Determination of intermediate proteins in the protein-protein interaction network considering common diseases in Moonlighting proteins

Shirafkan, Farshid; Gharaghani, Sajjad

Determination of intermediate proteins in the protein-protein interaction network considering common diseases in Moonlighting proteins

Document Type : Original Research

Authors

Farshid Shirafkan

Sajjad Gharaghani

Laboratory of Bioinformatics and Drug Design, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran,

Abstract

Moonlight proteins are a subset of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Analyzing the interactive networks of proteins in the cell makes it possible to understand how complex processes cause disease. With the help of systems biology, larger and more complex systems can be studied, and the molecular basis of several diseases can be considered. The proteins of the human organism that are moonlight are mostly involved in cancer, anemia, and neurodegeneration. In this work, we created a subnet according to the human PPI network, in which the nodes, the proteins that cause the three selected diseases, and the edges, are the connection of these proteins with each other. We measured the power of the indirect effects of non-disease mediators between the three disease groups and identified key disease-binding intermediate proteins. The results show the relationship between mediator role and centrality and between mediator role and functional properties of these proteins. We have shown that a protein that plays a key indirect mediator between two diseases is not necessarily a hub in the PPI network. Therefore, as hub proteins are considered, intermediate proteins should be considered. We have observed that the mediators between anemia and neurodegeneration diseases are functionally important in the cell. The mediator proteins suggested herein should be experimentally tested as hypothetical disease-related proteins.

Keywords

protein-protein interaction network

Moonlighting proteins

diseases

20.1001.1.23222115.1401.13.2.7.2

Subjects

Bioinformatics

1. Daphne H.E.W. Huberts and Ida J. van der Klei. )2010(. Moonlighting proteins: An intriguing mode of multitasking. Biochimica et Biophysica Acta 1803, page 520{525.
2. C. J. Jeffery. (2018). Intracellular/surface moonlighting proteins. Biochemistry and Molecular Biology.
3. J. Piatigorsky and G. J. Wistow. (1989). Enzyme/crystallins: Gene sharing as an evolutionary strategy. Cell, 57(2):197{199.
4. C. Chen et al. (2018). MoonProt 2.0: An expansion and update of the moonlighting proteins database. Nucleic Acids Res, 46(D1):D640{D644.
5. C. J. Jeffery. (2015). Why study moonlighting proteins? Frontiers in Genetics, 6(JUN).
6. NCBI: Genes and disease. National Library of Medicine (US), NCBI 2007.
7. Kann MG: Protein interactions and disease: computational approaches to
uncover the etiology of diseases. Brief Bioinform 2007, 8:333-346.
8. Ideker T, Sharan R: Protein networks in disease. Genome Res 2008,
18:644-652.
9. Xu J, Li Y: Discovering disease-genes by topological features in human protein-protein interaction network. Bioinformatics 2006, 22:2800-2805.
10. Thanh-Phuong Nguyen, Ferenc Jordán. A quantitative approach to study indirect effects among disease proteins in the human protein interaction network .BMC Systems Biology.
11. Müller CB, Godfray HCJ: Indirect interactions in aphid-parasitoid communities. Research on Population Ecology 1999, 41:93-106.
12. Jordàn F, Liu WC, van Veen FJF: Quantifying the importance of species
and their interactions in a host-parasitoid community. Community Ecology 2003, 4:79-88.
13. Jeong H, Mason SP, Barabàsi AL, Oltvai ZN: Lethality and centrality in protein networks. Nature 2001, 411:41-42.
14. Batada NN, Hurst LD, Tyers M: Evolutionary and physiological importance of hub proteins. PLoS Comput Biol 2006, 2(7):e88.
15. 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.
16. Erickson, R. P., Bodensteiner, J. B. Oro-facial-digital syndrome IX
with severe microcephaly: a new variant in a genetically isolated population. Am. J. Med. Genet. 143A: 3309-3313, 2007.
17. Diogo M Ribeiro et al. (2019). Moondb 2.0: an updated database of extreme multifunctional and moonlighting proteins. Nucleic Acids Research, 47(D1):D398{D402.
18. Uhrigshardt H., Singh A., Kovtunovych G., Ghosh M., Rouault T.A.Characterization of the human HSC20, an unusual DnaJ type III protein, involved in iron-sulfur cluster biogenesis. Hum Mol Genet.2010.
19. Ki Soon Kim, Nunziata Maio, Anamika Singh, Tracey A Rouault. Cytosolic HSC20 integrates de novo iron-sulfur cluster biogenesis with the CIAO1-mediated transfer to recipients. Hum Mol Genet.2018.
20. Ostedgaard L.S., Baldursson O., Vermeer D.W., Welsh M.J., Robertson A.D. A functional R domain from cystic fibrosis transmembrane conductance regulator is predominantly unstructured in solution.
21. Nauseef W.M., McCormick S.J., Clark R.A. .Calreticulin functions as a molecular chaperone in the biosynthesis of myeloperoxidase.
22. Shirafkan, F., Gharaghani, S., Rahimian, K. et al. Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods. BMC Bioinformatics 22, 261 (2021).
23. do Valle, I.F., Roweth, H.G., Malloy, M.W. et al. Network medicine framework shows that proximity of polyphenol targets and disease proteins predicts therapeutic effects of polyphenols. Nat Food 2, 143–155 (2021).