Die Interaktion des onkogenen Transkriptionsfaktors MYCN mit der Ser/Thr Kinase Aurora-A verhindert dessen Abbau über das Ubiquitin Proteasomsystem indem die Rekrutierung des SCF FbxW7 Komplexes verhindert wird. Die Kinase nimmt mit der Bindung an MYCN eine aktive Konformation ein und erhält somit die Fähigkeit zur Kinaseaktivität ohne die sonst notwendige Phosphorylierung von Thr288 oder die Anwesenheit eines Aktivators wie TPX2. Da hohe MYCN Konzentrationen Tumore wie Neuroblastome antreiben, ist die Störung der Komplexbildung mit Aurora-A eine valide Strategie zur Entwicklung von Chemotherapeutika. Einige Inhibitoren von Aurora-A wie Alisertib (MLN8237) sind in der Lage, eine Konformationsänderung in der Kinase zu verursachen, die mit der Bindung von MYCN inkompatibel ist und auf diese Weise den Abbau des Transkriptionsfaktors induziert. Da Aurora-A wichtige Funktionen in der Mitose übernimmt, könnte eine direkte Adressierung des Komplexes anstelle einer systemischen Inhibition der Kinase vielversprechender sein. Ziel des Projektes war die Identifizierung von Molekülen, die selektiv an das Interface des Aurora-A – MYCN Komplexes binden und weiter optimiert werden können, um einen gezielten Abbau des Transkriptionsfaktors über einen PROTAC Ansatz zu ermöglichen. Virtuelle Screenings und molekulardynamische Simulationen wurden durchgeführt, um kommerziell erhältliche Verbindungen zu identifizieren, welche mit einer Bindetasche des Komplexes interagieren, die nur zustande kommt, wenn beide Proteine miteinander interagieren. Aus einem ersten Set von zehn potentiellen Liganden wurde für vier eine selektive Interaktion mit dem Protein – Protein Komplex gegenüber Aurora-A oder MYCN alleine in STD-NMR Experimenten bestätigt. Zwei der Hits besaßen ein identisches Grundgerüst und wurden als Ausganspunkt für die Optimierung zu potenteren Liganden genutzt. Das Gerüst wurde fragmentweise vergrößert und in Richtung besserer in-silico Ergebnisse und Funktionalisierung zur Anbringung von E3-Ligase-Liganden optimiert. Neun dieser Liganden der zweiten Generation wurden synthetisiert. Um quantitative Bindungsdaten zu erhalten, wurde ein kovalent verknüpftes Aurora-A – MYCN Konstrukt entworfen. Die strukturelle und funktionale Integrität wurde in STD-NMR und BLI Experimenten mit bekannten Aurora-A Inhibitoren bestätigt, sowie in NMR-basierten ATPase Assays. Zusätzlich konnte die Kristallstruktur des Konstrukts gelöst und damit die Validität des Designs bestätigt werden. Quantitative Messungen der synthetisierten Moleküle identifizierten HD19S als Hit mit einer zehnfach höheren Affinität für das Aurora-A – MYCN Konstrukt im Vergleich zu der Kinase allein. Zusätzlich wurden in-silico Untersuchungen zu PROTACs der Aurora-A Kinase durchgeführt. Interaktionen zwischen Aurora-A, der E3-Ligase Cereblon und den Liganden wurden modelliert und für die Erklärung unterschiedlicher Aktivitäten der eingesetzten PROTACs verwendet. Zudem zeigte das aktivste PROTAC eine hohe Selektivität für Aurora-A gegenüber Aurora-B, obwohl die verwendete Erkennungseinheit (Alisertib) an beide Aurora-Proteine bindet. Dieser Umstand konnte durch energetische Analysen von molekulardynamischen Simulationen der ternären Komplexe erklärt werden. Optimierungsmöglichkeiten für eine effizientere Degradation von Aurora-A durch die PROTACs wurden basierend auf modifizierten Erkennungseinheiten und verbesserten Linkern untersucht. / The association of the oncogenic transcription factor MYCN with the Ser/Thr kinase Aurora-A prevents its degradation via the ubiquitin proteasome system by preventing the SCF FbxW7 complex from binding. The kinase adopts an active conformation when bound to MYCN, enabling kinase activity without prior phosphorylation on Thr288 or the presence of an activator like TPX2, and therefore at inappropriate times during the cell cycle. As high levels of MYCN have been shown to drive cancers like neuroblastoma, disrupting the complex