Amino acid network for the discrimination of native protein structures from decoys

Current Protein and Peptide Science

Volumn 15, Issue 6, 2014, Pages 522-528

  Zhou, Jianhong ^a   Yan, Wenying ^a   Hu, Guang ^a   Shen, Bairong ^a  

^a SOOCHOW UNIVERSITY   (China)

Author keywords

Amino acid network; Network characterization; Protein decoy discrimination

Indexed keywords

RIBOSOME PROTEIN; AMINO ACID; PROTEIN;

AMINO ACID NETWORK; AMINO ACID SEQUENCE; ANALYTICAL PARAMETERS; AVERAGE DEGREE; AVERAGE PATH LENGTH; CLUSTER COEFFICIENT; CLUSTER SIZE; CONSTANTS AND COEFFICIENTS; COVALENT BOND; CUMULATIVE COMMUNITY SIZE; MOLECULAR INTERACTION; PHYSICAL PARAMETERS; PREDICTION; PROTEIN CONFORMATION; PROTEIN DATA BANK; PROTEIN DECOY DISCRIMINATION; PROTEIN FOLDING; PROTEIN FUNCTION; PROTEIN INTERACTION; PROTEIN LOCALIZATION; PROTEIN SECONDARY STRUCTURE; PROTEIN STABILITY; PROTEIN STRUCTURE; REVIEW; SEQUENCE HOMOLOGY; STRUCTURAL GENOMICS; STRUCTURE ANALYSIS; ANIMAL; CHEMICAL STRUCTURE; CHEMISTRY; CLUSTER ANALYSIS; HUMAN; ARTICLE; PARAMETERS; SCORING SYSTEM; SUPPORT VECTOR MACHINE; THEORY;

AMINO ACIDS; ANIMALS; CLUSTER ANALYSIS; HUMANS; MODELS, MOLECULAR; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEINS;

EID: 84896357579     PISSN: 13892037     EISSN: 18755550     Source Type: Journal    
DOI: 10.2174/1389203715666140724084709     Document Type: Review

References (90)

