Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Amyloid Fibrils03:03

Amyloid Fibrils

12.8K
Amyloid fibrils are aggregates of misfolded proteins.  Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils. 
Amyloid deposits were observed as early as 1639 in the liver and the spleen.   In 1854, Rudolph Virchow performed iodine staining,...
12.8K
Amyloid Fibrils03:03

Amyloid Fibrils

6.9K
6.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Plug-and-(Dis)Play Epitope Engineering on Ring-like Particles: Rational Design of Multivalent Immunoreagents for Diagnostics.

ACS applied bio materials·2026
Same author

Programmable CAR immunotherapies for neurodegenerative proteinopathies.

Trends in pharmacological sciences·2026
Same author

AGGRESCAN and its evolution: A two-decade perspective on protein aggregation prediction.

Biophysical reviews·2026
Same author

AggrescanAI: Prediction of Aggregation-Prone Regions Using Contextualized Embeddings.

Journal of molecular biology·2026
Same author

Mass spectrometry footprinting reveals how kinetic stabilizers counteract transthyretin dynamics altered by pathogenic mutations.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Multivalent Protein Nanorings for Broad and Potent SARS-CoV-2 Neutralization.

Advanced healthcare materials·2025
Same journal

A harmonized fast-fashion garment-variant dataset for textile circularity and sustainability assessment.

Data in brief·2026
Same journal

Terahertz reflectivity dataset: Reading text on both sides of the page.

Data in brief·2026
Same journal

High-quality draft genome sequence data of <i>Levilactobacillus brevis</i> 3LB isolated from fermented milk koumiss.

Data in brief·2026
Same journal

Interview dataset: Encouraging the development of industrial symbiosis networks in Slovenia - transition to the circular economy.

Data in brief·2026
Same journal

Timeseries of multispectral and radar data and vegetation indices from Sentinel-1, Sentinel-2 and Landsat-8 at field scale.

Data in brief·2026
Same journal

BACI-VI-Bench: A dataset of variational inequality benchmark instances for multi-agent trade-network equilibrium.

Data in brief·2026
See all related articles

Related Experiment Video

Updated: Mar 18, 2026

Modeling Amyloid-&#946;42 Toxicity and Neurodegeneration in Adult Zebrafish Brain
10:01

Modeling Amyloid-β42 Toxicity and Neurodegeneration in Adult Zebrafish Brain

Published on: October 25, 2017

11.8K

Data on correlation between Aβ42 structural aggregation propensity and toxicity in bacteria.

Anita Carija1, Susanna Navarro1, Salvador Ventura1

  • 1Institut de Biotecnologia i Biomedicina, Departament de Bioquimica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.

Data in Brief
|July 14, 2016
PubMed
Summary
This summary is machine-generated.

Protein aggregation, a hallmark of human disorders, is detrimental to cell fitness. This study shows structure-based predictions of aggregation propensity correlate with toxic effects, suggesting evolutionary selection against such proteins.

More Related Videos

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast
11:04

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

Published on: June 23, 2018

7.8K
A Method to Study &#945;-Synuclein Toxicity and Aggregation Using a Humanized Yeast Model
08:24

A Method to Study α-Synuclein Toxicity and Aggregation Using a Humanized Yeast Model

Published on: November 25, 2022

2.7K

Related Experiment Videos

Last Updated: Mar 18, 2026

Modeling Amyloid-&#946;42 Toxicity and Neurodegeneration in Adult Zebrafish Brain
10:01

Modeling Amyloid-β42 Toxicity and Neurodegeneration in Adult Zebrafish Brain

Published on: October 25, 2017

11.8K
Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast
11:04

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

Published on: June 23, 2018

7.8K
A Method to Study &#945;-Synuclein Toxicity and Aggregation Using a Humanized Yeast Model
08:24

A Method to Study α-Synuclein Toxicity and Aggregation Using a Humanized Yeast Model

Published on: November 25, 2022

2.7K

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Evolutionary Biology

Background:

  • Protein aggregation and amyloid formation are implicated in numerous human diseases.
  • Cellular protein aggregation reduces fitness, suggesting evolutionary pressure against such sequences.
  • Previous research indicates selection against aggregation-prone proteins in bacteria.

Purpose of the Study:

  • To present complementary data supporting the study 'Selection against toxic aggregation-prone protein sequences in bacteria'.
  • To investigate the correlation between structure-based predictions of protein aggregation propensity and deleterious effects.
  • To utilize the AGGRESCAN3D (A3D) server for predicting protein aggregation properties.

Main Methods:

  • Employing the AGGRESCAN3D (A3D) server for in-house prediction of protein aggregation properties.
  • Analyzing protein structures to forecast aggregation propensities.
  • Correlating structure-based aggregation predictions with previously reported deleterious effects.

Main Results:

  • Demonstrated a striking correlation between structure-based aggregation propensity predictions for Alzheimer's Aβ42 peptide variants and their known deleterious effects.
  • Validated the utility of the A3D server in forecasting protein aggregation behavior.
  • Provided complementary data supporting evolutionary selection against toxic protein sequences.

Conclusions:

  • Structure-based prediction of protein aggregation propensity is a viable method for assessing potential cellular toxicity.
  • The findings support the hypothesis that natural selection acts to eliminate aggregation-prone protein sequences.
  • This work offers valuable insights into the evolution of protein sequences and their relationship to disease.