How tumor cells migrate and metastasize from primary sites requires four major steps: invasion, intravasation, extravasation and proliferation from micrometastases to malignant tumor. The initiation of tumor cell invasion requires Epithelial-Mesenchymal Transition (EMT), by which tumor cells lose cell-cell interactions and gain the ability of migration. The gene expression profile during the EMT process has been extensively investigated to study the initiation of EMT. In our studies, we indicated that tyrosine phosphorylation of human p68 RNA helicase positively associated with the malignant status of tumor tissue or cells. Studying of this relationship revealed that p68 RNA helicase played a critical role in EMT progression by repression of E-cadherin as an epithelial marker and upregulation of Vimentin as a mesenchymal marker. Insight into the mechanism of how p68 RNA helicase represses E-cadherin expression indicated that p68 RNA helicase initiated EMT by transcriptional upregulation of Snail. Human p68 RNA helicase has been documented as an RNA-dependent ATPase. The protein is an essential factor in the pre-mRNA splicing procedure. Some examples show that p68 RNA helicase functions as a transcriptional coactivator in ATPase dependent or independent manner. Here we indicated that p68 RNA helicase unwound protein complexes to modulate protein-protein interactions by using protein-dependent ATPase activity. The phosphorylated p68 RNA helicase displaced HDAC1 from the chromatin remodeling MBD3:Mi2/NuRD complex at the Snail promoter. Thus, our data demonstrated an example of protein-dependent ATPase which modulates protein-protein interactions within the chromatin remodeling machine.

Proteases are essential for regulating a wide range of physiological and pathological processes. The imbalance of protease activation and inhibition will result in a number of major diseases including cancers, atherosclerosis, and neurodegenerative diseases. Although fluorescence resonance energy transfer (FRET)-based protease probes, a small molecular dye and other methods are powerful, they still have drawbacks or limitations for providing significant information about the dynamics and pattern of endogenous protease activation and inhibition in a single living cell or in vivo. Currently protease sensors capable of quantitatively measuring specific protease activity in real time and monitoring activation and inhibition of enzymatic activity in various cellular compartments are highly desired. In this dissertation, we report a novel strategy to create protease sensors by grafting an enzymatic cleavage linker into a sensitive location for changing chromophore properties of enhanced green fluorescent protein (EGFP) following protease cleavage, which can be used to determine protease activity and track protease activation and inhibition with a ratiometric measurement mode in living cells. Our designed protease sensors exhibit large relative ratiometric optical signal change in both absorbance and fluorescence, and fast response to proteases. Meanwhile, these protease sensors exhibiting high enzymatic selectivity and kinetic responses are comparable or better than current small peptide probes and FRET-based protease probes. Additionally, our protease sensors can be utilized for real-time monitoring of cellular enzymogen activation and effects of inhibitors in living cells. This novel strategy opens a new avenue for developing specific protease sensors to investigate enzymatic activity in real time, to probe disease mechanisms corresponding to proteases in vitro and in vivo, and to screen protease inhibitors with therapeutic effects. Strong fluorescence was still retained in the cleaved EGFP-based protease sensors, which stimulated us to identify the EGFP fragment with fluorescence properties for further understanding chromophore formation mechanisms and investigating protein-protein interactions through fluorescence complementation of split EGFP fragments. Through fusing EF-hand motifs from calbindin D9k to split EGFP fragments, a novel molecular probe was developed to simultaneously track the calcium change or calcium signaling pathways and calcium-dependent protein-protein interaction in living cells in real time.

