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Incorporation of Local Structural Preference Potential Improves Fold Recognition

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  • Yun Hu
  • Xiaoxi Dong
  • Aiping Wu
  • Yang Cao
  • Liqing Tian
  • Taijiao Jiang

Abstract

Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Here we introduce another type of information, local structural preference potentials of 3-residue and 9-residue fragments, for fold recognition. By combining the two local structural preference potentials with the widely used sequence profile, secondary structure information and hydrophobic score, we have developed a new threading method called FR-t5 (fold recognition by use of 5 terms). In benchmark testings, we have found the consideration of local structural preference potentials in FR-t5 not only greatly enhances the alignment accuracy and recognition sensitivity, but also significantly improves the quality of prediction models.

Suggested Citation

  • Yun Hu & Xiaoxi Dong & Aiping Wu & Yang Cao & Liqing Tian & Taijiao Jiang, 2011. "Incorporation of Local Structural Preference Potential Improves Fold Recognition," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
    • Handle: RePEc:plo:pone00:0017215
    DOI: 10.1371/journal.pone.0017215
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    Cited by:

    1. Wentao Dai & Tingrui Song & Xuan Wang & Xiaoyang Jin & Lizong Deng & Aiping Wu & Taijiao Jiang, 2014. "Improvement in Low-Homology Template-Based Modeling by Employing a Model Evaluation Method with Focus on Topology," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-9, February.

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