Evidence map›Paper›PMID 25695764›Full record

ArticlePLoS computational biology2015

Data-driven prediction and design of bZIP coiled-coil interactions.

Vladimir Potapov, Jenifer B Kaplan, Amy E Keating

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

25 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Data-driven computational protein design.Current opinion in structural biology · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. Selective antagonism of cJun for cancer therapy.Journal of experimental & clinical cancer research : CR · 2020
    Review
  13. A general-purpose protein design framework based on mining sequence-structure relationships in known protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  14. Article
  15. Article
  16. Peptide design by optimization on a data-parameterized protein interaction landscape.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  17. Article
  18. CCBuilder 2.0: Powerful and accessible coiled-coil modeling.Protein science : a publication of the Protein Society · 2018
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Vladimir PotapovDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Jenifer B KaplanDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Amy E KeatingDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Massachusetts Institute of Technology · US

Funding

PRE-DOCTORAL TRAINING IN THE BIOLOGICAL SCIENCEST32GM007287 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELL, STEPHEN P., KEATING, AMY E · 1985 to 2019
$40.8M
Analysis and Design of Coiled Coil PartneringR01GM067681 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KEATING, AMY E · 2004 to 2012
$2.9M
NIGMS NIH HHS GM067681NIGMS NIH HHS R01 GM067681NIGMS NIH HHS T32 GM007287
6 · The paper itself

Abstract

Selective dimerization of the basic-region leucine-zipper (bZIP) transcription factors presents a vivid example of how a high degree of interaction specificity can be achieved within a family of structurally similar proteins. The coiled-coil motif that mediates homo- or hetero-dimerization of the bZIP proteins has been intensively studied, and a variety of methods have been proposed to predict these interactions from sequence data. In this work, we used a large quantitative set of 4,549 bZIP coiled-coil interactions to develop a predictive model that exploits knowledge of structurally conserved residue-residue interactions in the coiled-coil motif. Our model, which expresses interaction energies as a sum of interpretable residue-pair and triplet terms, achieves a correlation with experimental binding free energies of R = 0.68 and significantly out-performs other scoring functions. To use our model in protein design applications, we devised a strategy in which synthetic peptides are built by assembling 7-residue native-protein heptad modules into new combinations. An integer linear program was used to find the optimal combination of heptads to bind selectively to a target human bZIP coiled coil, but not to target paralogs. Using this approach, we designed peptides to interact with the bZIP domains from human JUN, XBP1, ATF4 and ATF5. Testing more than 132 candidate protein complexes using a fluorescence resonance energy transfer assay confirmed the formation of tight and selective heterodimers between the designed peptides and their targets. This approach can be used to make inhibitors of native proteins, or to develop novel peptides for applications in synthetic biology or nanotechnology.

Indexed as

Protein Structure, SecondaryAmino Acid SequenceBasic-Leucine Zipper Transcription FactorsComputational BiologyHumansModels, MolecularModels, StatisticalPeptidesProtein MultimerizationBasic-Leucine Zipper Transcription FactorsPeptides

Identifiers

PMID25695764
PMCPMC4335062
OpenAlexW2053983828

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.