Functional Diversification after Gene Duplication: Paralog Specific Regions of Structural Disorder and Phosphorylation in p53, p63, and p73

Conformational and functional flexibility promote protein evolvability. High evolvability allows related proteins to functionally diverge and perhaps to neostructuralize. p53 is a multifunctional protein frequently referred to as the Guardian of the Genome–a hub for e.g. incoming and outgoing signals in apoptosis and DNA repair. p53 has been found to be structurally disordered, an extreme form of conformational flexibility. Here, p53, and its paralogs p63 and p73, were studied for further insights into the evolutionary dynamics of structural disorder, secondary structure, and phosphorylation. This study is focused on the post gene duplication phase for the p53 family in vertebrates, but also visits the origin of the protein family and the early domain loss and gain events. Functional divergence, measured by rapid evolutionary dynamics of protein domains, structural properties, and phosphorylation propensity, is inferred across vertebrate p53 proteins, in p63 and p73 from fish, and between the three paralogs. In particular, structurally disordered regions are redistributed among paralogs, but within clades redistribution of structural disorder also appears to be an ongoing process. Despite its deemed importance as the Guardian of the Genome, p53 is indeed a protein with high evolvability as seen not only in rearranged structural disorder, but also in fluctuating domain sequence signatures among lineages

New Perspectives, Opportunities, and Challenges in Exploring the Human Protein Kinome.

The human protein kinome comprises 535 proteins that, with the exception of approximately 50 pseudokinases, control intracellular signaling networks by catalyzing the phosphorylation of multiple protein substrates. While a major research focus of the last 30 years has been cancer-associated Tyr and Ser/Thr kinases, over 85% of the kinome has been identified to be dysregulated in at least one disease or developmental disorder. Despite this remarkable statistic, for the majority of protein kinases and pseudokinases, there are currently no inhibitors progressing toward the clinic, and in most cases, details of their physiologic and pathologic mechanisms remain at least partially obscure. By curating and annotating data from the literature and major public databases of phosphorylation sites, kinases, and disease associations, we generate an unbiased resource that highlights areas of unmet need within the kinome. We discuss strategies and challenges associated with characterizing catalytic and noncatalytic outputs in cells, and describe successes and new frontiers that will support more comprehensive cancer-targeting and therapeutic evaluation in the future. Cancer Res; 78(1); 15-29. ©2017 AACR

