Evidence map›Paper›PMID 24021383›Full record

ArticleBioinformatics (Oxford, England)2013

Accounting for epistatic interactions improves the functional analysis of protein structures.

Angela D Wilkins, Eric Venner, David C Marciano, Serkan Erdin, Benu Atri, Rhonald C Lua, Olivier Lichtarge

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

19 citing papers in PubMed.

  1. Article
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  10. How mutational epistasis impairs predictability in protein evolution and design.Protein science : a publication of the Protein Society · 2016
    Article
  11. Article
  12. Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  13. Article
  14. Elucidation of G-protein and β-arrestin functional selectivity at the dopamine D2 receptor.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Prediction and redesign of protein-protein interactions.Progress in biophysics and molecular biology
    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

7 authors.

Angela D WilkinsDepartment of Molecular and Human Genetics, CIBR Center for Computational and Integrative Biomedical Research and Program in Structural and Computational Biology & Molecular Biophysics, Baylor College of Medicine, Houston, TX 77030 and Center for Human Genetic Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Eric Venner
David C Marciano
Serkan Erdin
Benu Atri
Rhonald C Lua
Olivier Lichtarge

Funding

TRAINING PROGRAM IN COMPUTATIONAL BIOLOGY AND MEDICINET15LM007093 · NLM · RICE UNIVERSITY · PI Lydia E. Kavraki · 1992 to 2026
$20.8M
Functional Determinnats in G Protein-coupled ReceptorsR01GM066099 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI LICHTARGE, OLIVIER · 2003 to 2022
$7.5M
Comparative genomics of protein structure and functionR01GM079656 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI LICHTARGE, OLIVIER · 2007 to 2019
$4.3M
NIGMS NIH HHS GM066099NIGMS NIH HHS GM079656NIGMS NIH HHS R01 GM066099NIGMS NIH HHS R01 GM079656NLM NIH HHS 5T15LM07093NLM NIH HHS T15 LM007093
6 · The paper itself

Abstract

motivationThe constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. METHODS AND

resultsWe find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions.

conclusionsOur data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. CONTACT: lichtarge@bcm.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Protein ConformationAlgorithmsBacterial ProteinsEpistasis, GeneticEvolution, MolecularLexA Repressor ProteinMolecular Sequence AnnotationMutationProteinsProteomeSequence Analysis, ProteinSerine EndopeptidasesBacterial ProteinsLexA Repressor ProteinProteinsProteomeSerine Endopeptidases

Identifiers

PMID24021383
PMCPMC3799481

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LicenceCC BY-NC
Read underepoch 390

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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.