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Protein–Protein Interface and Disease: Perspective from Biomolecular Networks

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Network Biology

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 160))

Abstract

Protein–protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein–protein interactions. Characterizing protein–protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein–protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.

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References

  1. Gonzalez MW, Kann MG (2012) Chapter 4: protein interactions and disease. PLoS Comput Biol 8(12):11

    Article  Google Scholar 

  2. Kann MG (2007) Protein interactions and disease: computational approaches to uncover the etiology of diseases. Brief Bioinform 8(5):333–346

    Article  CAS  Google Scholar 

  3. Pitre S, Alamgir M, Green JR, Dumontier M, Dehne F, Golshani A (2008) Computational methods for predicting protein-protein interactions. Adv Biochem Eng Biotechnol 110:247–267

    CAS  Google Scholar 

  4. Cavga AD, Karahan N, Keskin O, Gursoy A (2015) Taming oncogenic signaling at protein interfaces: challenges and opportunities. Curr Top Med Chem 15(20):2005–2018

    Article  CAS  Google Scholar 

  5. Nero TL, Morton CJ, Holien JK, Wielens J, Parker MW (2014) Oncogenic protein interfaces: small molecules, big challenges. Nat Rev Cancer 14(4):248–262

    Article  CAS  Google Scholar 

  6. Nussinov R, Tsai CJ (2013) Allostery in disease and in drug discovery. Cell 153(2):293–305

    Article  CAS  Google Scholar 

  7. Persico M, Di Dato A, Orteca N, Fattorusso C, Novellino E, Andreoli M, Ferlini C (2015) From protein communication to drug discovery. Curr Top Med Chem 15(20):2019–2031

    Article  CAS  Google Scholar 

  8. Engin HB, Keskin O, Nussinov R, Gursoy A (2012) A strategy based on protein-protein interface motifs may help in identifying drug off-targets. J Chem Inf Model 52(8):2273–2286

    Article  CAS  Google Scholar 

  9. Lesieur C (2014) The assembly of protein oligomers — old stories and new perspectives with graph theory. In: DCL: INTECH (ed) Oligomerization of chemical and biological compounds. doi:10.5772/58576

    Google Scholar 

  10. Fernandez-Recio J (2011) Prediction of protein binding sites and hot spots. Wiley Interdiscip Rev Comput Mol Sci 1(5):680–698

    Article  CAS  Google Scholar 

  11. Zen A, Micheletti C, Keskin O, Nussinov R (2010) Comparing interfacial dynamics in protein-protein complexes: an elastic network approach. BMC Struct Biol 10:13

    Article  Google Scholar 

  12. Ulucan O, Eyrisch S, Helms V (2012) Druggability of dynamic protein-protein interfaces. Curr Pharm Des 18(30):4599–4606

    Article  CAS  Google Scholar 

  13. Lin JJ, Lin ZL, Hwang JK, Huang TT (2015) On the packing density of the unbound protein-protein interaction interface and its implications in dynamics. BMC Bioinformatics 16(Suppl 1):S7

    Google Scholar 

  14. Cukuroglu E, Engin HB, Gursoy A, Keskin O (2014) Hot spots in protein-protein interfaces: towards drug discovery. Prog Biophys Mol Biol 116(2-3):165–173

    Article  CAS  Google Scholar 

  15. David A, Razali R, Wass MN, Sternberg MJE (2012) Protein-protein interaction sites are hot spots for disease-associated nonsynonymous SNPs. Hum Mutat 33(2):359–363

    Article  CAS  Google Scholar 

  16. Kar G, Gursoy A, Keskin O (2009) Human cancer protein-protein interaction network: a structural perspective. PLoS Comput Biol 5(12):e1000601

    Google Scholar 

  17. Brinda KV, Vishveshwara S (2005) A network representation of protein structures: implications for protein stability. Biophys J 89(6):4159–4170

    Article  CAS  Google Scholar 

  18. Bode C, Kovacs IA, Szalay MS, Palotai R, Korcsmaros T, Csermely P (2007) Network analysis of protein dynamics. FEBS Lett 581(15):2776–2782

    Article  Google Scholar 

  19. Doncheva NT, Assenov Y, Domingues FS, Albrecht M (2012) Topological analysis and interactive visualization of biological networks and protein structures. Nat Protoc 7(4):670–685

