16 resultados para Biological Systems

em CaltechTHESIS


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This work quantifies the nature of delays in genetic regulatory networks and their effect on system dynamics. It is known that a time lag can emerge from a sequence of biochemical reactions. Applying this modeling framework to the protein production processes, delay distributions are derived in a stochastic (probability density function) and deterministic setting (impulse function), whilst being shown to be equivalent under different assumptions. The dependence of the distribution properties on rate constants, gene length, and time-varying temperatures is investigated. Overall, the distribution of the delay in the context of protein production processes is shown to be highly dependent on the size of the genes and mRNA strands as well as the reaction rates. Results suggest longer genes have delay distributions with a smaller relative variance, and hence, less uncertainty in the completion times, however, they lead to larger delays. On the other hand large uncertainties may actually play a positive role, as broader distributions can lead to larger stability regions when this formalization of the protein production delays is incorporated into a feedback system.

Furthermore, evidence suggests that delays may play a role as an explicit design into existing controlling mechanisms. Accordingly, the reccurring dual-feedback motif is also investigated with delays incorporated into the feedback channels. The dual-delayed feedback is shown to have stabilizing effects through a control theoretic approach. Lastly, a distributed delay based controller design method is proposed as a potential design tool. In a preliminary study, the dual-delayed feedback system re-emerges as an effective controller design.

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Computation technology has dramatically changed the world around us; you can hardly find an area where cell phones have not saturated the market, yet there is a significant lack of breakthroughs in the development to integrate the computer with biological environments. This is largely the result of the incompatibility of the materials used in both environments; biological environments and experiments tend to need aqueous environments. To help aid in these development chemists, engineers, physicists and biologists have begun to develop microfluidics to help bridge this divide. Unfortunately, the microfluidic devices required large external support equipment to run the device. This thesis presents a series of several microfluidic methods that can help integrate engineering and biology by exploiting nanotechnology to help push the field of microfluidics back to its intended purpose, small integrated biological and electrical devices. I demonstrate this goal by developing different methods and devices to (1) separate membrane bound proteins with the use of microfluidics, (2) use optical technology to make fiber optic cables into protein sensors, (3) generate new fluidic devices using semiconductor material to manipulate single cells, and (4) develop a new genetic microfluidic based diagnostic assay that works with current PCR methodology to provide faster and cheaper results. All of these methods and systems can be used as components to build a self-contained biomedical device.

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Using neuromorphic analog VLSI techniques for modeling large neural systems has several advantages over software techniques. By designing massively-parallel analog circuit arrays which are ubiquitous in neural systems, analog VLSI models are extremely fast, particularly when local interactions are important in the computation. While analog VLSI circuits are not as flexible as software methods, the constraints posed by this approach are often very similar to the constraints faced by biological systems. As a result, these constraints can offer many insights into the solutions found by evolution. This dissertation describes a hardware modeling effort to mimic the primate oculomotor system which requires both fast sensory processing and fast motor control. A one-dimensional hardware model of the primate eye has been built which simulates the physical dynamics of the biological system. It is driven by analog VLSI circuits mimicking brainstem and cortical circuits that control eye movements. In this framework, a visually-triggered saccadic system is demonstrated which generates averaging saccades. In addition, an auditory localization system, based on the neural circuits of the barn owl, is used to trigger saccades to acoustic targets in parallel with visual targets. Two different types of learning are also demonstrated on the saccadic system using floating-gate technology allowing the non-volatile storage of analog parameters directly on the chip. Finally, a model of visual attention is used to select and track moving targets against textured backgrounds, driving both saccadic and smooth pursuit eye movements to maintain the image of the target in the center of the field of view. This system represents one of the few efforts in this field to integrate both neuromorphic sensory processing and motor control in a closed-loop fashion.

