ArticleQuantitative biology (Beijing, China)2018
Deciphering the protein-DNA code of bacterial winged helix-turn-helix transcription factors.
Article in Quantitative biology (Beijing, China), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- ENcyclopedia of TRAnscription Factors in Bacteria and Archaea genomes (ENTRAF) version 2.0.Database : the journal of biological databases and curation · 2025Article
- Exploring the mono-/bistability range of positively autoregulated signaling systems in the presence of competing transcription factor binding sites.PLoS computational biology · 2022Article
- The ArcAB Two-Component System: Function in Metabolism, Redox Control, and Infection.Microbiology and molecular biology reviews : MMBR · 2022Review
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Authors and funding
2 authors.
Funding
Abstract
Background: Sequence-specific binding by transcription factors (TFs) plays a significant role in the selection and regulation of target genes. At the protein:DNA interface, amino acid side-chains construct a diverse physicochemical network of specific and non-specific interactions, and seemingly subtle changes in amino acid identity at certain positions may dramatically impact TF:DNA binding. Variation of these specificity-determining residues (SDRs) is a major mechanism of functional divergence between TFs with strong structural or sequence homology. Methods: In this study, we employed a combination of high-throughput specificity profiling by SELEX and Spec-seq, structural modeling, and evolutionary analysis to probe the binding preferences of winged helix-turn-helix TFs belonging to the OmpR sub-family in Results: We found that Conclusions: Overall, our work provides evidence for a common structural code for sequence-specific wHTH:DNA interactions, and demonstrates that surprisingly modest residue changes can enable recognition of highly divergent sequence motifs. Further examination of SDR predictions will likely reveal additional mechanisms controlling the evolutionary divergence of this important class of transcriptional regulators.
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