Design and data analysis of kinome microarrays

Catalyzed by protein kinases, phosphorylation is the most important post-translational modification in eukaryotes and is involved in the regulation of almost all cellular processes. Investigating phosphorylation events and how they change in response to different biological conditions is integral to understanding cellular signaling processes in general, as well as to defining the role of phosphorylation in health and disease. A recently-developed technology for studying phosphorylation events is the kinome microarray, which consists of several hundred "spots" arranged in a grid-like pattern on a glass slide. Each spot contains many peptides of a particular amino acid sequence chemically fixed to the slide, with different spots containing peptides with different sequences. Each peptide is a subsequence of a full protein, containing an amino acid residue that is known or suspected to undergo phosphorylation in vivo, as well as several surrounding residues. When a kinome microarray is exposed to cell lysate, the protein kinases in the lysate catalyze the phosphorylation of the peptides on the array. By measuring the degree to which the peptides comprising each spot are phosphorylated, insight can be gained into the upregulation or downregulation of signaling pathways in response to different biological treatments or conditions. There are two main computational challenges associated with kinome microarrays. The first is array design, which involves selecting the peptides to be included on a given array. The level of difficulty of this task depends largely on the number of phosphorylation sites that have been experimentally identified in the proteome of the organism being studied. For instance, thousands of phosphorylation sites are known for human and mouse, allowing considerable freedom to select peptides that are relevant to the problem being examined. In contrast, few sites are known for, say, honeybee and soybean. For such organisms, it is useful to expand the set of possible peptides by using computational techniques to predict probable phosphorylation sites. In this thesis, existing techniques for the computational prediction of phosphorylation sites are reviewed. In addition, two novel methods are described for predicting phosphorylation events in organisms with few known sites, with each method using a fundamentally different approach. The first technique, called PHOSFER, uses a random forest-based machine-learning strategy, while the second, called DAPPLE, takes advantage of sequence homology between known sites and the proteome of interest. Both methods are shown to allow quicker or more accurate predictions in organisms with few known sites than comparable previous techniques. Therefore, the use of kinome microarrays is no longer limited to the study of organisms having many known phosphorylation sites; rather, this technology can potentially be applied to any organism having a sequenced genome. It is shown that PHOSFER and DAPPLE are suitable for identifying phosphorylation sites in a wide variety of organisms, including cow, honeybee, and soybean. The second computational challenge is data analysis, which involves the normalization, clustering, statistical analysis, and visualization of data resulting from the arrays. While software designed for the analysis of DNA microarrays has also been used for kinome arrays, differences between the two technologies prompted the development of PIIKA, a software package specifically designed for the analysis of kinome microarray data. By comparing with methods used for DNA microarrays, it is shown that PIIKA improves the ability to identify biological pathways that are differentially regulated in a treatment condition compared to a control condition. Also described is an updated version, PIIKA 2, which contains improvements and new features in the areas of clustering, statistical analysis, and data visualization. Given the previous absence of dedicated tools for analyzing kinome microarray data, as well as their wealth of features, PIIKA and PIIKA 2 represent an important step in maximizing the scientific value of this technology. In addition to the above techniques, this thesis presents three studies involving biological applications of kinome microarray analysis. The first study demonstrates the existence of "kinotypes" - species- or individual-specific kinome profiles - which has implications for personalized medicine and for the use of model organisms in the study of human disease. The second study uses kinome analysis to characterize how the calf immune system responds to infection by the bacterium Mycobacterium avium subsp. paratuberculosis. Finally, the third study uses kinome arrays to study parasitism of honeybees by the mite Varroa destructor, which is thought to be a major cause of colony collapse disorder. In order to make the methods described above readily available, a website called the SAskatchewan PHosphorylation Internet REsource (SAPHIRE) has been developed. Located at the URL http://saphire.usask.ca, SAPHIRE allows researchers to easily make use of PHOSFER, DAPPLE, and PIIKA 2. These resources facilitate both the design and data analysis of kinome microarrays, making them an even more effective technique for studying cellular signaling

The MACC1 Dimerization and its Function in Tumor Metastasis

Colorectal cancer, a highly heterogeneous cancer, continues to be a leading cause of mortality worldwide. While the 5-year survival rates for patients with Stage I and II are high, there has been little or no improvement of survival for patients with metastases. To make matters worse, 20% of the patients already present with metastasis at the time of diagnosis. Therefore, early detection of patients who are at high risk of developing metastases using biomarkers is key to improving patient survival. Metastasis-associated in colon cancer 1 (MACC1) is one such biomarker that has been directly linked to metastasis development, reduced survival, and worse overall outcomes. In addition to identifying high-risk patients, MACC1 is biologically linked to tumor and metastasis development. Specifically, the MACC1 structure contains diverse domains and several tyrosine sites capable of versatile interactions. Therefore, the aim of the first part of the project was to study the role of tyrosine sites close to the N-terminus of MACC1. Employing computational tyrosine phosphorylation prediction tools, site Tyr379 and SRC kinase as one of the promising kinases responsible for its phosphorylation were identified. Preliminary examination reveals an association between MACC1 and SRC. Despite extensive evidence describing the functional diversity of MACC1, little is known about the structural features and self-association property of MACC1. To address this gap in knowledge, the goal of the second part of this project was to systematically evaluate the structural properties of MACC1 and the self-association capability of MACC1. Using AlphaFold2, the structures of MACC1 and MACC1 dimer were revealed. Val212, Ileu214, and Cys216 present in the ZU5 domain of MACC1 were found to be critical for dimerization. The knowledge gained from the AI prediction was transferred to set up a bioluminescence resonance energy transfer (BRET) assay to analyze MACC1 dimerization and the effect of mutation on dimerization. In addition to validating the presence of MACC1 dimer in living cells, the BRET assay confirmed reduced MACC1 self-association when the above residues were mutated. Ultimately, the impact of these mutations on MACC1 signaling and metastasis properties was verified using an in vitro metastasis assay. In summary, these results shed new light on the MACC1 structural characteristics particularly the presence of MACC1 homodimer, and reveal the residues important for dimerization, thus providing a framework for future development of intervention strategies

