Nucleic Acids Research, 2002, Vol. 30, No. 20 4442-4451
© 2002 Oxford University Press
Additivity in protein–DNA interactions: how good an approximation is it?
1 Department of Genetics, Campus Box 8232, Washington University, School of Medicine, St Louis, MO 63110, USA, 2 Department of Human Genetics and Center for Computational Biology and Bioinformatics and Cancer Institute, University of Pittsburgh, PA 15261, USA and 3 Division of Genetics, Department of Medicine and Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, and Harvard-MIT Division of Health Sciences and Technology, Boston, MA 02115, USA
*To whom correspondence should be addressed. Tel: +1 314 747 5534; Fax: +1 314 362 7855; Email: stormo{at}genetics.wustl.edu
Man and Stormo and Bulyk et al. recently presented their results on the study of the DNA binding affinity of proteins. In both of these studies the main conclusion is that the additivity assumption, usually applied in methods to search for binding sites, is not true. In the first study, the analysis of binding affinity data from the Mnt repressor protein bound to all possible DNA (sub)targets at positions 16 and 17 of the binding site, showed that those positions are not independent. In the second study, the authors analysed DNA binding affinity data of the wild-type mouse EGR1 protein and four variants differing on the middle finger. The binding affinity of these proteins was measured to all 64 possible trinucleotide (sub)targets of the middle finger using microarray technology. The analysis of the measurements also showed interdependence among the positions in the DNA target. In the present report, we review the data of both studies and we re- analyse them using various statistical methods, including a comparison with a multiple regression approach. We conclude that despite the fact that the additivity assumption does not fit the data perfectly, in most cases it provides a very good approximation of the true nature of the specific protein–DNA interactions. Therefore, additive models can be very useful for the discovery and prediction of binding sites in genomic DNA.
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