1. Levitt, M.; Chothia, C. Structural patterns in globular proteins. Nature, 1976, 261(5561), 552-558.
2. Orengo, C.A.; Michie, A.D.; Jones, S.; Jones, D.T.; Swindells, M.B.; Thornton, J.M. CATH--a hierarchic classification of protein domain structures. Structure, 1997, 5(8), 1093-1108.
3. Murzin, A.G.; Brenner, S.E.; Hubbard, T.; Chothia, C. SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol., 1995, 247(4), 536-540.
4. Greene, L.H.; Higman, V.A. Uncovering Network Systems Within Protein Structures. J. Mol. Biol., 2003, 334, 781-791.
5. Hu, G.; Yan, W.; Zhou, J.; Shen, B. Residue Interaction Network Analysis of Dronpa and a DNA clamp. J. Theor. Biol., 2014, 348, 55-64.
6. Hu, G.; Zhou, J.; Yan, W.; Chen, J.; Shen, B. The topology and dynamics of protein complexes: insights from intra-molecular network theory. Curr. Protein Pept. Sci., 2013, 14(2), 121-132.
7. Yang, Y.; Chen, B.; Tan, G.; Vihinen, M.; Shen, B. Structure-based prediction of the effects of a missense variant on protein stability. Amino Acids, 2013, 44(3), 847-855.
8. Zhou, J.; Yan, W.; Hu, G.; Shen, B. SVR_CAF: An integrated score function for detecting native protein structures among decoys. Proteins, 2014, 82(4), 556-564.
9. Mitchell, E.M.; Artymiuk, P.J.; Rice, D.W.; Willett, P. Use of techniques derived from graph theory to compare secondary structure motifs in proteins. J. Mol. Biol., 1990, 212, 151-166.
10. Artymiuk, P.J.; Rice, D.W.; Mitchell, E.M.; Willett, P. Structural resemblance between the families of bacterial signaltransduction proteins and of G proteins revealed by graph theoretical techniques. Protein Eng., 1990, 4, 39-43.
11. Kannan, N.; Vishveshwara, S. Identification of side-chain clusters in protein structures by a graph spectral method. J. Mol. Biol., 1999, 292(2), 441-464.
12. Vendruscolo, M.; Paci, E.; Dobson, C.M.; Karplus, M. Three key residues form a critical contact network in a protein folding transition state. Nature, 2001, 409(6820), 641-645.
13. 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(6 Pt 1), 061910.
14. Amitai, G.; Shemesh, A.; Sitbon, E.; Shklar, M.; Netanely, D.; Venger, I.; Pietrokovski, S. Network analysis of protein structures identifies functional residues. J. Mol. Biol., 2004, 344(4), 1135-1146.
15. Dokholyan, N.V.; Li, L.; Ding, F.; Shakhnovich, E.I. Topological determinants of protein folding. PNAS, 2002, 99(13), 8637-8641.
16. Brinda, K.V.; Vishveshwara, S. A network representation of protein structures: implications for protein stability. Biophys. J, 2005, 89(6), 4159-4170.
17. Raes, J.; Harrington, E.D.; Singh, A.H.; Bork, P. Protein function space: viewing the limits or limited by our view?. Curr. Opin. Struct. Biol., 2007, 17(3), 362-369.
18. Sasson, O.; Kaplan, N.; Linial, M. Functional annotation prediction: all for one and one for all. Protein Sci., 2006, 15(6), 1557-1562.
19. Anfinsen, C.B. Principles that govern the folding of protein chains. Science, 1973, 181(4096), 223-230.
20. Lee, M.C.; Duan, Y. Distinguish protein decoys by using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model. Proteins, 2004, 55(3), 620-634.
21. Shen, B.; Bai, J.; Vihinen, M. Physicochemical feature-based classification of amino acid mutations. Protein Eng. Des. Sel., 2008, 21(1), 37-44.
22. Shen, B.; Vihinen, M. RankViaContact: ranking and visualization of amino acid contacts. Bioinformatics, 2003, 19(16), 2161-2162.
23. Shen, B.; Vihinen, M. Conservation and covariance in PH domain sequences: physicochemical profile and information theoretical analysis of XLA-causing mutations in the Btk PH domain. Protein Eng. Des. Sel., 2004, 17(3), 267-276.
24. Skolnick, J. In quest of an empirical potential for protein structure prediction. Curr. Opin. Struct. Biol., 2006, 16(2), 166-171.
25. Asensio, J.L.; Jimenez-Barbero, J. The use of the AMBER force field in conformational analysis of carbohydrate molecules: determination of the solution conformation of methyl alphalactoside by NMR spectroscopy, assisted by molecular mechanics and dynamics calculations. Biopolymers, 1995, 35(1), 55-73.
26. McKelvey, D.R.; Brooks, C. L.; Mokotoff, M. A CHARMM analysis of the conformations of the metastasis-inhibiting laminin pentapeptide. J. Protein Chem., 1991, 10(3), 265-271.
27. Roterman, I.K.; Lambert, M.H.; Gibson, K.D.; Scheraga, H.A. A comparison of the CHARMM, AMBER and ECEPP potentials for peptides. II. Phi-psi maps for N-acetyl alanine N'-methyl amide: comparisons, contrasts and simple experimental tests. J. Biomol. Struct. Dyn., 1989, 7(3), 421-453.
28. Roterman, I.K.; Gibson, K.D.; Scheraga, H.A. A comparison of the CHARMM, AMBER and ECEPP potentials for peptides. I. Conformational predictions for the tandemly repeated peptide (Asn-Ala-Asn-Pro)9. J. Biomol. Struct. Dyn., 1989, 7(3), 391-419.
