Abstract
Fumarate adduction to cysteines has been implicated in the pathogenesis of several disorders. Its role, however, still remains elusive, and the need of predictive methods has not yet been met. The reactivity of cysteines found in fumarate-sensitive proteins was predicted when the collected data for eight network-type features were analyzed using classification models. Therefore, methods for evaluating the likelihood of a cysteine site to be modified by fumarate could be developed by combining concepts of network theory and machine learning.
This is a preview of subscription content, log in via an institution to check access.
Abbreviations
- 2SC:
-
S-(2-succino)cysteine
- C :
-
Clustering coefficient
- Cb :
-
Betweenness centrality
- Cc :
-
Closeness centrality
- Cs :
-
Stress centrality
- E :
-
Eccentricity
- k :
-
Degree
- L :
-
Shortest path length
- MC:
-
Modifiable cysteine
- NC:
-
Neighborhood connectivity
- NMC:
-
Non-modifiable cysteine
- PDB:
-
Protein Data Bank
- PMENP :
-
Partner of multi-edged node pairs
- PTM:
-
Post-translational modification
- R :
-
Radiality
- RIN:
-
Residue interaction network
- AUROC:
-
Area under the receiver operating characteristic curve
- T :
-
Topological coefficient
References
Adam J, Hatipoglu E, O’Flaherty L, Ternette N, Sahgal N, Lockstone H, Baban D, Nye E, Stamp GW, Wolhuter K, Stevens M, Fischer R, Carmeliet P, Maxwell PH, Pugh CW, Frizzell N, Soga T, Kessler BM, El-Bahrawy M, Ratcliffe PJ, Pollard PJ (2011) Renal cyst formation in Fh1-deficient mice is independent of the Hif/Phd pathway: roles for fumarate in KEAP1 succination and Nrf2 signaling. Cancer Cell 20:524–537. https://doi.org/10.1016/j.ccr.2011.09.006
Adam J, Ramracheya R, Chibalina MV, Ternette N, Hamilton A, Tarasov AI, Zhang Q, Rebelato E, Rorsman NJG, Martín-Del-Río R, Lewis A, Özkan G, Do HW, Spégel P, Saitoh K, Kato K, Igarashi K, Kessler BM, Pugh CW, Tamarit-Rodriguez J, Mulder H, Clark A, Frizzell N, Soga T, Ashcroft FM, Silver A, Pollard PJ, Rorsman P (2017) Fumarate hydratase deletion in pancreatic β cells leads to progressive diabetes. Cell Rep 20:3135–3148. https://doi.org/10.1016/j.celrep.2017.08.093
Alderson NL, Wang Y, Blatnik M, Frizzell N, Walla MD, Lyons TJ, Alt N, Carson JA, Nagai R, Thorpe SR, Baynes JW (2006) S-(2-Succinyl)cysteine: a novel chemical modification of tissue proteins by a Krebs cycle intermediate. Arch Biochem Biophys 450:1–8
Bagler G, Sinha S (2005) Network properties of protein structures. Phys A 346:27–33
Bhattacharyya M, Ghosh S, Vishveshwara S (2016) Protein structure and function: looking through the network of side-chain interactions. Curr Protein Pept Sci 17:4–25
Blagus R, Lusa L (2013) SMOTE for high-dimensional class-imbalanced data. BMC Bioinf 14:106. https://doi.org/10.1186/1471-2105-14-106
Blatnik M, Frizzell N, Thorpe SR, Baynes JW (2008) Inactivation of glyceraldehyde-3-phosphate dehydrogenase by fumarate in diabetes: formation of S-(2-succinyl)cysteine, a novel chemical modification of protein and possible biomarker of mitochondrial stress. Diabetes 57:41–49
Csermely P, Nussinov R, Szilágyi A (2013) From allosteric drugs to allo-network drugs: state of the art and trends of design, synthesis and computational methods. Curr Top Med Chem 13:2–4
Di Paola L, Giuliani A (2015) Protein contact network topology: a natural language for allostery. Curr Opin Struct Biol 31:43–48. https://doi.org/10.1016/j.sbi.2015.03.001
Doncheva NT, Assenov Y, Domingues FS, Albrecht M (2012) Topological analysis and interactive visualization of biological networks and protein structures. Nat Protoc 7:670–685. https://doi.org/10.1038/nprot.2012.004
Fanelli F, Felline A, Raimondi F, Seeber M (2016) Structure network analysis to gain insights into GPCR function. Biochem Soc Trans 44:613–618. https://doi.org/10.1042/BST20150283
Frizzell N, Rajesh M, Jepson MJ, Nagai R, Carson JA, Thorpe SR, Baynes JW (2009) Succination of thiol groups in adipose tissue proteins in diabetes: succination inhibits polymerization and secretion of adiponectin. J Biol Chem 284:25772–25781. https://doi.org/10.1074/jbc.M109.019257
Frizzell N, Thomas SA, Carson JA, Baynes JW (2012) Mitochondrial stress causes increased succination of proteins in adipocytes in response to glucotoxicity. Biochem J 445:247–254. https://doi.org/10.1042/BJ20112142
Giollo M, Martin AJ, Walsh I, Ferrari C, Tosatto SC (2014) NeMO: a method using residue interaction networks to improve prediction of protein stability upon mutation. BMC Genom 15:S7. https://doi.org/10.1186/1471-2164-15-S4-S7
