The study was published today as a reviewed preprint. e-lifeThe authors say this provides important biophysical insight into the molecular mechanisms underlying α-synuclein chain binding, which is essential for understanding the pathogenesis of Parkinson’s disease. Data analysis is robust and this methodology is useful for investigating other molecular processes involving intrinsically disordered proteins (IDPs).

IDPs play important roles in the human body. These proteins do not have a well-defined 3D structure, allowing them to function flexibly, fulfilling different roles as needed. However, this makes them susceptible to irreversible aggregation, especially when mutated. These aggregates are known to be associated with a variety of diseases, including neurodegenerative diseases, cancer, diabetes, and heart disease. For example, Alzheimer’s disease is characterized by aggregation of amyloid beta protein, whereas Parkinson’s disease is associated with the accumulation of alpha-synuclein.

“Increasing evidence supports a link between intrinsically disordered proteins and liquid-liquid phase separation (LLPS), a phenomenon seen when oil and water are mixed,” said lead author of the Tata study Abdul Wasim, a doctoral student at the school, says: Basic Research, Hyderabad, India. “This is interesting because LLPS itself is known to form intracellular compartments that can cause incurable disease.”

α-synuclein can undergo LLPS, and α-synuclein aggregation is known to be affected by crowding from nearby molecules and the surrounding pH. However, characterizing the precise interactions and dynamics of these tiny aggregated proteins is difficult.

“Previous attempts have simulated individual IDPs, but these simulations can be extremely time- and resource-intensive, and even with state-of-the-art software and hardware, protein The study of agglomeration is unrealistic,” explains Jagannath Mondal, associate professor at Tata University and lead author. Basic research institute. “We used coarse-grained molecular dynamics simulations, which allowed us to study the aggregation of multiple IDPs in mixtures, although with lower resolution.”

Using this model, the authors simulated the collective interactions of many α-synuclein chains within a droplet under various conditions. First, we studied protein chains mixed with water alone and found that approximately 60% of the protein chains remained free and did not show a strong tendency to spontaneously aggregate.

Next, they added some “crowder” molecules, large biomolecules that made the environment a very dense space for proteins. Previous research on Alzheimer’s disease has shown that protein aggregation increases in crowded environments. As expected, addition of crowder promoted α-synuclein aggregation and reduced the number of free proteins.

Similarly, the research team found that changing the ionic environment through the addition of salt also promoted aggregation. However, further investigation revealed that these two environmental factors (crowding and salt) cause aggregation through different mechanisms. Adding salt to the mixture increased the surface tension of the droplets, but adding crowder molecules had no effect on surface tension. This is important to know because the greater the surface tension, the greater the tendency for proteins to aggregate. Additionally, droplet fusion to relieve surface tension is commonly seen in liquid-liquid phase separation (LLPS) droplets characteristic of diseases involving disordered proteins.

LLPS is characterized by the elongated shape of the protein molecules within the droplet, all oriented in a consistent direction. So the team next decided to see if this was true within a simulation. They found that proteins in the dense (high concentration) phase of liquid-liquid separations actually have an extended shape, regardless of whether crowder molecules or salts are present. All protein molecules had a similar orientation. This is because α-synuclein IDP is a characteristic of the LLPS phenomenon.

Next, the research team wanted to examine how different alpha-synuclein proteins interact to achieve these effects. By studying the positions and characteristics of different amino acids within a protein, we can determine the likelihood of their contact under different conditions. This reveals that certain amino acids in proteins are likely present to prevent aggregation, and that proteins are oriented to minimize interactions between these residues. I did.

The editors note that the study has limitations that should be addressed. In short, they say, they could improve the benchmarking of their simulations against other methods and increase readers’ confidence in the conclusions presented.

“Taken together, these results suggest that both the crowder molecule and the salt promote α-synuclein aggregation and simultaneously stabilize the resulting aggregates,” Wasim says. “Regardless of the factors that cause aggregation, the interactions that drive droplet formation remain the same.”

“Our study focused on normal alpha-synuclein and identified key sites within the protein that are important for aggregation,” concludes Dr. Mondal. “Genetic variations in alpha-synuclein are thought to significantly increase the likelihood of aggregation. These mutations involve small changes in the protein sequence, highlighting the importance of understanding the molecular basis of this process. It highlights.”