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

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: ¤ Current address: Max Planck Institute for Molecular Genetics, Berlin, Germany . These authors contributed equally to this work.

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...
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