Computational approaches to predicting essential proteins: A survey

Proteomics - Clinical Applications

Volumn 7, Issue 1-2, 2013, Pages 181-192

  Wang, Jianxin ^a   Peng, Wei ^a   Wu, Fang Xiang ^b  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

Drug targets; Essential genes; Essential proteins

Indexed keywords

ESSENTIAL PROTEIN; PROTEIN; UNCLASSIFIED DRUG;

ACINETOBACTER BAYLYI; ANALYTIC METHOD; BACILLUS SUBTILIS; BETWEENESS LIKE FEATURE; CAENORHABDITIS ELEGANS; CENTRALITY LETHALITY RULE; CLASSIFICATION; CLASSIFIER; CLOSENESS LIKE FEATURE; DAMAGE LIKE FEATURE; DEGREE LIKE FEATURE; DROSOPHILA MELANOGASTER; EIGENVECTOR LIKE FEATURE; ESCHERICHIA COLI; ESSENTIAL GENE; FEATURES WITH RESPECT TO NEIGHBORS; GENE EXPRESSION; GENETIC CONSERVATION; GENETIC DATABASE; LETHALITY; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; PROTEIN SYNTHESIS REGULATION; PSEUDOMONAS AERUGINOSA; REVIEW; SEQUENCE BASED FEATURE; SUBGRAPH LIKE FEATURE; SUPERVISED APPROACH; TOPOLOGY BASED FEATURE; UNSUPERVISED APPROACH; YEAST;

GENES, ESSENTIAL; HUMANS; PROTEINS; PROTEOMICS;

EID: 84872707941     PISSN: 18628346     EISSN: 18628354     Source Type: Journal    
DOI: 10.1002/prca.201200068     Document Type: Review

References (93)