    Article  CAS  Google Scholar 

  20. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442

    Article  CAS  Google Scholar 

  21. del Sol A, O’Meara P (2005) Small-world network approach to identify key residues in protein-protein interaction. Proteins Struct Funct Bioinf 58(3):672–682

    Article  Google Scholar 

  22. Amitai G, Shemesh A, Sitbon E, Shklar M, Netanely D, Venger I, Pietrokovski S (2004) Network analysis of protein structures identifies functional residues. J Mol Biol 344(4):1135–1146

    Article  CAS  Google Scholar 

  23. Yan WY, Zhou JH, Sun MM, Chen JJ, Hu G, Shen BR (2014) The construction of an amino acid network for understanding protein structure and function. Amino Acids 46(6):1419–1439

    Article  CAS  Google Scholar 

  24. Vuillon L, Lesieur C (2015) From local to global changes in proteins: a network view. Curr Opin Struct Biol 31:1–8

    Article  CAS  Google Scholar 

  25. Di Paola L, Giuliani A (2015) Protein contact network topology: a natural language for allostery. Curr Opin Struct Biol 31:43–48

    Article  Google Scholar 

  26. Viswanathan K, Shriver Z, Babcock GJ (2015) Amino acid interaction networks provide a new lens for therapeutic antibody discovery and anti-viral drug optimization. Curr Opin Virol 11:122–129

    Article  CAS  Google Scholar 

  27. Csermely P, Korcsmaros T, Kiss HJ, London G, Nussinov R (2013) Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol Ther 138(3):333–408

    Article  CAS  Google Scholar 

  28. Liang Z, Hu G (2016) Protein structure network-based drug design. Mini Rev Med Chem 16(16):1330–1343

    Google Scholar 

  29. Zhang XW, Perica T, Teichmann SA (2013) Evolution of protein structures and interactions from the perspective of residue contact networks. Curr Opin Struct Biol 23(6):954–963

    Article  CAS  Google Scholar 

  30. Sethi A, Eargle J, Black AA, Luthey-Schulten Z (2009) Dynamical networks in tRNA: protein complexes. Proc Natl Acad Sci U S A 106(16):6620–6625

    Article  CAS  Google Scholar 

  31. Sathyapriya R, Vijayabaskar MS, Vishveshwara S (2008) Insights into protein-DNA interactions through structure network analysis. PLoS Comput Biol 4(9):e1000170

    Google Scholar 

  32. Doncheva NT, Klein K, Domingues FS, Albrecht M (2011) Analyzing and visualizing residue networks of protein structures. Trends Biochem Sci 36(4):179–182

    Article  CAS  Google Scholar 

  33. Reichmann D, Rahat O, Albeck S, Meged R, Dym O, Schreiber G (2005) The modular architecture of protein-protein binding interfaces. Proc Natl Acad Sci U S A 102(1):57–62

    Article  CAS  Google Scholar 

  34. Hayden EY, Teplow DB (2013) Amyloid beta-protein oligomers and Alzheimer’s disease. Alzheimers Res Ther 5(6):60

    Google Scholar 

  35. Gabizon R, Friedler A (2014) Allosteric modulation of protein oligomerization: an emerging approach to drug design. Front Chem 2:9

    Article  Google Scholar 

  36. Cherezov V, Rosenbaum DM, Hanson MA, Rasmussen SGF, Thian FS, Kobilka TS, Choi HJ, Kuhn P, Weis WI, Kobilka BK et al (2007) High-resolution crystal structure of an engineered human beta(2)-adrenergic G protein-coupled receptor. Science 318(5854):1258–1265

    Article  CAS  Google Scholar 

  37. Mariani S, Dell’Orco D, Felline A, Raimondi F, Fanelli F (2013) Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases. PLoS Comput Biol 9(8):14

    Article  Google Scholar 

  38. Raimondi F, Felline A, Portella G, Orozco M, Fanelli F (2013) Light on the structural communication in Ras GTPases. J Biomol Struct Dyn 31(2):142–157

    Article  CAS  Google Scholar 

  39. Hu G, Michielssens S, Moors SLC, Ceulemans A (2011) Normal mode analysis of Trp RNA binding attenuation protein: structure and collective motions. J Chem Inf Model 51(9):2361–2371

