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Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome. Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...

Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Cis-regulatory Sequences

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

Cis-regulatory Sequences

Cis-regulatory Sequences

Combinatorial Gene Control

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...

General Transcription Factors

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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...

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In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

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Rosetta comparative modeling for library design: Engineering alternative inducer specificity in a transcription

Ramesh K Jha¹, Subhendu Chakraborti¹, Theresa L Kern¹

¹Bioscience Division, Los Alamos National Laboratory, Los Alamos, New Mexico, 87545.

|May 15, 2015

Summary

This study introduces a novel computational method to engineer protein function, overcoming limitations of traditional structure-based and directed evolution techniques. The approach successfully modified a transcription factor to respond to new molecules while maintaining specificity.

Keywords:

BLOSUM62 Rosetta altered specificity comparative modeling ligand docking pobR protein engineering transcription factor

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Area of Science:

Protein Engineering
Computational Biology
Molecular Biology

Background:

Traditional protein engineering methods like structure-based mutagenesis and directed evolution have limitations.
Structure-based methods require scarce crystal structures, while directed evolution is often random and lacks rationalization.
A need exists for rational approaches to protein engineering that are efficient and do not solely rely on precise structural data.

Purpose of the Study:

To develop and apply a novel computational strategy for rational protein engineering.
To engineer a transcription factor (TF) for altered ligand specificity and enhanced function.
To demonstrate the applicability of Rosetta modeling protocols in protein engineering without prior structural information.

Main Methods:

Combined comparative modeling of dimer structures, ab initio loop reconstruction, and ligand docking to identify key mutagenesis sites.
Created a rationally reduced library focused on ligand-contacting residues for efficient oligonucleotide synthesis.
Applied a single-cell flow cytometry selection system to screen for desired protein variants based on transcriptional induction.

Main Results:

Successfully engineered the inducer-binding domain of the Acinetobacter transcription factor pobR.
Achieved gain-of-function for induction by 3,4-dihydroxy benzoate (34DHB) and enhanced sensitivity to the native inducer 4-hydroxy benzoate (4HB).
Demonstrated high specificity, with no response to the chemically similar molecule 2-hydroxy benzoate (2HB).

Conclusions:

The integrated computational approach enables rational engineering of protein functionality, even without precise structural data.
This method allows for the creation of focused mutant libraries with controlled substitutions, improving efficiency.
The successful engineering of pobR highlights the power of Rosetta modeling for designing transcription factors with novel specificities.