1. Zhang, R., Lin, Y., DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes. Nucleic Acids Res. 2009, 37, D455-D458.
2. Glass, J. I., Hutchison, C. A., 3rd, Smith, H. O., Venter, J. C., A systems biology tour de force for a near-minimal bacterium. Mol. Syst. Biol. 2009, 5, 330.
3. Clatworthy, A. E., Pierson, E., Hung, D. T., Targeting virulence: a new paradigm for antimicrobial therapy. Nat. Chem. Biol. 2007, 3, 541-548.
4. Furney, S. J., Alba, M. M., Lopez-Bigas, N., Differences in the evolutionary history of disease genes affected by dominant or recessive mutations. BMC Genomics 2006, 7, 165.
5. Giaever, G., Chu, A. M., Ni, L., Connelly, C. et al., Functional profiling of the Saccharomyces cerevisiae genome. Nature 2002, 418, 387-391.
6. Kobayashi, K., Ehrlich, S. D., Albertini, A., Amati, G. et al., Essential Bacillus subtilis genes. Proc. Natl. Acad. Sci. 2003, 100, 4678-4683.
7. Cullen, L. M., Arndt, G. M., Genome-wide screening for gene function using RNAi in mammalian cells. Immunol. Cell Biol. 2005, 83, 217-223.
8. Kamath, R. S., Fraser, A. G., Dong, Y., Poulin, G. et al., Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 2003, 421, 231-237.
9. Ji, Y., Zhang, B., Van Horn, S. F., Warren, P. et al., Identification of critical staphylococcal genes using conditional phenotypes generated by antisense RNA. Science 2001, 293, 2266-2269.
10. Gallagher, L. A., Ramage, E., Jacobs, M. A., Kaul, R. et al., A comprehensive transposon mutant library of Francisella novicida, a bioweapon surrogate. Proc. Natl. Acad. Sci. 2007, 104, 1009-1014.
11. Langridge, G. C., Phan, M.-D, Turner, D. J., Perkins, T. T. et al., Simultaneous assay of every Salmonella typhi gene using one million transposon mutants. Genome Res. 2009, 19, 2308-2316.
12. Tong, X., Campbell, J. W., Balázsi, G., Kay, K. A. et al., Genome-scale identification of conditionally essential genes in E. coli by DNA microarrays. Biochem. Biophys. Res. Commun. 2004, 322, 347-354.
13. Molina-Henares, M. A., De La Torre, J., García-Salamanca, A., Molina-Henares, A. J. et al., Identification of conditionally essential genes for growth of Pseudomonas putida KT2440 on minimal medium through the screening of a genome-wide mutant library. Environ. Microbiol. 2010, 12, 1468-1485.
14. Fraser, H. B., Hirsh, A. E., Steinmetz, L. M., Scharfe, C. et al., Evolutionary rate in the protein interaction network. Science 2002, 296, 750-752.
15. Jordan, I. K., Rogozin, I. B., Wolf, Y. I., Koonin, E. V., Essential genes are more evolutionarily conserved than are nonessential genes in bacteria. Genome Res 2002, 12, 962-968.
16. Batada, N. N., Hurst, L. D., Tyers, M., Evolutionary and physiological importance of hub proteins. PLoS Comput. Biol. 2006, 2, e88.
17. Gustafson, A. M., Snitkin, E. S., Parker, S. C., DeLisi, C. et al., Towards the identification of essential genes using targeted genome sequencing and comparative analysis. BMC Genomics 2006, 7, 265.
18. Hwang, Y. C., Lin, C. C., Chang, J. Y., Mori, H. et al., Predicting essential genes based on network and sequence analysis. Mol. Biosyst. 2009, 5, 1672-1678.
19. Deng, J., Deng, L., Su, S., Zhang, M. et al., Investigating the predictability of essential genes across distantly related organisms using an integrative approach. Nucleic Acids Res. 2010, 39, 795-807.
20. Saha, S., Heber, S., In silico prediction of yeast deletion phenotypes. Genet. Mol. Res. 2006, 5, 224-232.
21. Sharp, P. M., Determinants of DNA sequence divergence between Escherichia coli and Salmonella typhimurium: codon usage, map position, and concerted evolution. J. Mol. Evol. 1991, 33, 23-33.
22. Rocha, E. P. C., Danchin, A., An analysis of determinants of amino acids substitution rates in bacterial proteins. Mol. Biol. Evol. 2004, 21, 108-116.
23. Krylov, D. M., Wolf, Y. I., Rogozin, I. B., Koonin, E. V., Gene loss, protein sequence divergence, gene dispensability, expression level, and interactivity are correlated in eukaryotic evolution. Genome Res. 2003, 13, 2229-2235.
24. Rocha, E. P., Danchin, A., Essentiality, not expressiveness, drives gene-strand bias in bacteria. Nat. Genet. 2003, 34, 377-378.
25. Lin, Y., Gao, F., Zhang, C.-T, Functionality of essential genes drives gene strand-bias in bacterial genomes. Biochem. Biophys. Res. Commun. 2010, 396, 472-476.
26. Hawoong Jeong, Z. N. O., Albert-László Barabási, Prediction of protein essentiality based on genomic data. ComPlexUs 2002, 2003, 10.
27. Acencio, M. L., Lemke, N., Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information. BMC Bioinformatics 2009, 10, 290.
28. Yu, H., Greenbaum, D., Xin Lu, H., Zhu, X. et al., Genomic analysis of essentiality within protein networks. Trends Genet. 2004, 20, 227-231.
29. Hahn, M. W., Kern, A. D., Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol. Biol. Evol. 2005, 22, 803-806.
30. Wang, J., Li, M., Wang, H., Pan, Y., Identification of essential proteins based on edge clustering coefficient. IEEE/ACM Trans. Comput. Biol. Bioinform. 2012, 9, 1070-1080.
