Cells process information from their environment, such as the stimuli to grow, divide, or die, via cell signaling. Deregulated processing of extracellular stimuli can lead to aberrant cell responses and cause cancer. Given that the in vivo cell environment constantly changes, it is important to understand how cells incorporate the context of their environment into their decision making processes. The idea of responding to relative, not absolute, changes in stimuli was first proposed in studies of human perception and became known as Weber's Law. Although, evidence of Weber's Law at the molecular level has been previously presented in studies of several organisms, to the best of our knowledge, it has never been explored in the case of relative sensing of extracellular stimuli in mammalian signaling cascades. The Mitogen-Activated Protein Kinase (MAPK) signaling pathway has been implicated in multiple human diseases, including cancers, and therefore cell signaling through this pathway is an important subject of research. Here we present a theoretical framework and an experimental validation of the mechanism of Weber's Law in the ability of cells to sense relative changes in the levels of extracellular stimuli in the MAPK signaling pathway. In particular, in this work we consider relative sensing in levels of Epidermal Growth Factor (EGF) in the MAPK pathway. We derive an analytical model of steady state behavior of the MAPK signaling pathway stimulated with constant doses of EGF. We demonstrate a mechanism that produces phosphorylation responses proportional to relative changes in ligand concentrations. The mechanism of Weber's Law presented here entails the retention of memory of the dose of the past chronic stimulation with EGF. The molecular mechanisms responsible for Weber's Law in MAPK signaling are likely to contribute to many other receptors signaling systems. Therefore, the mechanism of relative sensing of extracellular ligand concentrations derived here can be generalized beyond the EGF-activated MAPK signaling pathway to many other cell signaling systems. This thesis also presents a probabilistic framework to explore the parameter space of a detailed mechanistic ODE model of EGFR signaling cascades. The application of the model simulation allows us to generate probabilistic predictions of EGFR system behavior and to explore structure-to-function relationships between the model's parameter space and EGFR system responses. Overall, this work suggests an alternative view on the role of cellular endocytosis in the MAPK signaling in vivo. Specifically, traditionally viewed as a mechanism to downregulate and terminate cell signaling, endocytosis may enable cells to dynamically adjust their sensitivity to extracellular stimuli, and hence allow cells to integrate information about the past stimulations into the cell responses to the consequent stimulations and thus, cell fate decisions.

