▼ Characterizing the specificity of proteases is important to illuminate their role as signaling moieties in a range of diverse biological processes. Proteases often display multispecificity, which is the ability of a single receptor protein molecule to interact with multiple substrates. The ability to accurately recapitulate protease specificity profiles would aid in the design of custom proteases designed to cleave targets in biotechnology or therapeutic scenarios. Current specificity prediction methods use machine - learning techniques that are not generalizable and relatively slow, and thus limited in use for prediction and especially design of multispecificity. We tackle these challenges using a two - pronged approach - by increasing the accuracy of scoring for biophysical protease substrate models as well as by hastening the process of sampling. We develop a general approach for prediction of protease specificity through the construction of high - resolution atomic models, using protein structure modeling and biophysical energetic evaluation of enzyme substrate complexes. Specifically, we develop a discriminatory scoring function using enzyme design modules from Rosetta and Amber-MMPBSA. Analysis of structural models provides physical insight into the structural basis for the observed specificities. We further test the predictive capability of the model by designing and experimentally characterizing the cleavage of four novel substrate motifs for the Hepatitis C virus NS3/4A protease using an in vivo assay. The presented structure-based approach is generalizable to other protease enzymes with known or modeled structures, and complements existing experimental methods for specificity determination. To improve our sampling approach, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities. Viral systems encoding proteases are exemplars of multispecificity. Multispecific proteases mediate the precise cleavage of the polyprotein during replication and viral assembly. The HCV NS3/4A protease is a multispecific protease, which is likely a result of both positive selection pressure to maintain cleavability of its four native substrates, i.e. known sites on the polyprotein, and negative selection pressure to avoid cleavage of other sites in the polyprotein. We map the specificity landscape of the HCV NS3/4A protease to obtain a comprehensive understanding of the protease–substrate interaction network. Using an in vivo yeast surface display assay, Fluorescence Assisted Cell Sorting, Next Generation Sequencing technology and computational modeling using Rosetta and Amber packages, we were able to reconstruct the entire (3.2 million sequences) HCV NS3/4A substrate landscape learning… Advisors/Committee Members: Khare, Sagar D (chair), School of Graduate Studies.

▼ Alpha-synuclein (asyn) is a 140 amino acid intrinsically disordered protein that is known to form fibrils found in patients with Parkinson's Disease and Dementia with Lewy Bodies. Beta-synuclein (bsyn) is a homolog of asyn, but is not known to form fibrils and is an inhibitor of asyn aggregation under physiological conditions. Both proteins can be divided into three domains with distinct properties: N-terminal, NAC, and C-terminal. By combining domains of asyn and bsyn to form chimera structures and analyzing them through a combination of Thioflavin T binding assays, NMR, AFM, and computational studies of each expected fibril state, this study will show that chimeras with a bsyn NAC region require a reduction in pH to form fibrils, while asyn NAC chimeras are more similar to asyn in their aggregation behavior and possibly energetics within the fibril state. The regions flanking the NAC seemed to be able to regulate aggregation, where certain combinations were more inhibiting of aggregation (asyn N-terminal with bsyn C-terminal), while one combination may have actually accelerated aggregation (bsyn N-terminal with asyn C-terminal) relative to asyn. Computational studies made clear that the bsyn NAC proteins must have a different fibrillar structure than asyn, and a combination of NMR chemical shift data and energies determined from computation supported the idea that some allosteric effects may influence a possibly crucial region in the chimeras (residues ~55 to 60). This study provided more information as to how a protein like bsyn can possibly overcome the influence of inhibiting regions under non-physiological conditions to form fibrils and indicates that utilizing the properties of bsyn's C-terminal domain can lead to the proposal of especially effective inhibitors of asyn aggregation. Advisors/Committee Members: Baum, Jean (chair), Khare, Sagar (internal member), Olson, Wilma (internal member).