formation is thought to be a viable development strategy for chemotherapeutics. Several small-molecule inhibitors of Aurora-A, like Alisertib (MLN8237), are able to induce a conformational change in the kinase, preventing the formation of the protein – protein complex and therefore promoting MYCN degradation. However, since Aurora-A has important roles during mitosis targeting only the complex could be a more promising approach than the systemic inhibition of the kinase. This project aimed to identify small molecules which selectively bind at the Aurora-A – MYCN interface and can be further optimized to induce targeted degradation via a PROTAC approach. Virtual screenings and molecular dynamics simulations were performed to identify commercially available compounds which should bind to a pocket formed only when the two proteins come together. Of a first set of ten potential binders, four showed binding to the Aurora-A – MYCN complex but not the individual proteins in STD-NMR experiments. Two of these hit molecules contained the same scaffold and were used as a starting point for optimization towards more potent ligands. In a fragment-based fashion, the scaffold was grown to achieve better affinity in-silico and provide linkage points for functionalization such as the attachment of E3 ligase ligands to create PROTACs. Nine of these second-generation compounds were then synthesized. In order to obtain quantitative binding data a covalently linked Aurora-A – MYCN construct was designed. Its structural and functional validity was shown in STD-NMR and BLI experiments with known Aurora-A inhibitors and in NMR-based ATPase assays. In addition, a crystal structure of the construct was solved, validating the designed structure. Quantitative measurements with the synthesized compounds revealed a positive hit (HD19S) with a ten-fold higher affinity to the covalently linked AuroraA – MYCN as compared to Aurora-A alone. Additionally, effects of PROTACs designed to degrade Aurora-A were studied in-silico. Interactions between Aurora-A, the E3-ligase Cereblon and small molecules were modelled and successfully used to explain the differences in activities observed with different PROTACs. The most active PROTAC also showed a high selectivity for Aurora-A over Aurora-B, even though the recognition unit (Alisertib) can bind both family members. Through energetic analysis of molecular dynamics simulations of the ternary complexes, these differences could be explained. Optimizations for a more efficient degradation of Aurora-A by the PROTACs were examined by changing the recognition unit and improving linkers.

Techn. Universiẗat, Diss., 2005--Darmstadt.

Universiẗat, Diss., 2005--Düsseldorf. / Erscheinungsjahr an der Haupttitelstelle : 2004.

Phosducin-like Protein existiert in zwei Splicevarianten: PhLPLONG (PhLPL) und PhLPSHORT (PhLPS). Sie unterscheiden sich in der Länge ihres N-Terminus und in ihrem Expressionsmusters: Die lange Form (PhLPL) wird ubiquitär exprimiert und bindet G-Protein-betagamma-Untereinheiten (Gbetagama), was zur Hemmung von Gbetagamma-abhängigen Funktionen führt. Der um 83 Aminosäuren verlängerte N-Terminus besitzt ein hoch konserviertes Motiv, welches für die Gbetagamma-Bindung und Regulation von entscheidender Bedeutung ist. Im Gegensatz hierzu besitzt die kurzen Spliceform PhLPS, deren Expression in verschiedenen Gewebetypen deutlich geringer ist, diese hoch konservierte Region nicht. In der vorliegenden Arbeit wurde nun erstmals die Rolle von PhLPL und PhLPS bei der Gbetagamma-Regulation in intakten Zellen untersucht. Hierbei konnte überraschenderweise gefunden werden, dass PhLPS der potentere und effizientere Regulator für Gbetagamma-abhängige Signale war. PhLPL hingegen schien in seiner Gbetagamma-regulierenden Fähigkeit limitiert zu werden. Die Ursache dieser Limitierung von PhLPL in intakten Zellen wurde auf eine konstitutive Phosphorylierung seines verlängerten N-Terminus durch die ubiquitäre