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Despite the complexity of biological networks, we find that certain common architectures govern network structures. These architectures impose fundamental constraints on system performance and create tradeoffs that the system must balance in the face of uncertainty in the environment. This means that while a system may be optimized for a specific function through evolution, the optimal achievable state must follow these constraints. One such constraining architecture is autocatalysis, as seen in many biological networks including glycolysis and ribosomal protein synthesis. Using a minimal model, we show that ATP autocatalysis in glycolysis imposes stability and performance constraints and that the experimentally well-studied glycolytic oscillations are in fact a consequence of a tradeoff between error minimization and stability. We also show that additional complexity in the network results in increased robustness. Ribosome synthesis is also autocatalytic where ribosomes must be used to make more ribosomal proteins. When ribosomes have higher protein content, the autocatalysis is increased. We show that this autocatalysis destabilizes the system, slows down response, and also constrains the system’s performance. On a larger scale, transcriptional regulation of whole organisms also follows architectural constraints and this can be seen in the differences between bacterial and yeast transcription networks. We show that the degree distributions of bacterial transcription network follow a power law distribution while the yeast network follows an exponential distribution. We then explored the evolutionary models that have previously been proposed and show that neither the preferential linking model nor the duplication-divergence model of network evolution generates the power-law, hierarchical structure found in bacteria. However, in real biological systems, the generation of new nodes occurs through both duplication and horizontal gene transfers, and we show that a biologically reasonable combination of the two mechanisms generates the desired network.

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Multi-step electron tunneling, or “hopping,” has become a fast-developing research field with studies ranging from theoretical modeling systems, inorganic complexes, to biological systems. In particular, the field is exploring hopping mechanisms in new proteins and protein complexes, as well as further understanding the classical biological hopping systems such as ribonuclease reductase, DNA photolyases, and photosystem II. Despite the plethora of natural systems, only a few biologically engineered systems exist. Engineered hopping systems can provide valuable information on key structural and electronic features, just like other kinds of biological model systems. Also, engineered systems can harness common biologic processes and utilize them for alternative reactions. In this thesis, two new hopping systems are engineered and characterized.

The protein Pseudomonas aeruginosa azurin is used as a building block to create the two new hopping systems. Besides being well studied and amenable to mutation, azurin already has been used to successfully engineer a hopping system. The two hopping systems presented in this thesis have a histidine-attached high potential rhenium 4,7-dimethyl-1,10-phenanthroline tricarbonyl [Re(dmp)(CO)3] + label which, when excited, acts as the initial electron acceptor. The metal donor is the type I copper of the azurin protein. The hopping intermediates are all tryptophan, an amino acid mutated into the azurin at select sites between the photoactive metal label and the protein metal site. One system exhibits an inter-molecular hopping through a protein dimer interface; the other system undergoes intra-molecular multi-hopping utilizing a tryptophan “wire.” The electron transfer reactions are triggered by excitation of the rhenium label and monitored by UV-Visible transient absorption, luminescence decays measurements, and time-resolved Infrared spectroscopy (TRIR). Both systems were structurally characterized by protein X-ray crystallography.

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Systems-level studies of biological systems rely on observations taken at a resolution lower than the essential unit of biology, the cell. Recent technical advances in DNA sequencing have enabled measurements of the transcriptomes in single cells excised from their environment, but it remains a daunting technical problem to reconstruct in situ gene expression patterns from sequencing data. In this thesis I develop methods for the routine, quantitative in situ measurement of gene expression using fluorescence microscopy.

The number of molecular species that can be measured simultaneously by fluorescence microscopy is limited by the pallet of spectrally distinct fluorophores. Thus, fluorescence microscopy is traditionally limited to the simultaneous measurement of only five labeled biomolecules at a time. The two methods described in this thesis, super-resolution barcoding and temporal barcoding, represent strategies for overcoming this limitation to monitor expression of many genes in a single cell. Super-resolution barcoding employs optical super-resolution microscopy (SRM) and combinatorial labeling via-smFISH (single molecule fluorescence in situ hybridization) to uniquely label individual mRNA species with distinct barcodes resolvable at nanometer resolution. This method dramatically increases the optical space in a cell, allowing a large numbers of barcodes to be visualized simultaneously. As a proof of principle this technology was used to study the S. cerevisiae calcium stress response. The second method, sequential barcoding, reads out a temporal barcode through multiple rounds of oligonucleotide hybridization to the same mRNA. The multiplexing capacity of sequential barcoding increases exponentially with the number of rounds of hybridization, allowing over a hundred genes to be profiled in only a few rounds of hybridization.

