Towards understanding the molecular recognition process in prokaryotic zinc-finger domain

Eukaryotic Cys2His2 zinc finger domain is one of the most common and important structural motifs involved in protein-DNA interaction. The recognition motif is characterized by the tetrahedral coordination of a zinc ion by conserved cysteine and histidine residues. We have characterized the prokaryotic Cys2His2 zinc finger motif, included in the DNA binding region (Ros87) of Ros protein from Agrobacterium tumefaciens, demonstrating that, although possessing a similar zinc coordination sphere, this domain presents significant differences from its eukaryotic counterpart. Furthermore, basic residues flanking the zinc binding region on either side have been demonstrated, by Electrophoretic Mobility Shift Assay (EMSA) experiments, to be essential for Ros DNA binding. In spite of this wealth of knowledge, the structural details of the mechanism through which the prokaryotic zinc fingers recognize their target genes are still unclear. Here, to gain insights into the molecular DNA recognition process of prokaryotic zinc finger domains we applied a strategy in which we performed molecular docking studies using a combination of Nuclear Magnetic Resonance (NMR) and Molecular Dynamics (MD) simulations data. The results demonstrate that the MD ensemble provides a reasonable picture of Ros87 backbone dynamics in solution. The Ros87-DNA model indicates that the interaction involves the first two residue of the first α-helix, and several residues located in the basic regions flanking the zinc finger domain. Interestingly, the prokaryotic zinc finger domain, mainly with the C-terminal tail that is wrapped around the DNA, binds a more extended recognition site than the eukaryotic counterpart. Our analysis demonstrates that the introduction of the protein flexibility in docking studies can improve, in terms of accuracy, the quality of the obtained models and could be particularly useful for protein showing high conformational heterogeneity as well as for computational drug design applications.