Computational mapping of DNA-binding protein affinity landscapes

Lydia Freddolino, University of Michigan

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Transcription factors and other DNA-binding proteins shape the behavior of all cells, coordinating gene expression patterns in response to internal or external cues. Our ability to understand and manipulate cellular behavior thus relies on our understanding of their transcriptional regulatory networks, including the locations and occupancies of transcription factor binding sites. Those binding sites, in turn, are dictated by the binding affinity of each transcription factor for different DNA sequences. These binding affinity landscapes can at present be determined only through costly and laborious experiments. We will apply the massive computing resources provided by Blue Waters to map the binding affinity landscapes of several human transcription factors, using rigorous, fully atomistic molecular dynamics simulations on the interactions of those transcription factors with varied DNA sequences. The results of these calculations will provide us with unprecedented insight into the biophysics underlying transcription factor specificity, which we will subsequently use to enable more efficient computational estimations of transcription factor binding affinity landscapes that could routinely supplement or replace experimental results.