Non-protein-coding RNAs play critical regulatory roles in cellular life. Many ncRNAs fold into specific structures in order to perform their biological functions. Some of the RNAs, such as riboswitches, can even fold into alternative structural conformations in order to participate in different biological processes. In addition, these RNAs can transit dynamically between different functional structures along folding pathways on their energy landscapes. These alternative functional structures are usually energetically favored and are stable in their local energy landscapes. Moreover, conformational transitions between any pair of alternate structures usually involve high energy barriers, such that RNAs can become kinetically trapped by these stable and local optimal structures. We have proposed a suite of computational approaches for analyzing and discovering regulatory RNAs through studying folding pathways, alternative structures and energy landscapes associated with conformational transitions of regulatory RNAs. First, we developed an approach, RNAEAPath, which can predict low-barrier folding pathways between two conformational structures of a single RNA molecule. Using RNAEAPath, we can analyze folding iii pathways between two functional RNA structures, and therefore study the mechanism behind RNA functional transitions from a thermodynamic perspective. Second, we introduced an approach, RNASLOpt, for finding all the stable and local optimal structures on the energy landscape of a single RNA molecule. We can use the generated stable and local optimal structures to represent the RNA energy landscape in a compact manner. In addition, we applied RNASLOpt to several known riboswitches and predicted their alternate functional structures accurately. Third, we integrated a comparative approach with RNASLOpt, and developed RNAConSLOpt, which can find all the consensus stable and local optimal structures that are conserved among a set of homologous regulatory RNAs. We can use RNAConSLOpt to predict alternate functional structures for regulatory RNA families. Finally, we have proposed a pipeline making use of RNAConSLOpt to computationally discover novel riboswitches in bacterial genomes. An application of the proposed pipeline to a set of bacteria in Bacillus genus results in the re-discovery of many known riboswitches, and the detection of several novel putative riboswitch elements.

Protein aggregation has been implicated in several catastrophic diseases (neurodegeneration, diabetes, ALS) and its complexity has also become a major obstacle in large-scale production of protein-based therapeutics. Despite the generic behavior of proteins to aggregate, only a few globular proteins have known aggregation mechanisms. At present, there have been no clear connections between a protein folding, function and aggregation. We have tackled the challenge of understanding the links between a protein's natural tendency to fold and function with its propensity to misfold and aggregate. Using a predominantly beta-sheet protein whose in vitro folding has been explored in detail: cellular retinoic acid-binding protein I (CRABP 1), as a model, we investigated sequence determinants for folding and aggregation. In addition, we characterized the aggregation-prone intermediate under native conditions. Our studies revealed similar contiguous aggregation cores in in vitro and in vivo aggregates of CRABP 1 validating the importance of sequence information under extremely different conditions. Hydrophobic stretches that comprise the interface in aggregates include residues surrounding the ligand binding portal and residues at the C-terminal strands of CRABP 1. Folding studies reveal that docking of the N and C terminals happen in the early stages of barrel closure of CRABP 1 emphasizing the role of folding in preventing exposure of risky aggregation-prone sequences. We further examined the intermediate that initiates aggregation under native conditions. We found that inherent structural fluctuations in the native protein, relevant to ligand binding of CRABP 1, expose aggregation-prone sequences. Binding of the ligand, retinoic acid decreases the aggregation of CRABP 1 illustrating the contribution functional interactions in avoiding aggregation. Our study implies that because of the evolutionary requirement for proteins to fold and function, aggregation becomes an unavoidable risk.

