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.
Keywords: bioinformatics; computational methods; databases; neurodegenerative diseases; protein aggregation.