31. Kovacs, I. A., Palotai, R., Szalay, M. S., Csermely, P., Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics. PLoS One 2010, 5, e12528.
32. Katz, L., A new status index derived from sociometric analysis. Psychometrika 1953, 18, 39-43.
33. Ghosh, R., Lerman, K., Parameterized centrality metric for network analysis. Phys. Rev. E 2011, 83, 066118.
34. Joy, M. P., Brock, A., Ingber, D. E., Huang, S., High-betweenness proteins in the yeast protein interaction network. J. Biomed. Biotechnol. 2005, 2005, 96-103.
35. Shimbel, A., Structural parameters of communication networks. Bull. Math Biol. 1953, 15, 501-507.
36. Ercsey-Ravasz, M., Lichtenwalter, R. N., Chawla, N. V., Toroczkai, Z., Range-limited centrality measures in complex networks. Phys. Rev. E 2012, 85, 066103.
37. Yu, H., Kim, P. M., Sprecher, E., Trifonov, V. et al., The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput. Biol. 2007, 3, e59.
38. Wuchty, S., Stadler, P. F., Centers of complex networks. J. Theor. Biol. 2003, 223, 45-53.
39. Karen, Stephenson, Zelen, M., Rethinking centrality: methods and examples. Social Networks 2002, 11, 37.
40. Hage, P., Harary, F., Eccentricity and centrality in networks. Social Networks 1995, 17, 57-63.
41. Valente, T. W., Foreman, R. K., Integration and radiality: measuring the extent of an individual's connectedness and reachability in a network. Social Networks 1998, 20, 89-105.
42. Bonacich, P., Power and centrality: a family of measures. Am. J. Sociol. 1987, 92, 12.
43. Page, L., Brin, S., Motwani, R., Winograd, T., The PageRank Citation Ranking: Bringing Order to the Web. Technical report, Stanford Digital Library Technologies Project, 1998.
44. Lü, L., Zhang, Y.-C., Yeung, C. H., Zhou, T., Leaders in social networks, the delicious case. PLoS One 2011, 6, e21202.
45. Estrada, E., Rodriguez-Velazquez, J. A., Subgraph centrality in complex networks. Phys. Rev. E 2005, 71, 056103.
46. Schmith, J., Lemke, N., Mombach, J. C. M., Benelli, P. et al., Damage, connectivity and essentiality in protein-protein interaction networks. Physica A: Statistical Mechanics and its Applications 2005, 349, 675-684.
47. Chin, C.-S., Samanta, M. P., Global snapshot of a protein interaction network-a percolation based approach. Bioinformatics 2003, 19, 2413-2419.
48. Watts, D. J., Strogatz, S. H., Collective dynamics of 'small-world' networks. Nature 1998, 393, 440-442.
49. Li, M., Wang, J., Chen, X., Wang, H. et al., A local average connectivity-based method for identifying essential proteins from the network level. Comput. Biol. Chem. 2011, 35, 143-150.
50. Korn, A., Schubert, A., Telcs, A., Lobby index in networks. Physica A 2009, 388, 2221-2226.
51. Manimaran, P., Hegde, S. R., Mande, S. C., Prediction of conditional gene essentiality through graph theoretical analysis of genome-wide functional linkages. Mol. Biosyst. 2009, 5, 1936-1942.
52. Plaimas, K., Eils, R., Konig, R., Identifying essential genes in bacterial metabolic networks with machine learning methods. BMC Syst. Biol. 2010, 4, 56.
53. Seringhaus, M., Paccanaro, A., Borneman, A., Snyder, M. et al., Predicting essential genes in fungal genomes. Genome Res. 2006, 16, 1126-1135.
54. Chen, Y., Xu, D., Understanding protein dispensability through machine-learning analysis of high-throughput data. Bioinformatics 2005, 21, 575-581.
55. Holman, A., Davis, P., Foster, J., Carlow, C. et al., Computational prediction of essential genes in an unculturable endosymbiotic bacterium, Wolbachia of Brugia malayi. BMC Microbiol. 2009, 9, 243.
56. Bruccoleri, R. E., Dougherty, T. J., Davison, D. B., Concordance analysis of microbial genomes. Nucleic Acids Res. 1998, 26, 4482-4486.
57. Lin, Y., Zhang, R. R., Putative essential and core-essential genes in mycoplasma genomes. Sci. Rep. 2011, 1, 53.
58. Jeong, H., Mason, S. P., Barabasi, A. L., Oltvai, Z. N., Lethality and centrality in protein networks. Nature 2001, 411, 41-42.
59. Zotenko, E., Mestre, J., O'Leary, D.P., Przytycka, T. M., Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS Comput. Biol. 2008, 4, 1-16.
60. He, X. L., Zhang, J. Z., Why do hubs tend to be essential in protein networks? PLoS Genet. 2006, 2, 826-834.
61. Ning, K., Ng, H. K., Srihari, S., Leong, H. W. et al., Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology. BMC Bioinformatics 2010, 11, 505.
62. Estrada, E., Virtual identification of essential proteins within the protein interaction network of yeast. Proteomics 2006, 6, 35-40.
63. Park, K., Kim, D., Localized network centrality and essentiality in the yeast-protein interaction network. Proteomics 2009, 9, 5143-5154.
64. Lin, C.-Y., Chin, C.-H., Wu, H.-H., Chen, S.-H. et al., Hubba: hub objects analyzer-a framework of interactome hubs identification for network biology. Nucleic Acids Res. 2008, 36, W438-W443.
65. del Rio, G., Koschutzki, D., Coello, G., How to identify essential genes from molecular networks? BMC Syst. Biol. 2009, 3, 102.