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We present a broad effort at the development of crystal simulation methodology and its application to benefit both macromolecular crystallography and molecular dynamics methods. Crystallography is the current method of choice for structural determination of biomolecules, but it is hampered by the inherently time and space-averaged nature of the experiment as well as methodological limitations that do not sufficiently account for the heterogeneous and dynamic nature of crystals. Molecular dynamics has proven itself as a method capable of probing the physics and chemistry of biomolecules on an atomic scale, but requires continued development of the underlying force field parameters to more accurately reproduce observables. Our effort has focused on developing the framework for molecular dynamics simulations of biomolecular crystals. We first present our methodology for performing crystal simulations and show how it is applied first to simple peptide crystals and then to increasingly complex biomolecular systems. We demonstrate the the utility of crystal simulations for validation of molecular dynamics. Then we show the improvement to crystallographic methods that can be gained by incorporating molecular dynamics methods. Our work is of significant benefit to both the molecular dynamics and macromolecular crystallography communities and proposes specific approaches to integrate the two fields for the benefit of both.

Advisors/Committee Members: Case, David (chair), York, Darrin (co-chair), Khare, Sagar (internal member), Marcotrigiano, Joseph (outside member).

▼ PT3 is a redesigned adenosine deaminase that could catalyze the hydrolysis of organophosphate. In this present work, we evaluate the impact of previous designed mutations by investigating the mechanism of PT3. We started from the high-resolution crystal structure and truncated the active site residues as the QM model. Then the potential surface of the reaction was discovered by locating the transition states and intermediates along the reaction path with QM method B3LYP. The results showed a similar energy profile compared to natural phosphotriesterase and the nucleophilic attack turned out to be the rate-limiting step. The impact of a single mutation V218F that leaded to 20-fold increase in the catalytic rate kcat was rationalized by including this residue in QM model and a 5.0 kcal/mol difference of the reaction barrier was discovered. Then with the rationalized model, we performed a low-level QM calculation with key bond lengths fixed at a value from high-level QM results. The barrier difference of V218F changed to 3.6kcal/mol, which was still consistent with experimental results while the computation time was cut half. With this fast computational setting, we are able to analyze more mutations of their impact on the reaction barrier quantum mechanically. Advisors/Committee Members: Baum, Jean (chair), York, Darrin (internal member), Case, David (internal member), Khare, Sagar (internal member).

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Proteases are ubiquitous and significant to both normal cellular functioning and disease states. They are generally multispecific, cleaving a set of substrates without recognizing other peptides. Computational methods to predict and design protease multispecificity would advance our understanding of the biophysical basis of protease specificity, enable the characterization of novel proteases, allow the identification of novel biological roles for proteases, elucidate protease specificity landscapes and ultimately further the design of custom proteases to serve as therapeutics or protein-level knockout reagents in cell culture. Current methods of computational protease specificity prediction are limited in a variety of ways. Techniques to classify substrates as cleaved or uncleaved are constrained by the quality of the input data, cannot be easily generalized to other proteases, and require large training data sets to learn correlations between substrate positions. Methods that predict specificity profiles are computationally expensive and thus unable to be used directly within design. While fitness landscapes have been explored experimentally and via low-resolution computational models, no methods have yet explored the full fitness landscape using chemically realistic atomic-resolution computations. In this dissertation, we further the understanding of protease multispecificity via a variety of experimental and computational techniques that can be generalized to other proteases. First, we develop a structure-based classifier that distinguishes robustly between cleaved and uncleaved substrates, benchmark the classifier performance for five model proteases, and apply the classifier in a blind test to identify novel substrates. Second, we implement a mean-field structure-based algorithm (MFPred) to rapidly and accurately predict protease specificity profiles, benchmark MFPred performance on a range of protease and protein-recognition domains, and demonstrate that MFPred accurately predicts the impact of receptor-side mutations, thus showing putative utility in protease design. Third, we construct a specificity landscape of hepatitis C virus NS3 protease using both experimental and computational methods and find evidence for a structural basis of mutational robustness. Finally, we compare the Rosetta and Amber energy functions used in the computational prediction of protease multispecificity in a systematic benchmark.

Advisors/Committee Members: Khare, Sagar (chair), Case, David (internal member), Nanda, Vikas (internal member), Bonneau, Richard (outside member), School of Graduate Studies.

