Transcription is controlled through a number of mechanisms including the specific interactions between DNA and regulatory proteins. Identifying precisely which DNA sequences interact with transcription factors will give us a profound insight into gene regulation.Many bioinformatics approaches are based on position weight matrices (PWM) that can be used for a probabilistic search of the genomic sequence. Recent in vitro methods such as Protein Binding Microarrays (PBM) have allowed the unbiased large-scale assessment of protein-DNA affinity, although the interpretation of PBM data is a matter of debate. We have employed a third method, based on protein structure and biophysical simulation, to predict possible solutions from the sequence space.In order to evaluate the merit of each method, we compared our results with PWM and PBM-based predictions for the Notch downstream effector CSL. Using genome-wide CSL binding data from chromatin immunoprecipitation (ChIP) experiments, we investigated how well the methods perform to explain CSL ChIP peaks.

Structure-based prediction of transcription factor specificity: Comparison to position weight matrix and in vitro prediction methods

243rd National Meeting (2012)

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