Generic placeholder image

Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Refining Protein Interaction Network for Identifying Essential Proteins

Author(s): Houwang Zhang*, Zhenan Feng and Chong Wu

Volume 18, Issue 3, 2023

Published on: 13 March, 2023

Page: [255 - 265] Pages: 11

DOI: 10.2174/1574893618666230217140446

Price: $65

conference banner
Abstract

Aim: The study aimed to reconstruct the protein-protein interaction network for the identification of essential proteins.

Background: In a living organism, essential proteins play an indispensable role in its survival and development. Hence, how to identify essential proteins from the protein interaction network (PIN) has become a hot topic in the field of bioinformatics. However, existing methods’ accuracies for identifying essential proteins are still limited due to the false positives of the protein-protein interaction data.

Objective: The objective of the study was to propose an efficient algorithm for the reconstruction of a protein-protein interaction network.

Methods: In this paper, a method for the refinement of PIN based on three kinds of biological data (subcellular localization data, protein complex data, and gene expression data) is proposed. Through evaluating each interaction within the original PIN, a refined clean PIN could be obtained. To verify the effectiveness of the refined PIN for the identification of essential proteins, we applied eight networkbased essential protein discovery methods (DC, BC, CC, LC, HC, SC, LAC, and NC) to it.

Results: Based on the obtained experimental results, we demonstrated that the precision for identifying essential proteins could be greatly improved by refining the original PIN using our method.

Conclusion: Our method could effectively enhance the protein-protein interaction network and improve the accuracy of identifying essential proteins. In the future, we plan to integrate more biological information to enhance our refinement method and apply it to more species and more PIN-based discovery tasks, like the identification of protein complexes or functional modules.

