Evidence map›Paper›PMID 18536016›Full record

ArticleProteins2008

Experimental identification of specificity determinants in the domain linker of a LacI/GalR protein: bioinformatics-based predictions generate true positives and false negatives.

Sarah Meinhardt, Liskin Swint-Kruse

Abstract read
In one paragraph

Article in Proteins, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. ENcyclopedia of TRAnscription Factors in Bacteria and Archaea genomes (ENTRAF) version 2.0.Database : the journal of biological databases and curation · 2025
    Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Fructose-1-kinase has pleiotropic roles inbioRxiv : the preprint server for biology · 2023
    Article
  8. Review
  9. Recent trends in biocatalysis.Chemical Society reviews · 2021
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Tailor-made transcriptional biosensors for optimizing microbial cell factories.Journal of industrial microbiology & biotechnology · 2017
    Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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.

Sarah MeinhardtDepartment of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, Kansas 66160, USA.
Liskin Swint-Kruse

Funding

TRAFFICKING OF THE PLASMA MEMBRANE CA2+-ATPASE TO RAFTSP20RR017708 · NCRR · UNIVERSITY OF KANSAS LAWRENCE · PI FISCHER, CHRISTOPHER JAMES · 2002 to 2011
$20.1M
Functional effects of exchanging domains and linkers in transcription regulatorsR01GM079423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI SWINT-KRUSE, LISKIN · 2007 to 2011
$1.6M
NCRR NIH HHS P20 RR017708NCRR NIH HHS P20 RR17708NIGMS NIH HHS GM079423NIGMS NIH HHS R01 GM079423
6 · The paper itself

Abstract

In protein families, conserved residues often contribute to a common general function, such as DNA-binding. However, unique attributes for each homolog (e.g. recognition of alternative DNA sequences) must arise from variation in other functionally-important positions. The locations of these "specificity determinant" positions are obscured amongst the background of varied residues that do not make significant contributions to either structure or function. To isolate specificity determinants, a number of bioinformatics algorithms have been developed. When applied to the LacI/GalR family of transcription regulators, several specificity determinants are predicted in the 18 amino acids that link the DNA-binding and regulatory domains. However, results from alternative algorithms are only in partial agreement with each other. Here, we experimentally evaluate these predictions using an engineered repressor comprising the LacI DNA-binding domain, the LacI linker, and the GalR regulatory domain (LLhG). "Wild-type" LLhG has altered DNA specificity and weaker lacO(1) repression compared to LacI or a similar LacI:PurR chimera. Next, predictions of linker specificity determinants were tested, using amino acid substitution and in vivo repression assays to assess functional change. In LLhG, all predicted sites are specificity determinants, as well as three sites not predicted by any algorithm. Strategies are suggested for diminishing the number of false negative predictions. Finally, individual substitutions at LLhG specificity determinants exhibited a broad range of functional changes that are not predicted by bioinformatics algorithms. Results suggest that some variants have altered affinity for DNA, some have altered allosteric response, and some appear to have changed specificity for alternative DNA ligands.

Indexed as

Computational BiologyAmino Acid SequenceAmino Acid SubstitutionBacterial ProteinsEscherichia coliEscherichia coli ProteinsLac RepressorsMolecular Sequence DataProtein Structure, SecondaryProtein Structure, TertiaryRecombinant Fusion ProteinsRepressor ProteinsSequence Homology, Amino AcidBacterial ProteinsEscherichia coli ProteinsGalactose repressor proteinsLacI protein, E coliLac RepressorsRecombinant Fusion ProteinsRepressor Proteins

Identifiers

PMID18536016
PMCPMC2585155

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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.