Evidence map›Paper›PMID 27253392›Full record

ArticlePLoS computational biology2016

Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches.

Tobias Sikosek, Heinrich Krobath, Hue Sun Chan

Abstract read
In one paragraph

Article in PLoS computational biology, 2016. 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

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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Seesaw protein: Design of a protein that adopts interconvertible alternative functional conformations and its dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Article
  7. Review
  8. SSDraw: Software for generating comparative protein secondary structure diagrams.Protein science : a publication of the Protein Society · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Protein ensembles link genotype to phenotype.PLoS computational biology · 2019
    Review
  16. Conformational dynamics and enzyme evolution.Journal of the Royal Society, Interface · 2018
    Review
  17. Article
  18. Article
  19. 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

3 authors.

Tobias SikosekDepartments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-9929-3525
Heinrich KrobathDepartments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
Hue Sun ChanDepartments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein's folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the GA all-α and GB α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between GA and GB. In agreement with experiment, we observe conformational switching from GA to GB upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp GA/GB switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.

Indexed as

Evolution, MolecularModels, ChemicalComputer SimulationGenes, SwitchGenetic VariationGenomic InstabilityGTP-Binding ProteinsModels, GeneticModels, MolecularProtein ConformationProtein FoldingSequence Analysis, ProteinGTP-Binding Proteins

Identifiers

PMID27253392
PMCPMC4890782

What OpenQuestion holds

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Registered trials

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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.