Evidence map›Paper›PMID 16085755›Full record

ArticleNucleic acids research2005

Predicting specificity-determining residues in two large eukaryotic transcription factor families.

Jason E Donald, Eugene I Shakhnovich

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Nucleic acids research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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.

Jason E DonaldDepartment of Chemistry and Chemical Biology, Harvard University 12 Oxford Street, Cambridge, MA 02138, USA.
Eugene I Shakhnovich

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Certain amino acid residues in a protein, when mutated, change the protein's function. We present an improved method of finding these specificity-determining positions that uses all the protein sequence data available for a family of homologous proteins. We study in detail two families of eukaryotic transcription factors, basic leucine zippers and nuclear receptors, because of the large amount of sequences and experimental data available. These protein families also have a clear definition of functional specificity: DNA-binding specificity. We compare our results to three other methods, including the evolutionary trace algorithm and a method that depends on orthology relationships. All of the predictions are compared to the available mutational and crystallographic data. We find that our method provides superior predictions of the known specificity-determining residues and also predicts residue positions within these families that deserve further study for their roles in functional specificity.

Indexed as

AlgorithmsAnimalsDNA-Binding ProteinsLeucine ZippersMutationProtein KinasesRatsReceptors, Cytoplasmic and NuclearReceptors, GlucocorticoidSaccharomyces cerevisiae ProteinsSequence Analysis, ProteinTranscription FactorsZinc FingersDNA-Binding ProteinsProtein KinasesReceptors, Cytoplasmic and NuclearReceptors, GlucocorticoidSaccharomyces cerevisiae ProteinsTranscription Factors

Identifiers

PMID16085755
PMCPMC1183107

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.