Protein Dna Interaction Lab Report

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Protein-DNA Interaction



Protein–DNA interactions play a major role in all fields of genetics from regulation and transcription of individual genes to repair of damaged sequences, even to the stabilization of DNA in chromatin and the replication of entire genomes. It is estimated that 2–3% of prokaryotic and 6–7% of eukaryotic genes code for DNA-binding proteins. Additionally, many of these proteins do not merely bind DNA, but also interact with other proteins and sometimes, as is shown in the example of RNA polymerase, only display theirfull activity when organized in multimeric complexes.

Protein recognition of specific sequences on the DNA double
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Still, the liberation of water molecules constitutes the most important contribution to T_S0; the actual complex formation lowers entropy. Further destabilizing enthalpy contributions result when complex formation forces one of the partners into a disadvantageous conformation. In many protein–DNA complexes the DNA double helix is bent from its canonical B-conformation in this manner.

Methods to Study Protein–DNA Interactions
The methods used to examine protein–DNA interactions are similar to those that have already been described in the first part of this chapter .

Method Experiment Results
DNase footprinting Binding to a protein protects DNA. The DNA is first either radiolabeled or chemically marked and then exposed to DNase (or in situ generated OH radicals) and then analyzed by gel electrophoresis.
The DNA target sequence can be determined. Varying the concentration leads to binding constants. In addition, the influence of activating or inhibiting chemical can be assessed.
Electrophoretic mobility shift assays (EMSA or band shift)
Gel electrophoresis under native, nondenaturing conditions of the protein–DNA complex. Pure DNA serves as the standard. If the protein is bound the complex will travel at lower velocity and hence the band will appear shifted compared to the DNA alone. Using different DNA oligonucleotides enables the determination of target sequences. Varying the
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One of the great challenges of systems biology is to translate and summarize this vast amount of information in so-called regulatory networks that can be simulated in computational models . The long-term goal is to be able to simulate and ultimately predict the responses of cells and organism to a changing environment. In order to construct regulatory networks, the system can be divided into three organizational levels. The lowest level is represented by the interactions of one single element (transcription factor) with its target DNA promoter . This interaction can either activate or repress the expression of the downstream gene(s). In many, but not all, cases is the DNA-binding activity of the transcription factor itself that is regulated, for instance by binding of a small molecule or even a single atom such as iron. The next level is composed of certain network motifs where the single transcriptions factor is part of a regulatory module. Three examples of such motifs are depicted in Fig. 24.9 B. The single-input module (SIM) consists of one transcription factor that controls a number of genes. The feed-forward loop (FFL) is represented by one transcription factor that activates the expression of another transcription factor. Regulons are characterized by several transcription

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