Kuhn M, Johnson K (2013) Applied predictive modelling. Springer, New York
Leichert LI, Dick TP (2015) Incidence and physiological relevance of protein thiol switches. Biol Chem 396:389–399. https://doi.org/10.1515/hsz-2014-0314
Manuel AM, Frizzell N (2013) Adipocyte protein modification by Krebs cycle intermediates and fumarate ester-derived succination. Amino Acids 45:1243–1247. https://doi.org/10.1007/s00726-013-1568-z
Manuel AM, Walla MD, Faccenda A, Martin SL, Tanis RM, Piroli GG, Adam J, Kantor B, Mutus B, Townsend DM, Frizzell N (2017) Succination of protein disulphide isomerase links mitochondrial stress and endoplasmic reticulum stress in the adipocyte during diabetes. Antioxid Redox Signal 27:1281–1296. https://doi.org/10.1089/ars.2016.6853
Marino SM, Gladyshev VN (2012) Analysis and functional prediction of reactive cysteine residues. J Biol Chem 287:4419–4425. https://doi.org/10.1074/jbc.R111.275578
Merkley ED, Metz TO, Smith RD, Baynes JW, Frizzell N (2014) The succinated proteome. Mass Spectrom Rev 33:98–109. https://doi.org/10.1002/mas.21382
Miglio G, Sabatino AD, Veglia E, Giraudo MT, Beccuti M, Cordero F (2016) A computational analysis of S-(2-succino)cysteine sites in proteins. Biochim Biophys Acta 1864:211–218. https://doi.org/10.1016/j.bbapap.2015.11.003
Nagai R, Brock JW, Blatnik M, Baatz JE, Bethard J, Walla MD, Thorpe SR, Baynes JW, Frizzell N (2007) Succination of protein thiols during adipocyte maturation: a biomarker of mitochondrial stress. J Biol Chem 282:34219–34228
Piroli GG, Manuel AM, Walla MD, Jepson MJ, Brock JW, Rajesh MP, Tanis RM, Cotham WE, Frizzell N (2014) Identification of protein succination as a novel modification of tubulin. Biochem J 462:231–245. https://doi.org/10.1042/BJ20131581
Piroli GG, Manuel AM, Clapper AC, Walla MD, Baatz JE, Palmiter RD, Quintana A, Frizzell N (2016) Succination is increased on select proteins in the brainstem of the NADH dehydrogenase (ubiquinone) Fe-S protein 4 (Ndufs4) knockout mouse, a model of Leigh syndrome. Mol Cell Proteom 15:445–461. https://doi.org/10.1074/mcp.M115.051516
Salamanca Viloria J, Allega MF, Lambrughi M, Papaleo E (2017) An optimal distance cutoff for contact-based Protein Structure Networks using side-chain centers of mass. Sci Rep 7(1):2838. https://doi.org/10.1038/s41598-017-01498-6
Ternette N, Yang M, Laroyia M, Kitagawa M, O’Flaherty L, Wolhulter K, Igarashi K, Saito K, Kato K, Fischer R, Berquand A, Kessler BM, Lappin T, Frizzell N, Soga T, Adam J, Pollard PJ (2013) Inhibition of mitochondrial aconitase by succination in fumarate hydratase deficiency. Cell Rep 3:689–700. https://doi.org/10.1016/j.celrep.2013.02.013
Thomas SA, Storey KB, Baynes JW, Frizzell N (2012) Tissue distribution of S-(2-succino)cysteine (2SC), a biomarker of mitochondrial stress in obesity and diabetes. Obesity (Silver Spring) 20:263–269. https://doi.org/10.1038/oby.2011.340
Vendruscolo M, Dokholyan NV, Paci E, Karplus M (2002) Small-world view of the amino acids that play a key role in protein folding. Phys Rev E Stat Nonlin Soft Matter Phys 65:061910
Yang M, Ternette N, Su H, Dabiri R, Kessler BM, Adam J, Teh BT, Pollard PJ (2014) The succinated proteome of FH-mutant tumours. Metabolites 4:640–654. https://doi.org/10.3390/metabo4030640
Acknowledgements
Dr Francesca Damiano and Dr Carlotta Corgiat Loia (Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino) are gratefully acknowledged for their support in the method implementation. This work was supported by funding of the Università degli Studi di Torino, Ricerca Locale Ex 60% 2015 and 2016–2017 to GM.
Funding
GM has received research grants from the Università degli Studi di Torino, Ricerca Locale Ex 60% 2015 and 2016–2017.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that he has no conflict of interest.
Research involving human participants and/or animals
This article does not contain any studies with human participants or animals performed by the author.
Informed consent
It is not applicable.
Additional information
Handling Editor: P. R. Jungblut.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Miglio, G. Analysis of fumarate-sensitive proteins and sites by exploiting residue interaction networks. Amino Acids 50, 647–652 (2018). https://doi.org/10.1007/s00726-018-2548-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00726-018-2548-0