Mammalian cells possess a variety of different DNA repair pathways, which work together to safeguard genomic integrity upon encountering different types of DNA damage. Among all lesions, DNA double-strand breaks (DSBs) are most toxic and, if left unrepaired, results in loss of genetic information and genomic instability- a hallmark of tumorigenesis. Ataxia Telangiectasia Mutated (ATM) is a protein kinase, a master regulator of the DNA damage response, and is activated upon the formation of DSBs. ATM senses DNA DSBs through its accessory proteins and functions as a transducer of the DNA damage response (DDR), which entails the activation of genes involved in DNA repair, cell cycle checkpoint, and apoptosis. Consequently, loss of ATM results in increased genomic instability and compromised checkpoint regulation. Moreover, loss of ATM has been reported in various human cancers, and Atm-deficient mice uniformly develop thymic lymphomas, highlighting its role as a tumor suppressor. Although ATM has been extensively studied, much of its known functions to date pertained to its kinase activity, and the structural function of ATM remains elusive. To investigate whether ATM possesses structural functions beyond its kinase activity, we generated a mouse model expressing kinase-dead (KD) ATM protein. Intriguingly, while Atm-/- are viable, AtmKD/KD and AtmKD/- mice were embryonic lethal and AtmKD/KD and AtmKD/- cells displayed greater genomic instability compared to ATM-null cells, suggesting that the presence of the ATM KD protein blocks additional DNA repair pathways that are not affected in ATM-null cells. In this context, we identified defects in homologous recombination, resolution of Camptothecin (CPT)-induced Topoisomerase-I lesions, and replication progression specifically in AtmKD/- cells beyond those observed in Atm-/-. Mouse model expressing KD ATM (AtmKD/-) in hematopoietic stem cells (HSCs) developed thymic lymphomas faster and more frequently than the corresponding model with the ATM-null HSCs, which was associated with increased genomic instability and loss of tumor-suppressor Pten. In collaboration with others, we showed that the majority of tumor-associated ATM mutations reported in TCGA are missense mutations and are highly enriched in the kinase domain, while Ataxia-Telangiectasia (A-T) associated germline ATM mutations are almost always truncating mutations leading to complete loss of ATM protein. This result suggests that ATM KD protein might be expressed in a significant fraction of human cancer. These results, for the first time, identified a previously unknown phosphorylation-dependent, structural function of ATM in the maintenance of genomic integrity and tumor suppression. Furthermore, the tumorigenicity and vulnerability to particular DNA damaging agents caused by the expression of the ATM KD protein relative to the loss of ATM highlight the importance of distinguishing the types of ATM mutations in tumors, and provide novel insights into the clinical use of specific ATM kinase inhibitors, as well as the prognosis and treatments of ATM-mutated cancers. ATM has been reported to be frequently inactivated in human B-cell lymphomas, including up to 50% Mantle Cell Lymphoma (MCL), which represents around 6% of all Non-Hodgkins Lymphomas (NHLs). MCL is characterized by the recurrent t(11;14)(q13;q32) translocation, which juxtaposes CCND1/BCL-1 to the IGH enhancer, leading to deregulated expression of CyclinD1 (CCND1). However, CyclinD1 overexpression in B cells alone is not sufficient to induce MCL in mouse models, and the role of ATM in the suppression of B-cell lymphomas is not well understood, in part due to the lack of ATM-deficient mature B-cell lymphoma models. To address this, we generated a mouse model that combines conditional deletion of ATM specifically in early progenitor B-cells via Mb1cre, and overexpressing CyclinD1 in lymphoid cells via EµCyclinD1 transgene. While ATM loss alone resulted in the development of indolent, clonal, mature B-cell lymphoma, combined ATM-loss and CyclinD1 overexpression accelerated and increased the incidence of B-cell lymphoma. Furthermore, ATM-loss combined with CyclinD1 overexpression led to greater genomic instability and the expansion of naïve ATM-deficient B-cells in the spleen. This study, for the first time, developed an ATM-deficient B-cell lymphoma model and demonstrated a synergistic function of ATM and CyclinD1 in pre-GC B-cell proliferation and lymphomagenesis. Furthermore, the mice described here provide a prototypic animal model to study the pathogenesis of human MCL, for which there are no suitable mouse models.

A insulina regula a expressão de GLUT4, porém os mecanismos envolvidos nesta regulação não estão definidos. Alguns fatores de transcrição e proteínas cinases estão relacionados com a expressão de GLUT4. Assim, o objetivo desta pesquisa foi investigar a participação dos fatores de transcrição MEF2, HIF-1<font face=\"Symbol\">a e NF-<font face=\"Symbol\">kB, e das proteínas cinases mTOR, PI3K e AKT na regulação da expressão de Slc2a4/GLUT4 induzida pela insulina. Para isso, músculos sóleos de ratos foram incubados por 3 horas em tampão Krebs, tratados ou não com insulina, wortmanina, rapamicina, ML-9 ou TNF-<font face=\"Symbol\">a. Nesses tecidos foram avaliados o conteúdo das proteínas GLUT4 e mTOR (Western), o conteúdo de mRNA de GLUT4, NF-<font face=\"Symbol\">kB1, HIF-1<font face=\"Symbol\">a e MEF2A/C/D (PCR) e a atividade de ligação de proteínas nucleares no sítio de ligação de NF-<font face=\"Symbol\">kB, AT-rich element e E-Box do promotor do gene Slc2a4 (EMSA). O tratamento com insulina aumentou a expressão de Slc2a4/GLUT4 no músculo sóleo, in vitro, ativando os fatores de transcrição MEF2A/D e possivelmente MyoD, através da via da PI3K/AKT e diminuindo a expressão e atividade de NF-<font face=\"Symbol\">kB. / Insulin regulates the GLUT4 expression, but the mechanisms involved in this regulation are not defined. Some transcription factors and protein kinases are related to the expression of GLUT4. Thus, the aim of this research was to investigate the role of the transcription factors MEF2, HIF-1<font face=\"symbol\">a and NF-<font face=\"Symbol\">kB, and the proteins kinases mTOR, PI3K and AKT, in regulation of Slc2a4 and GLUT4 expression by insulin. For this, rat soleus muscles were incubated for 3 hours in Krebs buffer, treated or not with insulin, wortmanina, rapamycin, ML-9 or TNF-<font face=\"Symbol\">a. In these tissues were evaluated the GLUT4 and mTOR protein content (Western), the content of GLUT4, NF-<font face=\"Symbol\">kB1, HIF-1<font face=\"Symbol\">a and MEF2A/C/D mRNAs (PCR) and the binding activity of protein nuclear in binding site of NF-<font face=\"Symbol\">kB, AT-rich element and E-Box in the promoter of the gene Slc2a4 (EMSA). Insulin treatment increased the expression of Slc2a4/GLUT4 in the soleus muscle in vitro, activating the transcription factors MEF2A/D and possibly MyoD, via PI3K/AKT and decreasing the expression and activity of NF-<font face=\"Symbol\">kB.