<p>The cell cycle is one of the fundamental processes in all living organisms, and all cells arise from the division of existing cells. To better understand the regulation of the cell cycle, synchrony experiments are widely used to monitor cellular dynamics during this process. In such experiments, a large population of cells is generally arrested or selected at one stage of the cycle, and then released to progress through subsequent division stages. Measurements are then taken in this population at a variety of time points after release to provide insight into the dynamics of the cell cycle. However, due to cell-to-cell variability and asymmetric cell division, cells in a synchronized population lose synchrony over time. As a result, the time-series measurements from the synchronized cell populations do not accurately reflect the underlying dynamics of cell-cycle processes.</p><p>In this thesis, we introduce a deconvolution algorithm that learns a more accurate view of cell-cycle dynamics, free from the convolution effects associated with imperfect cell synchronization. Through wavelet-basis regularization, our method sharpens signal without sharpening noise, and can remarkably increase both the dynamic range and the temporal resolution of time-series data. Though it can be applied to any such data, we demonstrate the utility of our method by applying it to a recent cell-cycle transcription time course in the eukaryote <italic>Saccharomyces cerevisiae</italic>. We show that our method more sensitively detects cell-cycle-regulated transcription, and reveals subtle timing differences that are masked in the original population measurements. Our algorithm also explicitly learns distinct transcription programs for both mother and daughter cells, enabling us to identify 82 genes transcribed almost entirely in the early G1 in a daughter-specific manner.</p><p>In addition to the cell-cycle deconvolution algorithm, we introduce <italic>DOMAIN</italic>, a protein-protein interaction (PPI) network alignment method, which employs a novel <italic>direct-edge-alignment</italic> paradigm to detect conserved functional modules (e.g., protein complexes, molecular pathways) from pairwise PPI networks. By applying our approach to detect protein complexes conserved in yeast-fly and yeast-worm PPI networks, we show that our approach outperforms two widely used approaches in most alignment performance metrics. We also show that our approach enables us to identify conserved cell-cycle-related functional modules across yeast-fly PPI networks.</p> / Dissertation

Many pathological processes are associated with excessive neurotransmitter release that leads to the over-stimulation of post-synaptic neurotransmitter receptors. Examples include excessive activation of glutamate receptors in ischemic stroke and hyper-dopaminergic state in schizophrenia and drug addiction. Thus, it would seem that simply antagonizing the involved receptors should be able to correct the pathological condition. In some instances, this strategy has been somewhat effective, such as with the use of dopamine D2 receptor antagonists as antipsychotics in the treatment of positive symptoms of schizophrenia despite severe side effect. However, clinical application of drugs antagonizing glutamate receptor in the treatment of stoke, although attracting intensive research effort, has been restricted by serious side effects caused by suppressing postsynaptic responses that are needed for normal brain function. As a consequence, it is important to develop novel therapeutics aiming at specific targets with minimized side effects. Numerous studies have suggested that the pathophysiology of neuropsychiatric disorders, drug addictions and stroke involves multiple neurotransmitter receptor systems such as the dopamine and glutamate systems. The activation or inhibition of one receptor can have cross-functional effect that will be better understood by investigating the functional and structural relationship between receptor systems. Thus, the present study has focused on characterizing receptor-receptor interactions associated with dopamine receptors and glutamate receptors, and to elucidate the physiological and pathological consequence of altered receptor interactions in schizophrenia, depression and ischemic stroke.

Many pathological processes are associated with excessive neurotransmitter release that leads to the over-stimulation of post-synaptic neurotransmitter receptors. Examples include excessive activation of glutamate receptors in ischemic stroke and hyper-dopaminergic state in schizophrenia and drug addiction. Thus, it would seem that simply antagonizing the involved receptors should be able to correct the pathological condition. In some instances, this strategy has been somewhat effective, such as with the use of dopamine D2 receptor antagonists as antipsychotics in the treatment of positive symptoms of schizophrenia despite severe side effect. However, clinical application of drugs antagonizing glutamate receptor in the treatment of stoke, although attracting intensive research effort, has been restricted by serious side effects caused by suppressing postsynaptic responses that are needed for normal brain function. As a consequence, it is important to develop novel therapeutics aiming at specific targets with minimized side effects. Numerous studies have suggested that the pathophysiology of neuropsychiatric disorders, drug addictions and stroke involves multiple neurotransmitter receptor systems such as the dopamine and glutamate systems. The activation or inhibition of one receptor can have cross-functional effect that will be better understood by investigating the functional and structural relationship between receptor systems. Thus, the present study has focused on characterizing receptor-receptor interactions associated with dopamine receptors and glutamate receptors, and to elucidate the physiological and pathological consequence of altered receptor interactions in schizophrenia, depression and ischemic stroke.

