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Method for Efficient Refolding and Purification of Chemoreceptor Ligand Binding Domain
Published on: December 12, 2017
Conformational model for binding site recognition by the E.coli MetJ transcription factor
R Liu1, T W Blackwell, D J States
1Center for Computational Biology and Department of Genetics, Washington University School of Medicine, 700 S. Euclid Ave, St Louis, MO 63110, USA.
This study introduces a novel DNA conformation model to improve transcription factor binding site identification. The hybrid model enhances prediction accuracy and reduces false positives, discovering new binding sites in E. coli.
Area of Science:
- Molecular Biology
- Bioinformatics
- Structural Biology
Background:
- Current methods for identifying DNA sequence-specific binding sites, like position-specific weight matrices, lack sensitivity and specificity.
- DNA's double helix exhibits sequence-dependent conformational variations influencing macromolecular interactions.
- These conformational variations are hypothesized to play a role in transcription factor binding site recognition.
Purpose of the Study:
- To develop and validate a computational model incorporating DNA conformational information for improved transcription factor binding site prediction.
- To enhance the predictive power of existing models by integrating sequence and structure data.
- To identify novel functional transcription factor binding sites within a genome.
Main Methods:
- Development of sequence-dependent DNA helix distortion conformation models.
- Definition of a tertiary structure template for the MetJ repressor binding site using these models.
- Creation of a hybrid model combining conformational and primary sequence profile data.
- Genome-wide search of E. coli using the hybrid model.
Main Results:
- The conformational model identified distinct features of protein binding sites compared to sequence-based profiles.
- A hybrid model integrating conformational and sequence data demonstrated improved discriminatory power.
- The hybrid model successfully identified known MetJ binding sites in E. coli.
- Several novel MetJ binding sites were discovered, including upstream of metK and abc genes, with a significantly lower false positive rate than sequence profile methods.
Conclusions:
- Incorporating DNA conformational information significantly enhances the accuracy of transcription factor binding site prediction.
- The developed hybrid model offers a more sensitive and specific approach for identifying regulatory elements.
- This method facilitates the discovery of novel functional binding sites, advancing our understanding of gene regulation.
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