Modeling proteins as residue interaction networks

Protein and Peptide Letters

Volumn 22, Issue 10, 2015, Pages 923-933

  Grewal, Rajdeep K ^a   Roy, Soumen ^a  

^a BOSE INSTITUTE   (India)

Author keywords

Allostery; Amino acid residues; Graph theory; Protein contact networks; Protein folding; Residue interaction networks

Indexed keywords

TRANSFER RNA; PROTEIN;

ALLOSTERISM; AMINO ACID RESIDUE INTERACTION NETWORK; ARTICLE; CAENORHABDITIS ELEGANS; CRYSTAL STRUCTURE; ENERGY TRANSFER; GENE CONSTRUCT; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; HYDROPHOBICITY; LIGAND BINDING; MOLECULAR DYNAMICS; NONHUMAN; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PROTEIN CONFORMATION; PROTEIN CONTACT NETWORK; PROTEIN FOLDING; PROTEIN FUNCTION; PROTEIN INTERACTION; PROTEIN LOCALIZATION; RESIDUE CONTACT NETWORK; SIGNAL TRANSDUCTION; STATIC ELECTRICITY; X RAY CRYSTALLOGRAPHY; ANIMAL; CHEMISTRY; GENETICS; HUMAN; METABOLISM; PHYSIOLOGY;

ALLOSTERIC REGULATION; ANIMALS; HUMANS; PROTEIN FOLDING; PROTEINS;

EID: 84940844734     PISSN: 09298665     EISSN: 18755305     Source Type: Journal    
DOI: 10.2174/0929866522666150728115552     Document Type: Article

References (81)