Beyond hairballs: depicting complexity of a kinase-phosphatase network in the budding yeast

Les kinases et les phosphatases (KP) représentent la plus grande famille des enzymes dans la cellule. Elles régulent les unes les autres ainsi que 60 % du protéome, formant des réseaux complexes kinase-phosphatase (KP-Net) jouant un rôle essentiel dans la signalisation cellulaire. Ces réseaux caractérisés d’une organisation de type commandes-exécutions possèdent généralement une structure hiérarchique. Malgré les nombreuse études effectuées sur le réseau KP-Net chez la levure, la structure hiérarchique ainsi que les principes fonctionnels sont toujours peux connu pour ce réseau. Dans ce contexte, le but de cette thèse consistait à effectuer une analyse d’intégration des données provenant de différentes sources avec la structure hiérarchique d’un réseau KP-Net de haute qualité chez la levure, S. cerevisiae, afin de générer des hypothèses concernant les principes fonctionnels de chaque couche de la hiérarchie du réseau KP-Net. En se basant sur une curation de données d’interactions effectuée dans la présente et dans d’autres études, le plus grand et authentique réseau KP-Net reconnu jusqu’à ce jour chez la levure a été assemblé dans cette étude. En évaluant le niveau hiérarchique du KP-Net en utilisant la métrique de la centralisation globale et en élucidant sa structure hiérarchique en utilisant l'algorithme vertex-sort (VS), nous avons trouvé que le réseau KP-Net possède une structure hiérarchique ayant la forme d’un sablier, formée de trois niveaux disjoints (supérieur, central et inférieur). En effet, le niveau supérieur du réseau, contenant un nombre élevé de KPs, était enrichi par des KPs associées à la régulation des signaux cellulaire; le niveau central, formé d’un nombre limité de KPs fortement connectées les unes aux autres, était enrichi en KPs impliquées dans la régulation du cycle cellulaire; et le niveau inférieur, composé d’un nombre important de KPs, était enrichi en KPs impliquées dans des processus cellulaires diversifiés. En superposant une grande multitude de propriétés biologiques des KPs sur le réseau KP-Net, le niveau supérieur était enrichi en phosphatases alors que le niveau inférieur en était appauvri, suggérant que les phosphatases seraient moins régulées par phosphorylation et déphosphorylation que les kinases. De plus, le niveau central était enrichi en KPs représentant des « bottlenecks », participant à plus d’une voie de signalisation, codées par des gènes essentiels et en KPs qui étaient les plus strictement régulées dans l’espace et dans le temps. Ceci implique que les KPs qui jouent un rôle essentiel dans le réseau KP-Net devraient être étroitement contrôlées. En outre, cette étude a montré que les protéines des KPs classées au niveau supérieur du réseau sont exprimées à des niveaux d’abondance plus élevés et à un niveau de bruit moins élevé que celles classées au niveau inférieur du réseau, suggérant que l’expression des enzymes à des abondances élevées invariables au niveau supérieur du réseau KP-Net pourrait être importante pour assurer un système robuste de signalisation. L’étude de l’algorithme VS a montré que le degré des nœuds affecte leur classement dans les différents niveaux d’un réseau hiérarchique sans biaiser les résultats biologiques du réseau étudié. En outre, une analyse de robustesse du réseau KP-Net a montré que les niveaus du réseau KP-Net sont modérément stable dans des réseaux bruités générés par ajout d’arrêtes au réseau KP-Net. Cependant, les niveaux de ces réseaux bruités et de ceux du réseau KP-Net se superposent significativement. De plus, les propriétés topologiques et biologiques du réseau KP-Net étaient retenues dans les réseaux bruités à différents niveaux. Ces résultats indiquant que bien qu’une robustesse partielle de nos résultats ait été observée, ces derniers représentent l’état actuel de nos connaissances des réseaux KP-Nets. Finalement, l’amélioration des techniques dédiées à l’identification des substrats des KPs aideront davantage à comprendre comment les réseaux KP-Nets fonctionnent. À titre d’exemple, je décris, dans cette thèse, une stratégie que nous avons conçu et qui permet à déterminer les interactions KP-substrats et les sous-unités régulatrices sur lesquelles ces interactions dépendent. Cette stratégie est basée sur la complémentation des fragments de protéines basée sur la cytosine désaminase chez la levure (OyCD PCA). L’OyCD PCA représente un essai in vivo à haut débit qui promet une description plus précise des réseaux KP-Nets