Evidence map›Paper›PMID 23850142›Full record

ReviewCurrent opinion in structural biology2013

Modeling protein association mechanisms and kinetics.

Huan-Xiang Zhou, Paul A Bates

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  8. In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  9. Article
  10. bioRxiv : the preprint server for biology · 2023
    Article
  11. Article
  12. Article
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  14. Multivalency enables unidirectional switch-like competition between intrinsically disordered proteins.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  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.

Huan-Xiang ZhouDepartment of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, FL 32306, USA. Electronic address: hzhou4@fsu.edu.
Paul A Bates

Funding

THEORY OF PROTEIN/PROTEIN ASSOCIATIONR01GM058187 · NIGMS · FLORIDA STATE UNIVERSITY · PI ZHOU, HUAN-XIANG · 1998 to 2016
$3.7M
Modeling Crowding and Confinement of Cellular EnvironmentsR01GM088187 · NIGMS · FLORIDA STATE UNIVERSITY · PI ZHOU, HUAN-XIANG · 2010 to 2015
$1.6M
Cancer Research UK 10748NIGMS NIH HHS GM58187NIGMS NIH HHS GM88187NIGMS NIH HHS R01 GM058187NIGMS NIH HHS R01 GM088187
6 · The paper itself

Abstract

Substantial advances have been made in modeling protein association mechanisms and in calculating association rate constants (ka). We now have a clear understanding of the physical factors underlying the wide range of experimental ka values. Half of the association problem, where ka is limited by diffusion, is perhaps solved, and for the other half, where conformational changes become rate-limiting, a number of promising methods are being developed for ka calculations. Notably, the binding kinetics of disordered proteins are receiving growing attention, with 'dock-and-coalesce' emerging as a general mechanism. Progress too has been made in the modeling of protein association kinetics under conditions mimicking the heterogeneous, crowded environments of cells, an endeavor that should ultimately lead to a better understanding of cellular functions.

Indexed as

Models, MolecularCellsKineticsProtein ConformationProtein Interaction MappingProteinsProteins

Identifiers

PMID23850142
PMCPMC3844007

What OpenQuestion holds

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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.