1. Albert, R.; Barabási, A.L. Statistical mechanics of complex networks. Rev. Mod. Phys., 2002, 74, 47-97.
2. Newman, M.E.J. Networks: An Introduction; Oxford University Press: Oxford, UK, 2010.
3. Barabási, A.L.; Oltvai, Z.N. Network biology: understanding the cell's functional organization. Nat. Rev. Genet., 2004, 5, 101-113.
4. Girvan, M.; Newman, M.E.J. Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA, 2002, 99, 7821- 7826.
5. Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z.N.; Barabasi, A.L. The large-scale organization of metabolic network. Nature, 2000, 407, 651-654.
6. Filkov, V.; Saul, Z.M.; Roy, S.; D'Souza, R.M.; Devanbu, P.T. Modeling and verifying a broad array of network properties. Europhys. Lett., 2009, 86, 28003.
7. Roy, S.; Filkov, V. Strong associations between microbe phenotypes and their network architecture. Phys. Rev. E., 2009, 80, 040902 (R).
8. Dandekar, A.M.; Martinelli, F.; Davis, C.E.; Bhushan, A.; Zhao, W.; Fiehn, O.; Skogerson, K.; Wohlgemuth, G.; D'Souza, R.; Roy, S.; Reagan, R.L.; Lin, D.; Cary, R.; Pardington, P.; Gupta, G. Analysis of early host responses for asymptomatic disease detection and management of specialty crops. Crit. Rev. Immunol., 2010, 30, 277-289.
9. Di Paola, L.; De Ruvo, M.; Paci, P.; Santoni, D., Giuliani, A. Protein Contact Networks: An Emerging Paradigm in Chemistry. Chem. Revs., 2013, 113, 1598-1613.
10. Roy, S. Systems biology beyond degree, hubs and scale-free networks: The case for multiple metrics in complex networks. Syst. Synth. Biol., 2012, 6, 31-34.
11. Barabasi, A.L; Albert, R. Emergence of scaling in random networks. Science, 1999, 286, 509-512.
12. Watts, D.; Strogatz, S.H. Collective dynamics of 'small-world' networks. Nature, 1998, 393, 440-442.
13. Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A. The architecture of complex weighted networks. Proc. Natl. Acad. Sci. U.S.A, 2004, 101, 3747.
14. Bagler, G.; Sinha, S. Assortative mixing in Protein Contact Networks and protein folding kinetics. Bioinformatics, 2007, 23(14), 1760-1767.
15. Gromiha, M.M.; Selvaraj, S. Comparison between long-range interactions and contact order in determining the folding rate of two-state proteins: Application of long-range order to folding rate prediction. J. Mol. Biol., 2001, 310, 27-32.
16. Vendruscolo, M.; Dokholyan, N.V.; Paci, E.; Karplus, M. Smallworld view of the amino acids that play a key role in protein folding. Phys. Rev. E, 2002, 65, 061910.
17. Brinda, K.V.; Vishveshwara, S. A network representation of protein structures: implications for protein stability. Biophys. J., 2005, 89, 4159-4170.
18. Greene, L.H.; Higman, V.A. Uncovering network systems within protein structures. J. Mol. Biol., 2003, 334, 781-791.
19. Chennubhotla, C.; Bahar, I. Markov propagation of allosteric effects in biomolecular systems: Application to GroEL-GroES. Mol. Syst. Bio., 2006, 2, 36.
20. Tinoco, I.; Sauer, K.; Wang, J.C.: Physical chemistry: Principles and application in biological sciences. New Jersey: Prentice-Hall Englewood Cliffs; 2001.
21. Aftabuddin, M.d.; Kundu, S. Hydrophobic, hydrophilic, and charged amino acid networks within protein. Biophys. J., 2007, 9, 225-231.
22. Park, K.; Kim, D. Modeling allosteric signal propagation using protein structure networks. BMC Bioinformatics, 2011, 12, 1471- 2105.
23. Kannan, N.; Vishveshwara, S. Identification of side-chain clusters in protein structures by a graph spectral method. J. Mol. Biol., 1999, 292, 441-464.
24. Bhattacharyya, M.; Vishveshwara, S. Probing the allosteric mechanism in pyrrolysyl-tRNA synthetase using energy-weighted network formalism. Biochemistry, 2011, 50, 6225-6236.
25. Vijayabaskar, M.S.; Vishveshwara, S. Interaction energy based protein structure networks. Biophys. J., 2010, 99, 3704-3715.
26. Bhattacharyya, M.; Ghosh, A.; Hansia, P.; Vishveshwara, S. Allostery and conformational free energy changes in human tryptophanyl- TRNA synthetase from essential dynamics and structure networks. Proteins, 2010, 7, 506-517.
27. Blacklock, K.; Verkhivker, G.M.; Computational modeling of allosteric regulation in the hsp90 chaperones: A statistical ensemble analysis of protein structure networks and allosteric communications. PLoS Comput. Biol., 2014, 10(6), e1003679.
