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PLoS One. 2014 May 2;9(5):e96694. doi: 10.1371/journal.pone.0096694. eCollection 2014.

Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

Author information

1
School of Informatics, Indiana University Purdue University, Indianapolis, Indiana, United States of America; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America; QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
2
Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America; Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou University, Dezhou, Shandong, China.
3
School of Informatics, Indiana University Purdue University, Indianapolis, Indiana, United States of America; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America; Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou University, Dezhou, Shandong, China; Institute for Glycomics and School of Information and Communication Technique, Griffith University, Southport, Queensland, Australia.
4
School of Informatics, Indiana University Purdue University, Indianapolis, Indiana, United States of America; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America; Institute for Glycomics and School of Information and Communication Technique, Griffith University, Southport, Queensland, Australia.

Abstract

As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions). A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC) of 0.77 with high precision (94%) and high sensitivity (65%). We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA)] is available as an on-line server at http://sparks-lab.org.

PMID:
24792350
PMCID:
PMC4008587
DOI:
10.1371/journal.pone.0096694
[Indexed for MEDLINE]
Free PMC Article

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