Evidence map›Paper›PMID 41280756›Full record

ArticleACS omega2025

Aggregation of Intrinsically Fluorescent Proteins: Combining Coarse-Grained Molecular Dynamics with Alphafold Predictions.

Margherita Bini, Giorgia Brancolini, Valentina Tozzini

Abstract read
In one paragraph

Article in ACS omega, 2025. 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.

Margherita BiniScuola Normale Superiore, Piazza San Silvestro, 12, Pisa 56127, Italy.ORCID https://orcid.org/0000-0002-7829-3507
Giorgia BrancoliniIstituto Nanoscienze, National Research Council (CNR-NANO), Modena 41100, Italy.ORCID https://orcid.org/0000-0002-1083-9198
Valentina TozziniIstituto Nanoscienze, National Research Council (CNR-NANO), Piazza San Silvestro, 12, Pisa 56127, Italy.ORCID https://orcid.org/0000-0002-7586-5039

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aggregation is a pervasive phenomenon affecting both disordered and folded proteins, modulated by the balance between hydrophobic attraction and electrostatics, and generally explored by means of molecular dynamics simulations, often performed with low-resolution models. On the other hand, the AI based structure prediction AlphaFold software, extremely accurate for single chains, has been recently provided with the capability of predicting the structure of protein complexes. In this work, we compare coarse-grained molecular dynamics simulations to assess the relative performance of different force fields and those of AlphaFold3 (AF3) in predicting the aggregation of four variants of intrinsically fluorescent proteins. Our results are useful for guiding the choice or design of new potentials for systems containing both disordered and folded proteins and outline a possible scheme to integrate AlphaFold with molecular dynamics simulations.

Identifiers

PMID41280756
PMCPMC12631483

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.