New Model Captures Multiple Factors Driving Alpha-Synuclein Aggregation

Using computational models, researchers have delved into the factors behind the buildup of alpha-synuclein protein, a significant player in the progression of Parkinson’s disease.

The research offers significant biophysical insights into the molecular mechanism behind the connection of alpha-synuclein chains, which is crucial for comprehending the onset of Parkinson's disease.

The research was published in the journal eLife. The data analysis is solid, and the technology can aid in the investigation of various molecular processes involving intrinsically disordered proteins (IDPs).

IDPs are vital to the functioning of the human body. Their three-dimensional (3D) structure is not well defined, and, as a result, these proteins can act flexibly, changing roles as needed. This, however, also leaves them open to irreversible aggregation, particularly in the event of a mutation.

Numerous illnesses, including cancer, diabetes, heart disease, and neurological disorders, have been linked to these aggregates. For instance, amyloid-beta protein aggregation is a hallmark of Alzheimer's disease, whereas alpha-synuclein accumulation is associated with Parkinson's illness.

A growing body of evidence has established a connection between intrinsically disordered proteins and liquid-liquid phase separation, or LLPS, the phenomenon you see if you mix oil and water, and this is of interest because LLPS is itself known to form subcellular compartments that can lead to incurable diseases.

Abdul Wasim, Ph.D., Study Lead Author, Tata Institute of Fundamental Research

It is known that alpha-synuclein can undergo LLPS and that the pH of the environment and crowding from adjacent molecules affect alpha-synuclein aggregation. However, it is difficult to precisely characterize the dynamics and interactions of these tiny aggregation proteins.

Previous attempts have simulated individual IDPs, but these simulations can be extremely time-consuming and resource-intensive, making the study of protein aggregation impractical even with cutting-edge software and hardware; we used coarse-grained molecular dynamic simulations, which although offering lower resolution allowed us to study the aggregation of multiple IDPs in a mixture.

Jagannath Mondal, Associate Professor and Study Senior Author, Tata Institute of Fundamental Research

The authors used this model to mimic the collective interaction of many alpha-synuclein chains in droplets under various circumstances. First, they observed that about 60 % of the protein chains remained free and did not exhibit a significant, spontaneous inclination to clump together when they examined the protein chains mixed solely with water.

Subsequently, they introduced a few “crowder” molecules, which are sizable biological molecules that provide an extremely densely packed habitat for proteins. Prior research on Alzheimer's disease has demonstrated that a crowded environment causes more proteins to aggregate. Crowders, as predicted, increased alpha-synuclein aggregation and reduced the number of free proteins.

Similarly, the researchers discovered that introducing salt to alter the ionic environment encouraged aggregation. However, more investigation showed that the two environmental factors, salt and crowding, caused aggregation in distinct ways.

The droplets' surface tension rose when salt was added to the mixture, but crowder molecules had no influence on surface tension. This is crucial to understand since proteins have a greater propensity to cluster at higher surface tensions.

In addition, it is frequently observed that liquid-liquid phase separated (LLPS) droplets, which are indicative of disorders involving disordered proteins, merge to reduce surface tension.

One feature of LLPS is that the protein molecules in the droplets take on an elongated form and align themselves all in the same direction. The group's next goal was to use their simulations to determine whether this was the case.

They discovered that all protein molecules in the dense (highly concentrated) phase of the liquid-liquid separation had similar orientations, indicating that alpha-synuclein IDPs exhibit the characteristics of the LLPS phenomenon. This was true regardless of the presence of crowder molecules or salt.

The group then investigated the mechanisms by which distinct alpha-synuclein proteins interact to produce these outcomes. They could determine their likelihood of coming into touch in various scenarios by examining the locations and characteristics of the different amino acids within the protein.

This demonstrated that proteins position themselves to minimize interactions between these residues and that specific amino acids in the protein most likely prevent aggregation.

The researchers acknowledge the flaws of the research, which need to be addressed. To be more specific, they suggest that the simulations' benchmarking against alternative techniques should be strengthened to provide more confidence in the findings drawn,

Together, these results suggest that both crowder molecules and salt enhance the aggregation of alpha-synuclein while also stabilizing the resulting aggregates; irrespective of the factors causing the aggregation, the interactions that drive the formation of droplets remain the same.

Abdul Wasim, Ph.D. and Study Lead Author, Tata Institute of Fundamental Research

Mondal said, “Our study focused on normal alpha-synuclein and identified key sites within the protein that are crucial for aggregation; inherited mutations in alpha-synuclein are thought to significantly increase the likelihood of aggregation. These mutations, involving minor alterations to protein sequence, highlight the importance of understanding the molecular basis of this process.”

Source:
Journal reference:

‌Wasim, A., et al. (2024). Modulation of α-Synuclein Aggregation Amid Diverse Environmental Perturbation. eLife. doi.org/10.7554/eLife.95180.1.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Cataloging Bacteria in Cancer Metastases