Insights into Protein'DNA Interactions through Structure Network Analysis

Topics: DNA, Amino acid, Protein Pages: 35 (11158 words) Published: July 28, 2010
Insights into Protein–DNA Interactions through Structure Network Analysis R. Sathyapriya.¤, M. S. Vijayabaskar., Saraswathi Vishveshwara* Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India

Abstract
Protein–DNA interactions are crucial for many cellular processes. Now with the increased availability of structures of protein–DNA complexes, gaining deeper insights into the nature of protein–DNA interactions has become possible. Earlier, investigations have characterized the interface properties by considering pairwise interactions. However, the information communicated along the interfaces is rarely a pairwise phenomenon, and we feel that a global picture can be obtained by considering a protein–DNA complex as a network of noncovalently interacting systems. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein-centric), and the present network approach aims to combine both the protein-centric and the DNA-centric points of view. Part of the study involves the development of methodology to investigate protein–DNA graphs/networks with the development of key parameters. A network representation provides a holistic view of the interacting surface and has been reported here for the first time. The second part of the study involves the analyses of these graphs in terms of clusters of interacting residues and the identification of highly connected residues (hubs) along the protein–DNA interface. A predominance of deoxyribose–amino acid clusters in b-sheet proteins, distinction of the interface clusters in helix–turn–helix, and the zipper-type proteins would not have been possible by conventional pairwise interaction analysis. Additionally, we propose a potential classification scheme for a set of protein–DNA complexes on the basis of the protein–DNA interface clusters. This provides a general idea of how the proteins interact with the different components of DNA in different complexes. Thus, we believe that the present graph-based method provides a deeper insight into the analysis of the protein–DNA recognition mechanisms by throwing more light on the nature and the specificity of these interactions. Citation: Sathyapriya R, Vijayabaskar MS, Vishveshwara S (2008) Insights into Protein–DNA Interactions through Structure Network Analysis. PLoS Comput Biol 4(9): e1000170. doi:10.1371/journal.pcbi.1000170 Editor: Ruth Nussinov, National Cancer Institute, United States of America and Tel Aviv University, Israel Received January 10, 2008; Accepted July 29, 2008; Published September 5, 2008 Copyright: ß 2008 Sathyapriya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Department of Biotechnology, Government of India, support for Basic Biological Research Competing Interests: The authors have declared that no competing interests exist. * E-mail: sv@mbu.iisc.ernet.in ¤ Current address: Max Planck Institute for Molecular Genetics, Berlin, Germany . These authors contributed equally to this work.

Introduction
A network of interactions among the macromolecules drives the cell. The protein–DNA interactions orchestrate the high fidelity processes like DNA recombination, DNA replication, and transcription. With the increasing number of high-resolution structures of macromolecular complexes, it is now possible to obtain insights into the atomic details of interactions governing their structural and functional integrity. In the present study, we focus on protein–DNA interactions, which can either be specific or non-specific depending on the functional requirement. Insights into the mechanism of protein–DNA binding and recognition have come from extensive analysis of protein–DNA interfaces [1– 14]. Some of these investigations have been carried out at the level of...

