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Assessment of the optimization of affinity and specificity at protein-DNA interfaces.

Ashworth J, Baker D - Nucleic Acids Res. (2009)

Bottom Line: The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity.Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface.The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. ashwortj@u.washington.edu

ABSTRACT
The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein-DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.

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Distributions of optimality for affinity [Equation (1)] and specificity [Equation (3)] in four catagories of protein–DNA interfaces. Red: helical transcription factors; green: restriction endonucleases; blue: homing endonucleases; black: nonspecific enzymes. Histogram bin centers are indicated on the horizontal axes. Only positions at which mutation to glycine is predicted to result in the loss of >3 kcal/mol of binding energy were included.
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Figure 2: Distributions of optimality for affinity [Equation (1)] and specificity [Equation (3)] in four catagories of protein–DNA interfaces. Red: helical transcription factors; green: restriction endonucleases; blue: homing endonucleases; black: nonspecific enzymes. Histogram bin centers are indicated on the horizontal axes. Only positions at which mutation to glycine is predicted to result in the loss of >3 kcal/mol of binding energy were included.

Mentions: We next analyzed a larger set of 57 high-resolution crystal structures of protein–DNA complexes, including helical-motif transcription factors, restriction endonucleases, homing endonucleases and nonspecific interfaces. Figure 2 compares the the extent to which native amino acids are optimal for DNA-binding affinity and specificity across these different classes. The extent to which amino acids are predicted to be optimized for affinity appears roughly equivalent across all categories (Figure 2B). In contrast, more residues are found to be optimized for specificity in the classes that exhibit sequence specific binding (Figure 2A).Figure 2.


Assessment of the optimization of affinity and specificity at protein-DNA interfaces.

Ashworth J, Baker D - Nucleic Acids Res. (2009)

Distributions of optimality for affinity [Equation (1)] and specificity [Equation (3)] in four catagories of protein–DNA interfaces. Red: helical transcription factors; green: restriction endonucleases; blue: homing endonucleases; black: nonspecific enzymes. Histogram bin centers are indicated on the horizontal axes. Only positions at which mutation to glycine is predicted to result in the loss of >3 kcal/mol of binding energy were included.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2691843&req=5

Figure 2: Distributions of optimality for affinity [Equation (1)] and specificity [Equation (3)] in four catagories of protein–DNA interfaces. Red: helical transcription factors; green: restriction endonucleases; blue: homing endonucleases; black: nonspecific enzymes. Histogram bin centers are indicated on the horizontal axes. Only positions at which mutation to glycine is predicted to result in the loss of >3 kcal/mol of binding energy were included.
Mentions: We next analyzed a larger set of 57 high-resolution crystal structures of protein–DNA complexes, including helical-motif transcription factors, restriction endonucleases, homing endonucleases and nonspecific interfaces. Figure 2 compares the the extent to which native amino acids are optimal for DNA-binding affinity and specificity across these different classes. The extent to which amino acids are predicted to be optimized for affinity appears roughly equivalent across all categories (Figure 2B). In contrast, more residues are found to be optimized for specificity in the classes that exhibit sequence specific binding (Figure 2A).Figure 2.

Bottom Line: The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity.Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface.The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. ashwortj@u.washington.edu

ABSTRACT
The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein-DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein-DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein-DNA interfaces.

Show MeSH