is a functionally diverse large group of proteins sharing a jelly roll β-barrel fold. An enzymatic member 3-hydroxyanthranilate-3,4-dioxygenase (HAO) and a non-enzymatic member pirin, which is a human nuclear metalloprotein of unknown function present in all human tissues, were selected for structural and functional studies in this dissertation work. HAO is an important enzyme for tryptophan catabolism and for 2-nitrobenzoic acid biodegradation. In this work, seven catalytic intermediate were captured in HAO single crystals, enabling for the first time a nearly complete structural snapshot viewing of the entire molecular oxygen activation and insertion mechanism in an iron- and O2-depedent enzyme. The rapid catalytic turnover rate was found achieved in large part by protein dynamics that facilitates O2 binding to the catalytic iron, which is bound to the enzyme by a facile 2-His-1-carboxylate ligand motif. An iron storage and chaperon mechanism was also discovered in the bacterial source of this enzyme, which led to a proposed novel biological function of a mononuclear iron-sulfur center. Although human pirin protein shares the same structural fold with HAO, its iron ion is coordinated by a 3-His-1-carboxylate ligand motif. Pirin belongs to a subset of proteins whose members are playing regulatory functions in the superfamily. In this work, pirin is shown to act as a redox sensor for the NF-κB transcription factor, a critical mediator of intracellular signaling that has been linked to cellular responses to pro-inflammatory signals which controls the expression of a vast array of genes involved in immune and stress responses.

Calmodulin (CaM) is a ubiquitous cytosolic Ca2+-binding protein involved in the binding and regulation of more than three-hundred intracellular target proteins. CaM consists of two globular domains joined by a central linker region. In the archetypical model of CaM binding to a target protein, the Ca2+-replete CaM wraps its two domains around a single α-helical target peptide; however, other conformations of CaM bound to target peptides and proteins have recently been discovered. Due to its ability to bind and affect many different intracellular processes, there is significant interest in a better understanding of the structural and conformational basis of CaM’s ability to bind and recognize target proteins. The mammalian nitric oxide synthase (NOS) enzymes are bound and activated by CaM. The NOS enzymes catalyze the production of nitric oxide (•NO), a free radical involved in numerous intercellular processes such as neurotransmission, vasodilation, and immune defense. There are three different isoforms of nitric oxide synthase (NOS) found in mammals – neuronal NOS (nNOS), endothelial NOS (eNOS), and inducible NOS (iNOS). All three enzymes are homodimeric with each monomer consisting of an N-terminal oxygenase domain and a multidomain C-terminal reductase domain. A CaM-binding domain separates the oxygenase and reductase domains. There is a unique opportunity to investigate CaM’s control over •NO production by the NOS enzymes since each isoform shows a different mode of activation and control by CaM. At elevated cellular Ca2+ concentrations, CaM is able to bind and activate nNOS and eNOS. In contrast, the iNOS isozyme is transcriptionally regulated and binds to CaM in the absence of Ca2+. The focus of this thesis is to better our present understanding of the conformational and structural basis for CaM’s ability to bind and activate the three mammalian NOS isozymes with particular emphasis on the interactions between CaM and iNOS. To further investigate the differences in the association of CaM to the Ca2+-dependent and Ca2+-independent NOS isoforms, a variety of CaM mutants including CaM-troponin C chimeras, CaM EF hand pair proteins, and CaM mutants incapable of binding to Ca2+ were employed. The inherent differences in binding and activation observed using these CaM mutants is described. Differences in the binding of the N- and C-terminal domains, as well as the central linker of CaM to peptides corresponding to the CaM-binding domain of each NOS enzyme and holo-NOS enzymes was investigated. The conformation of CaM when bound to NOS peptides and holo-NOS enzymes was also studied using fluorescence (Förster) resonance energy transfer (FRET). A preliminary three-dimensional structural study of Ca2+-replete and Ca2+-deplete CaM in complex with an iNOS CaM-binding domain peptide is also described. Combining the cumulative results in this thesis, a working model for iNOS’s regulation by CaM is proposed. Future suggested experiments are described to further the characterization of CaM binding to the NOS enzymes and other CaM-target proteins. The studies described in this thesis have expanded and improved the present understanding of the CaM-dependent binding and activation of the NOS isozymes, particularly the interactions between CaM and iNOS.

