Abstract
Essential proteins play a vital role in the biological and cellular activity of a living organism. Identification of essential proteins is crucial for understanding the cellular life mechanisms for medical treatments and disease diagnosis. The existing computational measures are primarily based on identifying dense sub-graphs from the protein interaction network. In this research paper, the existing computational, graph theoretic approaches are reviewed and a novel research direction to find essential proteins is proposed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- PPI:
-
Protein-protein interaction
- RNA:
-
Ribonucleic acid
- Bio GRID:
-
The Biological General Repository for Interaction Datasets
- PPIM:
-
Protein-protein interaction database for maize
- DIP:
-
Database of Interacting Proteins
- SGD:
-
The Saccharomyces Genome Database
- MIPS :
-
Munich Information Center for Protein Sequences
References
Pál C, Papp B, Hurst LD (2003) Genomic function (communication arising): rate of evolution and gene dispensability. Nature 421:496
He X, Zhang J (2006) Why do hubs tend to be essential in protein networks? PLoS Gen 2:e88
Fuentes G et al (2011) Role of protein flexibility in the discovery of new drugs. Drug Dev Res 72:26–35
Clatworthy AE, Pierson E, Hung DT (2007) Targeting virulence: a new paradigm for antimicrobial therapy. Nat Chem Biol. 3:541
Roemer T, Jiang B, Davison J, Ketela T, Veillette K, Breton A, Tandia F, Linteau A, Sillaots S, Marta C (2003) Large-scale essential gene identification in candida albicans and applications to antifungal drug discovery. Mol Microbiol 50:167–181
Xu Z, Zikos D, Osterrieder N, KarstenTischer B (2014) Generation of a complete single-gene knockout bacterial artificial chromosome library of cowpox virus and identification of its essential genes. J Virol 88:490–502
Walia RR, Caragea C, Lewis BA, Towfic F, Terribilini M, El-Manzalawy Y, Dobbs D, Honavar V (2012) Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinform 13:89
Qin C, Sun Y, Dong Y (2016) A new method for identifying essential proteins based on network topology properties and protein complexes. PLoS One 11:e0161042
Hermjakob H, Montecchi-Palazzi L, Lewington C, Mudali S, Kerrien S, Orchard S, Vingron M, Roechert B, Roepstorff P, Valencia A, Margalit H (2004) Int Act: an open source molecular interaction database. Nuc Acid Res 32(Suppl_1):D452–D455
Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M (2006) Bio GRID: a general repository for interaction datasets. Nuc Acid Res 34(Database issue):D535–D539
Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G (2007) MINT: the molecular interaction database. Nuc Acid Re 35(Database issue):D572–D574
Zhu G, Wu A, Xu X-J, Xiao P-P, Lu L, Liu J, Zhao X-M (2016) PPIM: a protein-protein interaction database for maize. Plant Physiol 170:618–626
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, von Mering C (2017) The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucl Acid Res 45(Database issue):D362–D368
Arighi CN, Roberts PM, Agarwal S, Bhattacharya S, Cesareni G, Chatr-aryamontri A, Wu CH (2011) Bio Creative III interactive task: an overview. BMC Bioinform 12(Suppl 8):S4
Xenarios I, Rice DW, Salwinski L, Baron MK, Marcotte EM, Eisenberg D (2000) DIP: the database of interacting proteins. Nuc Acid Res 28:289–291
Luo H, Lin Y, Gao F, Zhang CT, Zhang R (2013) DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements. Nuc Acid Res 42:D574–D580
Pagel P, Kovac S, Oesterheld M, Brauner B, Dunger-Kaltenbach I, Frishman G, Montrone C, Mark P, Stümpflen V, Mewes HW, Ruepp A (2004) The MIPS mammalian protein–proteininteraction database. Bioinformatics 21:832–834
Vazquez A, Alzate O (eds) (2010) Protein interaction networks, neuroproteomics. CRC Press/Taylor & Francis, Boca Raton
Hahn MW, Kern AD (2005) Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 22:803–806
Mistry D, Wise RP, Dickerson JA (2017) Diff SLC: a graph centrality method to detect essential proteins of a protein-protein interaction network. PLoS One 12:e0187091
Opsahl T, Agneessens F, Skvoretz J (2010) Node centrality in weighted networks: generalizing degree and shortest paths. Social Net 32:245–251
Abedi M, Gheisari Y (2015) Nodes with high centrality in protein interaction networks are responsible for driving signaling pathways in diabetic nephropathy. Peer J 3:e1284
Joy MP, Brock A, Ingber DE, Huang S (2005) High-betweenness proteins in the yeast protein interaction network. Bio Med Res Int 2:96–103
Girvan M, Newman ME (2002) Community structure in social and biological networks. Proc Nat Acad Sci USA 99:12–7821-7826
Hahn MW, Kern AD (2004) Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 22:803–806
Bihari A, Pandia MK (2015) Eigenvector centrality and its application in research professionals’ relationship network. In: Futuristic trends on computational analysis and knowledge management (ABLAZE), pp 510–514
Özgür A, Vu T, Erkan G, Radev DR (2008) Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics 24:i277–i285
Newman ME (2006) Modularity and community structure in networks. Proceed Nat Acad Sci 103:8577–8582
Bennett L, Kittas A, Liu S, Papageorgiou LG, Tsoka S (2014) Community structure detection for overlapping modules through mathematical programming in protein interaction networks. PloS One 20:e112821
Lewis AC, Jones NS, Porter MA, Deane CM (2010) The function of communities in protein interaction networks at multiple scales. BMC Syst Biol 4:100
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Narmadha, D., Pravin, A., Naveen Sundar, G., Premnath Dhanaraj (2020). A Review on Graph Analytics-Based Approaches in Protein-Protein Interaction Network. In: Kumar, L., Jayashree, L., Manimegalai, R. (eds) Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. AISGSC 2019 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-24051-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-24051-6_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24050-9
Online ISBN: 978-3-030-24051-6
eBook Packages: EngineeringEngineering (R0)