This work focuses on understanding the buckling deformation mechanisms of bending, wrinkling, and folding that occur on the surfaces and interfaces of polymer systems. We gained fundamental insight into the formation mechanism of these buckled structures for thin glassy films placed on an elastomeric substrate. By taking advantage of geometric confinement, we demonstrated new strategies in controlling wrinkling morphologies. We were able to achieve surfaces with controlled patterned structures which will have a broad impact in optical, adhesive, microelectronics, and microfluidics applications. Wrinkles and strain localized features, such as delaminations and folds, are observed in many natural systems and are useful for a wide range of patterning applications. However, the transition from sinusoidal wrinkles to more complex strain localized structures is not well understood. We investigated the onset of wrinkling and strain localizations under uniaxial strain. We show that careful measurement of feature amplitude allowed not only the determination of wrinkle, fold, or delamination onset, but also allowed clear distinction between each feature. The folds observed in this experiment have an outward morphology from the surface in contrast to folds that form into the plane, as observed in a film floating on a liquid substrate. A critical strain map was constructed, where the critical strain was measured experimentally for wrinkling, folding, and delamination with varying film thickness and modulus. Wrinkle morphologies, i.e. amplitude and wavelength of wrinkles, affect properties such as electron transport in stretchable electronics and adhesion properties of smart surfaces. To gain an understanding of how the wrinkle morphology can be controlled, we introduced a geometrical confinement in the form of rigid boundaries. Upon straining, we found that wrinkles started near the rigid boundaries where maximum local strain occurred and propagated towards the middle as more global strain was applied. In contrast to homogeneous wrinkling with constant amplitude that is observed for an unconfined system, the wrinkling observed here had varying amplitude as a function of distance from the rigid boundaries. We demonstrated that the number of wrinkles can be tuned by controlling the distance between the rigid boundaries. Location of wrinkles was also controlled by introducing local stress distributions via patterning the elastomeric substrate. Two distinct wrinkled regions were achieved on a surface where the film is free-standing over a circular hole pattern and where the film is supported by the substrate. The hoe diameter and applied strain affected the wavelength and amplitude of the free-standing membrane. Using discontinuous dewetting, a one-step fabrication method was developed to selectively deposit a small volume of liquid in patterned microwells and encapsulate it with a polymeric film. The pull-out velocity, a velocity at which the sample is removed from a bath of liquid, was controlled to observe how encapsulation process is affected. The polymeric film was observed to wrinkle at low pull-out velocity due to no encapsulation of liquid; whereas the film bent at medium pull-out velocity due to capillary effect as the liquid evaporated through the film. To quantify the amount of liquid encapsulated, we mixed salt in water and measured the size of the deposited salt crystals. The salt crystal size, and hence the amount of liquid encapsulated, was controlled by varying either the encapsulation velocity or the size of the patterned microwells. In addition, we showed that the deposited salt crystals are protected by the laminated film until the film is removed, providing advantageous control for delivery and release. Yeast cells were also captured in the microwells to show the versatility. This encapsulation method is useful for wide range of applications, such as trapping single cells for biological studies, growing microcrystals for optical and magnetic applications, and single-use sensor technologies.

Hsp70 molecular chaperones protect proteins from aggregation, assist in their native structure formation, and regulate stress responses in the cell. A mechanistic understanding of Hsp70 function will be necessary to explain its physiological roles and guide the therapeutic modulation of various disease states. To this end, several fundamental features of the Hsp70 structure-function relationship are investigated. The central component of Hsp70 chaperone function is its capacity for allosteric signaling between structural domains and tunable binding of misfolded protein substrates. In order to identify a cooperative network of sites that mediates interdomain allostery within Hsp70, a mutational correlation analysis is performed using genetic data. Evolutionarily correlations that describe an allosteric network are validated by examining roles for implicated sites in cellular fitness and molecular function. In a second component of the Hsp70 molecular mechanism, a novel function is discovered for the disordered C-terminal tail. This region of the protein enhances the refolding efficiency of substrate proteins independently of interdomain allostery and is required in the cell upon depletion of compensatory chaperones, suggesting a previously undescribed mode of chaperone action. Finally, experiments are initiated to assess the dynamic assembly of Hsp70 domains in various allosteric states and how domain orientations may be guided through interaction with partner co-chaperone proteins.

No description available.