The work describes the development of a new class of protein-inhibitors for protein-protein interactions, based on metallopeptides comprised of a dirhodium metal center. The metal incorporation in the peptide sequence leads to high increase in binding affinity of the inhibitors. The source of this strong affinity is the interaction of histidine on the protein surface with the rhodium center. In addition to this work, rhodium-based small molecule inhibitors for FK-506 binding proteins are investigated. Also, methodology for rhodium-catalyzed modification of proteins containing surface cysteine has been developed where a simple rhodium(II) complex catalyzes cysteine modification with diazo reagents. The reaction is marked by clean cysteine selectivity and mild reaction conditions. The resulting linkage is significantly more stable in human plasma serum, when compared to common maleimide reagents. Apart from this body of work in chemical-biology, the thesis contains the discussion of development of copper-catalyzed remote chlorination of alkyl hydroperoxides. The atom transfer chlorination utilizes simple ammonium chloride salts as the chlorine source and the internal redox process requires no external redox reagents.

Calmodulin (CaM) is a ubiquitous cytosolic Ca2+-binding protein involved in the binding and regulation of more than three-hundred intracellular target proteins. CaM consists of two globular domains joined by a central linker region. In the archetypical model of CaM binding to a target protein, the Ca2+-replete CaM wraps its two domains around a single α-helical target peptide; however, other conformations of CaM bound to target peptides and proteins have recently been discovered. Due to its ability to bind and affect many different intracellular processes, there is significant interest in a better understanding of the structural and conformational basis of CaM’s ability to bind and recognize target proteins. The mammalian nitric oxide synthase (NOS) enzymes are bound and activated by CaM. The NOS enzymes catalyze the production of nitric oxide (•NO), a free radical involved in numerous intercellular processes such as neurotransmission, vasodilation, and immune defense. There are three different isoforms of nitric oxide synthase (NOS) found in mammals – neuronal NOS (nNOS), endothelial NOS (eNOS), and inducible NOS (iNOS). All three enzymes are homodimeric with each monomer consisting of an N-terminal oxygenase domain and a multidomain C-terminal reductase domain. A CaM-binding domain separates the oxygenase and reductase domains. There is a unique opportunity to investigate CaM’s control over •NO production by the NOS enzymes since each isoform shows a different mode of activation and control by CaM. At elevated cellular Ca2+ concentrations, CaM is able to bind and activate nNOS and eNOS. In contrast, the iNOS isozyme is transcriptionally regulated and binds to CaM in the absence of Ca2+. The focus of this thesis is to better our present understanding of the conformational and structural basis for CaM’s ability to bind and activate the three mammalian NOS isozymes with particular emphasis on the interactions between CaM and iNOS. To further investigate the differences in the association of CaM to the Ca2+-dependent and Ca2+-independent NOS isoforms, a variety of CaM mutants including CaM-troponin C chimeras, CaM EF hand pair proteins, and CaM mutants incapable of binding to Ca2+ were employed. The inherent differences in binding and activation observed using these CaM mutants is described. Differences in the binding of the N- and C-terminal domains, as well as the central linker of CaM to peptides corresponding to the CaM-binding domain of each NOS enzyme and holo-NOS enzymes was investigated. The conformation of CaM when bound to NOS peptides and holo-NOS enzymes was also studied using fluorescence (Förster) resonance energy transfer (FRET). A preliminary three-dimensional structural study of Ca2+-replete and Ca2+-deplete CaM in complex with an iNOS CaM-binding domain peptide is also described. Combining the cumulative results in this thesis, a working model for iNOS’s regulation by CaM is proposed. Future suggested experiments are described to further the characterization of CaM binding to the NOS enzymes and other CaM-target proteins. The studies described in this thesis have expanded and improved the present understanding of the CaM-dependent binding and activation of the NOS isozymes, particularly the interactions between CaM and iNOS.

