Additivity in protein-DNA interactions: how good an approximation is it?

Abstract

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.

Specificity landscapes of DNA binding molecules elucidate biological function

“…However placing this finger at the N terminus leads to a significant diminution of its sequence specificity. This observation is consistent with previous observations of nonadditive behavior of these modules (34) and recent reports that the predictability of sequence recognition by engineered ZFPs is less than desired (41). Taken together, SSLs show that hairpin polyamides are among the most specific DNA binders.…”

“…2A left panel) (34)(35)(36). To surmount this limitation, we created the SSL as an adaptable tool to display and interpret the full recognition preferences of DNA binding molecules (Fig.…”

Improved Models for Transcription Factor Binding Site Identification Using Nonindependent Interactions

“…One such unanswered question is the average effect size of interactions between positions. Even though statistically significant interactions may exist between positions within the binding site of a TF, if their effect size is small, then the PWM model may still provide a good approximation of the true TF specificity (Benos et al 2002). However, if the effect size is large, then more complex statistical models, requiring additional parameters, must be used to adequately model the specificity of the TF.…”

Decoding transcriptional regulatory interactions

“…This assumption yields the standard position-weightmatrix representation of a binding site. Recent work continues to point to the accuracy of the additive approximation [26], particularly for sequences similar to the most favored sequence [31]. The main cause for non-additive contributions may be DNA backbone deformations [29], pointing again to the important of incorporating DNA flexibility in simulations.…”