Evidence map›Paper›PMID 38149742›Full record

ArticleThe Journal of chemical physics2023

Molecularly informed field theory for estimating critical micelle concentrations of intrinsically disordered protein surfactants.

My V T Nguyen, Kate Dolph, Kris T Delaney, Kevin Shen, Nicholas Sherck, Stephan Köhler, Rohini Gupta, Matthew B Francis, M Scott Shell, Glenn H Fredrickson

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of chemical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

3 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

10 authors at 5 institutions in 2 countries.

My V T NguyenDepartment of Chemical Engineering, University of California, Santa Barbara, California 93106, USA.ORCID 0000-0002-5567-9378
Kate DolphDepartment of Chemistry, University of California, Berkeley, California 94720, USA.ORCID 0000-0003-0023-5873
Kris T DelaneyMaterials Research Laboratory, University of California, Santa Barbara, California 93106, USA.ORCID 0000-0003-0356-1391
Kevin ShenDepartment of Chemical Engineering, University of California, Santa Barbara, California 93106, USA.ORCID 0000-0001-9715-7474
Nicholas SherckBASF Corporation, Iselin, New Jersey 08830, USA.ORCID 0000-0001-5503-1494
Stephan KöhlerBASF SE, Ludwigshafen am Rhein 67056, Germany.ORCID 0000-0002-1829-1059
Rohini GuptaCalifornia Research Alliance (CARA) by BASF, Berkeley, California 94720, USA.ORCID 0000-0002-6608-9867
Matthew B FrancisDepartment of Chemistry, University of California, Berkeley, California 94720, USA.ORCID 0000-0003-2837-2538
M Scott ShellDepartment of Chemical Engineering, University of California, Santa Barbara, California 93106, USA.ORCID 0000-0002-0439-1534
Glenn H FredricksonDepartment of Chemical Engineering, University of California, Santa Barbara, California 93106, USA.ORCID 0000-0002-6716-9017
University of California, Santa Barbara · USBASF (Germany) · DEBASF (United States) · USLawrence Berkeley National Laboratory · USUniversity of California, Berkeley · US

Funding

Univ of Calif Berkeley Chemistry-Biology Interface ProgramT32GM066698 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI CHANG, CHRISTOPHER J., FRANCIS, MATTHEW B · 2004 to 2023
$7.5M
NIGMS NIH HHS T32 GM066698
6 · The paper itself

Abstract

The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically.

Indexed as

Intrinsically Disordered ProteinsMicellesComputer SimulationSurface-Active AgentsIntrinsically Disordered ProteinsMicellesSurface-Active Agents

Identifiers

PMID38149742
PMCPMC10754628
OpenAlexW4390268595

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.