The utility of sequential barcoding was further demonstrated by adapting this method to study gene expression in mammalian tissues. Mammalian tissues suffer both from a large amount of auto-fluorescence and light scattering, making detection of smFISH probes on mRNA difficult. An amplified single molecule detection technology, smHCR (single molecule hairpin chain reaction), was developed to allow for the quantification of mRNA in tissue. This technology is demonstrated in combination with light sheet microscopy and background reducing tissue clearing technology, enabling whole-organ sequential barcoding to monitor in situ gene expression directly in intact mammalian tissue.

The methods presented in this thesis, specifically sequential barcoding and smHCR, enable multiplexed transcriptional observations in any tissue of interest. These technologies will serve as a general platform for future transcriptomic studies of complex tissues.

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Nucleic acids are most commonly associated with the genetic code, transcription and gene expression. Recently, interest has grown in engineering nucleic acids for biological applications such as controlling or detecting gene expression. The natural presence and functionality of nucleic acids within living organisms coupled with their thermodynamic properties of base-pairing make them ideal for interfacing (and possibly altering) biological systems. We use engineered small conditional RNA or DNA (scRNA, scDNA, respectively) molecules to control and detect gene expression. Three novel systems are presented: two for conditional down-regulation of gene expression via RNA interference (RNAi) and a third system for simultaneous sensitive detection of multiple RNAs using labeled scRNAs.

RNAi is a powerful tool to study genetic circuits by knocking down a gene of interest. RNAi executes the logic: If gene Y is detected, silence gene Y. The fact that detection and silencing are restricted to the same gene means that RNAi is constitutively on. This poses a significant limitation when spatiotemporal control is needed. In this work, we engineered small nucleic acid molecules that execute the logic: If mRNA X is detected, form a Dicer substrate that targets independent mRNA Y for silencing. This is a step towards implementing the logic of conditional RNAi: If gene X is detected, silence gene Y. We use scRNAs and scDNAs to engineer signal transduction cascades that produce an RNAi effector molecule in response to hybridization to a nucleic acid target X. The first mechanism is solely based on hybridization cascades and uses scRNAs to produce a double-stranded RNA (dsRNA) Dicer substrate against target gene Y. The second mechanism is based on hybridization of scDNAs to detect a nucleic acid target and produce a template for transcription of a short hairpin RNA (shRNA) Dicer substrate against target gene Y. Test-tube studies for both mechanisms demonstrate that the output Dicer substrate is produced predominantly in the presence of a correct input target and is cleaved by Dicer to produce a small interfering RNA (siRNA). Both output products can lead to gene knockdown in tissue culture. To date, signal transduction is not observed in cells; possible reasons are explored.

Signal transduction cascades are composed of multiple scRNAs (or scDNAs). The need to study multiple molecules simultaneously has motivated the development of a highly sensitive method for multiplexed northern blots. The core technology of our system is the utilization of a hybridization chain reaction (HCR) of scRNAs as the detection signal for a northern blot. To achieve multiplexing (simultaneous detection of multiple genes), we use fluorescently tagged scRNAs. Moreover, by using radioactive labeling of scRNAs, the system exhibits a five-fold increase, compared to the literature, in detection sensitivity. Sensitive multiplexed northern blot detection provides an avenue for exploring the fate of scRNAs and scDNAs in tissue culture.

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To better understand human diseases, much recent work has focused on proteins to either identify disease targets through proteomics or produce therapeutics via protein engineering. Noncanonical amino acids (ncAAs) are tools for altering the chemical and physical properties of proteins, providing a facile strategy not only to label proteins but also to engineer proteins with novel properties. My thesis research has focused on the development and applications of noncanonical amino acids in identifying, imaging, and engineering proteins for studying human diseases. Chapter 1 introduces the concept of ncAAs and reveals insights to how I chose my thesis projects.

ncAAs have been incorporated to tag and enrich newly synthesized proteins for mass spectrometry through a method termed BONCAT, or bioorthogonal noncanonical amino acid tagging. Chapter 2 describes the investigation of the proteomic response of human breast cancer cells to induced expression of tumor suppressor microRNA miR-126 by combining BONCAT with another proteomic method, SILAC or stable isotope labeling by amino acids in cell culture. This proteomic analysis led to the discovery of a direct target of miR-126, shedding new light on its role in suppressing cancer metastasis.

