In eukaryotes, mRNA turnover starts with the truncation of 3′ poly(A) tail and proceeds with either 3′-to-5′ degradation by the exosome complex or with decapping followed by 5′-to-3′ degradation by Xrn1. mRNA decapping is catalyzed by the decapping enzyme complex Dcp1-Dcp2 and is regulated by a highly conserved set of decapping activator proteins, including Pat1, Dhh1, Edc3 and the heptameric Lsm1-7 complex. The mechanisms regarding the interplay of mRNA decapping activators remains elusive owing to limited structural and biochemical understanding. My doctoral research was focused on elucidating the structural and functional roles of mRNA decapping activators involved in mRNA decay. Pat1 has a modular domain architecture that allows it to interact with multiple decapping activators simultaneously. Pat1 acts as a bridging factor between the 3′-end and the 5′-end of the mRNA by interacting with multiple proteins involved in decapping. The interaction of S. cerevisiae Pat1 N-terminus with the DEAD-box protein Dhh1 was characterized by biochemical pull-down assays and binding affinities were determined quantitatively by isothermal titration calorimetery. Based on these experiments, the crystal structure of Dhh1 bound to Pat1 was determined at 2.8 Å resolution. The structure reveals that Pat1 wraps around RecA2 domain of Dhh1 via evolutionary conserved interactions. This conserved surface of Dhh1 is also implicated in interaction with another decapping activator, Edc3, rationalizing why Pat1 and Edc3 binding to Dhh1 is mutually exclusive. These interactions were supported by testing mutations in in vitro assays with the yeast proteins and in co-immunoprecipitation assays with the corresponding human orthologs. Furthermore, structural analysis combined with RNA pull-down assays and a crosslinking mass spectrometry based approach gave definitive evidence that Dhh1 engages with Pat1, Edc3 and RNA in a mutually exclusive manner. The Lsm1-7 complex is another important activator of mRNA decapping. It protects the mRNA transcripts from 3′-end degradation and enhances the mRNA decapping. I determined the crystal structure of the Lsm1-7 complex at 2.3 Å resolution showing a hetero-heptameric complex of Lsm1-7 proteins that make a ring-like overall topology. Furthermore, an unusual helical structure of Lsm1 C-terminal extension and protrudes into the central channel of the heptameric ring, explaining how it is modulates the RNA binding properties of the complex. The Lsm1-7 complex interacts with the C-terminal domain of Pat1. Structure determination of this octameric Lsm1-7-Pat1 complex at 3.7 Å gave insights into the interaction of Pat1 with Lsm1-7 complex. Unexpectedly, Pat1 binds to Lsm2 and Lsm3 but not with the cytoplasmic specific subunit Lsm1. The Pat1 C-terminus makes a super-helical structure consisting of HEAT-like repeats of anti-parallel helices similar to the structure of its human ortholog. Structure based mutagenesis analysis by in vitro pull-downs showed that these interactions are conserved. This doctoral thesis gives structural and mechanistic insight into the role of multi-domain protein Pat1 and how it engages at two distinct ends of mRNA by interacting with Dhh1 at 5′-end and with Lsm1-7 complex that at 3′-end. Combining these results present a model of dynamic interplay of these activators and gives a better understanding of protein-protein and protein-RNA interaction network in the decapping machinery.

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Searching sequence databases and building 3D models for proteins are important tasks for biologists. When the structure of a query protein is given, its function can be inferred. However, experimental methods for structure prediction are both expensive and time consuming. Fully automatic homology modeling refers to building a 3D model for a query sequence from an alignment to related homologous proteins with known structure (templates) by a computer. Current prediction servers can provide accurate models within a few hours to days. Our group has developed HHpred, which is one of the top performing structure prediction servers in the field. In general, homology based structure modeling consists of four steps: (1) finding homologous templates in a database, (2) selecting and (3) aligning templates to the query, (4) building a 3D model based on the alignment. In part one of this thesis, we will present improvements of step (2) and (4). Specifically, homology modeling has been shown to work best when multiple templates are selected instead of only a single one. Yet, current servers are using rather ad-hoc approaches to combine information from multiple templates. We provide a rigorous statistical framework for multi-template homology modeling. Given an alignment, we employ Modeller to calculate the most probable structure for a query. The 3D model is obtained by optimally satisfying spatial restraints derived from the alignment and expressed as probability density functions. We find that the query’s atomic distance restraints can be accurately described by two-component Gaussian mixtures. Moreover, we derive statistical weights to quantify the redundancy among related templates. This allows us to apply the standard rules of probability theory to combine restraints from several templates. Together with a heuristic template selection strategy, we have implemented this approach within HHpred and could significantly improve model quality. Furthermore, we took part in CASP, a community wide competition for structure prediction, where we were ranked first in template based modeling and, at the same time, were more than 450 times faster than all other top servers. Homology modeling heavily relies on detecting and correctly aligning templates to the query sequence (step (1) and (3) from above). But remote homologies are difficult to detect and hard to align on a pure sequence level. Hence, modern tools are based on profiles instead of sequences. A profile summarizes the evolutionary history of a given sequence and consists of position specific amino acid probabilities for each residue. In addition to the similarity score between profile columns, most methods use extra terms that compare 1D structural properties such as secondary structure or solvent accessibility. These can be predicted from local profile windows. In the second part of this thesis, we develop a new score that is independent of any predefined structural property. For this purpose, we learn a library of 32 profile patterns that are most conserved in alignments of remotely homologous, structurally aligned proteins. Each so called “context state” in the library consists of a 13-residue sequence profile. We integrate the new context score into our Hmm-Hmm alignment tool HHsearch and improve especially the sensitivity and precision of difficult pairwise alignments significantly. Taken together, we introduced probabilistic methods to improve all four main steps in homology based structure prediction.