29. Baran, M.; Mazerski, J. Molecular modelling of membrane sterols with the use of the GROMOS 96 force field. Chem. Phys. Lipids, 2002, 120(1-2), 21-31.
30. Zimmerman, S.S.; Pottle, M.S.; Nemethy, G.; Scheraga, H.A. Conformational analysis of the 20 naturally occurring amino acid residues using ECEPP. Macromolecules, 1977, 10(1), 1-9.
31. Kahn, K.; Bruice, T.C. Parameterization of OPLS-AA force field for the conformational analysis of macrocyclic polyketides. J. Comput. Chem., 2002, 23(10), 977-996.
32. Xu, Z.; Luo, H.H.; Tieleman, D.P. Modifying the OPLS-AA force field to improve hydration free energies for several amino acid side chains using new atomic charges and an off-plane charge model for aromatic residues. J. Comput. Chem., 2007, 28(3), 689-697.
33. Cao, Z.; Liu, L.; Wang, J. Why the OPLS-AA force field cannot produce the beta-hairpin structure of H1 peptide in solution when comparing with the GROMOS 43A1 force field?. J. Biomol. Struct. Dyn., 2011, 29(3), 527-539.
34. Huang, E.S.; Samudrala, R.; Park, B.H. Scoring functions for ab initio protein structure prediction. Methods Mol. Biol., 2000, 143, 223-245.
35. Samudrala, R.; Moult, J. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. J. Mol. Biol., 1998, 275(5), 895-916.
36. Lu, H.; Skolnick, J. A distance-dependent atomic knowledge-based potential for improved protein structure selection. Proteins, 2001, 44(3), 223-232.
37. Zhou, H.; Zhou, Y. Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Protein Sci., 2002, 11(11), 2714-2726.
38. Shen, M.Y.; Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci., 2006, 15(11), 2507-2524.
39. Lu, M.; Dousis, A.D.; Ma, J. OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing. J. Mol. Biol., 2008, 376(1), 288-301.
40. Bonneau, R.; Tsai, J.; Ruczinski, I.; Chivian, D.; Rohl, C.; Strauss, C.E.; Baker, D. Rosetta in CASP4: progress in ab initio protein structure prediction. Proteins, 2001, Suppl 5, 119-126.
41. Simons, K.T.; Bonneau, R.; Ruczinski, I.; Baker, D. Ab initio protein structure prediction of CASP III targets using ROSETTA. Proteins, 1999, Suppl 3, 171-176.
42. Zhang, Y. I-TASSER: fully automated protein structure prediction in CASP8. Proteins, 2009, 77(Suppl 9), 100-113.
43. Zhang, Y.; Arakaki, A.K.; Skolnick, J. TASSER: an automated method for the prediction of protein tertiary structures in CASP6. Proteins, 2005, 61(Suppl 7), 91-98.
44. Benkert, P.; Tosatto, S.C.; Schwede, T. Global and local model quality estimation at CASP8 using the scoring functions QMEAN and QMEANclust. Proteins, 2009, 77(Suppl 9), 173-180.
45. Benkert, P.; Tosatto, S.C.; Schomburg, D. QMEAN: A comprehensive scoring function for model quality assessment. Proteins, 2008, 71(1), 261-277.
46. Mirzaie, M.; Sadeghi, M. Knowledge-based potentials in protein fold recognition. J. Paramed. Sci., 2010, 1(4), 63-73.
47. Zhang, C.; Kim, S.H. Environment-dependent residue contact energies for proteins. Proc. Natl. Acad. Sci. U. S. A., 2000, 97(6), 2550-2555.
48. Zhang, C.; Vasmatzis, G.; Cornette, J.L.; DeLisi, C. Determination of atomic desolvation energies from the structures of crystallized proteins. J. Mol. Biol., 1997, 267(3), 707-726.
49. Zhou, H.; Zhou, Y. Single-body residue-level knowledge-based energy score combined with sequence-profile and secondary structure information for fold recognition. Proteins, 2004, 55(4), 1005-1013.
50. Chen, C.; Li, L.; Xiao, Y. All-atom contact potential approach to protein thermostability analysis. Biopolymers, 2007, 85(1), 28-37.
51. Arab, S.; Sadeghi, M.; Eslahchi, C.; Pezeshk, H.; Sheari, A. A pairwise residue contact area-based mean force potential for discrimination of native protein structure. BMC Bioinformatics, 2010, 11, 16.
52. Zhou, H.; Skolnick, J. Protein model quality assessment prediction by combining fragment comparisons and a consensus C(alpha) contact potential. Proteins, 2008, 71(3), 1211-1218.
53. Rohl, C.A.; Strauss, C.E.; Misura, K.M.; Baker, D. Protein structure prediction using Rosetta. Methods Enzymol., 2004 383, 66-93.
54. Eramian, D.; Shen, M.Y.; Devos, D.; Melo, F.; Sali, A.; Marti-Renom, M.A. A composite score for predicting errors in protein structure models. Protein Sci., 2006 15 (7), 1653-1666.
55. Wallner, B.; Elofsson, A. Can correct protein models be identified?. Protein Sci., 2003 12 (5), 1073-1086.
56. Rykunov, D.; Fiser, A. Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Proteins, 2007 67 (3), 559-568.
57. Taylor, T.J.; Vaisman, II. Graph theoretic properties of networks formed by the Delaunay tessellation of protein structures. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2006 73 (4), 041925.
58. Galan, J.F.; Gao, J.; Pabuwal, V.; Meek, P.J.; Li, Z.J. Application of Network Theory in Understanding and Predicting Protein Structure and Function. Curr. Proteomics, 2008 5 (3), 181-190.
