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Related Experiment Video

Updated: Jun 25, 2025

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

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

Published on: June 23, 2018

Prediction of protein aggregation.

Kavyan Khalili¹, Farnoosh Farzam¹, Bahareh Dabirmanesh¹

¹Department of Biochemistry, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.

Progress in Molecular Biology and Translational Science

|May 29, 2024

Summary

Predicting protein aggregation is crucial for understanding neurodegenerative diseases and industrial applications. Computational methods are advancing to analyze aggregation, predict mutations

Keywords:

Aggregation propensity Computational methods Prediction Protein aggregation

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

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Monitoring Protein Aggregation Kinetics In Vivo using Automated Inclusion Counting in Caenorhabditis elegans

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Area of Science:

Biochemistry and Molecular Biology
Computational Biology and Bioinformatics

Background:

Protein aggregation is implicated in neurodegenerative diseases and has industrial relevance.
Fibrillar protein aggregates serve natural structural roles and can be engineered into nanomaterials.

Purpose of the Study:

To review computational methods for predicting protein aggregation.
To highlight accessible resources and future directions in in silico protein aggregation research.

Main Methods:

Assessment of computational tools for predicting protein aggregation propensity.
Analysis of methods for detecting aggregation-prone regions (sequential and structural).
Evaluation of computational approaches for studying mutation effects and identifying prion-like domains.

Main Results:

A summary of advancements in computational methodologies for protein aggregation.
An overview of existing in silico resources and tools.
Identification of key areas for prospective developments in the field.

Conclusions:

Computational approaches are essential for rationalizing and predicting protein aggregation.
Continued development of in silico tools will enhance understanding and manipulation of protein aggregation.
This review provides a comprehensive overview for researchers in the field.