Abstract
The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the native states of 66 proteins (belonging to different families) in terms of their core–periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers – having higher core order – with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein. A publicly available Web resource for performing core–periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/~sitabhra/proteinKcore/index.html .
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abkevich VI, Gutin AM and Shakhnovich EI 1994 Specific nucleus as the transition state for protein folding: evidence from the lattice model. Biochemistry 33 10026–10036
Afonnikov DA, Morozov AV and Kolchanov NA 2006 Prediction of contact numbers of amino acid residues using a neural network regression algorithm. Biophysics 51 56–60
Aftabuddin M and Kundu S 2006 Weighted and unweighted network of amino acids within protein. Phys. A. 369 895–904
Aloy P, Querol E, Aviles FX and Sternberg MJE 2001 Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking. J. Mol. Biol. 311 395–408
Alvarez-Hamelin JI, Dall'Asta L, Barrat A and Vespignani A 2005 k-core decomposition: a tool for the visualization of large scale networks. arXiv preprint cs/0504107.
Amitai G, Shemesh A, Sitbon E, Shklar M, Netanely D, Venger I and Pietrokovski S 2004 Network analysis of protein structures identifies functional residues. J. Mol. Biol. 344 1135–1146
Ashkenazy H, Erez E, Martz E, Pupko T and Ben-Tal N 2010 ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res. gkq399
Atilgan AR, Akan P and Baysal C 2004 Small-world communication of residues and significance for protein dynamics. Biophys. J. 86 85–91
Bagler G and Sinha S 2005 Network properties of protein structures. Phys. A. 346 27–33
Bagler G and Sinha S 2007 Assortative mixing in protein contact networks and protein folding kinetics. Bioinformatics 23 1760–1767
Bahar I, Atilgan AR and Erman B 1997 Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential. Fold. Des. 2 173–181
Bahar I, Atilgan AR, Demirel MC and Erman B 1998 Vibrational dynamics of folded proteins: significance of slow and fast motions in relation to function and stability. Phys. Rev. Lett. 80 2733
Bahar I, Erman B, Jernigan RL, Atilgan AR and Covell DG 1999 Collective motions in HIV-1 reverse transcriptase: examination of flexibility and enzyme function. J. Mol. Biol. 285 1023–1037
Barah P and Sinha S 2008 Analysis of protein folds using protein contact networks. Pramana 71 369–378
Brinda K and Vishveshwara S 2005 A network representation of protein structures: implications for protein stability. Biophys. J. 89 4159–4170
Brinda K, Surolia A and Vishveshwara S 2005 Insights into the quaternary association of proteins through structure graphs: a case study of lectins. Biochem. J. 391 1–15
Brinda K, Vishveshwara S and Vishveshwara S 2010 Random network behaviour of protein structures. Mol. Biosyst. 6 391–398
Carmi S, Havlin S, Kirkpatrick S, Shavitt Y and Shir E 2007 A model of Internet topology using k-shell decomposition. Proc. Natl. Acad. Sci. USA 104 11150–11154
Chatterjee N and Sinha S 2007 Understanding the mind of a worm: hierarchical network structure underlying nervous system function in C. elegans Prog. Brain Res. 168 145–153
Clementi C, Nymeyer H and Onuchic JN 2000 Topological and energetic factors: what determines the structural details of the transition state ensemble and “en-route” intermediates for protein folding? An investigation for small globular proteins. J. Mol. Biol. 298 937–953
Csermely P, Korcsmaros T, Kiss HJM, London G and Nussinov R 2013 Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol. Ther. 138 333–408
da Silveira CH, Pires DEV, Minardi RC, Ribeiro C, Veloso CJM, Lopes JCD, Meira W, Neshich G, et al. 2009 Protein cutoff scanning: a comparative analysis of cutoff dependent and cutoff free methods for prospecting contacts in proteins. Proteins: Struct. Funct. Bioinf. 74 727–743
del Sol A and O'Meara P 2005 Small-world network approach to identify key residues in protein-protein interaction. Proteins: Struct. Funct. Bioinf. 58 672–682
del Sol A, Fujihashi H, Amoros D and Nussinov R 2006a Residue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families. Protein Sci. 15 2120–2128
del Sol A, Fujihashi H, Amoros D and Nussinov R 2006b Residues crucial for maintaining short paths in network communication mediate signaling in proteins. Mol. Syst. Biol. 2
Demirel MC, Atilgan AR, Bahar I, Jernigan RL and Erman B 1998 Identification of kinetically hot residues in proteins. Protein Sci. 7 2522–2532
Di Paola L, De Ruvo M, Paci P, Santoni D and Giuliani A 2012 Protein contact networks: an emerging paradigm in chemistry. Chem. Rev. 113 1598–1613