complexes. En l’appliquant pour déterminer les substrats de la kinase cycline-dépendante de type 1 (Cdk1, appelée aussi Cdc28) chez la levure et l’implication des cyclines dans la phosphorylation de ces substrats par Cdk1, l’essai OyCD PCA a montré un comportement compensatoire collectif des cyclines pour la majorité des substrats. De plus, cet essai a montré que la tubuline- γ est phosphorylée spécifiquement par Clb3-Cdk1, établissant ainsi le moment pendant lequel cet événement contrôle l'assemblage du fuseau mitotique.Kinases and phosphatases (KP) form the largest family of enzymes in living cells. They regulate each other and 60 % of the proteome forming complex kinase-phosphatase networks (KP-Net) essential for cell signaling. Such networks having the command-execution aspect tend to have a hierarchical structure. Despite the extensive study of the KP-Net in the budding yeast, the hierarchical structure as well as the functional principles of this network are still not known. In this context, this thesis aims to perform an integrative analysis of multi-omics data with the hierarchical structure of a bona fide KP-Net in the budding yeast Saccharomyces cerevisiae, in order to generate hypotheses about the functional principles of each layer in the KP-Net hierarchy. Based on a literature curation effort accomplished in this and in other studies, the largest bona fide KP-Net of the S. cerevisiae known to date was assembled in this thesis. By assessing the hierarchical level of the KP-Net using the global reaching centrality and by elucidating the its hierarchical structure using the vertex-sort (VS) algorithm, we found that the KP-Net has a moderate hierarchical structure made of three disjoint layers (top, core and bottom) resembling a bow tie shape. The top layer having a large size was found enriched for signaling regulation; the core layer made of few strongly connected KPs was found enriched mostly for cell cycle regulation; and the bottom layer having a large size was found enriched for diverse biological processes. On overlaying a wide range of KP biological properties on top of the KP-Net hierarchical structure, the top layer was found enriched for and the bottom layer was found depleted for phosphatases, suggesting that phosphatases are less regulated by phosphorylation and dephosphoryation interactions (PDI) than kinases. Moreover, the core layer was found enriched for KPs representing bottlenecks, pathway-shared components, essential genes and for the most tightly regulated KPs in time and space, implying that KPs playing an essential role in the KP-Net should be firmly controlled. Interestingly, KP proteins in the top layer were found more abundant and less noisy than those of the bottom layer, suggesting that availability of enzymes at invariable protein expression level at the top of the network might be important to ensure a robust signaling. Analysis of the VS algorithm showed that node degrees affect their classification in the different layers of a network hierarchical structure without biasing biological results of the sorted network. Robustness analysis of the KP-Net showed that KP-Net layers are moderately stable in noisy networks generated by adding edges to the KP-Net. However, layers of these noisy overlap significantly with those of the KP-Net. Moreover, topological and biological properties of the KP-Net were retained in the noisy networks to different levels. These findings indicate that despite the observed partial robustness of our results, they mostly represent our current knowledge about KP-Nets. Finally, enhancement of techniques dedicated to identify KPs substrates will enhance our understanding about how KP-Nets function. As an example, I describe here a strategy that we devised to help in determining KP-substrate interactions and the regulatory subunits on which these interactions depend. The strategy is based on a protein-fragment complementation assay based on the optimized yeast cytosine deaminase (OyCD PCA). The OyCD PCA represents a large scale in vivo screen that promises a substantial improvement in delineating the complex KP-Nets. We applied the strategy to determine substrates of the cyclin-dependent kinase 1 (Cdk1; also called Cdc28) and cyclins implicated in phosphorylation of these substrates by Cdk1 in S. cerevisiae. The OyCD PCA showed a wide compensatory behavior of cyclins for most of the substrates and the phosphorylation of γ-tubulin specifically by Clb3-Cdk1, thus establishing the timing of the latter event in controlling assembly of the mitotic spindle

