A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling

作者：Zhou, Weiqiang^*; Yan, Hong

来源：Bioinformatics, 2010, 26(20): 2541-2548.

DOI：10.1093/bioinformatics/btq478

• FACTOR-BINDING SITES
• SCORING FUNCTION
• ALL-ATOM
• INTERFACES
• DOCKING
• MACROMOLECULES
• REPRESENTATION
• RECOGNITION
• INFORMATION
• COMPUTATION

Motivation: Protein-DNA interaction has significant importance in many biological processes. However, the underlying principle of the molecular recognition process is still largely unknown. As more high-resolution 3D structures of protein-DNA complex are becoming available, the surface characteristics of the complex become an important research topic.
Result: In our work, we apply an alpha shape model to represent the surface structure of the protein-DNA complex and developed an interface-atom curvature-dependent conditional probability discriminatory function for the prediction of protein-DNA interaction. The interface-atom curvature-dependent formalism captures atomic interaction details better than the atomic distance-based method. The proposed method provides good performance in discriminating the native structures from the docking decoy sets, and outperforms the distance-dependent formalism in terms of the z-score. Computer experiment results show that the curvature-dependent formalism with the optimal parameters can achieve a native z-score of -8.17 in discriminating the native structure from the highest surface-complementarity scored decoy set and a native z-score of -7.38 in discriminating the native structure from the lowest RMSD decoy set. The interface-atom curvature-dependent formalism can also be used to predict apo version of DNA-binding proteins. These results suggest that the interface-atom curvature-dependent formalism has a good prediction capability for protein-DNA interactions.

• 出版日期2010-10
• 单位香港城市大学