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Combining Simulation And The Mspa Nanopore To Study P53 Dynamics And Interactions, Samantha A. Schultz

Masters Theses

p53 is a transcription factor and an important tumor suppressor protein that becomes activated due to DNA damage. Because of its role as a tumor suppressor, mutations in the gene that encodes it are found in over 50% of human cancers. The N-terminal transactivation domain (NTAD) of p53 is intrinsically disordered and modulates the function and interactions of p53 in the cell. Its disordered structure allows it to be controlled closely by post-translation modifications that regulate p53’s ability to bind DNA and interact with regulatory binding partners. p53 is an attractive target for developing cancer therapeutics, but its intrinsically disordered …

Thermal Conductivity And Mechanical Properties Of Interlayer-Bonded Graphene Bilayers, Afnan Mostafa

Masters Theses

Graphene, an allotrope of carbon, has demonstrated exceptional mechanical, thermal, electronic, and optical properties. Complementary to such innate properties, structural modification through chemical functionalization or defect engineering can significantly enhance the properties and functionality of graphene and its derivatives. Hence, understanding structure-property relationships in graphene-based metamaterials has garnered much attention in recent years. In this thesis, we present molecular dynamics studies aimed at elucidating structure-property relationships that govern the thermomechanical response of interlayer-bonded graphene bilayers.

First, we present a systematic and thorough analysis of thermal transport in interlayer-bonded twisted bilayer graphene (IB-TBG). We find that the introduction of interlayer C-C …

Competitive And/Or Cooperative Interactions Of Graphene-Family Materials And Benzo[A]Pyrene With Pulmonary Surfactant: A Computational And Experimental Study, Tongtao Yue, Rujie Lv, Dongfang Xu, Yan Xu, Lu Liu, Yanhui Dai, Jian Zhao, Baoshan Xing

Stockbridge Faculty Publication Series

Background

Airborne nanoparticles can be inhaled and deposit in human alveoli, where pulmonary surfactant (PS) molecules lining at the alveolar air–water interface act as the first barrier against inhaled nanoparticles entering the body. Although considerable efforts have been devoted to elucidate the mechanisms underlying nanoparticle-PS interactions, our understanding on this important issue is limited due to the high complexity of the atmosphere, in which nanoparticles are believed to experience transformations that remarkably change the nanoparticles’ surface properties and states. By contrast with bare nanoparticles that have been extensively studied, relatively little is known about the interactions between PS and inhaled …

Targeting Intrinsically Disordered Proteins Through Dynamic Interactions, Jianlin Chen, Xiaorong Liu, Jianhian Chen

Biochemistry & Molecular Biology Department Faculty Publication Series

Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction …

Multiscale Simulations Of Intrinsically Disordered Proteins, Xiaorong Liu

Doctoral Dissertations

Intrinsically disordered proteins (IDPs) lack stable secondary and/or tertiary structures under physiological conditions. The have now been recognized to play important roles in numerous biological processes, particularly cellular signaling and regulation. Mutation of IDPs are frequently associated with human diseases, such as cancers and neuron degenerative diseases. Therefore, it is important to understand the structure, dynamics, and interactions of IDPs, so as to establish the mechanistic basis of how intrinsic disorder mediates versatile functions and how such mechanisms may fail in human diseases. However, the heterogeneous structural ensembles of IDPs are not amenable to high resolution characterization solely through experimental …

Modeling The Self-Assembly Of Ordered Nanoporous Materials, Szu-Chia Chien

Doctoral Dissertations

Porous materials are of great importance in many fields due to their wide applications. An ongoing theme in this area is the tailoring of materials for specific applications. With a better understanding of the formation mechanisms, tailoring and controlling the pore structure may be achieved. The objective of this research is acquiring further understanding of the fundamental physics that govern the formation of these materials using molecular simulations. We are aiming to unravel the assembly process of silica porous materials using a semi-rigid silica tetrahedral model. This model together with reaction ensemble Monte Carlo simulations allows us to study the …

Parametric Sensitivity Analysis For Stochastic Molecular Systems Using Information Theoretic Metrics, Anastasios Tsourtis, Yannis Pantazis, Markos Katsoulakis, Vagelis Harmandaris

Markos Katsoulakis

Background Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space. …