Insights to Protein Pathogenicity from the Lens of Protein Evolution

As protein sequences evolve, differences in selective constraints may lead to outcomes ranging from sequence conservation to structural and functional divergence. Evolutionary protein family analysis can illuminate which protein regions are likely to diverge or remain conserved in sequence, structure, and function. Moreover, nonsynonymous mutations in pathogens may result in the emergence of protein regions that affect the behavior of pathogenic proteins within a host and host response. I aimed to gain insight on pathogenic proteins from cancer and viruses using an evolutionary perspective. First, I examined p53, a conformationally flexible, multifunctional protein mutated in ~50% of human cancers. Multifunctional proteins may experience rapid sequence divergence given trade-offs between functions, while proteins with important functions may be more constrained. How, then, does a protein like p53 evolve? I assessed the evolutionary dynamics of structural and regulatory properties in the p53 family, revealing paralog-specific patterns of functional divergence. I also studied flaviviruses, like Dengue and Zika virus, whose conformational flexibility contributes to antibody-dependent enhancement (ADE). ADE has long complicated vaccine development for these viruses, making antiviral drug development an attractive alternative. I identified fitness-critical sites conserved in sequence and structure in the proteome of flaviviruses with the potential to act as broadly neutralizing antiviral drug target sites. I later developed Epitopedia, a computational method for epitope-based prediction of molecular mimicry. Molecular mimicry occurs when regions of antigenic proteins resemble protein regions from the host or other pathogens, leading to antibody cross-reactivity at these sites which can result in autoimmunity or have a protective effect. I applied Epitopedia to the antigenic Spike protein from SARS-CoV-2, the causative agent of COVID-19. Molecular mimicry may explain the varied symptoms and outcomes seen in COVID-19 patients. I found instances of molecular mimicry in Spike associated with COVID-19-related blood-clotting disorders and cardiac disease, with implications on disease treatment and vaccine design

