# Neurodegeneration Through the Lens of Bioinformatics Approaches: Computational Mechanisms of Protein Misfolding

## TL;DR

This review explores how bioinformatics tools help understand protein misfolding in neurodegenerative diseases like Alzheimer's and Parkinson's.

## Contribution

The paper offers a concise overview of current computational methods for studying protein aggregation in neurodegeneration.

## Key findings

- Computational methods and databases are widely used to predict aggregation-prone protein sequences and structures.
- Abnormal protein aggregation is a key factor in diseases like Alzheimer’s and Parkinson’s.
- In silico approaches aid in identifying therapeutic targets for neurodegenerative disorders.

## Abstract

Protein and peptide aggregation has become a prominent focus in biomedical research due to its critical role in the development of neurodegenerative diseases (NDs) and its relevance to industrial applications. Neurodegenerative disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and Amyotrophic Lateral Sclerosis (ALS) are closely associated with abnormal aggregation processes, highlighting the need for a deeper understanding of their molecular mechanisms. In recent years, a wide range of computational methods, bioinformatics tools, and curated databases have been developed to predict and analyze sequences and structures that are prone to aggregation. These in silico approaches offer valuable insights into the underlying principles of aggregation and contribute to the identification of potential therapeutic targets. This review provides a concise overview of the current bioinformatics resources and computational techniques available for studying protein and peptide aggregation, intending to guide future research efforts in the field of neurodegenerative disease modeling and drug discovery.