59. Vassura, M.; Margara, L.; Fariselli, P.; Casadio, R. A graph theoretic approach to protein structure selection. Artif. Intell. Med., 2009 45 (2-3), 229-237.
60. Jiao, X.; Chang, S.; Li, C.H.; Chen, W.Z.; Wang, C.X. Construction and application of the weighted amino acid network based on energy. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2007 75 (5 Pt 1), 051903.
61. Kundu, S. Amino acid network within protein. Physica. A., 2005 346, 104-109.
62. Aftabuddin, M.; Kundu, S. Weighted and unweighted network of amino acids in a protein. Physica. A., 2006 396, 895-904.
63. Chang, S.; Jiao, X.; Gong, X.Q.; Li, C.H.; Chen, W.Z.; Wang, C.X. Evolving model of amino acid networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2008 77 (6 Pt 1), 061920.
64. Gaci, O. A Dynamic Graph to Fold Amino Acid Interaction Networks. IEEE, 2010, 18-23.
65. Gaci, O.; Balev, S. A study of protein structure using amino acid interaction networks. Adv. Technologies, 2010, 19-46.
66. Atilgan, A.R.; Akan, P.; Baysal, C. Small-World Communication of Residues and Significance for Protein Dynamics. Biophys. J., 2004 86, 85-91.
67. Doncheva, N.T.; Klein, K.; Domingues, F.S.; Albrecht, M. Analyzing and visualizing residue networks of protein structures. Trends Biochem. Sci., 2011 36 (4), 179-182.
68. Martin, A.J.; Vidotto, M.; Boscariol, F.; Di Domenico, T.; Walsh, I.; Tosatto, S.C. RING: networking interacting residues, evolutionary information and energetics in protein structures. Bioinformatics, 2011 27 (14), 2003-2005.
69. Newman, M.E. Assortative mixing in networks. Phys. Rev. Lett., 2002 89 (20), 208701.
70. Bagler, G.; Sinha, S. Assortative mixing in Protein Contact Networks and protein folding kinetics. Bioinformatics, 2007 23 (14), 1760-1767.
71. Vijayabaskar, M.S.; Vishveshwara, S. Interaction energy based protein structure networks. Biophys. J., 2010 99 (11), 3704-3715.
72. 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), 2120-2128.
73. Ma, C.W.; Xiu, Z.L.; Zeng, A.P. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation. PLoS One, 2012 7 (2), e31529.
74. Samudrala, R.; Levitt, M. Decoys 'R' Us: a database of incorrect conformations to improve protein structure prediction. Protein Sci., 2000 9 (7), 1399-1401.
75. Gao, J.; Li, Z.J. Inter-Residue Interactions in protein structres exhibit power-law behavior. Biopolymers, 2008 89 (12), 1174-1178.
76. Aftabuddin, M.; Kundu, S. Hydrophobic, hydrophilic, and charged amino acid networks within protein. Biophys. J., 2007 93 (1), 225-231.
77. Chatterjee, S.; Bhattacharyya, M.; Vishveshwara, S. Network properties of protein-decoy structures. J. Biomol. Struct. Dyn., 2012 29 (6), 606-622.
78. Aftabuddin, M.; Kundu, S. AMINONET-a tool to construct and visualize amino acid networks, and to calculate topological parameters. J. Appl. Cryst., 2010 43, 367-369.
79. http://www.bioinformatics.org/aminonet/.
80. Vijayabaskar, M.S.; Niranjan, V.; and Vishveshwara, S. GraProStr-Graphs of Protein Structures: A Tool for Constructing the Graphs and Generating Graph Parameters for Protein Structures. Open Bioinformatics J., 2011 5, 53-58.
81. Muppirala, U.K.; Li, Z.J. A simple approach for protein structure discrimination based on the network pattern of conserved hydrophobic residues. Protein Eng. Des. Sel., 2006 19 (6), 265-275.
82. Pabuwal, V.; Li, Z.J. Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction. Protein Eng. Des. Sel., 2008 21 (1), 55-64.
83. KÜÇÜKURAL, A. Discrimination of native folds using network properties of protein structure, BMC System Biol., 2007, 1(suppl 1), 49.
84. Chatterjee, S.; Ghosh, S.; Vishveshwara, S. Network properties of decoys and CASP predicted models: a comparison with native protein structures. Mol. Biosyst., 2013 9 (7), 1774-1788.
85. Chang, S.; Jiao, X.; Li, C.H.; Gong, X.Q.; Chen, W.Z.; Wang, C.X. Amino acid network and its scoring application in protein-protein docking. Biophys. Chem., 2008 134 (3), 111-118.
86. Jiao, X.; Yang, L.F. The Scoring Function Based on Amino Acid Network. IEEE, 2011, 1997-2000.
87. Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res., 2003 13 (11), 2498-2504.
88. Gao, J.; Li, Z.J. Conserved network properties of helical membrane protein structures and its implication for improving membrane protein homology modeling at the twilight zone. J. Comput. Aided Mol. Des., 2009 23 (11), 755-763.
89. Sobolev, V.; Sorokine, A.; Prilusky, J.; Abola, E.E.; Edelman, M. Automated analysis of interatomic contacts in proteins. Bioinformatics, 1999 15 (4), 327-332.
90. Vijayabaskar, M.S.; Vishveshwara, S. Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks. BMC Bioinformatics, 2010, 11 (Suppl 1), S49.