Evidence map›Paper›PMID 25580576›Full record

ArticleNature structural & molecular biology2015

Control of repeat-protein curvature by computational protein design.

Keunwan Park, Betty W Shen, Fabio Parmeggiani, Po-Ssu Huang, Barry L Stoddard, David Baker

Abstract read
In one paragraph

Article in Nature structural & molecular biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. De novo design of alpha-beta repeat proteins.bioRxiv : the preprint server for biology · 2024
    Article
  7. Review
  8. Hallucination of closed repeat proteins containing central pockets.Nature structural & molecular biology · 2023
    Article
  9. Structure-Aware Annotation of Leucine-rich Repeat Domains.bioRxiv : the preprint server for biology · 2023
    Article
  10. Article
  11. Review
  12. Article
  13. Protein design via deep learning.Briefings in bioinformatics · 2022
    Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Development and applications of artificial symmetrical proteins.Computational and structural biotechnology journal · 2020
    Review
  20. 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

6 authors.

Keunwan Park1] Department of Biochemistry, University of Washington, Seattle, Washington, USA. [2] Institute for Protein Design, University of Washington, Seattle, Washington, USA.
Betty W ShenDivision of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Fabio Parmeggiani1] Department of Biochemistry, University of Washington, Seattle, Washington, USA. [2] Institute for Protein Design, University of Washington, Seattle, Washington, USA.
Po-Ssu Huang1] Department of Biochemistry, University of Washington, Seattle, Washington, USA. [2] Institute for Protein Design, University of Washington, Seattle, Washington, USA.
Barry L StoddardDivision of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
David Baker1] Department of Biochemistry, University of Washington, Seattle, Washington, USA. [2] Institute for Protein Design, University of Washington, Seattle, Washington, USA. [3] Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA.

Funding

Structure, function &engineering of nuclease catalystsR01GM049857 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI STODDARD, BARRY L. · 1994 to 2014
$4.2M
Determination of the basis of ligand binding via engineering and crystallographyR01GM115545 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI STODDARD, BARRY L. · 2015 to 2018
$1.4M
Howard Hughes Medical InstituteNIGMS NIH HHS R01 GM049857NIGMS NIH HHS R01 GM115545NIGMS NIH HHS R01 GM49857
6 · The paper itself

Abstract

Shape complementarity is an important component of molecular recognition, and the ability to precisely adjust the shape of a binding scaffold to match a target of interest would greatly facilitate the creation of high-affinity protein reagents and therapeutics. Here we describe a general approach to control the shape of the binding surface on repeat-protein scaffolds and apply it to leucine-rich-repeat proteins. First, self-compatible building-block modules are designed that, when polymerized, generate surfaces with unique but constant curvatures. Second, a set of junction modules that connect the different building blocks are designed. Finally, new proteins with custom-designed shapes are generated by appropriately combining building-block and junction modules. Crystal structures of the designs illustrate the power of the approach in controlling repeat-protein curvature.

Indexed as

Crystallography, X-RayLeucine-Rich Repeat ProteinsProtein ConformationProtein EngineeringProteinsLeucine-Rich Repeat ProteinsProteins

Identifiers

PMID25580576
PMCPMC4318719

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.