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The enzyme supercomplex Photosystem II (PSII) is the sole water oxidase known to have developed in nature. Accordingly, it is the source of almost all biologically useful reductant present in the biosphere, as well as the molecular oxygen in Earth’s atmosphere. Understanding this massive, complex protein is thus crucial to development of novel bioinspired water-oxidizing catalysts, a crucial step toward reducing dependence on fossil fuels, which are also ultimately products of PSII activity. Improving understanding and control of the operation and regulation of PSII is also critical for development of agriculture, biofuels, and bioproducts. As the active domains of PSII are highly conserved, substitution of functional and tuning components of the complex and investigation of alterations to functionality represents a well-proven method for study of this complex. However, the development of a range of novel techniques for phenomenological investigation of PSII has allowed for the observation of previously unknown processes and functionalities associated with certain components of PSII. The use of exogenous quinones to remove the kinetic constraint of electron removal from the acceptor side of PSII allows a more accurate determination of the first electron transfer steps within PSII, removing a major confounding variable from kinetic studies of processes within the enzyme. Expansion of fluorometric and oximetric techniques allows processes to be probed under conditions previously inaccessible due to the need to generate specific and often unnatural sample conditions. With these new developments, cofactor substitutions are employed to clarify the functionality of the native cofactors.

Advisors/Committee Members: Dismukes, G. Charles (chair), Khare, Sagar (internal member), Falkowski, Paul (internal member), Bhattacharya, Debashish (outside member), School of Graduate Studies.

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Integrin–collagen interactions play a critical role in numerous cellular functions. In this dissertation, the structures, dynamics, and interactions of the type I collagen and integrin I domains are investigated. The objective is to gain insight into the mechanism of the collagen–integrin interactions. Collagen fibril interactions with cells and macromolecules in the extracellular matrix drive numerous cellular functions. Binding motifs for dozens of collagen-binding proteins have been determined on fully exposed collagen triple helical monomers. However, when the monomers are assembled into the functional collagen fibril, binding motifs become inaccessible, and yet critical cellular processes continue to occur. Here we use an integrative approach by combining molecular dynamics (MD) simulations with atomic force microscopy (AFM) experiments and show that fluctuations of the collagen monomers within the complex fibril play a critical role in collagen interactions. To better understand the mechanisms underlying collagen-induced conformational switches of integrin I domains, we employ NMR hydrogen-deuterium exchange (HDX) experiments to explore the impact of slower timescale dynamic events. NMR HDX results suggest a relationship between regions exhibiting a reduced local stability in the unbound I domain and those that undergo significant conformational changes upon binding. This study supports a model in which intrinsically destabilized regions predispose conformational rearrangement in the integrin I domain. The morphology and mechanical properties of type I collagen fibrils vary greatly in different tissues. Integrins have been proposed to regulate the type I collagen fibrillogenesis in vivo. Here we report on the type I collagen fibrillogenesis affected by integrin I domains and mutants. The conducted experiments showed that integrins and variants slowed down the kinetics of type I collagen fibril formation and reduced the sizes of the immature fibrils. The gain-of-function mutants inhibited the fusions of fibrils. Enhanced viscosities of collagen gels were observed in the presence of integrin I domains, implying stronger interactions between collagen fibrils. We propose that in vivo, integrins of different activation states might regulate collagen fibrillogenesis.

Advisors/Committee Members: Baum, Jean (chair), Case, David (co-chair), Khare, Sagar (internal member), Nanda, Vikas (outside member), School of Graduate Studies.