In addition to mass spectrometry, ncAAs can also be utilized to fluorescently label proteins. Chapter 3 details the synthesis of a set of cell-permeant cyclooctyne probes and demonstration of selective labeling of newly synthesized proteins in live mammalian cells using azidohomoalanine. Similar to live cell imaging, the ability to selectively label a particular cell type within a mixed cell population is important to interrogating many biological systems, such as tumor microenvironments. By taking advantage of the metabolic differences between cancer and normal cells, Chapter 5 discusses efforts to develop selective labeling of cancer cells using a glutamine analogue.

Furthermore, Chapter 4 describes the first demonstration of global replacement at polar amino acid positions and its application in developing an alternative PEGylation strategy for therapeutic proteins. Polar amino acids typically occupy solvent-exposed positions on the protein surface, and incorporation of noncanonical amino acids at these positions should allow easier modification and cause less perturbation compared to replacements at the interior positions of proteins.

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Efficient and accurate localization of membrane proteins is essential to all cells and requires a complex cascade of interactions between protein machineries. This is exemplified in the recently discovered Guided Entry of Tail-anchored protein pathway, in which the central targeting factor Get3 must sequentially interact with three distinct binding partners (Get4, Get1 and Get2) to ensure the targeted delivery of Tail-anchored proteins to the endoplasmic reticulum membrane. To understand the molecular and energetic principles that provide the vectorial driving force of these interactions, we used a quantitative fluorescence approach combined with mechanistic enzymology to monitor the effector interactions of Get3 at each stage of Tail-anchored protein targeting. We show that nucleotide and membrane protein substrate generate a gradient of interaction energies that drive the cyclic and ordered transit of Get3 from Get4 to Get2 and lastly to Get1. These data also define how the Get3/Tail-anchored complex is captured, handed over, and disassembled by the Get1/2 receptor at the membrane, and reveal a novel role for Get4/5 in recycling Get3 from the endoplasmic reticulum membrane at the end of the targeting reaction. These results provide general insights into how complex cascades of protein interactions are coordinated and coupled to energy inputs in biological systems.

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Optical microscopy has become an indispensable tool for biological researches since its invention, mostly owing to its sub-cellular spatial resolutions, non-invasiveness, instrumental simplicity, and the intuitive observations it provides. Nonetheless, obtaining reliable, quantitative spatial information from conventional wide-field optical microscopy is not always intuitive as it appears to be. This is because in the acquired images of optical microscopy the information about out-of-focus regions is spatially blurred and mixed with in-focus information. In other words, conventional wide-field optical microscopy transforms the three-dimensional spatial information, or volumetric information about the objects into a two-dimensional form in each acquired image, and therefore distorts the spatial information about the object. Several fluorescence holography-based methods have demonstrated the ability to obtain three-dimensional information about the objects, but these methods generally rely on decomposing stereoscopic visualizations to extract volumetric information and are unable to resolve complex 3-dimensional structures such as a multi-layer sphere.

The concept of optical-sectioning techniques, on the other hand, is to detect only two-dimensional information about an object at each acquisition. Specifically, each image obtained by optical-sectioning techniques contains mainly the information about an optically thin layer inside the object, as if only a thin histological section is being observed at a time. Using such a methodology, obtaining undistorted volumetric information about the object simply requires taking images of the object at sequential depths.

Among existing methods of obtaining volumetric information, the practicability of optical sectioning has made it the most commonly used and most powerful one in biological science. However, when applied to imaging living biological systems, conventional single-point-scanning optical-sectioning techniques often result in certain degrees of photo-damages because of the high focal intensity at the scanning point. In order to overcome such an issue, several wide-field optical-sectioning techniques have been proposed and demonstrated, although not without introducing new limitations and compromises such as low signal-to-background ratios and reduced axial resolutions. As a result, single-point-scanning optical-sectioning techniques remain the most widely used instrumentations for volumetric imaging of living biological systems to date.

In order to develop wide-field optical-sectioning techniques that has equivalent optical performance as single-point-scanning ones, this thesis first introduces the mechanisms and limitations of existing wide-field optical-sectioning techniques, and then brings in our innovations that aim to overcome these limitations. We demonstrate, theoretically and experimentally, that our proposed wide-field optical-sectioning techniques can achieve diffraction-limited optical sectioning, low out-of-focus excitation and high-frame-rate imaging in living biological systems. In addition to such imaging capabilities, our proposed techniques can be instrumentally simple and economic, and are straightforward for implementation on conventional wide-field microscopes. These advantages together show the potential of our innovations to be widely used for high-speed, volumetric fluorescence imaging of living biological systems.

