Movement-associated proteins of Potato virus A: attachment to virus particles and phosphorylation

The particles of Potato virus A (PVA; genus Potyvirus) are helically constructed filaments that contain multiple copies of a single type of coat-protein (CP) subunit and a single copy of genome-linked protein (VPg), attached to one end of the virion. Examination of negatively-stained virions by electron microscopy revealed flexuous, rod-shaped particles with no obvious terminal structures. It is known that particles of several filamentous plant viruses incorporate additional minor protein components, forming stable complexes that mediate particle disassembly, movement or transmission by insect vectors. The first objective of this work was to study the interaction of PVA movement-associated proteins with virus particles and how these interactions contribute to the morphology and function of the virus particles. Purified particles of PVA were examined by atomic force microscopy (AFM) and immuno-gold electron microscopy. A protrusion was found at one end of some of the potyvirus particles, associated with the 5' end of the viral RNA. The tip contained two virus-encoded proteins, the genome-linked protein (VPg) and the helper-component proteinase (HC-Pro). Both are required for cell-to-cell movement of the virus. Biochemical and electron microscopy studies of purified PVA samples also revealed the presence of another protein required for cell-to-cell movement the cylindrical inclusion protein (CI), which is also an RNA helicase/ATPase. Centrifugation through a 5-40% sucrose gradient separated virus particles with no detectable CI to a fraction that remained in the gradient, from the CI-associated particles that went to the pellet. Both types of particles were infectious. AFM and translation experiments demonstrated that when the viral CI was not present in the sample, PVA virions had a beads-on-a-string phenotype, and RNA within the virus particles was more accessible to translation. The second objective of this work was to study phosphorylation of PVA movement-associated and structural proteins (CP and VPg) in vitro and, if possible, in vivo. PVA virion structural protein CP is necessary for virus cell-to-cell movement. The tobacco protein kinase CK2 was identified as a kinase phosphorylating PVA CP. A major site of CK2 phosphorylation in PVA CP was identified as a single threonine within a CK2 consensus sequence. Amino acid substitutions affecting the CK2 consensus sequence in CP resulted in viruses that were defective in cell-to-cell and long-distance movement. The CK2 regulation of virion assembly and cell-to-cell movement by phosphorylation of CP was possibly due to the inhibition of CP binding to viral RNA. Four putative phosphorylation sites were identified from an in vitro phosphorylated recombinant VPg. All four were mutated and the spread of mutant viruses in two different host plants was studied. Two putative phosphorylation site mutants (Thr45 and Thr49) had phenotypes identical to that of a wild type (WT) virus infection in both Nicotiana benthamiana and N. tabacum plants. The other two mutant viruses (Thr132/Ser133 and Thr168) showed different phenotypes with increased or decreased accumulation rates, respectively, in inoculated and the first two systemically infected leaves of N. benthamiana. The same mutants were occasionally restricted to single cells in N. tabacum plants, suggesting the importance of these amino acids in the PVA infection cycle in N. tabacum.

Enzyme molecular choreography : studies on soluble inorganic pyrophosphatases

Inorganic pyrophosphatases (PPases, EC 3.6.1.1) hydrolyse pyrophosphate in a reaction that provides the thermodynamic 'push' for many reactions in the cell, including DNA and protein synthesis. Soluble PPases can be classified into two families that differ completely in both sequence and structure. While Family I PPases are found in all kingdoms, family II PPases occur only in certain prokaryotes. The enzyme from baker's yeast (Saccharomyces cerevisiae) is very well characterised both kinetically and structurally, but the exact mechanism has remained elusive. The enzyme uses divalent cations as cofactors; in vivo the metal is magnesium. Two metals are permanently bound to the enzyme, while two come with the substrate. The reaction cycle involves the activation of the nucleophilic oxygen and allows different pathways for product release. In this thesis I have solved the crystal structures of wild type yeast PPase and seven active site variants in the presence of the native cofactor magnesium. These structures explain the effects of the mutations and have allowed me to describe each intermediate along the catalytic pathway with a structure. Although establishing the ʻchoreographyʼ of the heavy atoms is an important step in understanding the mechanism, hydrogen atoms are crucial for the mechanism. The most unambiguous method to determine the positions of these hydrogen atoms is neutron crystallography. In order to determine the neutron structure of yeast PPase I perdeuterated the enzyme and grew large crystals of it. Since the crystals were not stable at ambient temperature, a cooling device was developed to allow neutron data collection. In order to investigate the structural changes during the reaction in real time by time-resolved crystallography a photolysable substrate precursor is needed. I synthesised a candidate molecule and characterised its photolysis kinetics, but unfortunately it is hydrolysed by both yeast and Thermotoga maritima PPases. The mechanism of Family II PPases is subtly different from Family I. The native metal cofactor is manganese instead of magnesium, but the metal activation is more complex because the metal ions that arrive with the substrate are magnesium different from those permanently bound to the enzyme. I determined the crystal structures of wild type Bacillus subtilis PPase with the inhibitor imidodiphosphate and an inactive H98Q variant with the substrate pyrophosphate. These structures revealed a new trimetal site that activates the nucleophile. I also determined that the metal ion sites were partially occupied by manganese and iron using anomalous X- ray scattering.

