Tailor-Made Zinc-Finger Transcription Factors Activate FLO11 Gene Expression with Phenotypic Consequences in the Yeast Saccharomyces cerevisiae

Cys2His2 zinc fingers are eukaryotic DNA-binding motifs, capable of distinguishing different DNA sequences, and are suitable for engineering artificial transcription factors. In this work, we used the budding yeast Saccharomyces cerevisiae to study the ability of tailor-made zinc finger proteins to activate the expression of the FLO11 gene, with phenotypic consequences. Two three-finger peptides were identified, recognizing sites from the 5′ UTR of the FLO11 gene with nanomolar DNA-binding affinity. The three-finger domains and their combined six-finger motif, recognizing an 18-bp site, were fused to the activation domain of VP16 or VP64. These transcription factor constructs retained their DNA-binding ability, with the six-finger ones being the highest in affinity. However, when expressed in haploid yeast cells, only one three-finger recombinant transcription factor was able to activate the expression of FLO11 efficiently. Unlike in the wild-type, cells with such transcriptional activation displayed invasive growth and biofilm formation, without any requirement for glucose depletion. The VP16 and VP64 domains appeared to act equally well in the activation of FLO11 expression, with comparable effects in phenotypic alteration. We conclude that the functional activity of tailor-made transcription factors in cells is not easily predicted by the in vitro DNA-binding activity

Template-based structure prediction and classification of transcription factors in Arabidopsis thaliana

Transcription factors (TFs) play important roles in plants. However, there is no systematic study of their structures and functions of most TFs in plants. Here, we performed template-based structure prediction for all TFs in Arabidopsis thaliana, with their full-length sequences as well as C-terminal and N-terminal regions. A total of 2918 model structures were obtained with a high confidence score. We find that TF families employ only a smaller number of templates for DNA-binding domains (DBD) but a diverse number of templates for transcription regulatory domains (TRD). Although TF families are classified according to DBD, their sizes have a significant correlation with the number of unique non-DNA-binding templates employed in the family (Pearson correlation coefficient of 0.74). That is, the size of TF family is related to its functional diversity. Network analysis reveals new connections between TF families based on shared TRD or DBD templates; 81% TF families share DBD and 67% share TRD templates. Two large fully connected family clusters in this network are observed along with 69 island families. In addition, 25 genes with unknown functions are found to be DNA-binding and/or TF factors according to predicted structures. This work provides a global view of the classification of TFs based on their DBD or TRD templates, and hence, a deeper understanding of DNA-binding and regulatory functions from structural perspective. All structural models of TFs are deposited in the online database for public usage at http://sysbio.unl.edu/AthTF

Docking macromolecules with flexible segments

International audienceWe address a major obstacle to macromolecular docking algorithms by presenting a new method that takes into account the induced conformational adjustment of flexible loops situated at a protein/macromolecule interface. The method, MC2, is based on a multiple copy representation of the loops, coupled with a Monte Carlo conformational search of the relative position of the macromolecules and their side chain conformations. The selection of optimal loop conformations takes place during Monte Carlo cycling by the iterative adjustment of the weight of each copy. We describe here the parameterization of the method and trials on a protein-DNA complex of known 3-D structure, involving the Drosophila prd paired domain protein and its target oligonucleotide Wenqing, X. et al., Cell 1995, 80, 639. We demonstrate that our algorithm can correctly configure and position this protein, despite its relatively complex interactions with both grooves of DNA.We address a major obstacle to macromolecular docking algorithms by presenting a new method that takes into account the induced conformational adjustment of flexible loops situated at a protein/macromolecule interface. The method, MC2, is based on a multiple copy representation of the loops, coupled with a Monte Carlo conformational search of the relative position of the macromolecules and their side chain conformations. The selection of optimal loop conformations takes place during Monte Carlo cycling by the iterative adjustment of the weight of each copy. We describe here the parameterization of the method and trials on a protein-DNA complex of known 3-D structure, involving the Drosophila prd paired domain protein and its target oligonucleotide Wenqing, X. et al., Cell 1995, 80, 639. We demonstrate that our algorithm can correctly configure and position this protein, despite its relatively complex interactions with both grooves of DNA