Protein aggregation: in silico algorithms and applications.

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology
• Structural Biology

Background:

• Protein aggregation is implicated in neurodegenerative diseases and has industrial relevance.
• Understanding protein aggregation mechanisms is critical for therapeutic and biotechnological advancements.
• Existing in silico techniques offer valuable insights into protein aggregation.

Purpose of the Study:

• To review the current landscape of in silico approaches for predicting protein aggregation.
• To highlight available computational resources and databases for protein aggregation studies.
• To discuss future perspectives and emerging applications in the field of protein aggregation.

Main Methods:

• Review of aggregation-related databases.
• Analysis of mechanistic models, including aggregation-prone region and aggregation propensity prediction.
• Examination of kinetic models for aggregation rate prediction and molecular dynamics simulations.

Main Results:

• A comprehensive overview of diverse in silico tools and methodologies for protein aggregation prediction.
• Identification of key databases and computational resources facilitating protein aggregation research.
• Discussion on the maturity of the field, with numerous prediction models available.

Conclusions:

• The field of in silico protein aggregation prediction is rapidly evolving.
• Numerous computational tools and resources are available to the scientific community.
• The field is poised to address new and complex applications in protein aggregation.