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Synthetic biological systems promise to combine the spectacular diversity of biological functionality with engineering principles to design new life to address many pressing needs. As these engineered systems advance in sophistication, there is ever-greater need for customizable, situation-specific expression of desired genes. However, existing gene control platforms are generally not modular, or do not display performance requirements required for robust phenotypic responses to input signals. This work expands the capabilities of eukaryotic gene control in two important directions.

For development of greater modularity, we extend the use of synthetic self-cleaving ribozyme switches to detect changes in input protein levels and convey that information into programmed gene expression in eukaryotic cells. We demonstrate both up- and down-regulation of levels of an output transgene by more than 4-fold in response to rising input protein levels, with maximal output gene expression approaching the highest levels observed in yeast. In vitro experiments demonstrate protein-dependent ribozyme activity modulation. We further demonstrate the platform in mammalian cells. Our switch devices do not depend on special input protein activity, and can be tailored to respond to any input protein to which a suitable RNA aptamer can be developed. This platform can potentially be employed to regulate the expression of any transgene or any endogenous gene by 3’ UTR replacement, allowing for more complex cell state-specific reprogramming.

We also address an important concern with ribozyme switches, and riboswitch performance in general, their dynamic range. While riboswitches have generally allowed for versatile and modular regulation, so far their dynamic ranges of output gene modulation have been modest, generally at most 10-fold. We address this shortcoming by developing a modular genetic amplifier for near-digital control of eukaryotic gene expression. We combine ribozyme switch-mediated regulation of a synthetic TF with TF-mediated regulation of an output gene. The amplifier platform allows for as much as 20-fold regulation of output gene expression in response to input signal, with maximal expression approaching the highest levels observed in yeast, yet being tunable to intermediate and lower expression levels. EC50 values are more than 4 times lower than in previously best-performing non-amplifier ribozyme switches. The system design retains the modular-input architecture of the ribozyme switch platform, and the near-digital dynamic ranges of TF-based gene control.

Together, these developments suggest great potential for the wide applicability of these platforms for better-performing eukaryotic gene regulation, and more sophisticated, customizable reprogramming of cellular activity.

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Vortex rings constitute the main structure in the wakes of a wide class of swimming and flying animals, as well as in cardiac flows and in the jets generated by some moss and fungi. However, there is a physical limit, determined by an energy maximization principle called the Kelvin-Benjamin principle, to the size that axisymmetric vortex rings can achieve. The existence of this limit is known to lead to the separation of a growing vortex ring from the shear layer feeding it, a process known as `vortex pinch-off', and characterized by the dimensionless vortex formation number. The goal of this thesis is to improve our understanding of vortex pinch-off as it relates to biological propulsion, and to provide future researchers with tools to assist in identifying and predicting pinch-off in biological flows.

To this end, we introduce a method for identifying pinch-off in starting jets using the Lagrangian coherent structures in the flow, and apply this criterion to an experimentally generated starting jet. Since most naturally occurring vortex rings are not circular, we extend the definition of the vortex formation number to include non-axisymmetric vortex rings, and find that the formation number for moderately non-axisymmetric vortices is similar to that of circular vortex rings. This suggests that naturally occurring vortex rings may be modeled as axisymmetric vortex rings. Therefore, we consider the perturbation response of the Norbury family of axisymmetric vortex rings. This family is chosen to model vortex rings of increasing thickness and circulation, and their response to prolate shape perturbations is simulated using contour dynamics. Finally, the response of more realistic models for vortex rings, constructed from experimental data using nested contours, to perturbations which resemble those encountered by forming vortices more closely, is simulated using contour dynamics. In both families of models, a change in response analogous to pinch-off is found as members of the family with progressively thicker cores are considered. We posit that this analogy may be exploited to understand and predict pinch-off in complex biological flows, where current methods are not applicable in practice, and criteria based on the properties of vortex rings alone are necessary.

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Nature has used a variety of protein systems to mediate electron transfer. In this thesis I examine aspects of the control of biological electron transfer by two copper proteins that act as natural electron carriers.

