Matching Items (610)
ContributorsBuck, Elizabeth (Performer) / ASU Library. Music Library (Publisher)
Created1999-10-24
ContributorsMann, Rochelle (Performer) / Willey, Barbara (Performer) / Fitts, Jenny (Performer) / Strain, James (Performer) / ASU Library. Music Library (Publisher)
Created1990-10-20
ContributorsRaymond, Kelly (Performer) / Chen, Chia-I (Performer) / Lee, Sehee (Performer) / ASU Library. Music Library (Publisher)
Created2009-02-20
ContributorsHannon, Mikaela (Performer) / Marr, Mackenzie (Performer) / ASU Library. Music Library (Publisher)
Created2023-11-04
Description
This thesis explores a diverse array of topics related to the role of dynamic allostery in regulating protein functions. Allostery is the phenomenon where a catalytic pocket responds to perturbations caused by binding at another distant site. This response often involves a conformational change resulting in a protein function alteration. However, it is essential to note the existence of dynamic allostery mechanisms that regulate protein function without relying on conformational changes but on dynamic motions. Within this thesis, position-specific equilibrium dynamics-based metrics like Dynamic Flexibility Index and Dynamic Coupling Index are employed to quantify the contributions of specific residues to protein dynamics. I investigated the role of dynamics in protein binding of the WW domain. In particular, I focused on how the mutations of distal positions modulate the binding site dynamics. By employing Dynamic Flexibility Index, I discovered that a residue, 10T, located distally from the binding pocket, plays a significant role in the observed dynamics difference between two variants: N21 (a native folded WW domain not binding Group I peptide) and CC16_N21 (an artificial WW domain binding Group I peptide). The T10H variant, created by exchanging the position 10 residue, enhances flexibility at positions 10 and 16. Consequently, this modification has led to an enhancement in the binding function of N21, enabling it to bind to Group I peptide effectively. Moreover, I investigated the influence of dynamic allostery on protein binding specificity, specifically in the PDZ domain PSD95. To gain insights into the binding process and accurately measure binding affinity, I employed two parallel computational approaches: Adaptive BP-docking and Steered Molecular Dynamics. These methods allowed me to model the binding interactions and quantify the binding strength robustly and comprehensively. The significance of allostery can serve as foundational knowledge in Deep Learning models, enabling the efficient mapping of protein sequences to their corresponding functionalities. One particular metric, Dynamic Coupling Index asymmetry, offers valuable insights into how the three-dimensional network of interactions facilitates communication within a protein structure. Leveraging these interactions, I developed a deep neural network architecture demonstrating enhanced capability in capturing epistatic interactions within Beta-lactamase and protein G function.
ContributorsLu, Jin (Author) / Ozkan, Banu (Thesis advisor) / Mills, Jeremy (Committee member) / Hariadi, Rizal (Committee member) / Beckstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2023
ContributorsSeo, YoonJi (Performer) / Choi, Hyeongji (Performer) / Choi, Hyeri (Performer) / Ko, Eunbin (Performer) / Jeon, Dasom (Performer) / Kim, Sungmin (Performer) / Lee, Jiyoung (Performer) / Jeong, Jieun (Performer) / Park, Chulyoung (Performer) / Jo, Hyunsun (Performer) / Steinweg, Tiffany (Performer) / Browning, Natalie (Performer) / ASU Library. Music Library (Publisher)
Created2023-10-28
ContributorsPeterson, Danielle (Performer) / Beymanov, Polina (Performer) / ASU Library. Music Library (Publisher)
Created2023-10-29
ContributorsBeymanov, Polina (Performer) / Bolles, Olivia (Performer) / Ho, Ka I (Performer) / Peterson, Danielle (Performer) / Yu, Wan-Ting (Performer) / Salomon, Gabrielle (Performer) / ASU Library. Music Library (Publisher)
Created2023-11-03
Description