Casein Kinase 2 (CK2) zurückgeführt. Die verantwortlichen Phosphorylierungsstellen (S18, T19, S20) wurde identifiziert und die Mutation der CK2-Phosphorylierungsstellen (PhLPLA18-20) führte zu einer Verbesserung der hemmenden Funktion von PhLPL in Zellen. In vitro-Assays zur Bindungsfähigkeit von rekombinantem PhLPL (vor und nach CK2-Phosphorylierung) zeigten allerdings: die Phosphorylierung beeinflusste die Affinität nicht. Eine genaue Analyse der N-terminalen Strukuren von PhLPL zeigte indes, dass die Regulationsfähigkeit von PhLPL in intakten Zellen vor allem in dem konservierten Gbetagamma-Bindungsmotiv zu suchen war. Die Mutation einer einzigen Aminosäure (W66V) war ausreichend, um sowohl die Gbetagamma-Bindungsfähigkeit, als auch die Fähigkeit zur funktionellen Hemmung in intakten Zellen zu verlieren. Was war also der Mechanismus der Hemmung von Gbetagamma durch PhLPS und die phophorylierungsdefiziente Mutante von PhLPL? Ein erster Hinweis hierauf kam von der Beobachtung, dass die Gbeta- und Ggamma-Untereinheiten in Anwesenheit von PhLPS in ihrem Proteingehalt deutlich reduziert vorlagen (wie in Western Blots gezeigt). Dieser Mechanismus schien von proteasomalen Abbauwegen abzuhängen (gezeigt durch Effekte des spezifischen Proteasominhibitors Lactazystin). Allerdings schien eine Stabilisierung der Gbeta- und Ggamma-Untereinheiten (durch N-terminale Fusion mit einem Protein zur vitalen Proteinfärbung) nicht die Funktionsfähigkeit von Gbetagamma in Anwesenheit von PhLPS bewahren zu können. Ganz im Gegenteil, es wurde gezeigt, dass Gbeta und Ggamma hierbei nicht mehr zu einem funktionellen Dimer assoziierten. Dies war ein Hinweis darauf, dass möglicherweise Proteinfaltungsmechanismen bei der Regulation essentiell sein könnten. Eine postulierte Rolle bei der Faltung von WD40-Repeatproteinen wie der Gbeta-Untereinheit wurde dem Chaperonin-Komplex CCT (chaperonin containing TCP) zugedacht. Folgerichtig konnte PhLPS mit seinen funktionell aktiven Domänen an endogenes TCP-1alpha (einer Untereinheit von CCT) binden. Ferner konnte gezeigt werden, dass die Hemmung des CCT-Komplexes durch RNA-Interferenz mit TCP-1alpha ebenso wie PhLPS zur spezifischen Reduktion von Gbetagamma führte. In dieser Arbeit wurde also ein neuartiger Mechanismus der G-Protein-Regulation durch Hemmung der Proteinfaltung von Gbetagamma beschrieben. Ein Schaltmechanismus zwischen direkter Gbetagamma-Bindung (induziert durch CK2-Phosphorylierung von PhLPL) und Hemmung der Proteinfaltung von Gbetagamma (induziert durch alternatives Splicen oder durch Dephosphorylierung von PhLP) wird postuliert. / Phosducin-like protein (PhLP) exists in two splice variants PhLPLONG (PhLPL) and PhLPSHORT (PhLPS): They differ in the length of their N-termini and their expression pattern: The long form (PhLPL) is a ubiquitously expressed protein and binds G-protein betagamma-subunits (Gbetagamma) and thereby inhibits Gbetagamma-mediated function. The extended N-terminus of PhLPL (83 amino acids) contains a highly conserved Gbetagamma-binding motif which plays the crucial role in binding and regulating Gbetagamma-subunits. In contrast, the short splice variant PhLPS, which has a more restricted expression, lacks this motif and did not seem to exert a major Gbetagamma-inhibition, when tested with purified proteins. In the present work, for the first time, we investigated the Gbetagamma-inhibiting properties of PhLPL and PhLPS in intact cells. Surprisingly, PhLPS was the more potent and effective Gbetagamma inhibitor, while PhLPL was limited in this respect. The reason for the limited ability to inhibit Gbetagamma in intact cells was found in a constitutive phosphorylation by the ubiquitious kinase casein kinase 2 (CK2). The responsible phosphorylation sites could be identified (S18, T19, S20) and mutation of those sites into alanines could ameliorate the function of PhLPL. We therefore hypothesised that CK2 dependent phosphorylation of PhLPL should reduce