28. Ghosh, A.; Vishveshwara, S. A study of communication pathways in methionyl- TRNA synthetase by molecular dynamics simulations and structure network analysis. Proc. Natl. Acad. Sci. USA, 2007, 104 (40), 15711-15716.
29. Sethi, A.; Eargle, J.; Black, A.; Schulten, Z.L. Dynamical networks in tRNA:protein complexes. Proc. Natl. Acad. Sci. USA, 2009, 106(16), 6620-6625.
30. Brandes, U. A faster algorithm for betweenness centrality. J. Math. Sociol., 2001, 25, 163-177.
31. Banerjee, S.J.; Sinha, S.; Roy, S. Slow poisoning and destruction of networks: Edge proximity and its implications for biological and infrastructure networks. Phys. Rev. E, 2015, 91, 022807.
32. Newman, M.E.J. Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA, 2006, 103(23), 8577-8696.
33. Sengupta, D.; Kundu, S. Role of long- And short-range hydrophobic, hydrophilic and chargedresidues contact network in protein's structural organization. BMC Bioinf., 2012, 13, 142.
34. Pace, C.N.; Shirley, B.A.; McNutt, M.; Gajiwala, K. Forces contrib- uting to the conformational stability of proteins. FASEB J., 1996, 10, 75-83.
35. Vázquez, A.; Pastor-Satorras, R.; Vespignani, A. Large-scale topological and dynamical properties of the Internet. Phys. Rev. E., 2002, 65 (6), 066130.
36. Ravasz, E.B.; Barabási, A.L.S. Hierarchical organization in complex networks. Phys. Rev. E., 2003, 67(2), 026112.
37. Brinda, K.V.; Vishveshwara, S.; Vishveshwara, S. Random network behaviour of protein structures. Mol. Bio. Syst., 2010, 6, 391- 398.
38. Dill, K.A.; Ozkan, S.B.; Shell, M.S.; Weikl, T.R. The protein folding problem. Annu. Rev. Biophys., 2008, 37, 289-316.
39. Plaxco, K.W.; Simons, K.T.; Baker, D. Contact order, transition state placement and the refolding rates of single domain proteins. J. Mol. Biol., 1998, 277, 985-994.
40. Gromiha, M.M. Multiple contact network is a key determinant to protein folding rates. J. Chem. Inf. Model., 2009, 49, 1130-1135.
41. Li, J.; Wang, J.; Wang, W. Identifying folding nucleus based on residue contact networks of proteins. Proteins, 2008, 71, 1899- 1907.
42. Ghosh, A.; Brinda, K.V.; Vishveshwara, S. Dynamics of lysozyme structure network: Probing the process of unfolding. Biophys. J., 2007, 92, 2523-2535.
43. Amitai, G.; Shemesh, A.; Sibton, E.; Shklar, M.; Netanely, D.; Venger, I.; Pietrokovski, S. Network analysis of protein structures identifies functional residues. J. Mol. Biol., 2004, 344, 1135-1146.
44. Daily, M.D.; Upadhyaya, T.J.; Gray, J.J. Rearrangements form coupled networks from local motions in allosteric proteins. Proteins, 2008, 71, 455-466.
45. del Sol, A.; Fujihashi, H.; Amoros, D.; Nussinov, R. Residues crucial for maintaining short paths in network communication mediate signaling in proteins . Mol. Syst. Bio., 2006, 2, 2006.0019.
46. Guo, J.; Pang, X.; Zhou, H-X. Two pathways mediate interdomain allosteric regulation in Pin1. Structure, 2015, 23, 237-247.
47. Freddolino, P.L.; Gardner, K.H.; Schulten, K. Signaling mechanisms of LOV domains: New insights from molecular dynamics studies. Photochem. Photobiol. Sci., 2013, 12(7), 1158-1170.
48. Szilágyi, A.; Nussinov, R.; Csermely, P. Allo-network drugs: Extension of the allosteric drug concept to protein- protein interaction and signaling networks. Curr. Top. Med. Chem., 2013, 3(1), 64-77.
49. Yan, Y.; Zhang, S.; Wu, F.X. Applications of graph theory in protein structure identification. Proteome Sci., 2011, 9(Suppl 1), S17.
50. Kitano, H. Biological robustness. Nat. Rev. Genet., 2004, 5(11), 826-37.
51. Alon, U. Biological Networks: The Tinkerer as an Engineer. Science, 2003, 301, 1866-67.
52. Albert, R.; Jeong, H.; Barabassi, A.-L. Error and attack tolerance in complex networks. Nature, 2000, 406, 378-382.
53. Dunne, J.A.; Williams, R.J.; Martinez, N.D. Network structure and biodiversity loss in food webs: Robustness increases with connectance. Eco. Lett., 2002, 5, 558-567.
54. Oliva, G.; Di Paola, L.; Giuliani, A.; Pascucci, F.; Setola, R. Assessing protein resilience via a complex network approach. Network Science Workshop (NSW): IEEE 2nd, 2013, 131-137.
55. Lee, J.; Wu, S.; Zhang, Y. Ab Initio protein structure prediction. From Protein Structure to Function with Bioinformatics; D.J. Ridgen, Ed.; Springer Science + Business Media B.V. 2009, pp. 3-25.