Scientific research encompasses a variety of objectives, including measurement, making predictions, identifying laws, and more. The advent of advanced measurement technologies and computational methods has largely automated the processes of big data collection and prediction. However, the discovery of laws, particularly universal ones, still heavily relies on human intellect. Even with human intelligence, complex systems present a unique challenge in discerning the laws that govern them. Even the preliminary step, system description, poses a substantial challenge. Numerous metrics have been developed, but universally applicable laws remain elusive. Due to the cognitive limitations of human comprehension, a direct understanding of big data derived from complex systems is impractical. Therefore, simplification becomes essential for identifying hidden regularities, enabling scientists to abstract observations or draw connections with existing knowledge. As a result, the concept of macrostates -- simplified, lower-dimensional representations of high-dimensional systems -- proves to be indispensable. Macrostates serve a role beyond simplification. They are integral in deciphering reusable laws for complex systems. In physics, macrostates form the foundation for constructing laws and provide building blocks for studying relationships between quantities, rather than pursuing case-by-case analysis. Therefore, the concept of macrostates facilitates the discovery of regularities across various systems. Recognizing the importance of macrostates, I propose the relational macrostate theory and a machine learning framework, MacroNet, to identify macrostates and design microstates. The relational macrostate theory defines a macrostate based on the relationships between observations, enabling the abstraction from microscopic details. In MacroNet, I propose an architecture to encode microstates into macrostates, allowing for the sampling of microstates associated with a specific macrostate. My experiments on simulated systems demonstrate the effectiveness of this theory and method in identifying macrostates such as energy. Furthermore, I apply this theory and method to a complex chemical system, analyzing oil droplets with intricate movement patterns in a Petri dish, to answer the question, ``which combinations of parameters control which behavior?'' The macrostate theory allows me to identify a two-dimensional macrostate, establish a mapping between the chemical compound and the macrostate, and decipher the relationship between oil droplet patterns and the macrostate.
ContributorsZhang, Yanbo (Author) / Walker, Sara I (Thesis advisor) / Anbar, Ariel (Committee member) / Daniels, Bryan (Committee member) / Das, Jnaneshwar (Committee member) / Davies, Paul (Committee member) / Arizona State University (Publisher)
Created2023
Description
Over the past few years, research into the use of doped diamond in electronics has seen an exponential growth. In the course of finding ways to reduce the contact resistivity, nanocarbon materials have been an interesting focus. In this work, the transfer length method (TLM) was used to investigate Ohmic contact properties using the tri-layer stack Ti/Pt/Au on nitrogen-doped n-type conducting nano-carbon (nanoC) layers grown on (100) diamond substrates. The nanocarbon material was characterized using Secondary Ion Mass Spectrometry (SIMS), Scanning electron Microscopy (SEM) X-ray diffraction (XRD), Raman scattering and Hall effect measurements to probe the materials characteristics. Room temperature electrical measurements were taken, and samples were annealed to observe changes in electrical conductivity. Low specific contact resistivity values of 8 x 10^-5 Ωcm^2 were achieved, which was almost two orders of magnitude lower than previously reported values. The results were attributed to the increased nitrogen incorporation, and the presence of electrically active defects which leads to an increase in conduction in the nanocarbon. Further a study of light phosphorus doped layers using similar methods with Ti/Pt/Au contacts again yielded a low contact resistivity of about 9.88 x 10^-2 Ωcm^2 which is an interesting prospect among lightly doped diamond films for applications in devices such as transistors. In addition, for the first time, hafnium was substituted for Ti in the contact stack (Hf/Pt/Au) and studied on nitrogen doped nanocarbon films, which resulted in low contact resistivity values on the order of 10^-2 Ωcm^2. The implications of the results were discussed, and recommendations for improving the experimental process was outlined. Lastly, a method for the selective area growth of nanocarbon was developed and studied and the results provided an insight into how different characterizations can be used to confirm the presence of the nanocrystalline diamond material, the limitations due to the film thickness was explored and ideas for future work was proposed.
ContributorsAmonoo, Evangeline Abena (Author) / Thornton, Trevor (Thesis advisor) / Alford, Terry L (Thesis advisor) / Anwar, Shahriar (Committee member) / Theodore, David (Committee member) / Arizona State University (Publisher)
Created2023