binding affinity towards Gbetagamma subunits. But instead, direct phosphorylation of recombinant PhLPL by CK2 did not reduce its binding affinites. A thorough analysis of the N terminus of PhLPL revealed that a single mutation of the conserved N terminal binding motif (W66V) was sufficient to ablate Gbetagamma binding and Gbetagamma inhibition in intact cells. A first hint to an alternative mechanism came from the observation that - in the presence of PhLPS - the protein content of Gbeta and Ggamma subunits was dramatically reduced (as determined by Western blotting). This phenomenon seemed to be dependent on a proteasomal pathway (which was shown by effects of the specific proteasome inhibitor lactacystine). But a stabilization of the Gbeta and Ggamma subunits through N terminal fusion of a dye-labeling protein could not restore the function of Gbetagamma in the presence of PhLPS. Instead, it could be demonstrated that under these conditions Gbeta and Ggamma did not form functional dimers any more. This finding led to the conclusion that a protein folding mechanism was possibly involved. A postulated role in the folding of WD40 repeat proteins (like the Gbeta subunit) was assumed for the cytosolic chaperonin complex CCT in the literature. PhLPS was able to bind to TCP-1alpha, a subunit of CCT, as were the functionally active domains of PhLPS. We further demonstrated that the inhibition of CCT by RNA interference with TCP-1alpha also led to down-regulation of Gbeta and Ggamma subunits. So, in this thesis, a novel mechanism of G-protein regulation through inhibition of Gbetagamma protein folding was described. Further, a switch mechanism between direct Gbetagamm binding (induced by phosphorylation of PhLPL) and inhibition of Gbetagamm folding (induced by alternative splicing or dephosphorylation of PhLP) is postulated.

The major goal of this study was to develop an experimental proteomics approach for deciphering protein complexes and protein interaction networks in the budding and fission yeasts. Key steps of the employed analytical routine, including the purification of complexes and mass spectrometric identification of their subunits, were investigated in detail. Archiving, storage and handling of polyacylamide gels, visualization of protein bands and their effect on the efficiency of in-gel digestion and mass spectrometric identification of proteins were quantitatively evaluated. It was further demonstrated that a combination of several mass spectrometric techniques based on MALDI and ES ionization provided complementary data and enabled comprehensive characterization of protein digests. The optimized analytical procedures were employed in deciphering protein complexes and protein interaction networks in the budding and fission yeasts. A combination of Tandem Affinity Purification (TAP) and mass spectrometric identification of gel separated protein subunits is generic and robust strategy that provided accurate and reproducible data. The evaluation of TAP success rate, reproducibility and typical protein background presented in this work is based on TAP tagging and immunoprecepitation of 75 genes in S. cerevisiae and 22 in S. pombe. The molecular composition of characterized protein complexes was compared with protein-protein interactions uncovered by other established methods, such as yeast two hybrid screens or proteome-wide purification of protein complexes. We found that repetitive purification of protein complexes using different subunits as baits is crucially important for confident charting of proteomic environments. Accurate dissection of individual protein complexes and identification of their proteomic hyperlinks enabled to consider proteomic environments in the phylogenetic perspective and paved the way to reliable projection of proteomics data obtained in lower eukaryotic model organisms to higher eukaryotes, including humans.

University, Diss.--Köln, 2006. / Zsfassung in dt. Sprache.