Auf mehreren unterschiedlichen Synthesewegen wurden sterisch unterschiedlich anspruchsvolle, chirale 2-Alkyliden-imidazolidine hergestellt. Das sterisch anspruchvollste ist das 2-Bornyliden-imidazolidin. Sie wurden als „Superbasen“ in Bromwasserstoff-, Toluolsulfonsäure- und α,β-Dibrom-Eliminierungen eingesetzt. Das Konformerenverhältnis der gebildeten Alkene wurde untersucht. Die 2-Alkyliden-imidazolidine wurden auf ihre Eliminierungseffizienz und auf ihre sterische und chirale Selektivität getestet. Sie wurden mit achiralen Kernstuktur-analogen 2-Alkyliden-imidazolidinen verglichen. / Chiral 2-alkylidene-imidazolidines, varying in their sterical demand, were synthesized by serveral different methods. The sterical most demanding imidazolidine is the 2-Bornylidene-imidazolidine. The imidazolidines were used as „superbases“ in hydrogen-bromide-, toluenesulfonic-acid- and α,β-dibromine-eliminations. The chemical conformations of the resulting alkenes were analysed. The 2-alkylidene-imidazolidines were tested with regard to elimination efficiency, to sterical and to chiral selectivity. They were compared to achiral 2-alkylidene-imidazolidines with a similar basic structure.

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Fighting metastasis is a major challenge in cancer therapy and novel therapeutic targets and drugs are highly appreciated. Resistance of invasive cells to anoikis, a particular type of apoptosis induced by loss of cell-extracellular matrix (ECM) contact, is a major prerequisite for their metastatic spread. Inducing anoikis in metastatic cancer cells is therefore a promising therapeutic approach. The vacuolar H+-ATPase (V-ATPase), a proton pump located at the membrane of acidic organelles, has recently come to focus as an anti-metastatic cancer target. As V-ATPase inhibitors have shown to prevent invasion of tumor cells and are able to induce apoptosis we proposed that V-ATPase inhibition induces anoikis related pathways in invasive cancer cells. In this study the V-ATPase inhibitor archazolid A was used to investigate the mechanism of anoikis induction in various metastatic cancer cells (T24, MDA-MB-231, 4T1, 5637). Therefore, cells were forced to stay in a detached status to mimic loss of cell-ECM engagement following treatment with archazolid. Indeed, anoikis induction by archazolid was characterized by decreased expression of the caspase-8 inhibitor c-FLIP and caspase-8 activation, thus triggering the extrinsic apoptotic pathway. Interestingly, active integrin β1, which is known to play a major role in anoikis induction and resistance, is reduced on the cell surface of archazolid treated cells. Furthermore, a diminished phosphorylation of the integrin downstream target focal adhesion kinase could be demonstrated. The intrinsic apoptotic pathway was initiated by the pro-apoptotic protein BIM, increasing early after treatment. BIM activates cytochrome C release from the mitochondria consequently leading to cell death and is described as one major inducer of anoikis in non-malignant and anoikis sensitive cancer cells. Of note, we observed that archazolid also induces mechanisms opposing anoikis such as proteasomal degradation of BIM mediated by the pro-survival kinases ERK, c-Src and especially Akt at later time points. Moreover, induction of reactive oxygen species (ROS) influences BIM removal as well, as moderate levels of ROS have second messenger properties amplifying cell survival signals. Thus, to antagonize these anoikis escape strategies a combination of archazolid with proteasome or ROS inhibitors amplified cancer cell death synergistically. Most importantly, intravenous injection of archazolid treated 4T1-Luc2 mouse breast cancer cells in BALB/cByJRj mice resulted in reduced lung metastases in vivo. To summarize this work we propose archazolid as a very potent drug in inducing anoikis pathways in metastatic cancer cells even though having learned that detachment together with treatment triggers multiple resistance mechanisms opposing cell death. Hence, V-ATPase inhibition is not only an interesting option to reduce cancer metastasis but also to better understand anoikis resistance and to find choices to fight against it.