References: 1. Luscombe NM, Thornton JM (2002) Protein–DNA interactions: amino acid conservation and the effects of mutations on binding specificity. J Mol Biol 320: 991–1009. 2. Lustig B, Jernigan RL (1995) Consistencies of individual DNA base–amino acid interactions in structures and sequences. Nucleic Acids Res 23: 4707–4711. 3. Prabakaran P, Siebers JG, Ahmad S, Gromiha MM, Singarayan MG, et al. (2006) Classification of protein-DNA complexes based on structural descriptors. Structure 14: 1355–1367. 4. Sathyapriya R, Brinda KV, Vishveshwara S (2006) Correlation of the side-chain hubs with the functional residues in DNA binding protein structures. J Chem Inf Model 46: 123–129. 5. Luscombe NM, Laskowski RA, Thornton JM (2001) Amino acid–base interactions: a three-dimensional analysis of protein–DNA interactions at an atomic level. Nucleic Acids Res 29: 2860–2874. 6. Jones S, van Heyningen P, Berman HM, Thornton JM (1999) Protein-DNA interactions: a structural analysis. J Mol Biol 287: 877–896. 7. Siggers TW, Silkov A, Honig B (2005) Structural alignment of protein–DNA interfaces: insights into the determinants of binding specificity. J Mol Biol 345: 1027–1045. 8. Ahmad S, Kono H, Arauzo-Bravo MJ, Sarai A (2006) ReadOut: structure-based calculation of direct and indirect readout energies and specificities for protein– DNA recognition. Nucleic Acids Res 34: W124–W127. 9. Baker CM, Grant GH (2007) Role of aromatic amino acids in protein-nucleic acid recognition. Biopolymers 85: 456–470. 10. Coulocheri SA, Pigis DG, Papavassiliou KA, Papavassiliou AG (2007) Hydrogen bonds in protein–DNA complexes: where geometry meets plasticity. Biochimie 89: 1291–1303. 11. Lejeune D, Delsaux N, Charloteaux B, Thomas A, Brasseur R (2005) Proteinnucleic acid recognition: statistical analysis of atomic interactions and influence of DNA structure. Proteins 61: 258–271. 12. Gromiha MM, Siebers JG, Selvaraj S, Kono H, Sarai A (2005) Role of inter and intramolecular interactions in protein–DNA recognition. Gene 364: 108–113. 13. Kono H, Sarai A (1999) Structure-based prediction of DNA target sites by regulatory proteins. Proteins 35: 114–131. 14. Gromiha MM, Siebers JG, Selvaraj S, Kono H, Sarai A (2004) Intermolecular and intramolecular readout mechanisms in protein–DNA recognition. J Mol Biol 337: 285–294. 15. Kannan N, Vishveshwara S (1999) Identification of side-chain clusters in protein structures by a graph spectral method. J Mol Biol 292: 441–464. 16. Patra SM, Vishveshwara S (2000) Backbone cluster identification in proteins by a graph theoretical method. Biophys Chem 84: 13–25. 17. Vendruscolo M, Paci E, Dobson CM, Karplus M (2001) Three key residues form a critical contact network in a protein folding transition state. Nature 409: 641–645. 18. Greene LH, Higman VA (2003) Uncovering network systems within protein structures. J Mol Biol 334: 781–791. 19. Atilgan AR, Turgut D, Atilgan C (2007) Screened nonbonded interactions in native proteins manipulate optimal paths for robust residue communication. Biophys J 92: 3052–3062. 20. Chang S, Jiao X, Li CH, Gong XQ, Chen WZ, et al. (2008) Amino acid network and its scoring application in protein–protein docking. Biophys Chem 134: 111–118. 21. del Sol A, O’Meara P (2005) Small-world network approach to identify key residues in protein-protein interaction. Proteins 58: 672–682. 22. Brinda KV, Kannan N, Vishveshwara S (2002) Analysis of homodimeric protein interfaces by graph-spectral methods. Protein Eng 15: 265–277. 23. Brinda KV, Vishveshwara S (2005) A network representation of protein structures: implications for protein stability. Biophys J 89: 4159–4170. 24. Sen TZ, Kloczkowski A, Jernigan RL (2006) A DNA-centric look at proteinDNA complexes. Structure 14: 1341–1342. 25. Luscombe NM, Austin SE, Berman HM, Thornton JM (2000) An overview of the structures of protein-DNA complexes. Genome Biol 1: REVIEWS001. 26. Juo ZS, Chiu TK, Leiberman PM, Baikalov I, Berk AJ, et al. (1996) How proteins recognize the TATA box. J Mol Biol 261: 239–254. 27. Pastor N, Pardo L, Weinstein H (1997) Does TATA matter? A structural exploration of the selectivity determinants in its complexes with TATA boxbinding protein. Biophys J 73: 640–652. 28. Zhao X, Herr W (2002) A regulated two-step mechanism of TBP binding to DNA: a solvent-exposed surface of TBP inhibits TATA box recognition. Cell 108: 615–627. 29. Wintjens R, Rooman M (1996) Structural classification of HTH DNA-binding domains and protein–DNA interaction modes. J Mol Biol 262: 294–313. 30. Risse G, Jooss K, Neuberg M, Bruller HJ, Muller R (1989) Asymmetrical recognition of the palindromic AP1 binding site (TRE) by Fos protein complexes. EMBO J 8: 3825–3832. 31. Leonard DA, Rajaram N, Kerppola TK (1997) Structural basis of DNA bending and oriented heterodimer binding by the basic leucine zipper domains of Fos and Jun. Proc Natl Acad Sci U S A 94: 4913–4918. 32. Ellenberger TE, Brandl CJ, Struhl K, Harrison SC (1992) The GCN4 basic region leucine zipper binds DNA as a dimer of uninterrupted a helices: crystal structure of the protein-DNA complex. Cell 71: 1223–1237. 33. Grant PA, Sterner DE, Duggan LJ, Workman JL, Berger SL (1998) The SAGA unfolds: convergence of transcription regulators in chromatin-modifying complexes. Trends Cell Biol 8: 193–197. 34. Luger K, Mader AW, Richmond RK, Sargent DF, Richmond TJ (1997) Crystal ˚ structure of the nucleosome core particle at 2.8 A resolution. Nature 389: 251–260. 35. Luger K, Richmond TJ (1998) DNA binding within the nucleosome core. Curr Opin Struct Biol 8: 33–40.
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36. Woodcock CL (2006) Chromatin architecture. Curr Opin Struct Biol 16: 213–220. 37. Edayathumangalam RS, Weyermann P, Gottesfeld JM, Dervan PB, Luger K (2004) Molecular recognition of the nucleosomal ‘‘supergroove’’. Proc Natl Acad Sci U S A 101: 6864–6869. 38. Cavazza B, Brizzolara G, Lazzarini G, Patrone E, Piccardo M, et al. (1991) Thermodynamics of condensation of nuclear chromatin. A differential scanning calorimetry study of the salt-dependent structural transitions. Biochemistry 30: 9060–9072.
39. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, et al. (2000) The Protein Data Bank. Nucleic Acids Res 28: 235–242. 40. Kannan N, Vishveshwara S (1999) Identification of side-chain clusters in protein structures by a graph spectral method. J Mol Biol 292: 441–464. 41. Jones S, Shanahan HP, Berman HM, Thornton JM (2003) Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins. Nucleic Acids Res 31: 7189–7198. 42. Cormen TH, Leiserson CE, Rivest RL, Stein C (2001) Introduction to Algorithms. 2nd edition. New York: McGraw-Hill.
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