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Advanced computational approaches shed light on protein aggregation and disease mechanisms

APR 26, 2024
Examining the molecular basis for protein aggregation
Advanced computational approaches shed light on protein aggregation and disease mechanisms internal name

Advanced computational approaches shed light on protein aggregation and disease mechanisms lead image

Protein aggregation, a process where intrinsically disordered or misfolded proteins clump together, is linked to a variety of diseases, including Alzheimer’s, Parkinson’s, and cataracts. Yet, despite advances in medicine and technology, identifying the precise triggers of protein aggregation is challenging due to the small scale and dynamic nature of these processes.

Computational approaches are emerging as powerful tools for understanding protein aggregation.

In a review paper, Ghosh et al. highlighted the use of molecular dynamics (MD) simulations and bioinformatics in this field.

“Identifying specific interactions and factors leading to aggregation is difficult experimentally,” said author Mithun Radhakrishna. “Computational methods can bridge this knowledge gap. For instance, molecular simulations enable us to examine interactions at the atomic level, offering insights into potential triggers of protein aggregation.”

The review presents various MD simulation methods and advanced sampling techniques. Replica exchange molecular dynamics, for example, features multiple simulations of a system run at different temperatures and periodically exchanged; metadynamics introduces history-dependent biasing potential and is especially useful in studying protein folding/misfolding; and umbrella sampling divides a reaction coordinate into small windows so simulations can be performed with a biasing potential for each.

The paper also discusses the role of bioinformatics in predicting protein regions susceptible to aggregation.

“Bioinformatics, machine learning, and artificial intelligence help identify protein regions prone to aggregation,” Radhakrishna said. “Enhancing the predictive power of bioinformatics tools and refining sampling methods will boost the impact of computational approaches in the future. Additionally, focusing on the molecular dynamics of protein aggregation in specific diseases could pave the way for new drug development and treatments.”

Source: “Advanced computational approaches to understand protein aggregation,” by Deepshikha Ghosh, Anushka Biswas, and Mithun Radhakrishna, Biophysics Reviews (2024). Access the article at http://doi.org/10.1063/5.0180691 .

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