Evidence map›Paper›PMID 19472357›Full record

ArticleProtein science : a publication of the Protein Society2009

Motif-directed flexible backbone design of functional interactions.

James J Havranek, David Baker

Abstract readComparative Study
In one paragraph

Article in Protein science : a publication of the Protein Society, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Structure-based modeling of protein: DNA specificity.Briefings in functional genomics · 2015
    Review
  6. Motif-directed redesign of enzyme specificity.Protein science : a publication of the Protein Society · 2014
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Hotspot-centric de novo design of protein binders.Journal of molecular biology · 2011
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Specificity in computational protein design.The Journal of biological chemistry · 2010
    Review
  19. Conformational diversity and computational enzyme design.Current opinion in chemical biology · 2010
    Review
  20. 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

2 authors.

James J HavranekDepartment of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA. havranek@genetics.wustl.edu
David Baker

Funding

Computational Design of an LAGLIDADGs with Novel Recognition Specificities (CompoRL1GM084433 · NIGMS · UNIVERSITY OF WASHINGTON · PI BAKER, DAVID · 2007 to 2011
$1.9M
Computational Modeling and Design of Specific Protein-DNA InterfacesR00RR024107 · NCRR · WASHINGTON UNIVERSITY · PI HAVRANEK, JAMES J · 2008 to 2010
$742k
Computational Modeling and Design of Specific Protein-DNA InterfacesK99RR024107 · NCRR · UNIVERSITY OF WASHINGTON · PI HAVRANEK, JAMES J · 2007 to 2007
$83k
NCRR NIH HHS K99 RR 024107NCRR NIH HHS R00 RR024107NIGMS NIH HHS RL1 GM084433
6 · The paper itself

Abstract

Computational protein design relies on a number of approximations to efficiently search the huge sequence space available to proteins. The fixed backbone and rotamer approximations in particular are important for formulating protein design as a discrete combinatorial optimization problem. However, the resulting coarse-grained sampling of possible side-chain terminal positions is problematic for the design of protein function, which depends on precise positioning of side-chain atoms. Although backbone flexibility can greatly increase the conformation freedom of side-chain functional groups, it is not obvious which backbone movements will generate the critical constellation of atoms responsible for protein function. Here, we report an automated method for identifying protein backbone movements that can give rise to any specified set of desired side-chain atomic placements and interactions, using protein-DNA interfaces as a model system. We use a library of previously observed protein-DNA interactions (motifs) and a rotamer-based description of side-chain conformation freedom to identify placements for the protein backbone that can give rise to a favorable side-chain interaction with DNA. We describe a tree-search algorithm for identifying those combinations of interactions from the library that can be realized with minimal perturbation of the protein backbone. We compare the efficiency of this method with the alternative approach of building and screening alternate backbone conformations.

Indexed as

AlgorithmsAmino Acid MotifsComputer SimulationModels, ChemicalAnimalsDNAMiceModels, MolecularProtein BindingProtein ConformationProteinsDNAProteins

Identifiers

PMID19472357
PMCPMC2774439

What OpenQuestion holds

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Read underepoch 390

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.