Evidence map›Paper›PMID 39451523›Full record

ArticleCurrent issues in molecular biology2024

Statistical Thermodynamic Description of Self-Assembly of Large Inclusions in Biological Membranes.

Andres De Virgiliis, Ariel Meyra, Alina Ciach

Abstract read
In one paragraph

Article in Current issues in molecular biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Andres De VirgiliisInstituto de Física de Líquidos y Sistemas Bilógicos, Facultad de Ciencias Exactas-UNLP-CONICET, La Plata 1900, Argentina.ORCID 0000-0002-0180-4604
Ariel MeyraInstituto de Física de Líquidos y Sistemas Bilógicos, Facultad de Ciencias Exactas-UNLP-CONICET, La Plata 1900, Argentina.ORCID 0000-0003-2826-7922
Alina CiachInstitute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland.ORCID 0000-0002-5556-401X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies revealed anomalous underscreening in concentrated electrolytes, and we suggest that the underscreened electrostatic forces between membrane proteins play a significant role in the process of self-assembly. In this work, we assumed that the underscreened electrostatic forces compete with the thermodynamic Casimir forces induced by concentration fluctuations in the lipid bilayer, and developed a simplified model for a binary mixture of oppositely charged membrane proteins with different preference to liquid-ordered and liquid-disordered domains in the membrane. In the model, like macromolecules interact with short-range Casimir attraction and long-range electrostatic repulsion, and the cross-interaction is of the opposite sign. We determine energetically favored patterns in a system in equilibrium with a bulk reservoir of the macromolecules. Different patterns consisting of clusters and stripes of the two components and of vacancies are energetically favorable for different values of the chemical potentials. Effects of thermal flutuations at low temperature are studied using Monte Carlo simulations in grand canonical and canonical ensembles. For fixed numbers of the macromolecules, a single two-component cluster with a regular pattern coexists with dispersed small one-component clusters, and the number of small clusters depends on the ratio of the numbers of the molecules of the two components. Our results show that the pattern formation is controlled by the shape of the interactions, the density of the proteins, and the proportion of the components.

Indexed as

inhomogeneous mixturesmembrane proteinsself-assembled patternsspontaneous pattern formation

Identifiers

PMID39451523
PMCPMC11506602

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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.