Organized Nanostructures of Thermoresponsive Poly(N-isopropylacrylamide) Block Copolymers Obtained Through Controlled RAFT Polymerization

Kontrolloidut radikaalipolymerointimenetelmät, kuten RAFT-polymerointi, ovat moderni tapa valmistaa polymeerejä säädellysti. RAFT-polymeroinnilla polymeerien ketjunpituutta, moolimassajakaumaa, mikrorakennetta (taktisuus, järjestys), koostumusta ja funktionaalisuutta kyetään hallitsemaan. Siten menetelmällä voidaan valmistaa uudenlaisia polymeeriarkkitektuureja, kuten blokki- ja tähtipolymeerejä, sekä hybridimateriaaleja ja biokonjugaatteja. Polymeeristen rakennuspalikoiden itsejärjestyminen, missä huolellisesti syntetisoidut polymeerit järjestyvät halutulla tavalla nanoskaalassa, on suosittu tutkimuskohde materiaalitieteessä. On huomattava, että blokkipolymeerien itsejärjestyminen on vielä suhteellisen nuori tutkimusaihe. Tämän hetkiset polymeeriset nanomateriaalit ovat suhteellisen yksinkertaisia luonnon luomuksiin verrattuina, tarjoten jatkuvasti uusia mahdollisuuksia seuraavan sukupolven polymeereille. Tässä työssä RAFT-polymeroinnilla syntetisoitiin amfifiilisiä di- ja triblokkikopolymeerejä sekä tutkittiin niiden järjestymistä nanorakenteiksi. Kaikissa blokkikopolymeereissä käytettiin lämpöherkkää poly(N-isopropyyliakryyliamidia). Siten polymeerit ja tutkitut materiaalit reagoivat lämpötilanmuutokseen ympäristössä eli ovat ns. ympäristöherkkiä. Työssä tutkittiin taktisuuden kontrollointia N-isopropyyliakryyliamidin RAFT-polymeroinnissa. Polymeerin taktisuutta sekä ketjunpituutta ja blokkijärjestystä säätämällä voitiin hallita polymeerin itsejärjestymistä vesiliuoksessa. Amfifiiliset polymeerit järjestyivät laimeissa vesiliuoksissa erilaisiksi misellirakenteiksi, muodostaen ns. mikrosäiliöitä. Tällaisilla polymeereillä odotetaan olevan sovelluksia esim. lääkeainevapautuksessa. Amfifiilejä käytetään myös esimerkiksi apuaineina pinnoitteissa ja kosmetiikassa. Kiinteässä tilassa tutkitut triblokkikopolymeerit muodostivat teoreettisesti ennustettuja morfologioita. Lämpöherkän materiaalin hydrogeelit toimivat suodatinmembraanina nanokokoluokassa. RAFT-polymeroinnilla syntetisoituja polymeereja voidaan sellaisenaan käyttää kultananopartikkeleiden päällystämiseen. Kultananopartikkelit ovat erittäin kiinostavia mm. niiden stabiilisuuden ja ainutlaatuisten pintaominaisuuksien vuoksi. Kun amfifiilisiä polymeerejä kiinnitettiin kultapartikkelin pinnalle, sen liuos- ja optisia ominaisuuksia voitiin säädellä pH:n ja lämpötilan avulla. Tällaisilla kultananopartikkeleilla on sovelluksia mm. diagnostiikassa, sensoreina ja solukuvauksessa.