Dokholyan NV, Buldyrev SV, Stanley HE and Shakhnovich EI 2000 Identifying the protein folding nucleus using molecular dynamics. J. Mol. Biol. 296 1183–1188
Dundas J, Ouyang Z, Tseng J, Binkowski A, Turpaz Y and Liang J 2006 CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res. 34 W116–W118
Ertekin A, Nussinov R and Haliloglu T 2006 Association of putative concave protein-binding sites with the fluctuation behavior of residues. Protein Sci. 15 2265–2277
Everett MG and Borgatti SP 1999 The centrality of groups and classes. J. Math. Sociol. 23 181–201
Fersht AR 1995 Optimization of rates of protein folding: the nucleation-condensation mechanism and its implications. Proc. Natl. Acad. Sci. USA 92 10869–10873
Fersht AR 1997 Nucleation mechanisms in protein folding. Curr. Opin. Struct. Biol. 7 3–9
Glaser F, Pupko T, Paz I, Bell RE, Bechor-Shental D, Martz E and Ben-Tal N 2003 ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information. Bioinformatics 19 163–164
Grantcharova VP, Riddle DS, Santiago JV and Baker D 1998 Important role of hydrogen bonds in the structurally polarized transition state for folding of the src SH3 domain. Nat. Struct. Mol. Biol. 5 714–720
Greene LH and Higman VA 2003 Uncovering network systems within protein structures. J. Mol. Biol. 334 781–791
Gruebele M and Wolynes PG 1998 Satisfying turns in folding transitions. Nature Struct. Biol. 5 662–665
Haliloglu T and Erman B 2009 Analysis of correlations between energy and residue fluctuations in native proteins and determination of specific sites for binding. Phys. Rev. Lett. 102 088103
Haliloglu T, Bahar I and Erman B 1997 Gaussian dynamics of folded proteins. Phys. Rev. Lett. 79 3090
Haliloglu T, Keskin O, Ma B and Nussinov R 2005 How similar are protein folding and protein binding nuclei? Examination of vibrational motions of energy hot spots and conserved residues. Biophys. J. 88 1552–1559
Haliloglu T, Seyrek E and Erman B 2008 Prediction of binding sites in receptor-ligand complexes with the Gaussian Network Model. Phys. Rev. Lett. 100 228102
Haspel N, Tsai CJ, Wolfson H and Nussinov R 2003 Reducing the computational complexity of protein folding via fragment folding and assembly. Protein Sci. 12 1177–1187
Hleap JS, Susko E and Blouin C 2013 Defining structural and evolutionary modules in proteins: a community detection approach to explore sub-domain architecture. BMC Struct. Biol. 13 20
Holme P 2005 Core-periphery organization of complex networks. Phys. Rev. E. 72 046111
Hu G, Yan W, Zhou J and Shen B 2014 Residue interaction network analysis of Dronpa and a DNA clamp. J. Theor. Biol. 348 55–64
Hubner IA, Oliveberg M and Shakhnovich EI 2004 Simulation, experiment, and evolution: understanding nucleation in protein S6 folding. Proc. Natl. Acad. Sci. USA 101 8354–8359
Itzhaki LS, Otzen DE and Fersht AR 1995 The structure of the transition state for folding of chymotrypsin inhibitor 2 analysed by protein engineering methods: evidence for a nucleation-condensation mechanism for protein folding. J. Mol. Biol. 254 260–288
Jeong H, Mason SP, Barabási AL and Oltvai ZN 2001 Lethality and centrality in protein networks. Nature 411 41–42
Kitsak M, Gallos LK, Havlin S, Liljeros F, Muchnik L, Stanley HE and Makse HA 2010 Identification of influential spreaders in complex networks. Nat. Phys. 6 888–893
Kundu S 2005 Amino acid network within protein. Phys. A. 346 104–109
Landau M, Mayrose I, Rosenberg Y, Glaser F, Martz E, Pupko T and Ben-Tal N 2005 ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures. Nucleic Acids Res. 33 W299–W302
Landgraf R, Xenarios I and Eisenberg D 2001 Three-dimensional cluster analysis identifies interfaces and functional residue clusters in proteins. J. Mol. Biol. 307 1487–1502
Li H 2009 Predicting protein folding cores based on complex network and phylogenetic analyses. BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future, IEEE
Li L and Shakhnovich EI 2001 Constructing, verifying, and dissecting the folding transition state of chymotrypsin inhibitor 2 with all-atom simulations. Proc. Natl. Acad. Sci. USA 98 13014–13018
Li J, Wang J and Wang W 2008 Identifying folding nucleus based on residue contact networks of proteins. Proteins: Struct. Funct. Bioinf. 71 1899–1907
Lichtarge O, Bourne HR and Cohen FE 1996 An evolutionary trace method defines binding surfaces common to protein families. J. Mol. Biol. 257 342–358
Lin C-C, Juan H-F, Hsiang J-T, Hwang Y-C, Mori H and Huang H-C 2009 Essential Core of Protein-Protein Interaction Network in Escherichia coli. J. Proteome Res. 8 1925–1931
