Evidence map›Paper›PMID 37161095›Full record

ArticleBiophysical journal2023

FIREBALL: A tool to fit protein phase diagrams based on mean-field theories for polymer solutions.

Mina Farag, Alex S Holehouse, Xiangze Zeng, Rohit V Pappu

Abstract read
In one paragraph

Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Distinguishing near- versus off-critical phase behaviors of intrinsically disordered proteins.Reports on progress in physics. Physical Society (Great Britain) · 2026
    Article
  4. Article
  5. Article
  6. Dominance analysis to assess solute contributions to multicomponent phase equilibria.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Mina FaragDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri.
Alex S HolehouseCenter for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri.
Xiangze ZengDepartment of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong; Teaching and Research Division, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
Rohit V PappuDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri. Electronic address: pappu@wustl.edu.

Funding

Understanding the Sequence and Structural Determinants of Phase Behavior of ALS-Causing ProteinsR01NS121114 · NINDS · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI Tanja Mittag, ROHIT V PAPPU · 2021 to 2026
$3.8M
NINDS NIH HHS R01 NS121114
6 · The paper itself

Abstract

Biomolecular condensates form via phase transitions of condensate-specific biomacromolecules. Intrinsically disordered regions featuring the appropriate sequence grammars can contribute via homotypic and heterotypic interactions to the driving forces for phase separation of multivalent proteins. Experiments and computations have matured to the point where the concentrations of coexisting dense and dilute phases can be measured or computed for individual intrinsically disordered regions in complex milieus. For a macromolecule such as a disordered protein in a solvent, the locus of points that connects concentrations of the two coexisting phases defines a phase boundary, or binodal. Often, only a few points along the binodal are accessible via measurements. In such cases, and for quantitative and comparative analysis of parameters that describe the driving forces for phase separation, it is useful to fit measured or computed binodals to mean-field free energies for polymer solutions. The nonlinearity of the underlying free energy functions makes it challenging to put mean-field theories into practice. Here, we present FIREBALL, a suite of computational tools designed to enable efficient construction, analysis, and fitting to experimental or computed data of binodals. We show that depending on the theory being used, one can also extract information regarding coil-to-globule transitions of individual macromolecules.

Indexed as

Intrinsically Disordered ProteinsPolymersPhase TransitionProteinsIntrinsically Disordered ProteinsPolymersProteins

Identifiers

PMID37161095
PMCPMC10323018

What OpenQuestion holds

Textmetadata
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.