Aspects and Applications of Pulse Sequence Design for Solution-State Nuclear Magnetic Resonance Spectroscopy

NMR spectroscopy enables the study of biomolecules from peptides and carbohydrates to proteins at atomic resolution. The technique uniquely allows for structure determination of molecules in solution-state. It also gives insights into dynamics and intermolecular interactions important for determining biological function. Detailed molecular information is entangled in the nuclear spin states. The information can be extracted by pulse sequences designed to measure the desired molecular parameters. Advancement of pulse sequence methodology therefore plays a key role in the development of biomolecular NMR spectroscopy. A range of novel pulse sequences for solution-state NMR spectroscopy are presented in this thesis. The pulse sequences are described in relation to the molecular information they provide. The pulse sequence experiments represent several advances in NMR spectroscopy with particular emphasis on applications for proteins. Some of the novel methods are focusing on methyl-containing amino acids which are pivotal for structure determination. Methyl-specific assignment schemes are introduced for increasing the size range of 13C,15N labeled proteins amenable to structure determination without resolving to more elaborate labeling schemes. Furthermore, cost-effective means are presented for monitoring amide and methyl correlations simultaneously. Residual dipolar couplings can be applied for structure refinement as well as for studying dynamics. Accurate methods for measuring residual dipolar couplings in small proteins are devised along with special techniques applicable when proteins require high pH or high temperature solvent conditions. Finally, a new technique is demonstrated to diminish strong-coupling induced artifacts in HMBC, a routine experiment for establishing long-range correlations in unlabeled molecules. The presented experiments facilitate structural studies of biomolecules by NMR spectroscopy.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Boundedness and convergence of singular integrals on fractal type sets

The topic of this dissertation lies in the intersection of harmonic analysis and fractal geometry. We particulary consider singular integrals in Euclidean spaces with respect to general measures, and we study how the geometric structure of the measures affects certain analytic properties of the operators. The thesis consists of three research articles and an overview. In the first article we construct singular integral operators on lower dimensional Sierpinski gaskets associated with homogeneous Calderón-Zygmund kernels. While these operators are bounded their principal values fail to exist almost everywhere. Conformal iterated function systems generate a broad range of fractal sets. In the second article we prove that many of these limit sets are porous in a very strong sense, by showing that they contain holes spread in every direction. In the following we connect these results with singular integrals. We exploit the fractal structure of these limit sets, in order to establish that singular integrals associated with very general kernels converge weakly. Boundedness questions consist a central topic of investigation in the theory of singular integrals. In the third article we study singular integrals of different measures. We prove a very general boundedness result in the case where the two underlying measures are separated by a Lipshitz graph. As a consequence we show that a certain weak convergence holds for a large class of singular integrals.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Methods for Answer Extraction in Textual Question Answering

In this thesis we present and evaluate two pattern matching based methods for answer extraction in textual question answering systems. A textual question answering system is a system that seeks answers to natural language questions from unstructured text. Textual question answering systems are an important research problem because as the amount of natural language text in digital format grows all the time, the need for novel methods for pinpointing important knowledge from the vast textual databases becomes more and more urgent. We concentrate on developing methods for the automatic creation of answer extraction patterns. A new type of extraction pattern is developed also. The pattern matching based approach chosen is interesting because of its language and application independence. The answer extraction methods are developed in the framework of our own question answering system. Publicly available datasets in English are used as training and evaluation data for the methods. The techniques developed are based on the well known methods of sequence alignment and hierarchical clustering. The similarity metric used is based on edit distance. The main conclusions of the research are that answer extraction patterns consisting of the most important words of the question and of the following information extracted from the answer context: plain words, part-of-speech tags, punctuation marks and capitalization patterns, can be used in the answer extraction module of a question answering system. This type of patterns and the two new methods for generating answer extraction patterns provide average results when compared to those produced by other systems using the same dataset. However, most answer extraction methods in the question answering systems tested with the same dataset are both hand crafted and based on a system-specific and fine-grained question classification. The the new methods developed in this thesis require no manual creation of answer extraction patterns. As a source of knowledge, they require a dataset of sample questions and answers, as well as a set of text documents that contain answers to most of the questions. The question classification used in the training data is a standard one and provided already in the publicly available data.