3D struktury fosforylace

Fosforylace je běžná post-translační modifikace proteinů využívaná téměř ve všech buněčných procesech. Přidání fosfátové skupiny na vedlejší řetězec aminokyseliny může z důvodu velikosti fosfátové skupiny a jejího negativního náboje způsobit strukturní změny proteinu a ovlivnit proteinové interakce. Fosforylace také může vést ke změně proteinové funkce, aktivity, a dokonce umístění proteinu v rámci buňky. Experimentální studium fosforylačních míst je velmi časově a finančně náročné i dnes v době hmotnostní spektrometrie. Z tohoto důvodu je předmětem výzkumu mnoha bioinformatických vědeckých skupin predikce fosforylačních míst. Současné analýzy fosforylačních míst studovaly především nefosforylovaná fosforylační místa a rozdělení a zastoupení aminokyselin v jejich sekvenčním okolí. Protože ke specificitě proteinových kináz ale mohou přispívat i aminokyseliny sekvenčně sice vzdálené, ale strukturně blízké, byly v této práci studovány 3D strukturní vlastnosti fosforylačních míst. Zároveň byla poprvé rozsáhle zkoumána fosforylační místa ve fosforylovaném stavu a výsledky byly srovnány s fosforylačními místy v nefosforylovaném stavu. Fosforylační místa byla nalezena především ve smyčkách a na povrchu proteinů. Aminokyseliny v jejich okolí byly častěji hydrofilní, pozitivně nabité a méně blízko sebe než...Protein phosphorylation is a common post-translational protein modification used in almost all cellular processes. When a phosphate group is added to an amino acid side chain, it may alter the protein conformation and protein-protein interactions due to its size and its negative charge. It may also change the protein function, activity and even localization within the cell. Experimental detection of phosphorylation is still extremely labor demanding and very expensive, even when deploying protein mass spectrometry. For this very reason many bioinformatics scientific groups focus on the prediction of protein phosphorylation sites. Recent analyses of phosphorylation sites studied mainly non-phosphorylated phosphorylation sites and the distribution and representation of amino acids sequentially neighboring them. Since sequentially more distant, but structurally close amino acids can contribute to the recognition of protein substrate by protein kinase, structural environment of phosphorylation sites was studied in this thesis. Furthermore, 3D structures of phosphorylation sites were comprehensively studied for the first time in a phosphorylated state and the results were compared with the results obtained from the analysis of non- phosphorylated sites. Phosphorylation sites were found mostly within...Katedra filosofie a dějin přírodních vědDepartment of Philosophy and History of ScienceFaculty of SciencePřírodovědecká fakult

On the regulation of chromosome segregation in human cells : implications of Bub1 Kinase inhibition during cell division

The maintenance of correct chromosome number (euploidy) during cell division is essential for health. Loss of euploidy is observed in most cancers and is linked to tumorigenesis. During mitosis, a highly conserved surveillance mechanism termed âspindle assembly checkpointÕ safeguards correct chromosome segregation by delaying anaphase onset until all chromosomes are properly bi-oriented on the spindle apparatus. The kinase Bub1 functions in the spindle assembly checkpoint and in chromosome congression, but the impact of its catalytic activity on these function remains controversial. Here we present a thorough characterization of two novel small-molecule ATP-competitive inhibitors of Bub1 kinase, BAY-320 and BAY-524, to demonstrate potent Bub1 kinase inhibition both in vitro and in intact cells. We compared the cellular phenotypes of Bub1 kinase inhibition in HeLa and RPE-1 cells with those of protein depletion, indicative of catalytic or scaffolding functions, respectively. We demonstrate that Bub1 inhibition resulted in the persistence of chromosome arm cohesion. Furthermore, Bub1 inhibition affected chromosome association of Shugoshin and the chromosomal passenger complex, without abolishing global Aurora B function. Bub1 cooperates with Haspin on CPC localization, as inhibition of both kinases showed an additive effect. But for all that, Bub1 kinase inhibition exerted only minor effects on mitotic progression, chromosome alignment or spindle checkpoint function. In striking contrast, Bub1 depletion impaired all the mentioned mitotic processes, arguing that Bub1 largely operates as a scaffolding protein. Although, Bub1 inhibition seems to have little influence in mitotic fidelity, BAY-320 and BAY-524 treatment sensitized cells to low doses of Paclitaxel, resulting in remarkable impairment of chromosome segregation and cell proliferation. These findings are relevant to our understanding of Bub1 kinase function and the prospects of targeting Bub1 for therapeutic applications