Magyar C, Gromiha MM, Pujadas G, Tusnady GE and In S 2005 SRide: a server for identifying stabilizing residues in proteins. Nucleic Acids Res. 33 W303–W305
Newman M 2010 Networks: An Introduction (Oxford University Press)
Ng PC and Henikoff S 2003 SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 31 3812–3814
Nicola G and Vakser IA 2007 A simple shape characteristic of protein‒protein recognition. Bioinformatics 23 789–792
Ondrechen MJ, Clifton JG and Ringe D 2001 THEMATICS: a simple computational predictor of enzyme function from structure. Proc. Natl. Acad. Sci. USA 98 12473–12478
Pande VS, Grosberg AY, Tanaka T and Rokhsar DS 1998 Pathways for protein folding: is a new view needed? Curr. Opin. Struct. Biol. 8 68–79
Qin M, Zhang J and Wang W 2006 Effects of disulfide bonds on folding behavior and mechanism of the Î2-sheet protein tendamistat. Biophys. J. 90 272–286
Riddle DS, Grantcharova VP, Santiago JV, Alm E, Ruczinski I and Baker D 1999 Experiment and theory highlight role of native state topology in SH3 folding. Nat. Struct. Mol. Biol. 6 1016–1024
Seidman SB 1983 Network structure and minimum degree. Soc. Networks 5 269–287
Shander A, Gromiha M, Fawareh H and Sarai A 2004 ASA view: solvent accessibility graphics for proteins. Bioinformatics 51 51
Shen T, Hofmann CP, Oliveberg M and Wolynes PG 2005 Scanning malleable transition state ensembles: comparing theory and experiment for folding protein U1A. Biochemistry 44 6433–6439
Sobolev V, Sorokine A, Prilusky J, Abola EE and Edelman M 1999 Automated analysis of interatomic contacts in proteins. Bioinformatics 15 327–332
Tasdighian S, Di Paola L, De Ruvo M, Paci P, Santoni D, Palumbo P, Mei G, Di Venere A, et al. 2013 Modules identification in protein structures: the topological and geometrical solutions. J. Chem. Inf. Model. 54 159–168
Ternstrom T, Mayor U, Akke M and Oliveberg M 1999 From snapshot to movie: analysis of protein folding transition states taken one step further. Proc. Natl. Acad. Sci. USA 96 14854–14859
Toth-Petroczy A and Tawfik DS 2011 Slow protein evolutionary rates are dictated by surface-core association. Proc. Natl. Acad. Sci. USA 108 11151–11156
Vendruscolo M 2011 Protein regulation: the statistical theory of allostery. Nat. Chem. Biol. 7 411–412
Vendruscolo M, Paci E, Dobson CM and Karplus M 2001 Three key residues form a critical contact network in a protein folding transition state. Nature 409 641–645
Vendruscolo M, Dokholyan NV, Paci E and Karplus M 2002 Small-world view of the amino acids that play a key role in protein folding. Phys. Rev. E. 65 061910
Vijayabaskar MS and Vishveshwara S 2010 Interaction energy based protein structure networks. Biophys. J. 99 3704–3715
Vishveshwara S, Brinda KV and Kannan N 2002 Protein structure: insights from graph theory. J. Theor. Comput. Chem. 1 187–211
Vishveshwara S, Ghosh A and Hansia P 2009 Intra and inter-molecular communications through protein structure network. Curr. Protein Pept. Sci. 10 146–160
Watts DJ and Strogatz SH 1998 Collective dynamics of ‘small-world’ networks. Nature. 393 440–442
Wuchty S and Almaas E 2005 Peeling the yeast protein network. Proteomics 5 444–449
Yogurtcu ON, Gur M and Erman B 2009 Statistical thermodynamics of residue fluctuations in native proteins. J. Chem. Phys. 130 095103
Zhang J, Zhao H, Xu J-q and Ge X 2009 The K-core decomposition and visualization of internet router-level topology. Computer Science and Information Engineering, 2009 WRI World Congress on, IEEE
Zhang H, Zhao H, Cai W, Liu J and Zhou W 2010 Using the k-core decomposition to analyze the static structure of large-scale software systems. J. Supercomput. 53 352–369
Acknowledgements
We would like to thank Indrani Bose and Somdatta Sinha for helpful discussions. We also thank the VIT University and IMSc for providing computational facilities.
Author information
Authors and Affiliations
Corresponding author
Additional information
[Isaac AE and Sinha S 2015 Analysis of core–periphery organization in protein contact networks reveals groups of structurally and functionally critical residues. J. Biosci.] DOI 10.1007/s12038-015-9554-0
Supplementary materials pertaining to this article are available on the Journal of Biosciences Website at http://www.ias.ac.in/jbiosci/oct2015/supp/Emerson.pdf
Electronic supplementary material
Below is the link to the electronic supplementary material.
ESM 1
(PDF 980 kb)
Rights and permissions
About this article
Cite this article
Isaac, A.E., Sinha, S. Analysis of core–periphery organization in protein contact networks reveals groups of structurally and functionally critical residues. J Biosci 40, 683–699 (2015). https://doi.org/10.1007/s12038-015-9554-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12038-015-9554-0