66. Chua, H. N., Tew, K. L., Li, X. L., Ng, S. K., A Unified Scoring Scheme for Detecting Essential Proteins in Protein Interaction Networks. 20th IEEE International Conference on Tools with Artificial Intelligence, Vol. 2, Proceedings 2008, 66-73.
67. Tew, K. L., Li, X. L., Tan, S. H., Functional centrality: detecting lethality of proteins in protein interaction networks. Genome Inform Ser. 2007, 19, 166-177.
68. Li, M., Wang, J. X., Wang, H. A., Pan, Y., Essential proteins discovery from weighted protein interaction networks. Bioinformatics Res.Appl. 2010, 6053, 89-100.
69. Hart, G. T., Lee, I., Marcotte, E., A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality. BMC Bioinformatics 2007, 8, 236.
70. Ren, J., Wang, J. X., Li, M., Wang, H. et al., Prediction of essential proteins by integration of PPI network topology and protein complexes information. Bioinformatics Res. Appl. 2011, 6674, 12-24.
71. Li, M., Zhang, H., Wang, J., Pan, Y., A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data. BMC Syst. Biol. 2012, 6, 15.
72. Peng, W., Wang, J., Wang, W., Liu, Q. et al., Iteration method for predicting essential proteins based on orthology and protein-protein interaction networks. BMC Syst. Biol. 2012, 6, 87.
73. Fritz, B., Raczniak, G. A., Bacterial genomics-potential for antimicrobial drug discovery. BioDrugs 2002, 16, 331-337.
74. Perumal, D., Lim, C. S., Sakharkar, K. R., Sakharkar, M. K., Differential genome analyses of metabolic enzymes in Pseudomonas aeruginosa for drug target identification. In Silico Biol. 2007, 7, 453-465.
75. Dutta, A., Singh, S. K., Ghosh, P., Mukherjee, R. et al., In silico identification of potential therapeutic targets in the human pathogen Helicobacter pylori. In Silico Biol. 2006, 6, 43-47.
76. Chong, C. E., Lim, B. S., Nathan, S., Mohamed, R., In silico analysis of Burkholderia pseudomallei genome sequence for potential drug targets. In Silico Biol. 2006, 6, 341-346.
77. Anishetty, S., Pulimi, M., Pennathur, G., Potential drug targets in Mycobacterium tuberculosis through metabolic pathway analysis. Comput Biol. Chem. 2005, 29, 368-378.
78. Sharma, V., Gupta, P., Dixit, A., In silico identification of putative drug targets from different metabolic pathways of Aeromonas hydrophila. In Silico Biol. 2008, 8, 331-338.
79. Chhabra, G., Sharma, P., Anant, A., Deshmukh, S. et al., Identification and modeling of a drug target for Clostridium perfringens SM101. Bioinformation 2010, 4, 278-289.
80. Barh, D., Kumar, A., In silico identification of candidate drug and vaccine targets from various pathways in Neisseria gonorrhoeae. In Silico Biol. 2009, 9, 225-231.
81. Magariños, M. P., Carmona, S. J., Crowther, G. J., Ralph, S. A. et al., TDR Targets: a chemogenomics resource for neglected diseases. Nucleic Acids Res. 2012, 40, D1118-D1127.
82. Koonin, E. V., How many genes can make a cell: the minimal-gene-set concept. Annu. Rev. Genomics Hum. Genet. 2000, 1, 99-116.
83. Juhas, M., Eberl, L., Glass, J. I., Essence of life: essential genes of minimal genomes. Trends Cell Biol. 2011, 21, 562-568.
84. Gibson, D. G., Glass, J. I., Lartigue, C., Noskov, V. N. et al., Creation of a bacterial cell controlled by a chemically synthesized genome. Science 2010, 329, 52-56.
85. Goh, K.-I., Cusick, M. E., Valle, D., Childs, B. et al., The human disease network. Proc. Natl. Acad. Sci. 2007, 104, 8685-8690.
86. Huang, H., Winter, E. E., Wang, H. J., Weinstock, K. G. et al., Evolutionary conservation and selection of human disease gene orthologs in the rat and mouse genomes. Genome Biol. 2004, 5, R47.
87. Tu, Z. D., Wang, L., Xu, M., Zhou, X. H. et al., Further understanding human disease genes by comparing with housekeeping genes and other genes. BMC Genomics 2006, 7, 31-43.
88. López-Bigas, N., Ouzounis, C. A., Genome-wide identification of genes likely to be involved in human genetic disease. Nucleic Acids Res 2004, 32, 3108-3114.
89. Xu, J., Li, Y., Discovering disease-genes by topological features in human protein-protein interaction network. Bioinformatics 2006, 22, 2800-2805.
90. Lin, C. C., Juan, H. F., Hsiang, J. T., Hwang, Y. C. et al., Essential core of protein-protein interaction network in Escherichia coli. J. Proteome Res. 2009, 8, 1925-1931.
91. Wang, J., Chen, G., Liu, B., Li, M. et al., Identifying protein complexes from interactome based on essential proteins and local fitness method. IEEE Transactions on NanoBioscience 2012, 11, 324-335.
92. Li, M., Wang, J. X., Chen, J., A Graph-theoretic method for mining overlapping functional modules in protein interaction networks. In: Proceedings of the 4th International Symposium on Bioinformatics Research and Applications Lecture Notes in Bioinformatics 2008, 4983, 208-219.
93. Tang, X. W., Wang, J. X., Liu, B. B., Li, M. et al., A comparison of the functional modules identified from time course and static PPI network data. BMC Bioinformatics 2011, 12, 339.