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Bioinformatics 2007 23(13):i297-i304; doi:10.1093/bioinformatics/btm215
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Inferring protein–DNA dependencies using motif alignments and mutual information

Shaun Mahony 1,*, Philip E. Auron 2,3 and Panayiotis V. Benos 1,4,5,*

1Department of Computational Biology, 2Department of Molecular Genetics and Biochemistry, School of Medicine, University of Pittsburgh, 3Department of Biological Sciences, Duquesne University, 4Department of Human Genetics, Graduate School of Public Health and 5University of Pittsburgh Cancer Institute, School of Medicine, University of Pittsburgh, Pittsburgh, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Mutual information can be used to explore covarying positions in biological sequences. In the past, it has been successfully used to infer RNA secondary structure conformations from multiple sequence alignments. In this study, we show that the same principles allow the discovery of transcription factor amino acids that are coevolving with nucleotides in their DNA-binding targets.

Results: Given an alignment of transcription factor binding domains, and a separate alignment of their DNA target motifs, we demonstrate that mutually covarying base-amino acid positions may indicate possible protein–DNA contacts. Examples explored in this study include C2H2 zinc finger, homeodomain and bHLH DNA-binding motif families, where a number of known base-amino acid contacting positions are identified. Mutual information analyses may aid the prediction of base-amino acid contacting pairs for particular transcription factor families, thereby yielding structural insights from sequence information alone. Such inference of protein–DNA contacting positions may guide future experimental studies of DNA recognition.

Contact: shaun.mahony{at}ccbb.pitt.edu or benos{at}pitt.edu


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