    Article  CAS  Google Scholar 

  40. Zhao H, Lo YH, Ma L, Waltz SE, Gray JK, Hung MC, Wang SC (2011) Targeting tyrosine phosphorylation of PCNA inhibits prostate cancer growth. Mol Cancer Ther 10(1):29–36

    Article  CAS  Google Scholar 

  41. Zhao H, Chen MS, Lo YH, Waltz SE, Wang J, Ho PC, Vasiliauskas J, Plattner R, Wang YL, Wang SC (2014) The Ron receptor tyrosine kinase activates c-Abl to promote cell proliferation through tyrosine phosphorylation of PCNA in breast cancer. Oncogene 33(11):1429–1437

    Article  CAS  Google Scholar 

  42. Chapman E, Fry AN, Kang MJ (2011) The complexities of p97 function in health and disease. Mol Biosyst 7(3):700–710

    Article  CAS  Google Scholar 

  43. Ranford JC, Henderson B (2002) Chaperonins in disease: mechanisms, models, and treatments. J Clin Pathol Mol Pathol 55(4):209–213

    Article  CAS  Google Scholar 

  44. Malecka KA, Ho WC, Marmorstein R (2009) Crystal structure of a p53 core tetramer bound to DNA. Oncogene 28(3):325–333

    Article  CAS  Google Scholar 

  45. Tuncbag N, Kar G, Gursoy A, Keskin O, Nussinov R (2009) Towards inferring time dimensionality in protein-protein interaction networks by integrating structures: the p53 example. Mol Biosyst 5(12):1770–1778

    Article  CAS  Google Scholar 

  46. Ali MMU, Roe SM, Vaughan CK, Meyer P, Panaretou B, Piper PW, Prodromou C, Pearl LH (2006) Crystal structure of an Hsp90-nucleotide-p23/Sba1 closed chaperone complex. Nature 440(7087):1013–1017

    Article  CAS  Google Scholar 

  47. Verkhivker GM (2014) Computational studies of allosteric regulation in the Hsp90 molecular chaperone: from functional dynamics and protein structure networks to allosteric communications and targeted anti-cancer modulators. Isr J Chem 54(8-9):1052–1064

    Article  CAS  Google Scholar 

  48. Ma BY, Nussinov R (2014) Druggable orthosteric and allosteric hot spots to target protein-protein interactions. Curr Pharm Des 20(8):1293–1301

    Article  CAS  Google Scholar 

  49. Kanna N, Vishveshwara S (1999) Identification of side-chain clusters in protein structures by a graph spectral method. J Mol Biol 292(2):441–464

    Article  Google Scholar 

  50. Kannan N, Chander P, Ghosh P, Vishveshwara S, Chatterji D (2001) Stabilizing interactions in the dimer interface of alpha-subunit in Escherichia coli RNA polymerase: a graph spectral and point mutation study. Protein Sci 10(1):46–54

    Article  CAS  Google Scholar 

  51. Brinda KV, Kannan N, Vishveshwara S (2002) Analysis of homodimeric protein interfaces by graph-spectral methods. Protein Eng 15(4):265–277

    Article  CAS  Google Scholar 

  52. Brinda KV, Mitra N, Surolia A, Vishveshwara S (2004) Determinants of quaternary association in legume lectins. Protein Sci 13(7):1735–1749

    Article  CAS  Google Scholar 

  53. Brinda KV, Surolia A, Vishveshwara S (2005) Insights into the quaternary association of proteins through structure graphs: a case study of lectins. Biochem J 391:1–15

    Article  CAS  Google Scholar 

  54. Brinda KV, Vishveshwara S (2005) Oligomeric protein structure networks: insights into protein-protein interactions. BMC Bioinformatics 6

    Google Scholar 

  55. del Sol A, Fujihashi H, O’Meara P (2005) Topology of small-world networks of protein-protein complex structures. Bioinformatics 21(8):1311–1315

    Article  Google Scholar 

  56. Tuncbag N, Salman FS, Keskin O, Gursoy A (2010) Analysis and network representation of hotspots in protein interfaces using minimum cut trees. Proteins Struct Funct Bioinf 78(10):2283–2294

