Evidence map›Paper›PMID 37990674›Full record

ArticleQuantitative biology (Beijing, China)2018

Deciphering the protein-DNA code of bacterial winged helix-turn-helix transcription factors.

Adam P Joyce, James J Havranek

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. ENcyclopedia of TRAnscription Factors in Bacteria and Archaea genomes (ENTRAF) version 2.0.Database : the journal of biological databases and curation · 2025
    Article
  2. Article
  3. The ArcAB Two-Component System: Function in Metabolism, Redox Control, and Infection.Microbiology and molecular biology reviews : MMBR · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Adam P JoyceProgram in Developmental, Regenerative, and Stem Cell Biology, Washington University in St. Louis, St. Louis, MO 63110, USA.
James J HavranekDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, MO 63110, USA.

Funding

A MOLECULAR TOOLKIT FOR SINGLE-MOLECULE PROTEIN SEQUENCINGR01GM101602 · NIGMS · WASHINGTON UNIVERSITY · PI HAVRANEK, JAMES J · 2012 to 2016
$1.4M
NIGMS NIH HHS R01 GM101602
6 · The paper itself

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.

Indexed as

SELEXspecificity determinantstranscription factortwo-component signalingwinged helix-turn-helix

Identifiers

PMID37990674
PMCPMC10662834

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.