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DNA in eukaryotic cell nuclei is packaged in a highly compact, yet dynamic chromatin structure that provides a regulatory mechanism for many biological processes, such as gene expression. The basic packaging unit of chromatin is the nucleosome, which consists of ~1.7 turns of DNA wrapped around an octamer core of histone proteins (H3, H4, H2A, H2B). Chains of nucleosome-decorated DNA, which resemble beads on a string, fold into a higher-order arrangement, often referred to as the 30-nm fiber. However, the structure of this fiber remains poorly understood, despite decades of research. Many proposed models for the 3D organization of the nucleosomes and intervening DNA in chromatin vary quite significantly, and the very existence and relevance of a 30-nm structure in vivo has been questioned. An analysis of the available high-resolution nucleosome structures shows subtle, yet significant differences in DNA wrapping around the histone core. Monte Carlo simulations of regular nucleosome arrays generated using a meso-scale representation of DNA suggest that these local differences can lead to large changes in global nucleosome arrangements, comparable to the effect of changes in nucleosome spacing by ~2–3 base pairs. Our results suggest that a regular nucleosome array with a 177-base-pair (bp) repeat can display a loose three-stack or a more compact two-stack arrangement, on average, depending on the DNA wrapping profile of the nucleosome. These findings imply a very dynamic chromatin fiber with a multitude of mechanisms to control its folding. Using this meso-scale model, we have studied the role of chromatin fiber architecture and histone tails on chromatin compaction and long-range communication in constructs containing 177-bp repeats. Our predictions for chromatin fibers with a loose three-stack nucleosome arrangement can qualitatively account for experimental data from in vitro assays of enhancer-promoter communication (EPC) under physiologically-relevant conditions. On the other hand, fibers that display a two-stack arrangement are in better agreement with sedimentation velocity experiments performed under a different set of ionic conditions. Removal of histone tails diminishes EPC efficiency, and our simulations predict that H3/H4 tail removal has the biggest impact, in agreement with in vitro experiments.

Advisors/Committee Members: Olson, Wilma K (chair), Case, David A (internal member), Khare, Sagar (internal member), Studitsky, Vasily M (outside member), School of Graduate Studies.

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This thesis describes a computational protein engineering approach, which utilizes protein assemblies and enzyme engineering, for the biodegradation of an endocrine disruptor and common pollutant, atrazine, and describes all the experimental approaches that were used to further characterize the designed enzymes. A computational generalizable approach for designing fusion proteins that can self-assembly into fractal-like morphologies on the 10 nm – 10 µM length scale was developed. This approach will allow for any set of oligomeric proteins (with cyclic, dihedral, and other symmetries) to form multivalent connections along with designed flexible loops enabling the control of size of a fractal shaped assembly. Our current approach utilizes the SH2 binding domain-pY peptide to allow for a stimulus control of assembly formation through the post-translational modification of phosphorylation. This same generalizable approach can be applied to other metabolic pathways with other domain-peptide recognition proteins with various different responsiveness to other chemicals or physical stimuli. The phase to phase transition that the assembly produces under self-assembly has the potential to provide various applications, such as creating protein-based nanobiomaterials or creating nanocages (in our case protein fractals) to sequester antibodies and easily precipitate out the antibody as needed. In addition to engineering a stimulus responsive protein fractal assembly, the bottle neck enzyme in the biodegradation of atrazine, atzC, was computationally engineered to improve the catalytic efficiency of other known pollutants, N-t-butylammelide and ammelide. This general approach for computationally designing the active site of an enzyme by probing with energetically acceptable substitutions in the various shells of the protein (first and second shell), not including the active site, but instead focusing on mutations nearby the active site resulted in successfully designing variants of atzC with a broadened s-triazine substrate spectrum. To summarize, this dissertation presents a novel and innovative approach for engineering fractal self-assembly of enzymes and explores the design approach for engineering an enzyme with limited abilities for novel substrates.

Advisors/Committee Members: Khare, Sagar D (chair), Berman, Helen (internal member), Nieuwkoop, Andrew (internal member), Nanda, Vikas (outside member), School of Graduate Studies.

