431954 Dynamics of Aggregation of Proteins (Rapid Fire)

Wednesday, November 11, 2015
Exhibit Hall 1 (Salt Palace Convention Center)
Size Zheng, Katherine Shing and Muhammad Sahimi, Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA

Dynamics of Aggregation of Proteins

Size Zheng, Katherine S. Shing and Muhammad Sahimi

Misfolded proteins aggregate together and form large clusters. A normal protein typically has hydrophobic interior and shields itself with a hydrophilic exterior. When a protein misfolds, it exposes its inner hydrophobic portions to the outside, which may result in an inter-molecular interaction with other misfolded proteins, leading to aggregation. Protein aggregation is associated with a variety of human neurodegenerative diseases, including Alzheimer's, Parkinson's and prion disease. The aggregates' structural characteristics and molecular-level details are, however, hard to be studied by experimental methods and, thus, the mechanism of aggregations still remains poorly understood. But, advances in computational power and simulations, particularly, molecular dynamics (MD) simulations, provide the opportunity to simulate the aggregation process, hence helping us to unveil the secrets behind the phenomena and find the way to cure the diseases.

Previous works indicated that the proteins linked to neurodegenerative diseases, such as amyloid beta-protein to Alzheimer's disease and PrP prion protein to prion disease, only require a short portions of their entire chains, typically 4-10 residues in length, to begin aggregating. Such short portions contain high hydrophobic residues that are believed to drive the aggregation into fibrils. We have used discontinuous MD (DMD) technique to simulate the aggregation process of multiple 10-residue peptides into ordered fibrils, as the first step toward simulating the same in a crowded cellular environment. The DMD simulation uses coarse-grained peptides models and discontinuous stepwise potentials to provide dramatically faster simulation speed for big systems comparing with the classical continuous all-atom MD simulations, without sacrificing much of the necessary details.

We simulated multiple systems that have 8, 16 and 32 peptides. In each system we have simulated several cases at various temperatures, and investigated the characteristics of the aggregated protein clusters, including the number of hydrogen bonds and of the beta-sheets, the mean-square displacement and diffusion coefficient, as well as the radius of gyration, and the distribution of the cluster sizes. Interesting and physically relevant phenomena are observed, which will be reported.

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See more of this Session: Poster Session: Bioengineering
See more of this Group/Topical: Food, Pharmaceutical & Bioengineering Division