Evidence map›Paper›PMID 25671604›Full record

ArticlePLoS genetics2015

Combining natural sequence variation with high throughput mutational data to reveal protein interaction sites.

Daniel Melamed, David L Young, Christina R Miller, Stanley Fields

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

18 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
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  5. ExploringMicrobial cell (Graz, Austria) · 2021
    Review
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  15. Efforts to make and apply humanized yeast.Briefings in functional genomics · 2016
    Review
  16. Article
  17. Article
  18. 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

4 authors at 2 institutions in 1 country.

Daniel MelamedHoward Hughes Medical Institute, University of Washington, Seattle, Washington, United States of America; Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.
David L YoungDepartment of Genome Sciences, University of Washington, Seattle, Washington, United States of America.
Christina R MillerHoward Hughes Medical Institute, University of Washington, Seattle, Washington, United States of America; Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.
Stanley FieldsHoward Hughes Medical Institute, University of Washington, Seattle, Washington, United States of America; Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America; Department of Medicine, University of Washington, Seattle, Washington, United States of America.
Howard Hughes Medical Institute · USUniversity of Washington · US

Funding

University of Washington Medical Scientist Training Program: MD/PhDT32GM007266 · NIGMS · UNIVERSITY OF WASHINGTON · PI HORWITZ, MARSHALL S. · 1985 to 2023
$30.4M
TrainingP41GM103533 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2012 to 2021
$20.7M
Howard Hughes Medical InstituteNIGMS NIH HHS 5P41 GM103533NIGMS NIH HHS P41 GM103533NIGMS NIH HHS T32 GM007266
6 · The paper itself

Abstract

Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2-RRM1) or protein-RNA (RRM2-poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution.

Indexed as

Evolution, MolecularAmino Acid SequenceAmino Acid SubstitutionBinding SitesDNA Mutational AnalysisEukaryotic Initiation Factor-4GGenetic VariationHumansMutationPoly(A)-Binding ProteinsProtein BindingProtein Interaction MapsProtein Structure, TertiarySaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSequence AlignmentEukaryotic Initiation Factor-4Gpab1 protein, S cerevisiaePoly(A)-Binding ProteinsSaccharomyces cerevisiae ProteinsTIF4631 protein, S cerevisiae

Identifiers

PMID25671604
PMCPMC4335499
OpenAlexW2089645137

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.