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Influenza is a highly contagious respiratory disease, which can have severe impacts on human health. Influenza type B is traditionally known as the seasonal flu and is the main source for annually occurring influenza outbreaks. The Non-Structural protein 1 of influenza B (NS1B) is a highly conserved protein that the influenza virus produces post infection. NS1B is hypothesized to inhibit the innate immune system via interactions with the RIG-I activation pathway. NS1B has been known to bind dsRNA via its N-terminal domain (NS1B-NTD) for decades, but recently a second RNA binding site was discovered on the C-terminal domain of NS1B (NS1B-CTD). Due to the high conservation of NS1B, its ability to inhibit the innate immune system, and the recent discovery of a second RNA binding domain, this dissertation research focused on the biological function of this second RNA binding site. We discovered a surprising novel blunt-end binding orientation of the NS1B-CTD by dsRNA. We then looked at the connection between RIG-I’s well-known ability to detect and bind triphosphorylated-5’ hairpin RNA (3P-5’-hpRNA) with a much higher affinity than OH-5’ hairpin RNA (OH-5’ hpRNA). We discovered similar binding affinity changes and characteristics with NS1BCTD and the 3P-5’-hpRNA/OH-5’ hpRNA. When the second RNA binding site in NS1B was mutated in transgenic influenza B viruses, we observed reduction in the ability of the virus to suppress Rig-I activation, as Rig-I induced phosphorylation of IRF3 was no longer suppressed flowing virus infection. Our results suggests that the function of the second RNA binding site in the CTD of wildtype NS1B is to outcompete RIG-I for its RNA substrates, typically 5’ triphosphorylaed vRNA molecules. Based on these studies we propose that NS1B-CTD acts as a sensory domain with high specificity for vRNA molecules, which form a “panhandle dsRNA duplex structure” with a unique 3P-5’ modification not found in host cells. This interaction functions to prevent activation of Rig-I, and the innate host immune response.

Advisors/Committee Members: Montelione, Gaetano T. (chair), Arnold, Eddy (internal member), Khare, Sagar (internal member), Roth, Monica (outside member), School of Graduate Studies.

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Alpha-synuclein (αSynuclein) accumulation and aggregation is related to many neurodegenerative diseases like Alzheimer's diseases, Parkinson’s diseases, and dementia with Lewy bodies. However, the mechanism of αSynuclein aggregation and the relationship between aggregation pathways and toxicity are still unclear. Beta-synuclein (βSynuclein) is a homologue protein of αSynuclein with high sequence similarity but plays a different role in neurodegenerative diseases. βSynuclein has shown anti-Parkinson capacity in mouse models. In this work, we used βSynuclein as a comparison to answer why αSynuclein fibrils are good templates for seeding aggregation and what kind of interactions promote aggregate formation or inhibition. The work in this thesis explores structure, toxicity, dynamic and seeding aggregation capacity of different αSynuclein oligomers and fibrils which provide critical information for therapeutic targets and designs. By characterizing and comparing αSynuclein, βSynuclein and α/β co-incubated fibrils, we suggest that the stability and dynamics of the fibrils play an important role in controlling the fibril seeding aggregation ability. However, both αSynuclein and βSynuclein fibrils show similar cellular toxicity which suggest that seeding monomer aggregation is not the only contribution for fibril toxicity. Using solution NMR, we show that the initial step for fibril seeding is through interactions at the first 40 residues of the N-terminus. The interactions between αSynuclein stable oligomers and monomers are primarily located at the first 12 residues which results in inhibiting fibril seeding aggregation processes through competing interactions. Coupling these facts together suggests that peptides or small molecular targets that interact with the N-terminus of αSynuclein may be a good approach to inhibit αSynuclein seeding processes and increase the dynamics of fibril packing interfaces can be novel strategies to reduce amyloid toxicity.

Advisors/Committee Members: Baum, Jean (chair), Khare, Sagar (internal member), Nieuwkoop, Andrew (internal member), Mouradian, Maral (outside member), School of Graduate Studies.