No description available.

Thesis (Ph.D.)--University of Toledo, 2006. / "In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences." Major advisor: Brian G. Rowan. Includes abstract. Document formatted into pages: iv, 204 p. Title from title page of PDF document. Title at ETD Web site: Molecular mechanisms of protein kinase a signaling pathway on estrogen receptor action in breast cancer . Bibliography: pages 59-65, 100-104, 137-150, 167-202.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

<p>Protein kinases are enzymes that catalyse the phosphoryl transfer from the g-phosphate of ATP to acceptor amino acids in proteins. The specificity of selected model protein kinases was studied at three different levels using a) novel bi-substrate-analogue inhibitors, b) synthetic peptide substrates and c) mutated protein substrate analogues. </p><p>A new class of protein kinase bi-substrate-analogue inhibitors was designed on the basis of adenosine-5’-carboxylic acid derivatives, where a short arginine containing peptide was attached to the 5'-carbon atom of the adenosine sugar moiety via a linker chain. These compounds showed high inhibitory potential against two basophilic protein kinases, the protein kinase A (PKA) and protein kinase C (PKC), with IC50 values in the nanomolar range, but no inhibitory activity towards the acidophilic kinases CK1 and CK2. The inhibitors were efficiently applied for affinity purification of PKA using MgATP as well as L-arginine as eluting agents. </p><p>Ca2+-dependent protein kinase (CDPK-1) was purified from maize seedlings and its substrate specificity was studied using a set of synthetic peptides. These were derived from the phosphorylatable sequence RVLSRLHS(15)VRER of maize sucrose synthase 2 (SuSy2), and a consensus sequence motif A/LXRXXSXRZR (where X denotes a position with no strict amino acid requirements and Z a position strictly not tolerating arginine) was defined from a study using arrays of systematically varied peptides attached to cellulose membrane (SPOTs^TM membranes). The SuSy2 derived peptides were also found to be efficient substrates for mammalian PKC, but showed low reactivity in the case of PKA. On the basis of this peptide motif, a positionally oriented peptide library approach based on ESI-MS detection of phosphopeptides in initial velocity conditions was designed for quantitative kinetic characterization of protein kinase specificity profiles. On the basis of the obtained data an optimal peptide substrate for PKC, FRRRRSFRRR, was designed. </p><p>The specificity of protein kinase A was studied using site-directed mutagenesis in the phosphorylation site of L-type pyruvate kinase (L-PK), and comparison of the obtained data with the data from previous studies on structurally altered peptide substrates revealed that amino acid alterations in short peptide substrates cause stronger effects on the phosphorylation rate than the corresponding alterations in the protein substrate L-PK.</p>

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 147-163).

