Evidence map›Paper›PMID 27870911›Full record

ArticlePloS one2016

Long-Range Epistasis Mediated by Structural Change in a Model of Ligand Binding Proteins.

Erik D Nelson, Nick V Grishin

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Molecular ensembles make evolution unpredictable.Proceedings of the National Academy of Sciences of the United States of America · 2017
    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.

Erik D NelsonHoward Hughes Medical Institute, University of Texas Southwestern Medical Center, Room ND10.124, Dallas, Texas, United States of America.ORCID http://orcid.org/0000-0001-8345-227X
Nick V GrishinHoward Hughes Medical Institute, University of Texas Southwestern Medical Center, Room ND10.124, Dallas, Texas, United States of America.

Funding

Computational methods for structural-functional studies of proteinsR01GM094575 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI GRISHIN, NICK V. · 2010 to 2017
$2.4M
NIGMS NIH HHS R01 GM094575
6 · The paper itself

Abstract

Recent analyses of amino acid mutations in proteins reveal that mutations at many pairs of sites are epistatic-i.e., their effects on fitness are non-additive-the combined effect of two mutations being significantly larger or smaller than the sum of their effects considered independently. Interestingly, epistatic sites are not necessarily near each other in the folded structure of a protein, and may even be located on opposite sides of a molecule. However, the mechanistic reasons for long-range epistasis remain obscure. Here, we study long-range epistasis in proteins using a previously developed model in which off-lattice polymers are evolved under ligand binding constraints. Epistatic effects in the model are qualitatively similar to those recently reported for small proteins, and many are long-range. We find that a major reason for long-range epistasis is conformational change-a recurrent theme in both positive and negative epistasis being the transfer, or exchange of material between the ordered nucleus, which supports the binding site, and the liquid-like surface of a folded molecule. These local transitions in phase and folded structure are largely responsible for long-range epistasis in our model.

Indexed as

Epistasis, GeneticMutationBinding SitesEvolution, MolecularLigandsModels, GeneticModels, MolecularProtein BindingProtein ConformationProtein FoldingProteinsLigandsProteins

Identifiers

PMID27870911
PMCPMC5117711

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.