▼ Despite significant advances in the field of computational protein modeling and design, the prediction of de novo metal-coordination and supramolecular assembly remains a largely unexplored area of bottom-up design. The computational tools and methods outlined in this dissertation are intended to reduce design complexity, promote a generalizable design framework, and lay the groundwork for the development of de novo metal-coordination and supramolecular assembly. Thirty percent of proteins in Nature, by estimation, contain metal binding sites and these exhibit a diverse array of structural and functional utility. Among them, multi-nuclear metal clusters perform the most exquisite chemistry such as water oxidation, hydrogenation, and nitrogen fixation. In order to harness the catalytic potential of multi-nuclear metal clusters, we propose a general method for the design of multi-nuclear metalloprotein protein precursors, one that exploits the benefits of symmetric coordination and polydentate non-canonical amino acid derivatives. We have developed a computational searching algorithm (SyPRIS) to locate within a library of structurally determined symmetric protein oligomers a constellation of backbone atoms with a geometry compatible with a desired metal cluster. SyPRIS is shown to have 100% accuracy in the prediction of the native metal-binding sites of known symmetrically coordinated metal ions at the interface of oligomeric proteins (C2 and C3). Furthermore, in a crossmatch study of the benchmark structures, more than 1000 novel metal binding sites with native-like scores are predicted, suggesting the utility of SyPRIS for the incorporation of non-native amino acid coordination of a desired complex. In order to complement the benefits that symmetry offers for reducing design complexity, we sought to expand the palette of available biocompatible non-native amino acid derivatives. A two-step synthesis provides a high-metal affinity bioconjugatable unit, 2,2’-(ethene-1,1-diyl)bis(1-methyl-1H-imidazole) or BMIE. Direct attachement of BMIE occurs by thiol-selective conjugate addition on the surface of a carboxypeptidase G2 variant (S203C). Additionally, we find that BMIE adducts can bind an assortment of divalent metal ions (Co, Ni, Cu, and Zn) in various bi- and tri-dentate tetragonal coordination geometries. Non-BMIE coordinated positions of the copper-bound modified protein display lability in the presence of several counter ligands (H2O/OH, tris, and phenanthroline), which highlights the potential for future catalytic applications. The site-selective modification of proteins for high-affinity metal-binding, combined with the ease of adduct formation and metalation make BMIE an attractive tool to augment multi-nuclear metalloprotein design. The design of protein-based assembly is a burgeoning field with applications in biomedicine and bioremediation. However, topologies have been limited to integer-dimensions. Additionally, many questions remain with respect to the impact of protein anisotropy, colocalization on… Advisors/Committee Members: Khare, Sagar D (chair), Izgu, Enver C (internal member), Nanda, Vikas (internal member), Knapp, Spencer (outside member), School of Graduate Studies.

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This dissertation describes the development, benchmarking, validation, and application of computational methods, mostly written within the Rosetta suite of macromolecular modeling software, for the design and/or analysis of proteins. The introductory chapter brings the reader into the historical context of computational protein design, while detailing important concepts referenced in subsequent chapters. The second chapter is comprised of a benchmarking study of “LooDo”, a computational algorithm for the design of novel nested-domain proteins, which are proteins where one domain is inserted into another. This algorithm, named after its primary sampling method of loop-directed domain placement, was shown to be able to recapitulate native domain orientations for a benchmark set of five nested-domain proteins, as well as recapitulate domain-domain interface sequences and rank native versus nonnative domain combinations highly. In the next chapter, to improve the therapeutic ratio of the yeast cytosine deaminase (yCD)/5-fluorocytosine (5FC) directed-enzyme prodrug therapy system for targeted chemotherapy, we hypothesized that light-induced structural changes in yCD via bifunctional azobenzene derivative cross-linking would allow for the design of a photoswitchable yCD enzyme. Using generalizable computational design methods and experimental validation, we present one such design that allowed for a roughly 2-fold increase in activity towards cytosine under UV versus blue light stimuli. The fourth chapter presents a study in which the Rosetta and Amber energy functions are systematically compared by their performance in two structural evaluation tests and afterwards combined to increase the overall performance over both individually. The minimum-sum-of-ranks method employed in this chapter reduces the RMSD of the selected decoy by 1Å in 14 cases for the ff14SBonlySC energy function in Amber and 13 cases for the current Rosetta energy function, REF2015, in a large decoy discrimination benchmark test. The final chapter investigates bioisosteric alternatives to Axitinib in order to reduce the metabolic vulnerability of the heteroaryl thioether group. Using QM calculations, Rosetta docking protocols, and Amber molecular dynamics simulations, this study computationally evaluates four proposed structures by their predicted behaviors within the VEGFR2 kinase and ABL1 T315I gatekeeper mutant kinase binding pockets. Together, the work herein represents a collection of developments in the fields of computational biology and protein design.

Advisors/Committee Members: Khare, Sagar D (chair), Case, David (internal member), Montelione, Gaetano (internal member), Nanda, Vikas (internal member), Woolley, G. Andrew (outside member), School of Graduate Studies.