[1]
Glass JI, Hutchison CA III, Smith HO, Venter JC. A systems biology tour de force for a near-minimal bacterium. Mol Syst Biol 2009; 5(1): 330.
[http://dx.doi.org/10.1038/msb.2009.89] [PMID: 19953084]
[2]
Zhang R, Lin Y. DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes. Nucleic Acids Res 2009; 37(Database): D455-8.
[http://dx.doi.org/10.1093/nar/gkn858]
[3]
Clatworthy AE, Pierson E, Hung DT. Targeting virulence: A new paradigm for antimicrobial therapy. Nat Chem Biol 2007; 3(9): 541-8.
[http://dx.doi.org/10.1038/nchembio.2007.24] [PMID: 17710100]
[4]
Zeng M, Li M, Fei Z, Wu F-X, Li Y, Pan Y. A deep learning framework for identifying essential proteins based on protein-protein interaction network and gene expression data. In: IEEE International Conference on Bioinformatics and Biomedicine (BIBM); Madrid Spain. New York IEEE. 2018; pp. 583-8.
[http://dx.doi.org/10.1109/BIBM.2018.8621551]
[5]
Furney SJ, Albà MM, López-Bigas N. Differences in the evolutionary history of disease genes affected by dominant or recessive mutations. BMC Genomics 2006; 7(1): 165.
[http://dx.doi.org/10.1186/1471-2164-7-165] [PMID: 16817963]
[6]
Lu Y, Deng J, Rhodes JC, Lu H, Lu LJ. Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus. Comput Biol Chem 2014; 50: 29-40.
[http://dx.doi.org/10.1016/j.compbiolchem.2014.01.011] [PMID: 24569026]
[7]
Zhang Z, Luo Y, Hu S, Li X, Wang L, Zhao B. A novel method to predict essential proteins based on tensor and HITS algorithm. Hum Genomics 2020; 14(1): 14.
[http://dx.doi.org/10.1186/s40246-020-00263-7] [PMID: 32252824]
[8]
Belloze K, Campos L, Matias R, Luques I, Bezerra E. A review of artificial neural networks for the prediction of essential proteins Networks in Systems Biology. New York, USA: Springer International Publishing 2020; pp. 45-68.
[http://dx.doi.org/10.1007/978-3-030-51862-2_4]
[9]
Giaever G, Chu AM, Ni L, et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 2002; 418(6896): 387-91.
[http://dx.doi.org/10.1038/nature00935] [PMID: 12140549]
[10]
Cullen LM, Arndt GM. Genomewide screening for gene function using RNAi in mammalian cells. Immunol Cell Biol 2005; 83(3): 217-23.
[http://dx.doi.org/10.1111/j.1440-1711.2005.01332.x] [PMID: 15877598]
[11]
Roemer T, Jiang B, Davison J, et al. Large-scale essential gene identification in Candida albicans and applications to antifungal drug discovery. Mol Microbiol 2003; 50(1): 167-81.
[http://dx.doi.org/10.1046/j.1365-2958.2003.03697.x] [PMID: 14507372]
[12]
Wu C, Zhang H, Zhang L, Zheng H. Identification of essential proteins using a novel multi-objective optimization method. In: ICASSP 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); Barcelona, Spain. New York IEEE . 2020; pp. 1329-33.
[http://dx.doi.org/10.1109/ICASSP40776.2020.9052965]
[13]
Payra AK, Ghosh A. Identifying essential proteins using modified-monkey algorithm (MMA). Comput Biol Chem 2020; 88: 107324.
[http://dx.doi.org/10.1016/j.compbiolchem.2020.107324] [PMID: 32623358]
[14]
Li M, Ni P, Chen X, Wang J, Wu FX, Pan Y. Construction of refined protein interaction network for predicting essential proteins. IEEE/ACM Trans Comput Biol Bioinformatics 2019; 16(4): 1386-97.
[http://dx.doi.org/10.1109/TCBB.2017.2665482] [PMID: 28186903]
[15]
Chen Z, Meng Z, Liu C, et al. A novel model for predicting essential proteins based on heterogeneous protein-domain network. IEEE Access 2020; 8: 8946-58.
[http://dx.doi.org/10.1109/ACCESS.2020.2964571]
[16]
Jeong H, Mason SP, Barabási AL, Oltvai ZN. Lethality and centrality in protein networks. Nature 2001; 411(6833): 41-2.
[http://dx.doi.org/10.1038/35075138] [PMID: 11333967]
[17]
Hahn MW, Kern AD. Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 2005; 22(4): 803-6.
[http://dx.doi.org/10.1093/molbev/msi072] [PMID: 15616139]
[18]
Zotenko E, Mestre J, O’Leary DP, Przytycka TM. 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(8): e1000140.
[http://dx.doi.org/10.1371/journal.pcbi.1000140] [PMID: 18670624]
[19]
Li M, Wang JX, Wang H, Pan Y. Identification of essential proteins from weighted protein-protein interaction networks. J Bioinform Comput Biol 2013; 11(3): 1341002.
[http://dx.doi.org/10.1142/S0219720013410023] [PMID: 23796179]
[20]
Zhao B, Wang J, Li M, Wu F, Pan Y. Prediction of essential proteins based on overlapping essential modules. IEEE Trans Nanobiosci 2014; 13(4): 415-24.
[http://dx.doi.org/10.1109/TNB.2014.2337912] [PMID: 25122840]
[21]
Liang H, Li WH. Gene essentiality, gene duplicability and protein connectivity in human and mouse. Trends Genet 2007; 23(8): 375-8.
[http://dx.doi.org/10.1016/j.tig.2007.04.005] [PMID: 17512629]
[22]
Lin CC, Juan HF, Hsiang JT, Hwang YC, Mori H, Huang HC. Essential core of protein-protein interaction network in Escherichia coli. J Proteome Res 2009; 8(4): 1925-31.
[http://dx.doi.org/10.1021/pr8008786] [PMID: 19231892]
[23]
Ning K, Ng HK, Srihari S, Leong HW, Nesvizhskii AI. Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology. BMC Bioinformatics 2010; 11(1): 505.
[http://dx.doi.org/10.1186/1471-2105-11-505] [PMID: 20939873]
[24]
Yu H, Braun P. Yıldırım MA, et al. High-quality binary protein interaction map of the yeast interactome network. Science 2008; 322(5898): 104-10.
[http://dx.doi.org/10.1126/science.1158684] [PMID: 18719252]
[25]
Agarwal S, Deane CM, Porter MA, Jones NS. Revisiting date and party hubs: Novel approaches to role assignment in protein interaction networks. PLOS Comput Biol 2010; 6(6): e1000817.
