Evidence map›Paper›PMID 39660892›Full record

ReviewJournal of chemical information and modeling2024

Recent Progress in Modeling and Simulation of Biomolecular Crowding and Condensation Inside Cells.

Apoorva Mathur, Rikhia Ghosh, Ariane Nunes-Alves

Abstract readReview
In one paragraph

Review in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. A coarse-grained model for disordered proteins under crowded conditions.Protein science : a publication of the Protein Society · 2025
    Article
  5. 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

3 authors.

Apoorva MathurInstitute of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany.ORCID 0009-0007-0209-8362
Rikhia GhoshInstitute of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany.ORCID 0000-0002-2212-4392
Ariane Nunes-AlvesInstitute of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany.ORCID 0000-0002-5488-4732

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macromolecular crowding in the cellular cytoplasm can potentially impact diffusion rates of proteins, their intrinsic structural stability, binding of proteins to their corresponding partners as well as biomolecular organization and phase separation. While such intracellular crowding can have a large impact on biomolecular structure and function, the molecular mechanisms and driving forces that determine the effect of crowding on dynamics and conformations of macromolecules are so far not well understood. At a molecular level, computational methods can provide a unique lens to investigate the effect of macromolecular crowding on biomolecular behavior, providing us with a resolution that is challenging to reach with experimental techniques alone. In this review, we focus on the various physics-based and data-driven computational methods developed in the past few years to investigate macromolecular crowding and intracellular protein condensation. We review recent progress in modeling and simulation of biomolecular systems of varying sizes, ranging from single protein molecules to the entire cellular cytoplasm. We further discuss the effects of macromolecular crowding on different phenomena, such as diffusion, protein-ligand binding, and mechanical and viscoelastic properties, such as surface tension of condensates. Finally, we discuss some of the outstanding challenges that we anticipate the community addressing in the next few years in order to investigate biological phenomena in model cellular environments by reproducing

Indexed as

Macromolecular SubstancesModels, BiologicalModels, MolecularAnimalsCytoplasmDiffusionHumansProteinsMacromolecular SubstancesProteinsBrownian dynamics simulationscellular cytoplasmmacromolecular crowdingmolecular dynamics simulationsphase separationprotein condensation

Identifiers

PMID39660892
PMCPMC11683874

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.