    Article  CAS  Google Scholar 

  57. Calvo B, Santana R, Bielza C, Galdiano J, Inza I, Lozano JA, Armananza R, Santafe G, Perez A, Robles V (2006) Machine learning in bioinformatics. Brief Bioinform 7(1):86–112

    Article  Google Scholar 

  58. Ye L, Kuang QF, Jiang L, Luo JS, Jiang YP, Ding ZL, Li YZ, Li ML (2014) Prediction of hot spots residues in protein-protein interface using network feature and microenvironment feature. Chemom Intell Lab Syst 131:16–21

    Article  CAS  Google Scholar 

  59. Feverati G, Lesieur C (2010) Oligomeric interfaces under the lens: gemini. PLoS One 5(3):15

    Article  Google Scholar 

  60. Feverati G, Achoch M, Zrimi J, Vuillon L, Lesieur C (2012) Beta-strand interfaces of non-dimeric protein oligomers are characterized by scattered charged residue patterns. PLoS One 7(4):e32558

    Google Scholar 

  61. Feverati G, Achoch M, Vuillon L, Lesieur C (2014) Intermolecular beta-strand networks avoid hub residues and favor low interconnectedness: a potential protection mechanism against chain dissociation upon mutation. PLoS One 9(4):e94745

    Google Scholar 

  62. Yan WY, Sun MM, Hu G, Zhou JH, Zhang WY, Chen JJ, Chen B, Shen BR (2014) Amino acid contact energy networks impact protein structure and evolution. J Theor Biol 355:95–104

    Article  CAS  Google Scholar 

  63. Yan WY, Hu G, Shen BR (2016) Network analysis of protein structures: the comparison of three topologies. Curr Bioinformatics 11(4):480–489. doi:10.2174/1574893611666160602124707

    Google Scholar 

  64. Feher VA, Durrant JD, Van Wart AT, Amaro RE (2014) Computational approaches to mapping allosteric pathways. Curr Opin Struct Biol 25:98–103

    Article  CAS  Google Scholar 

  65. Fanelli F, Felline A, Raimondi F (2013) Network analysis to uncover the structural communication in GPCRs. In: Receptor-receptor interactions, vol 117. pp 43–61

    Google Scholar 

  66. Fanelli F, Felline A (2011) Dimerization and ligand binding affect the structure network of A(2A) adenosine receptor. Biochim Biophys Acta 1808(5):1256–1266

    Article  CAS  Google Scholar 

  67. Fanelli F, Mauri M, Capra V, Raimondi F, Guzzi F, Ambrosio M, Rovati G, Parenti M (2011) Light on the structure of thromboxane A(2) receptor heterodimers. Cell Mol Life Sci 68(18):3109–3120

    Article  CAS  Google Scholar 

  68. Fanelli F, Seeber M, Felline A, Casciari D, Raimondi F (2013) Quaternary structure predictions and structural communication features of GPCR dimers. In: Oligomerization in health and disease, vol 117. pp 105–142

    Google Scholar 

  69. Nichols SE, Hernandez CX, Wang Y, McCammon JA (2013) Structure-based network analysis of an evolved G protein-coupled receptor homodimer interface. Protein Sci 22(6):745–754

    Article  CAS  Google Scholar 

  70. Blacklock K, Verkhivker GM (2013) Experimentally guided structural modeling and dynamics analysis of Hsp90-p53 interactions: allosteric regulation of the Hsp90 chaperone by a client protein. J Chem Inf Model 53(11):2962–2978

    Article  CAS  Google Scholar 

  71. Blacklock K, Verkhivker GM (2014) Allosteric regulation of the Hsp90 dynamics and stability by client recruiter cochaperones: protein structure network modeling. PLoS One 9(1):e86547

    Google Scholar 

  72. Blacklock K, Verkhivker GM (2014) Computational modeling of allosteric regulation in the Hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications. PLoS Comput Biol 10(6):e1003679

    Google Scholar 

  73. Tse A, Verkhivker GM (2015) Molecular dynamics simulations and structural network analysis of c-Abl and c-Src kinase core proteins: capturing allosteric mechanisms and communication pathways from residue centrality. J Chem Inf Model 55(8):1645–1662