Metabolic networks are the collections of all cellular activities taking place in a living cell and all the relationships among biological elements of the cell including genes, proteins, enzymes, metabolites, and reactions. They provide a better understanding of cellular mechanisms and phenotypic characteristics of the studied organism. In order to reconstruct a metabolic network, interactions among genes and their molecular attributes along with their functions must be known. Using this information, proteins are distributed among pathways as sub-networks of a greater metabolic network. Proteins which carry out various steps of a biological process operate in same pathway.<p>The metabolic network of <i>Caenorhabditis elegans</i> was reconstructed based on current genomic information obtained from the KEGG database, and commonly found in SWISS-PROT and WormBase. Assuming proteins operating in a pathway are interacting proteins, currently available protein-protein interaction map of the studied organism was assembled. This map contains all known protein-protein interactions collected from various sources up to the time. Topology of the reconstructed network was briefly studied and the role of key enzymes in the interconnectivity of the network was analysed. The analysis showed that the shortest metabolic paths represent the most probable routes taken by the organism where endogenous sources of nutrient are available to the organism. Nonetheless, there are alternate paths to allow the organism to survive under extraneous variations. <p>Signature content information of proteins was utilized to reveal protein interactions upon a notion that when two proteins share signature(s) in their primary structures, the two proteins are more likely to interact. The signature content of proteins was used to measure the extent of similarity between pairs of proteins based on binary similarity score. Pairs of proteins with a binary similarity score greater than a threshold corresponding to confidence level 95% were predicted as interacting proteins. The reliability of predicted pairs was statistically analyzed. The sensitivity and specificity analysis showed that the proposed approach outperformed maximum likelihood estimation (MLE) approach with a 22% increase in area under curve of receiving operator characteristic (ROC) when they were applied to the same datasets. When proteins containing one and two known signatures were removed from the protein dataset, the area under curve (AUC) increased from 0.549 to 0.584 and 0.655, respectively. Increase in the AUC indicates that proteins with one or two known signatures do not provide sufficient information to predict robust protein-protein interactions. Moreover, it demonstrates that when proteins with more known signatures are used in signature profiling methods the overlap with experimental findings will increase resulting in higher true positive rate and eventually greater AUC. <p>Despite the accuracy of protein-protein interaction methods proposed here and elsewhere, they often predict true positive interactions along with numerous false positive interactions. A global algorithm was also proposed to reduce the number of false positive predicted protein interacting pairs. This algorithm relies on gene ontology (GO) annotations of proteins involved in predicted interactions. A dataset of experimentally confirmed protein pair interactions and their GO annotations was used as a training set to train keywords which were able to recover both their source interactions (training set) and predicted interactions in other datasets (test sets). These keywords along with the cellular component annotation of proteins were employed to set a pair of rules that were to be satisfied by any predicted pair of interacting proteins. When this algorithm was applied to four predicted datasets obtained using phylogenetic profiles, gene expression patterns, chance co-occurrence distribution coefficient, and maximum likelihood estimation for S. cerevisiae and <i>C. elegans</i>, the improvement in true positive fractions of the datasets was observed in a magnitude of 2-fold to 10-fold depending on the computational method used to create the dataset and the available information on the organism of interest. <p>The predicted protein-protein interactions were incorporated into the prior reconstructed metabolic network of <i>C. elegans</i>, resulting in 1024 new interactions among 94 metabolic pathways. In each of 1024 new interactions one unknown protein was interacting with a known partner found in the reconstructed metabolic network. Unknown proteins were characterized based on the involvement of their known partners. Based on the binary similarity scores, the function of an uncharacterized protein in an interacting pair was defined according to its known counterpart whose function was already specified. With the incorporation of new predicted interactions to the metabolic network, an expanded version of that network was resulted with 27% increase in the number of known proteins involved in metabolism. Connectivity of proteins in protein-protein interaction map changed from 42 to 34 due to the increase in the number of characterized proteins in the network.