Rational Design of Surface Modified Nanoparticles for Modulation of Amyloid Protein Aggregation

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Non-Technical DescriptionThe aggregation of amyloid proteins is involved in a wide range of processes including the pathogenesis of numerous diseases (Alzheimer's disease, type 2 diabetes, etc.) as well as in biofouling associated with applications such as food production or water purification. The development of tools to prevent or slow this aggregation would thus be important in both therapeutics and industrial processes. The main goal of this work is to develop a platform for the rational design of nanoparticles capable of modulating amyloid protein aggregation. By coupling experiments and molecular modeling, this project will develop a novel description of the complex interactions that occur at the interface of biological environments and synthetic materials. This theory can then be applied to predict the influence of nanoparticle-protein interactions upon amyloid protein aggregation, thus representing a design platform. By advancing our understanding of interactions between nanoparticles and amyloid proteins, we will be able to rationally design nanoparticles for treating debilitating diseases, reduce unwanted biofouling, and facilitate industrial applications. Graduate and undergraduate students participating in the project will acquire cutting-edge experimental techniques and frontier modeling approaches to train them for future careers in these areas.Technical DescriptionThe proposed research considers surface modified nanoparticles for the modulation of amyloid protein aggregation, which plays a deleterious role in disease and industrial processes. Recently, nanoparticles have emerged as attractive tools for selective protein interactions. Nanoparticle surface properties, size, and shape can be accurately controlled, and therefore nanoparticles provide an ideal tunable platform to modulate amyloid protein aggregation. The main goal of this work is to couple experiments and molecular modeling to develop a novel description of the complex coupling of interactions that occur at the interface of biological environments and synthetic materials. These interactions can be subsequently used for the rational design of nanoparticles for modulation of amyloid protein aggregation. The research is guided by the central hypothesis that nanoparticle-induced changes in the local solution environment drive their ability to influence amyloid protein aggregation. The coupling of experiments and modeling will provide the fundamental understanding needed to create design platforms for building nanostructured biomaterial interfaces that influence protein aggregation. First, fully atomistic molecular simulations will be used in conjunction with detailed molecular theory to describe the local solution environment. Second, a molecular thermodynamic model of amyloid protein aggregation will be implemented. Finally, molecular level theories for nanoparticles and amyloid proteins will be coupled to quantify how a single nanoparticle influences local solution conditions to affect the stability of aggregates. This coupled model will be used to rationally design and synthesize surface modified nanoparticles to experimentally evaluate their predicted effects on amyloid protein aggregation. Agreement between experimental data and theoretical predictions will substantiate the proposed hypothesis.The collaborative nature of the research environment created in this project will be exploited to promote biomedical engineering education within both research and classroom settings. The proposed research will establish a summer undergraduate research internship in which students will complete complementary computational and experimental research tasks. To introduce this research area to pre-college students, a design-based module will be developed that familiarizes students with the concepts of biomaterial design for applications in protein aggregation. Together, these efforts will provide both undergraduate and pre-college students with an understanding of how engineering technologies can facilitate the control of biological phenomena.