    Article  CAS  Google Scholar 

  74. Martin AJM, Vidotto M, Boscariol F, Di Domenico T, Walsh I, Tosatto SCE (2011) RING: networking interacting residues, evolutionary information and energetics in protein structures. Bioinformatics 27(14):2003–2005

    Article  CAS  Google Scholar 

  75. Hu G, Yan WY, Zhou JH, Shen BR (2014) Residue interaction network analysis of Dronpa and a DNA clamp. J Theor Biol 348:55–64

    Article  CAS  Google Scholar 

  76. Kar G, Kuzu G, Keskin O, Gursoy A (2012) Protein-protein interfaces integrated into interaction networks: implications on drug design. Curr Pharm Des 18(30):4697–4705

    Article  CAS  Google Scholar 

  77. Aloy P, Russell RB (2006) Structural systems biology: modelling protein interactions. Nat Rev Mol Cell Biol 7(3):188–197

    Article  CAS  Google Scholar 

  78. Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Lin J, Minguez P, Bork P, von Mering C et al (2013) STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41(Database issue):D808–D815

    Article  CAS  Google Scholar 

  79. Li Y, Vongsangnak W, Chen L, Shen B (2014) Integrative analysis reveals disease-associated genes and biomarkers for prostate cancer progression. BMC Med Genomics 7(Suppl 1):S3

    Google Scholar 

  80. Ogmen U, Keskin O, Aytuna AS, Nussinov R, Gursoy A (2005) PRISM: protein interactions by structural matching. Nucleic Acids Res 33:W331–W336

    Article  CAS  Google Scholar 

  81. Cukuroglu E, Gursoy A, Nussinov R, Keskin O (2014) Non-redundant unique interface structures as templates for modeling protein interactions. PLoS One 9(1):e86738

    Google Scholar 

  82. Baspinar A, Cukuroglu E, Nussinov R, Keskin O, Gursoy A (2014) PRISM: a web server and repository for prediction of protein-protein interactions and modeling their 3D complexes. Nucleic Acids Res 42(W1):W285–W289

    Article  CAS  Google Scholar 

  83. Zhang QC, Petrey D, Deng L, Qiang L, Shi Y, Thu CA, Bisikirska B, Lefebvre C, Accili D, Hunter T et al (2012) Structure-based prediction of protein-protein interactions on a genome-wide scale. Nature 490(7421):556–560

    Google Scholar 

  84. Bahar I, Cheng MH, Lee JY, Kaya C, Zhang S (2015) Structure-encoded global motions and their role in mediating protein-substrate interactions. Biophys J 109(6):1101–1109

    Article  CAS  Google Scholar 

  85. Hwang YC, Lin CF, Valladares O, Malamon J, Kuksa PP, Zheng Q, Gregory BD, Wang LS (2015) HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements. Bioinformatics 31(8):1290–1292

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (21203131, 31200989, and 61401068), the Natural Science Foundation of the Jiangsu Higher Education Institutions (12KJB180014), and the China Postdoctoral Science Foundation (2016M590495), Preproposal Research Fund (PRF4/2558 and PRF-PII/59), Faculty of Science, Kasetsart University.

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Authors and Affiliations

  1. Center for Systems Biology, School of Electronic and Information Engineering, Soochow University, Suzhou, 215006, China

    Guang Hu & Yuan Li

  2. School of Basic Medicine and Biological Sciences, Medical College of Soochow University, Suzhou, 215123, China

    Fei Xiao

  3. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Yuqian Li

  4. Department of Zoology, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand

    Wanwipa Vongsangnak

  5. Computational Biomodelling Laboratory for Agricultural Science and Technology (CBLAST), Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand

    Wanwipa Vongsangnak

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  1. Guang Hu
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  2. Fei Xiao
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  3. Yuqian Li
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  4. Yuan Li
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  5. Wanwipa Vongsangnak
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Correspondence to Guang Hu or Wanwipa Vongsangnak .

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  1. Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Science, Little Rock, Arkansas, USA

    Intawat Nookaew

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Hu, G., Xiao, F., Li, Y., Li, Y., Vongsangnak, W. (2016). Protein–Protein Interface and Disease: Perspective from Biomolecular Networks. In: Nookaew, I. (eds) Network Biology. Advances in Biochemical Engineering/Biotechnology, vol 160. Springer, Cham. https://doi.org/10.1007/10_2016_40

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