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Updated: Jun 12, 2026
16:41
A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected
Huiying Zhao1, Yuedong Yang, Yaoqi Zhou
1School of Informatics, Indiana University Purdue University, Indianapolis, IN 46202, USA.
Bioinformatics (Oxford, England)
|June 8, 2010
Summary
Predicting DNA binding proteins is enhanced by a new method that improves binding affinity prediction. This approach significantly boosts accuracy and sensitivity for identifying DNA-binding proteins using structural information.
Area of Science:
- Computational Biology
- Structural Bioinformatics
- Biophysics
Background:
- Accurate prediction of DNA binding proteins is crucial for understanding biological functions.
- Template-based methods require both structural similarity and accurate binding affinity prediction.
- Existing methods for predicting protein-DNA interactions have limitations in accuracy and sensitivity.
Purpose of the Study:
- To develop a novel method for predicting protein-DNA binding affinity.
- To improve the accuracy and sensitivity of structure-based DNA binding protein prediction.
- To introduce a volume-fraction correction to a statistical energy function for enhanced prediction.
Main Methods:
- A modified statistical energy function based on the distance-scaled, finite, ideal-gas reference (DFIRE) state with volume-fraction correction was developed.
- The new energy function was integrated with the TM-align structural alignment program.
- The method was benchmarked on a dataset of known DNA binding and non-binding proteins.
Main Results:
- The proposed method achieved a Matthews correlation coefficient (MCC) of 0.76, outperforming previous methods (MCC 0.69).
- High accuracy (98%), precision (93%), and sensitivity (64%) were demonstrated in predicting DNA binding proteins.
- Application to structural genomics targets identified 37 potential DNA binding proteins, with high confidence for 73% of them.
Conclusions:
- The developed method offers a highly accurate and sensitive approach for structure-based prediction of DNA binding proteins.
- This technique significantly advances the capabilities for identifying DNA-binding proteins from structural data.
- The method is available as part of the Structure-based function-Prediction On-line Tools (SPOT) package.
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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.
The primary structure of a protein is its amino acid sequence.