56. Kriesel, D. A brief introduction to neural networks. http://www.dkriesel.com/en/science/neural-networks.
57. Fariselli, P.; Casadio, R. A neural network based predictor of residue contacts in proteins. Protein Eng., 1999, 12 (1), 15-21.
58. Xue, B.; Faraggi, E.; Zhou, Y. Predicting residue-residue contact maps by a two-layer, integrated neural-network method. Proteins, 2009, 76(1), 176-183.
59. Tegge, A.N.; Wang, Z.; Eickholt, J.; Cheng, J. NNcon: improved protein contact map prediction using 2D-recursive neural networks. Nucleic Acids Res, 2009, 37, W515-W518.
60. Chatterjee, S.; Ghoshz, S.; Vishveshwara, S. Network properties of decoys and CASP predicted models: A comparison with native protein structures. Mol. Bio. Syst., 2013, 9, 1774-1788.
61. Ghosh, S.; Vishveshwara, S. Ranking the quality of protein structure models using sidechain based network properties. F1000Res., 2014, 3(17), 3, 17.
62. Brinda, K.V.; Kannan, N.; Vishveshwara, S. Analysis of homodimeric protein interfaces by graph-spectral methods. Protein Eng., 2002, 15, 265-277.
63. Milo, R.; Shen-Orr, S.; Itzkovitz, S.; Kashtan, N.; Chklovskii, D.; Alon, U. Network motifs: simple building blocks of complex networks. Science, 2002, 298 (5594), 824-827.
64. Alon, U. Network motifs: Theory and experimental approaches. Nat. Rev. Genet., 2007, 8(6), 450.
65. Chakrabarty, B.; Parekh, N. Identifying tandem Ankyrin repeats in protein structures. BMC Bioinf., 2014, 15, 6599.
66. Chakrabarty, B; Parekh, N. PRIGSA: Protein repeat identification by graph spectral analysis. J. Bioinf. Comput. Biol., 2014, 12, 1442009.
67. Williams, S.M.; Chandran, A.V.; Vijayabaskar, M.S.; Roy, S.; Balaram, H.; Vishveshwara, S.; Vijayan, M.; Dipankar Chatterji, D. A histidine aspartate ionic lock gates the iron passage in miniferritins from mycobacterium smegmatis. J. Bio. Chem., 2014, 289(16), 11042-11058.
68. Ghosh, A.; Vishveshwara, S. Variations in Clique and Community Patterns in Protein Structures during Allosteric Communication: Investigation of Dynamically Equilibrated Structures of Methionyl tRNA Synthetase Complexes. Biochemistry, 2008, 47, 11398- 11407.
69. Bastian M., Heymann S., Jacomy M. Gephi: An open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media, 2009.
70. del Sol, A.; Fujihashi, H.; Amoros, D.; Nussinov, R. Residue centrality, functionally important residues, and active site shape: Analysis of enzyme and non-enzyme families. Protein Sci., 2006, 15(9), 2120-8.
71. Liu, R.; Hu, J. Computational Prediction of Heme-Binding Residues by Exploiting Residue Interaction Network. PLoS ONE, 2011, 6(10), e25560.
72. Pons, C.; Glaser, F.; Fernandez-Recio, J. Prediction of proteinbinding areas by small-world residue networks and application to docking. BMC Bioinf., 2011, 12, 378.
73. Huang, J.; Kawashima, S.; Kanehisa, M. New amino acid indices based on residue network topology. Genome Inform., 2007, 18, 152-61.
74. Hu, G.; Yan, W.; Zhou, J.; Shen, B. Residue interaction network analysis of Dronpa and a DNA. J. Theo. Bio., 2014, 348, 55-64.
75. Li, Y.; Wen, Z.; Xiao, J.; Yu, L.; Yang, L.; Li, M. Predicting disease- Associated substitution of a single amino acid by analyzing residue interactions. BMC Bioinformatics, 2011, 12, 14.
76. Tang, Y.R.; Sheng, Z.Y.; Chen, Y.Z.; Zhang, Z. An improved prediction of catalytic residues in enzyme structures. Protein Eng. Des. Select., 2008, 21(5), 295-302.
77. Chea, E.; Livesay, D.R. How accurate and statistically robust are catalytic site predictions based on closeness centrality? BMC Bioinformatics, 2007, 8, 153.
78. Thibert, B.; Bredesen, D.E.; del Rio, G. Improved prediction of critical residues for protein function based on network and phylogenetic analyses. BMC Bioinformatics, 2005, 6, 213.
79. Vijayan, R.S.K.; Arnold, E.; Das, K. Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations. Proteins, 2014, 82, 815- 829.
80. Wangikar, P.P.; Tendulkar, A.V.; Ramya, S.; Mali, D.N.; Sarawagi, S. Functional sites in protein families uncovered via an objective and automated graph theoretic approach. J. Mol. Biol., 2003, 326, 955-978.
81. Grewal K.R.; Mitra, D.; Roy, S. Mapping networks of light-dark transition in LOV photoreceptors. Bioinformatics, 2015, pii: btv429.