Protein kinases are enzymes that catalyse the phosphoryl transfer from the g-phosphate of ATP to acceptor amino acids in proteins. The specificity of selected model protein kinases was studied at three different levels using a) novel bi-substrate-analogue inhibitors, b) synthetic peptide substrates and c) mutated protein substrate analogues. A new class of protein kinase bi-substrate-analogue inhibitors was designed on the basis of adenosine-5’-carboxylic acid derivatives, where a short arginine containing peptide was attached to the 5'-carbon atom of the adenosine sugar moiety via a linker chain. These compounds showed high inhibitory potential against two basophilic protein kinases, the protein kinase A (PKA) and protein kinase C (PKC), with IC50 values in the nanomolar range, but no inhibitory activity towards the acidophilic kinases CK1 and CK2. The inhibitors were efficiently applied for affinity purification of PKA using MgATP as well as L-arginine as eluting agents. Ca2+-dependent protein kinase (CDPK-1) was purified from maize seedlings and its substrate specificity was studied using a set of synthetic peptides. These were derived from the phosphorylatable sequence RVLSRLHS(15)VRER of maize sucrose synthase 2 (SuSy2), and a consensus sequence motif A/LXRXXSXRZR (where X denotes a position with no strict amino acid requirements and Z a position strictly not tolerating arginine) was defined from a study using arrays of systematically varied peptides attached to cellulose membrane (SPOTsTM membranes). The SuSy2 derived peptides were also found to be efficient substrates for mammalian PKC, but showed low reactivity in the case of PKA. On the basis of this peptide motif, a positionally oriented peptide library approach based on ESI-MS detection of phosphopeptides in initial velocity conditions was designed for quantitative kinetic characterization of protein kinase specificity profiles. On the basis of the obtained data an optimal peptide substrate for PKC, FRRRRSFRRR, was designed. The specificity of protein kinase A was studied using site-directed mutagenesis in the phosphorylation site of L-type pyruvate kinase (L-PK), and comparison of the obtained data with the data from previous studies on structurally altered peptide substrates revealed that amino acid alterations in short peptide substrates cause stronger effects on the phosphorylation rate than the corresponding alterations in the protein substrate L-PK.

The protein kinases are a large family of enzymes that play a fundamental role in propagating signals within the cell. Because of the high degree of binding site similarity shared among protein kinases, designing drug compounds with high specificity among the kinases has proven difficult. However, computational approaches to comparing the 3-dimensional geometry and physicochemical properties of key binding site residues, referred to here as substructures, have been shown to be informative of inhibitor selectivity. This thesis introduces two fundamental approaches for the comparative analysis of substructure similarity and demonstrates the importance of each method on a variety of large protein structure datasets for multiple biological applications. The Family-wise Alignment of SubStructural Templates Framework (The FASST Framework) provides an unsupervised learning approach for identifying substructure clusterings. The substructure clusterings identified by FASST allow for the automatic evaluation of substructure variability, the identification of distinct structural conformations and the selection of anomalous outlier structures within large structure datasets. These clusterings are shown to be capable of identifying biologically meaningful structure trends among a diverse number of protein families. The FASST Live visualization and analysis platform provides multiple comparative analysis pipelines and allows the user to interactively explore the substructure clusterings computed by FASST. The Combinatorial Clustering Of Residue Position Subsets (CCORPS) method provides a supervised learning approach for identifying structural features that are correlated with a given set of annotation labels. The ability of CCORPS to identify structural features predictive of functional divergence among families of homologous enzymes is demonstrated across 48 distinct protein families. The CCORPS method is further demonstrated to generalize to the very difficult problem of predicting protein kinase inhibitor affinity. CCORPS is demonstrated to make perfect or near-perfect predictions for the binding ability of 12 of the 38 kinase inhibitors studied, while only having overall poor predictive ability for 1 of the 38 compounds. Additionally, CCORPS is shown to identify shared structural features across phylogenetically diverse groups of kinases that are correlated with binding affinity for particular inhibitors; such instances of structural similarity among phylogenetically diverse kinases are also shown to not be rare among kinases. Finally, these function-specific structural features may serve as potential starting points for the development of highly specific kinase inhibitors. Importantly, both The FASST Framework and CCORPS implement a redundancy-aware approach to dealing with structure overrepresentation that allows for the incorporation of all available structure data. As shown in this thesis, surprising structural variability exists even among structure datasets consisting of a single protein sequence. By incorporating the full variety of structural conformations within the analysis, the methods presented here provide a richer view of the variability of large protein structure datasets.