Proteins and their interactions are fundamental to cellular life. Disruption of protein-protein, protein-RNA, or protein-DNA interactions can lead to disease, by affecting the function of protein complexes or by affecting gene regulation. A better understanding of these interactions on the molecular level gives rise to new methods to predict protein interaction, and is critical for the rational design of new therapeutic agents that disrupt disease-causing interactions. This thesis consists of three parts that focus on various aspects of protein interactions and their prediction in the context of disease. In the first part of this thesis, we classify interfaces of protein-protein interactions. We do so by systematically computing all binding sites between protein domains in protein complex structures solved by X-ray crystallography. The result is SCOPPI, the Structural Classification of Protein Protein Interfaces. Clustering and classification of geometrically similar interfaces reveals interesting examples comprising viral mimicry of human interface binding sites, gene fusion events, conservation of interface residues, and diversity of interface localisations. We then develop a novel method to predict protein interactions which is based on these structural interface templates from SCOPPI. The method is applied in three use cases covering osteoclast differentiation, which is relevant for osteoporosis, the microtubule-associated network in meiosis, and proteins found deregulated in pancreatic cancer. As a result, we are able to reconstruct many interactions known to the expert molecular biologist, and predict novel high confidence interactions backed up by structural or experimental evidence. These predictions can facilitate the generation of hypotheses, and provide knowledge on binding sites of promising disease-relevant candidates for targeted drug development. In the second part, we present a novel algorithm to search for protein binding sites in RNA sequences. The algorithm combines RNA structure prediction with sequence motif scanning and evolutionary conservation to identify binding sites on candidate messenger RNAs. It is used to search for binding sites of the PTBP1 protein, an important regulator of glucose secretion in the pancreatic beta cell. First, applied to a benchmark set of mRNAs known to be regulated by PTBP1, the algorithm successfully finds significant binding sites in all benchmark mRNAs. Second, collaborators carried out a screen to identify changes in the proteome of beta cells upon glucose stimulation while inhibiting gene expression. Analysing this set of post-transcriptionally controlled candidate mRNAs for PTBP1 binding, the algorithm produced a ranked list of 11 high confident potential PTBP1 binding sites. Experimental validation of predicted targets is ongoing. Overall, identifying targets of PTBP1 and hence regulators of insulin secretion may contribute to the treatment of diabetes by providing novel protein drug targets or by aiding in the design of novel RNA-binding therapeutics. The third part of this thesis deals with gene regulation in disease. One of the great challenges in medicine is to correlate genotypic data, such as gene expression measurements, and other covariates, such as age or gender, to a variety of phenotypic data from the patient. Here, we address the problem of survival prediction based on microarray data in cancer patients. To this end, a computational approach was devised to find genes in human cancer tissue samples whose expression is predictive for the survival outcome of the patient. The central idea of the approach is the incorporation of background knowledge information in form of a network, and the use of an algorithm similar to Google s PageRank. Applied to pancreas cancer, it identifies a set of eight genes that allows to predict whether a patient has a poor or good prognosis. The approach shows an accuracy comparable to studies that were performed in breast cancer or lymphatic malignancies. Yet, no such study was done for pancreatic cancer. Regulatory networks contain information of transcription factors that bind to DNA in order to regulate genes. We find that including background knowledge in form of such regulatory networks gives highest improvement on prediction accuracy compared to including protein interaction or co-expression networks. Currently, our collaborators test the eight identified genes for their predictive power for survival in an independent group of 150 patients. Under a therapeutic perspective, reliable survival prediction greatly improves the correct choice of therapy. Whereas the live expectancy of some patients might benefit from extensive therapy such as surgery and chemotherapy, for other patients this may only be a burden. Instead, for this group, a less aggressive or different treatment could result in better quality of the remaining lifetime. Conclusively, this thesis contributes novel analytical tools that provide insight into disease-relevant interactions of proteins. Furthermore, this thesis work contributes a novel algorithm to deal with noisy microarray measurements, which allows to considerably improve prediction of survival of cancer patients from gene expression data.

München, Techn. University, Diss., 2005.

The major goal of this study was to develop an experimental proteomics approach for deciphering protein complexes and protein interaction networks in the budding and fission yeasts. Key steps of the employed analytical routine, including the purification of complexes and mass spectrometric identification of their subunits, were investigated in detail. Archiving, storage and handling of polyacylamide gels, visualization of protein bands and their effect on the efficiency of in-gel digestion and mass spectrometric identification of proteins were quantitatively evaluated. It was further demonstrated that a combination of several mass spectrometric techniques based on MALDI and ES ionization provided complementary data and enabled comprehensive characterization of protein digests. The optimized analytical procedures were employed in deciphering protein complexes and protein interaction networks in the budding and fission yeasts. A combination of Tandem Affinity Purification (TAP) and mass spectrometric identification of gel separated protein subunits is generic and robust strategy that provided accurate and reproducible data. The evaluation of TAP success rate, reproducibility and typical protein background presented in this work is based on TAP tagging and immunoprecepitation of 75 genes in S. cerevisiae and 22 in S. pombe. The molecular composition of characterized protein complexes was compared with protein-protein interactions uncovered by other established methods, such as yeast two hybrid screens or proteome-wide purification of protein complexes. We found that repetitive purification of protein complexes using different subunits as baits is crucially important for confident charting of proteomic environments. Accurate dissection of individual protein complexes and identification of their proteomic hyperlinks enabled to consider proteomic environments in the phylogenetic perspective and paved the way to reliable projection of proteomics data obtained in lower eukaryotic model organisms to higher eukaryotes, including humans.