▼ The works in this thesis explores the challenges involved in recapitulating the environment in which the synuclein family of proteins resides, functions and are active participants in Parkinson’s disease (PD) pathophysiology. The link between α-synuclein (αS or αsyn) aggregation and PD neurodegeneration has been established by its presence in fibrillar form in intracellular inclusions known as Lewy Bodies (LBs) and associated oligomerization, whereas β-synuclein (βS or βsyn) is thought to be a non-fibrillogenic partner to αS, beneficial to disease. The enclosed work covers two main topics surrounding the environmental sensitivities of these intrinsically disordered proteins’ (IDPs) role in generating disease-associated aggregation: 1) the impact of N-terminal acetylation on αS fibrillation, and 2) the pH responsive source of βS’ inhibited nature. First we generate an N-terminally acetylated αS in response to an investigation of the native oligomeric state of αS in the physiological environment. We find that N-terminal acetylation has minimal impact on the disordered monomeric ensemble of αS and that no evidence of a preference for a tetrameric or other kind of oligomer is found. We find also that acetylated αS forms fibrils of in a similar timeframe and morphology as the non-acetylated form of the protein. While the impact on our view of αS as an intrinsically disordered monomer ensemble is relatively non-consequential, we go on to show that with at least one binding partner, Cu2+, N-terminal acetylation can have a significant impact in vivo. Cu2+ had been shown in vitro to have a unique accelerating effect on αS fibrillation at low, physiological stoichiometries, and given the redox active nature of the metal, and the role of metal dyshomeostasis in neurodegeneration, it had been garnering interest as a significant player in disease-associated αS aggregation. However, we go on to show that N-terminal acetylation occurs at the most significant of three Cu2+ binding sites, blocks binding of the metal and abolishes any fibrillation accelerating effect. Therefore, this work forces reconsideration of how the N-terminally acetylated αS interacts with partners in vivo, and the ultimate role of Cu2+ as an exacerbator of αS pathophysiological aggregation, which may still occur through two other, although much weaker, binding sites at its histidine and C-terminus. In the second part of this thesis, we discover that the model for the physiological environment typically used to draw the conclusion that βS is non-fibrillogenic in contrast to αS, may not be adequate to use to infer things about its intracellular behavior. We discover that mildly acidic pH 5.8, achievable in several intracellular sub-environments, turns on a fibrillation switch and allows βS to form fibrils. We use this pH-responsiveness and a set of α/βS domain-swapped chimeras to study the roots of βS’ less fibril prone nature. We discover through the chimeras that the NAC domain is the most significant determinant of aggregation behavior, and through… Advisors/Committee Members: Baum, Jean (chair), Khare, Sagar (internal member), Case, David (internal member), Moghe, Prabhas (outside member), School of Graduate Studies.

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This dissertation describes the application of protein engineering and metabolic engineering approaches for rational redesign of metabolic pathway for biodegradation of important environmental pollutant 1,2,3-trichloropropane (TCP) utilizing both computational and experimental approaches. A yeast surface display based assay was developed for the limiting enzyme in the pathway - haloalkane dehalogeanse DhaA, which enables high-throughput screening for designed mutants and various strategies were attempted enzyme tunnel engineering on haloalkane dehalogenase DhaA to obtain new starting point towards TCP biodegradation including slot tunnel redesign, de novo tunnel design and chimeric protein design with preserved tunnels and generated combinatorial design library subject to high-throuput screening, but unfortunately no design with both decent expression and enhanced activity was detected. Apart from engineering, the TCP degradation pathway was optimized by metabolic engineering. A phosphorylation- and optically-responsive metabolon for the biodegradation of the environmental pollutant 1,2,3-trichloropropane (TCP) was constructed. The pathway efficiency improvement caused by co-localization in response to stimulus was demonstrated. The design method is modular and generalizable, and could enable spatio-temporal control over a wide variety of synthetic biotransformations. To summarize, this dissertation presents an innovative concept for rational engineering of a synthetic biodegradation pathway for pollutant compound 1,2,3-trichloropropane and explores design approaches of protein engineering and metabolic engineering.

Advisors/Committee Members: Khare, Sagar D (chair), Burley, Stephen K (internal member), Baum, Jean (internal member), Nanda, Vikas (outside member), School of Graduate Studies.