In the first study, I have made a mutation to one of the ligand residues in the azurin blue copper center, methionine 121 changed to a glutamic acid. Studies of intramolecular electron transfer rates from that mutated center to covalently attached ruthenium complexes indicate that the weak axial methionine ligand is important not only for tuning the reduction potential of the blue copper site but also for maintaining the low reorganization energy that is important for fast electron transfer at long distances.

In the second study, I begin to examine the reorganization energy of the purple copper center in the CuA domain of subunit II of cytochrome c oxidase. In this copper center, the unpaired electron is delocalized over the entire binuclear site. Because long-range electron transfer into and out of this center occurs over long distances with very small driving forces, the reorganization energy of the CuA center has been predicted to be extremely low. I describe a strategy for measuring this reorganization energy starting with the construction of a series of mutations introducing surface histidines. These histidines can then be labeled with a series of ruthenium compounds that differ primarily in their reduction potentials. The electron transfer rates to these ruthenium compounds can then be used to determine the reorganization energy of the CuA site.

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This dissertation describes efforts to model biological active sites with small molecule clusters. The approach used took advantage of a multinucleating ligand to control the structure and nuclearity of the product complexes, allowing the study of many different homo- and heterometallic clusters. Chapter 2 describes the synthesis of the multinucleating hexapyridyl trialkoxy ligand used throughout this thesis and the synthesis of trinuclear first row transition metal complexes supported by this framework, with an emphasis on tricopper systems as models of biological multicopper oxidases. The magnetic susceptibility of these complexes were studied, and a linear relation was found between the Cu-O(alkoxide)-Cu angles and the antiferromagnetic coupling between copper centers. The triiron(II) and trizinc(II) complexes of the ligand were also isolated and structurally characterized.

Chapter 3 describes the synthesis of a series of heterometallic tetranuclear manganese dioxido complexes with various incorporated apical redox-inactive metal cations (M = Na+, Ca2+, Sr2+, Zn2+, Y3+). Chapter 4 presents the synthesis of heterometallic trimanganese(IV) tetraoxido complexes structurally related to the CaMn3 subsite of the oxygen-evolving complex (OEC) of Photosystem II. The reduction potentials of these complexes were studied, and it was found that each isostructural series displays a linear correlation between the reduction potentials and the Lewis acidities of the incorporated redox-inactive metals. The slopes of the plotted lines for both the dioxido and tetraoxido clusters are the same, suggesting a more general relationship between the electrochemical potentials of heterometallic manganese oxido clusters and their “spectator” cations. Additionally, these studies suggest that Ca2+ plays a role in modulating the redox potential of the OEC for water oxidation.

Chapter 5 presents studies of the effects of the redox-inactive metals on the reactivities of the heterometallic manganese complexes discussed in Chapters 3 and 4. Oxygen atom transfer from the clusters to phosphines is studied; although the reactivity is kinetically controlled in the tetraoxido clusters, the dioxido clusters with more Lewis acidic metal ions (Y3+ vs. Ca2+) appear to be more reactive. Investigations of hydrogen atom transfer and electron transfer rates are also discussed.

Appendix A describes the synthesis, and metallation reactions of a new dinucleating bis(N-heterocyclic carbene)ligand framework. Dicopper(I) and dicobalt(II) complexes of this ligand were prepared and structurally characterized. A dinickel(I) dichloride complex was synthesized, reduced, and found to activate carbon dioxide. Appendix B describes preliminary efforts to desymmetrize the manganese oxido clusters via functionalization of the basal multinucleating ligand used in the preceding sections of this dissertation. Finally, Appendix C presents some partially characterized side products and unexpected structures that were isolated throughout the course of these studies.

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Accurate simulation of quantum dynamics in complex systems poses a fundamental theoretical challenge with immediate application to problems in biological catalysis, charge transfer, and solar energy conversion. The varied length- and timescales that characterize these kinds of processes necessitate development of novel simulation methodology that can both accurately evolve the coupled quantum and classical degrees of freedom and also be easily applicable to large, complex systems. In the following dissertation, the problems of quantum dynamics in complex systems are explored through direct simulation using path-integral methods as well as application of state-of-the-art analytical rate theories.