Biofilms formed on medical devices pose significant challenges, compromising device efficiency and serving as sources of infection. Staphylococcus epidermidis, an opportunistic pathogen, relies on the autolysin protein, notably its R2ab and amidase domains, to attach to polystyrene surfaces and initiate biofilm formation. Despite their pivotal role, the structural intricacies of these proteins’ interactions with surfaces remain elusive. In this dissertation, the multifaceted aspects of protein interactions with polystyrene surfaces and the implications of these interactions for biofilm control are studied. Over the course of this study, it is found how the R2ab and amidase domains influence biofilm formation on polystyrene surfaces. Pretreatment of polystyrene plates with these domains effectively inhibits biofilm growth, underscoring their strong affinity for polystyrene surfaces. Furthermore, these domains demonstrate a remarkable propensity for interactions with polystyrene nanoparticles (PSNPs). The insights gained from this study offer promising avenues for the development of novel biofilm eradication strategies, with the potential to enhance the longevity and effectiveness of medical devices. Shifting to a broader context of nanotechnology, the influence of nanoparticle size on protein adsorption and unfolding stabilities is studied using two distinct proteins, R2ab and GB3. Isothermal titration calorimetry reveals tighter binding to smaller PSNPs for both proteins, with enthalpy as the driving force. Structural changes in the adsorbed proteins are detected through fluorescence spectroscopy and circular dichroism, indicating a propensity for protein unfolding upon adsorption. Importantly, this unfolding effect is less pronounced with larger PSNPs, which has implications for protein binding on macroscopic surfaces. The significance of side-on interactions between neighboring proteins is underscored in this work, since they appear to stabilize proteins bound to surfaces with low curvature, an observation with critical implications for the protein corona formed around nanoparticles and its potential to preserve the structure of surface-adsorbed proteins in vivo. This dissertation also investigates the molecular-level interaction between R2ab and PSNPs of varying sizes. By utilizing lysine methylation in mass spectrometry and hydrogen-deuterium exchange (HDX) NMR spectroscopy, this work investigates how changes in methylation patterns and hydrogen-deuterium exchange rates in specific regions of R2ab reflect conformational changes upon binding to PSNPs. In conclusion, this dissertation comprehensively explores protein-surface interactions and reveals several important and surprising features of the proteins that drive biofilm formation.

Computational methods are commonly used by materials scientists to make predictions about materials. These methods can achieve in hours what would take days or weeks to accomplish in a lab. However, there are limits to what computational methods can do and how accurate the predictions are.A limiting factor for computational materials science is the size of the search space. The space of potential materials is infinite. Selecting specific systems of elements on a fixed lattice to study reduces the number of possible arrangements of atoms in the lattice to a finite number. However, this number can still be very large. Additionally this list of arrangements will contain duplicates, i.e., two different atomic arrangements could be equivalent by a rotation or translation of the lattice. Using symmetry to eliminate the duplicates saves time and resources. In order to ensure that the final list of unique structures will fit into computer memory it is also useful to know how many unique arrangements there are before actually finding them. For this reason the Pòlya enumeration algorithm was created to determine the number of unique arrangements before enumerating them. A new atomic enumeration algorithm has also been implemented in the enumlib package. This new algorithm has been optimized to find the symmetrically unique arrangements for systems with large amounts of configurational freedom, such as high-entropy alloys, which have been too computationally expensive for other algorithms.A popular computational method in materials science is Density Functional Theory (DFT). DFT codes perform first principles calculations by calculating the electron energy using numerical integrals. It is well known that the accuracy of the integrals depends heavily on the number of sample points, k-points, used. We have conducted a detailed study of how k-point sampling methods effect the accuracy of DFT calculations. This study shows that the most efficient k-point grids are those that have the fewest symmetrically distinct k-points, we call these general regular (GR) grids. GR grids are, however, difficult to generate, requiring a search across many possible grids. In order to make GR grids more accessible to the DFT community we have implemented an algorithm that can search k-point grids for the grid that has the fewest symmetry reduction in a matter of seconds.

No description available.

No description available.

No description available.