Transcription factors are proteins that bind to short sequence motifs on DNA typically called cisregulatory
elements. These cis-regulatory elements are characterized by their linear base pair sequence as
well as specific features of their three-dimensional structure. These structural features play an important role
in the recognition and binding of proteins to DNA.
Various computational approaches have been used to model protein-DNA interaction interfaces at an
atomic level. We describe their most promising scope of applications and discuss their assets and drawbacks.
Structure-based computational methods require three-dimensional protein-DNA complexes gained either by
X-ray crystallography or by in silico modeling. Docking approaches, molecular dynamics, and Monte Carlo
simulations are promising techniques to model transcription factor-DNA complexes in silico. Both experimentally
determined and ab initio designed protein-DNA complexes can be analyzed by statistical methods.
We describe the differences of several statistical potentials and how they were obtained. Position weight
matrices obtained from structure-based approaches can then be used to scan efficiently and more accurately
genome-wide for transcription factor binding sites.
In a case study on WRKY-DNA complexes we present a computational modeling technique for the ab
initio design of a specific transcription factor-DNA complex. This procedure is generally applicable to similar
problems. The resulting three-dimensional interaction interface provides the basis for studying specific side
chain and base interactions. Moreover, the results give hints towards varying specificity and function of
different representatives of the WRKY protein family. This study provides valuable insights into the interplay
between transcription factors and DNA in three dimensions and opens up new perspectives for their design.
Keywords: three-dimensional structure, 3D, in silico modelling, WRKY, transcription factors, DNA binding domain, DNAprotein
interface, DNA-protein interacion, ab initio design, Monte Carlo simulations, molecular dynamics, docking, forcefield
docking, plant transcription factors, W-box, position specific scoring matricies, simulations.