Protein-Protein Interaktions (PPI) Netzwerke liefern ein Grundgerüst für systematische Untersuchungen der komplexen molekularen Maschinerie in der Zelle. Die Komplexität von Protein-Wechselwirkungen stellt jedoch in Bezug auf ihre Identifizierung, Validierung und Annotation eine große experimentelle und rechnerische Herausforderung dar. In dieser Arbeit analysierte ich diese Probleme und lieferte Lösungen, um die Limitierungen aktueller humanen PPI Netzwerke zu überwinden. Meine Arbeit kann in zwei Teile aufgeteilt werden: Im ersten Teil führte ich eine kritischen Vergleich von acht unabhängig konstruierten humanen PPI Netzwerke durch, um mögliche experimentellen Verzerrungen zu erkennen. Die Ergebnisse zeigten starke Tendenzen bezüglich der Selektion und Detektion von Interaktionen, die in zukünftigen Anwendungen dieser Netzwerke berücksichtigt werden sollten. Einer der wichtigsten Schlussfolgerungen dieser Studie war, dass die derzeitigen humanen Interaktions Netzwerke komplementär sind und deshalb wurde eine Datenbank mit der Bezeichnung Unified Human Interaktome (UniHI) entwickelt, die menschliche PPI Daten aus zwölf wichtigsten Quellen integriert. Im zweiten Teil dieser Forschungsarbeit benutzte ich die Daten aus der UniHI Datenbank, die genetischen Modifikatoren in einer bestimmten Krankheit, Chorea Huntington (HD) eine autosomal dominante neurodegenerative Erkrankung, zu charakterisieren. Um die Proteine zu identifizieren, die den Krankheitsverlauf modifizieren können, wurden Protein Interaktion Daten mit Genexpressionsdaten von HD-Patienten in Kombination mit einem Mehrschritt-Filterungsverfahren integriert. Mit dem neuartigen Ansatz wurde ein Nucleus caudatus-spezifische Protein-Interaktion HD (PPI)-Netzwerk vorhergesagt, das 14 potentiell dysregulierten Proteine direkt oder indirekt mit dem Huntingtin-Protein verlinkt, mit mögliche Verbindung zu Molekularen Prozessen wie z.B. Apoptose, Metabolismus, neuronale Entwicklung. / Protein interaction networks aim to provide the scaffold maps for systematic studies of the complex molecular machinery in the cell. The complexity of protein interactions poses, however, large experimental and computational challenges regarding their identification, validation and annotation. Additionally, storage and linking is demanding since new data are rapidly accumulating. In this research work, I addressed these issues and provided solutions to overcome the limitations of current human protein-protein interaction (PPI) maps. In particular, my thesis can be partitioned into two parts: In the first part, I conducted a comparative assessment of eight recently constructed human protein-protein interaction networks to identify experimental biases. Results showed strong selection and detection biases which are necessary to take into consideration in future applications of these maps. One of the important conclusions of this study was that the current human interaction networks contain complementary information; hence, a database was developed, termed as Unified Human Interactome (UniHI), integrating human PPI data from twelve major sources. Several new tools were included for querying, analyzing and visualizing human PPI networks. In the second part of this research work, UniHI dataset was applied to characterize the genetic modifiers involved in a specific disease: Chorea Huntington (HD), an autosomal dominant neurodegenerative disease. To find the modifiers, a network-based modeling approach was implemented by integrating huntingtin-specific protein interaction network with gene expression data from HD patients in multiple steps. Using this approach, a Caudate Nucleus-specific HD protein interaction (PPI) network was predicted, connecting 14 potentially dysregulated proteins directly or indirectly to the disease protein, showing a possible link to molecular processes such as pro-apoptotic pathways, cell survival, anti-apoptotic, growth, and neuronal diseases.