A. Szilagyi, V. Grimm, A. K. Arakaki, and J. Sholnick, Prediction of physical protein-protein interactions, Physical Biology, 2, 1–16 (2005).
E. M. Marcotte, M. Pellegrini, M. J. Thompson, T. O. Yeates, and D. Eisenberg, A combined algorithm for genome-wide prediction of protein function, Nature, 402, 83–86 (1999).
F. Pazos and A. Valencia, Similarity of phylogenetic trees as indicator of protein-protein interaction, Protein Engineering, 14, 609–614 (2001).
J. Enright, I. N. Ilipoulos, C. Kyrpides, and C. A. Ouzounis, Protein interaction maps for complete genomes based on gene fusion events, Nature, 402, 86–90 (1999).
D. Eisenberg, E. M. Marcotte, I. Xenarios, and T. O. Yeates, Protein function in the post-genomic era, Nature, 405, 823–826 (2000).
J. Wojcik and V. Schachter, Protein-Protein interaction map inference using interacting domain profile pairs, Bioinformatics, 17, 296–305 (2001).
W. K. Kim, J. Park, and J. K. Suh, Large scale statistical prediction of protein-protein interaction by potentially interacting domain (PID) pair, Genome Informatics, 13, 42–50 (2002).
S. K. Ng, Z. Zhang, and S. H. Tan, integrative approach for computationally inferring protein domain interactions, Bioinformatics, 19, 923–929 (2002).
S. M. Gomez, W. S. Noble, and A. Rzhetsky, Learning to predict protein-protein interactions from protein sequences, Bioinformatics, 19, 1875–1881 (2003).
C. Huang, F. Morcos, S. P. Kanaan, S. Wuchty, A. Z. Chen, and J. A. Izaguirre, Predicting protein-protein interactions from protein domains using a set cover approach, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(1), 78–87 (2007).
T. Pawson and P. Nash, Assembly of cell regulatory systems through protein interaction domains, Science, 300, 445–452 (2003).
N. M. Zaki, S. Deris, and H. Alashwal, Protein—protein interaction detection based on substring sensitivity measure, International Journal of Biomedical Sciences, 1, 148–154 (2006).
P. Aloy and R. B. Russell, InterPreTS: protein interaction prediction through tertiary structure, Bioinformatics, 19, 161–162 (2003).
L. Lu, Multiprospector: an algorithm for the prediction of protein—protein interactions by multimeric threading, Proteins, 49, 350–364 (2002).
J. Espadaler, O. Romero-Isart, R. M. Jackson, and B. Oliva, Prediction of protein—protein interactions using distant conservation of sequence patterns and structure relationships, Bioinformatics, 21, 3360–3368 (2005).
O. Keskin, A new, structurally nonredundant, diverse data set of protein—protein interfaces and its implications, Protein Sciences, 13, 1043–1055 (2004).
T. Smith and M. Waterman, “Identification of common molecular subsequences”, Journal of Molecular Biology, 147, 195–197 (1981).
H. Saigo, J. Vert, N. Ueda, and T. Akutsu, Protein homology detection using string alignment kernels, Bioinformatics, 20(11), 1682–1689 (2004).
A. Bairoch and R. Apweiler, The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000, Nucleic Acids Research, 28, 45–48 (2000).
M. Suyama and O. Ohara, DomCut: prediction of inter-domain linker regions in amino acid sequences, Bioinformatics, 19, 673–674 (2003).
A. Gattiker, E. Gasteiger, and A. Bairoch, ScanProsite: a reference implementation of a PROSITE scanning tool, Applied Bioinformatics, 1, 107–108 (2002).
I. Xenarios, L. Salwínski, X. J. Duan, P. Higney, S. Kim, and D. Eisenberg, DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions, Nucleic Acids Research, Oxford University Press, 30, 303–305 (2002).
C. M. Deane, L. Salwinski, I. Xenarios, and D. Eisenberg, Protein interactions: two methods for assessment of the reliability of high throughput observations, Molecular & Cellular Proteomics, 1, 349–56 (2002).
W. R. Pearson, Rapid and sensitive sequence comparisons with FASTAP and FASTA method, Methods in Enzymology, 183, 63–93 (1985).
Q. Dong, X. Wang, L. Lin, and Z. Xu, Domain boundary prediction based on profile domain linker propensity index, Computational Biology and Chemistry, 30, 127–133 (2006).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media B.V
About this chapter
Cite this chapter
Zaki, N. (2009). Protein-Protein Interaction Prediction Using Homology and Inter-domain Linker Region Information. In: Ao, SI., Gelman, L. (eds) Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2311-7_54
Download citation
DOI: https://doi.org/10.1007/978-90-481-2311-7_54
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-2310-0
Online ISBN: 978-90-481-2311-7
eBook Packages: EngineeringEngineering (R0)