[http://dx.doi.org/10.1371/journal.pcbi.1000817] [PMID: 20585543]
[26]
Joy MP, Brock A, Ingber DE, Huang S. High-betweenness proteins in the yeast protein interaction network. J Biomed Biotechnol 2005; 2005(2): 96-103.
[http://dx.doi.org/10.1155/JBB.2005.96] [PMID: 16046814]
[27]
Wuchty S, Stadler PF. Centers of complex networks. J Theor Biol 2003; 223(1): 45-53.
[http://dx.doi.org/10.1016/S0022-5193(03)00071-7] [PMID: 12782116]
[28]
Estrada E, Rodríguez-Velázquez JA. Subgraph centrality in complex networks. Phys Rev E Stat Nonlin Soft Matter Phys 2005; 71(5): 056103.
[http://dx.doi.org/10.1103/PhysRevE.71.056103] [PMID: 16089598]
[29]
Goh KI, Kahng B, Kim D. Universal behavior of load distribution in scale-free networks. Phys Rev Lett 2001; 87(27): 278701.
[http://dx.doi.org/10.1103/PhysRevLett.87.278701] [PMID: 11800921]
[30]
Boldi P, Vigna S. Axioms for centrality. Internet Math 2014; 10(3-4): 222-62.
[http://dx.doi.org/10.1080/15427951.2013.865686]
[31]
Li M, Wang J, Chen X, Wang H, Pan Y. A local average connectivity-based method for identifying essential proteins from the network level. Comput Biol Chem 2011; 35(3): 143-50.
[http://dx.doi.org/10.1016/j.compbiolchem.2011.04.002] [PMID: 21704260]
[32]
Jianxin Wang , Min Li, Huan Wang, Yi Pan. Identification of essential proteins based on edge clustering coefficient. IEEE/ACM Trans Comput Biol Bioinformatics 2012; 9(4): 1070-80.
[http://dx.doi.org/10.1109/TCBB.2011.147] [PMID: 22084147]
[33]
Li G, Li M, Wang J, Wu J, Wu FX, Pan Y. Predicting essential proteins based on subcellular localization, orthology and PPI networks. BMC Bioinformatics 2016; 17(S8) (Suppl. 8): 279.
[http://dx.doi.org/10.1186/s12859-016-1115-5] [PMID: 27586883]
[34]
Wang J, Peng X, Li M, Pan Y. Construction and application of dynamic protein interaction network based on time course gene expression data. Proteomics 2013; 13(2): 301-12.
[http://dx.doi.org/10.1002/pmic.201200277] [PMID: 23225755]
[35]
Xenarios I, Salwínski L, Duan XJ, Higney P, Kim SM, Eisenberg D. DIP, the database of interacting proteins: A research tool for studying cellular networks of protein interactions. Nucleic Acids Res 2002; 30(1): 303-5.
[http://dx.doi.org/10.1093/nar/30.1.303] [PMID: 11752321]
[36]
Mewes HW, Frishman D, Mayer KFX, et al. MIPS: Analysis and annotation of proteins from whole genomes in 2005. Nucleic Acids Res 2006; 34(90001): D169-72.
[http://dx.doi.org/10.1093/nar/gkj148] [PMID: 16381839]
[37]
Cherry J, Adler C, Ball C, et al. Sgd: Saccharomyces genome database. Nucleic Acids Res 1998; 26(1): 73-9.
[http://dx.doi.org/10.1093/nar/26.1.73] [PMID: 9399804]
[38]
Saccharomyces genome deletion project. 2020. Available from: http://yeastdeletion.stanford.edu//
[39]
Compartments. Available from:http://compartments.jensenlab.org
[40]
Magrane M. Uniprot knowledgebase: A hub of integrated protein data. In: Database. 2011; 2011.(2011)
[41]
Eppig JT, Blake JA, Bult CJ, Kadin JA, Richardson JE. The Mouse Genome Database (MGD): Comprehensive resource for genetics and genomics of the laboratory mouse. Nucleic Acids Res 2012; 40(D1): D881-6.
[http://dx.doi.org/10.1093/nar/gkr974] [PMID: 22075990]
[42]
Cherry JM, Hong EL, Amundsen C, et al. Saccharomyces genome database: The genomics resource of budding yeast. Nucleic Acids Res 2012; 40(D1): D700-5.
[http://dx.doi.org/10.1093/nar/gkr1029] [PMID: 22110037]
[43]
McQuilton P, St Pierre SE, Thurmond J. FlyBase 101--the basics of navigating flybase. Nucleic Acids Res 2012; 40(1): D706-14.
[http://dx.doi.org/10.1093/nar/gkr1030] [PMID: 22127867]
[44]
Harris TW, Antoshechkin I, Bieri T, et al. WormBase: A comprehensive resource for nematode research. Nucleic Acids Res 2010; 38 (Suppl. 1): D463-7.
[http://dx.doi.org/10.1093/nar/gkp952] [PMID: 19910365]
[45]
Luo J, Qi Y. Identification of essential proteins based on a new combination of local interaction density and protein complexes. PLoS One 2015; 10(6): e0131418.
[http://dx.doi.org/10.1371/journal.pone.0131418] [PMID: 26125187]
[46]
Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 2002; 30(1): 207-10.
[http://dx.doi.org/10.1093/nar/30.1.207] [PMID: 11752295] [PMCID: PMC99122]
[47]
Scott MS, Calafell SJ, Thomas DY, Hallett MT. Refining protein subcellular localization. PLOS Comput Biol 2005; 1(6): e66.
[http://dx.doi.org/10.1371/journal.pcbi.0010066] [PMID: 16322766]
[48]
Peng X, Wang J, Wang J, Wu FX, Pan Y. Rechecking the centrality-lethality rule in the scope of protein subcellular localization interaction networks. PLoS One 2015; 10(6): e0130743.
[http://dx.doi.org/10.1371/journal.pone.0130743] [PMID: 26115027]
[49]
Lei X, Fang M, Wu FX, Chen L. Improved flower pollination algorithm for identifying essential proteins. BMC Syst Biol 2018; 12(S4) (Suppl. 4): 46.
[http://dx.doi.org/10.1186/s12918-018-0573-y] [PMID: 29745838]
[50]
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(1): 15.
[http://dx.doi.org/10.1186/1752-0509-6-15] [PMID: 22405054]
[51]
Rocha EPC, Danchin A. An analysis of determinants of amino acids substitution rates in bacterial proteins. Mol Biol Evol 2004; 21(1): 108-16.
[http://dx.doi.org/10.1093/molbev/msh004] [PMID: 14595100]
[52]
Maccari L, Ghiro L, Guerrieri A, Montresor A, Cigno RL. On the distributed computation of load centrality and its application to dv routing. IEEE INFOCOM 2018-IEEE Conference on Computer Communications. Honolulu, USA. New York, USA: IEEE 2018; pp. 2582-90.
[http://dx.doi.org/10.1109/INFOCOM.2018.8486345]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy