174 resultados para QUASI-MOLECULAR SHAPES


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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.

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Individual movement is very versatile and inevitable in ecology. In this thesis, I investigate two kinds of movement body condition dependent dispersal and small-range foraging movements resulting in quasi-local competition and their causes and consequences on the individual, population and metapopulation level. Body condition dependent dispersal is a widely evident but barely understood phenomenon. In nature, diverse relationships between body condition and dispersal are observed. I develop the first models that study the evolution of dispersal strategies that depend on individual body condition. In a patchy environment where patches differ in environmental conditions, individuals born in rich (e.g. nutritious) patches are on average stronger than their conspecifics that are born in poorer patches. Body condition (strength) determines competitive ability such that stronger individuals win competition with higher probability than weak individuals. Individuals compete for patches such that kin competition selects for dispersal. I determine the evolutionarily stable strategy (ESS) for different ecological scenarios. My models offer explanations for both dispersal of strong individuals and dispersal of weak individuals. Moreover, I find that within-family dispersal behaviour is not always reflected on the population level. This supports the fact that no consistent pattern is detected in data on body condition dependent dispersal. It also encourages the refining of empirical investigations. Quasi-local competition defines interactions between adjacent populations where one population negatively affects the growth of the other population. I model a metapopulation in a homogeneous environment where adults of different subpopulations compete for resources by spending part of their foraging time in the neighbouring patches, while their juveniles only feed on the resource in their natal patch. I show that spatial patterns (different population densities in the patches) are stable only if one age class depletes the resource very much but mainly the other age group depends on it.

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Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

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Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

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In cardiac myocytes (heart muscle cells), coupling of electric signal known as the action potential to contraction of the heart depends crucially on calcium-induced calcium release (CICR) in a microdomain known as the dyad. During CICR, the peak number of free calcium ions (Ca) present in the dyad is small, typically estimated to be within range 1-100. Since the free Ca ions mediate CICR, noise in Ca signaling due to the small number of free calcium ions influences Excitation-Contraction (EC) coupling gain. Noise in Ca signaling is only one noise type influencing cardiac myocytes, e.g., ion channels playing a central role in action potential propagation are stochastic machines, each of which gates more or less randomly, which produces gating noise present in membrane currents. How various noise sources influence macroscopic properties of a myocyte, how noise is attenuated and taken advantage of are largely open questions. In this thesis, the impact of noise on CICR, EC coupling and, more generally, macroscopic properties of a cardiac myocyte is investigated at multiple levels of detail using mathematical models. Complementarily to the investigation of the impact of noise on CICR, computationally-efficient yet spatially-detailed models of CICR are developed. The results of this thesis show that (1) gating noise due to the high-activity mode of L-type calcium channels playing a major role in CICR may induce early after-depolarizations associated with polymorphic tachycardia, which is a frequent precursor to sudden cardiac death in heart failure patients; (2) an increased level of voltage noise typically increases action potential duration and it skews distribution of action potential durations toward long durations in cardiac myocytes; and that (3) while a small number of Ca ions mediate CICR, Excitation-Contraction coupling is robust against this noise source, partly due to the shape of ryanodine receptor protein structures present in the cardiac dyad.

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Many Gram-negative bacteria pathogenic to plants and animals possess type III secretion systems that are used to cause disease. Effector proteins are injected into host cells using the type III secretion machineries. Despite vigorous studies, the nature of the secretion signal for type III secreted proteins still remains elusive. Both mRNA and proteinaceous signals have been proposed. Findings on coupling of translation to secretion by the type III secretion systems are also still contradictory. This study dealt with the secretion signal of HrpA from Pseudomonas syringae pathovar tomato. HrpA is the major component of the type III secretion system-associated Hrp pilus and a substrate for the type III secretion systems. The secretion signal was shown to reside in the first 15 codons or amino acids, a location typical for type III secretion signals. Translation of HrpA in the absence of a functional type III secretion system was established, but it does not exclude the possibility of coupling of translation to secretion when the secretion apparatus is present. The hrpA transcripts from various unrelated plant pathogenic bacteria were shown to be extremely stable. The biological relevance of this observation is unknown, but possible explanations include the high prevalence of HrpA protein, an mRNA secretion signal or timing of secretion. The hrpA mRNAs are stable over a wide range of temperatures, in the absence of translating ribosomes and even in the heterologous host Escherichia coli. The untranslated regions (UTRs) of hrpA transcripts from at least 20 pathovars of Pseudomonas syringae are highly homologous, whilst their coding regions exhibit low similarity. The stable nature of hrpA messenger RNAs is likely to be due to the folding of their 5 and 3 UTRs. In silico the UTRs seem to form stem-loop structures, the hairpin structures in the 3 UTRs being rich in guanidine and cytosine residues. The stable nature of the hrpA transcript redirected the studies to the stabilization of heterologous transcripts and to the use of stable messenger RNAs in recombinant protein production. Fragments of the hrpA transcript can be used to confer stability on heterologous transcripts from several sources of bacterial and eukaryotic origin, and to elevate the levels of production of the corresponding recombinant proteins several folds. hrpA transcript stabilizing elements can be used for improving the yields of recombinant proteins even in Escherichia coli, one of the most commonly used industrial protein production hosts.

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Meckel syndrome (MKS, MIM 249000) is a severe developmental disorder that leads to death already in utero or shortly after birth. MKS diagnosis can be established by a careful ultrasound examination already at 11-14 weeks of gestation. The main features of MKS are occipital meningoencephalocele, cystic kidney dysplasia and fibrotic changes of the liver. In addition, polydactyly is frequently reported in the cases. The aim of the study was to characterize the molecular and functional defects in MKS. In this study we were able to identify two major MKS mutations in Finnish population, which cover over 90% of the cases. The first mutation is a 29 bp intronic deletion in the MKS1 gene (c.1483-7_35del) that is found in 70% of the families and the second is a C>T substitution in the coding region of CC2D2A (c.1762C>T), that is found in 20% of the MKS families. Both of these mutations result in abnormal splicing. The discovery of the disease genes has revealed that MKS is caused by primary cilia dysfunction. MKS1 gene has a conserved B9 domain, and it is found in the predicted ciliary proteome. CC2D2A protein is also found in the predicted ciliary proteome and it has a Ca2+ binding domain. The number of genes behind MKS has increased rapidly in the past years and to date, mutations have been identified in five genes (MKS1, TMEM67/MKS3, CEP290/MKS4, RPGRIP1L/MKS5 and CC2D2A/MKS6). Identification of the disease genes mutations has also revealed that MKS is an allelic disorder with other syndromes with overlapping phenotypes. Disorders that are caused by primary cilia dysfunction are collectively known as ciliopathies. Sequence analysis of all the known MKS genes in Finnish and non-Finnish families available to us, where the mutation was still unknown, revealed mutations in 14 out of the 30 families included in the study. When we collected all the reported mutations in MKS genes in different syndromes we could see that there was clearly a genotype-syndrome correlation between the mutations and the syndromes, since the same pair of mutations has never been reported in different syndromes. The basic molecular events behind MKS will not only give us information of this syndrome, but also significant novel information on early fetal development in general.

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Transposable elements, transposons, are discrete DNA segments that are able to move or copy themselves from one locus to another within or between their host genome(s) without a requirement for DNA homology. They are abundant residents in virtually all the genomes studied, for instance, the genomic portion of TEs is approximately 3% in Saccharomyces cerevisiae, 45% in humans, and apparently more than 70% in some plant genomes such as maize and barley. Transposons plays essential role in genome evolution, in lateral transfer of antibiotic resistance genes among bacteria and in life cycle of certain viruses such as HIV-1 and bacteriophage Mu. Despite the diversity of transposable elements they all use a fundamentally similar mechanism called transpositional DNA recombination (transposition) for the movement within and between the genomes of their host organisms. The DNA breakage and joining reactions that underlie their transposition are chemically similar in virtually all known transposition systems. The similarity of the reactions is also reflected in the structure and function of the catalyzing enzymes, transposases and integrases. The transposition reactions take place within the context of a transposition machinery, which can be particularly complex, as in the case of the VLP (virus like particle) machinery of retroelements, which in vivo contains RNA or cDNA and a number of element encoded structural and catalytic proteins. Yet, the minimal core machinery required for transposition comprises a multimer of transposase or integrase proteins and their binding sites at the element DNA ends only. Although the chemistry of DNA transposition is fairly well characterized, the components and function of the transposition machinery have been investigated in detail for only a small group of elements. This work focuses on the identification, characterization, and functional studies of the molecular components of the transposition machineries of BARE-1, Hin-Mu and Mu. For BARE-1 and Hin-Mu transpositional activity has not been shown previously, whereas bacteriophage Mu is a general model of transposition. For BARE-1, which is a retroelement of barley (Hordeum vulgare), the protein and DNA components of the functional VLP machinery were identified from cell extracts. In the case of Hin-Mu, which is a Mu-like prophage in Haemophilus influenzae Rd genome, the components of the core machinery (transposase and its binding sites) were characterized and their functionality was studied by using an in vitro methodology developed for Mu. The function of Mu core machinery was studied for its ability to use various DNA substrates: Hin-Mu end specific DNA substrates and Mu end specific hairpin substrates. The hairpin processing reaction by MuA was characterized in detail. New information was gained of all three machineries. The components or their activity required for functional BARE-1 VLP machinery and retrotransposon life cycle were present in vivo and VLP-like structures could be detected. The Hin-Mu core machinery components were identified and shown to be functional. The components of the Mu and Hin-Mu core machineries were partially interchangeable, reflecting both evolutionary conservation and flexibility within the core machineries. The Mu core machinery displayed surprising flexibility in substrate usage, as it was able to utilize Hin-Mu end specific DNA substrates and to process Mu end DNA hairpin substrates. This flexibility may be evolutionarily and mechanistically important.

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Staphylococcus aureus is one of the most important bacteria that cause disease in humans, and methicillin-resistant S. aureus (MRSA) has become the most commonly identified antibiotic-resistant pathogen in many parts of the world. MRSA rates have been stable for many years in the Nordic countries and the Netherlands with a low MRSA prevalence in Europe, but in the recent decades, MRSA rates have increased in those low-prevalence countries as well. MRSA has been established as a major hospital pathogen, but has also been found increasingly in long-term facilities (LTF) and in communities of persons with no connections to the health-care setting. In Finland, the annual number of MRSA isolates reported to the National Infectious Disease Register (NIDR) has constantly increased, especially outside the Helsinki metropolitan area. Molecular typing has revealed numerous outbreak strains of MRSA, some of which have previously been associated with community acquisition. In this work, data on MRSA cases notified to the NIDR and on MRSA strain types identified with pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and staphylococcal cassette chromosome mec (SCCmec) typing at the National Reference Laboratory (NRL) in Finland from 1997 to 2004 were analyzed. An increasing trend in MRSA incidence in Finland from 1997 to 2004 was shown. In addition, non-multi-drug resistant (NMDR) MRSA isolates, especially those resistant only to methicillin/oxacillin, showed an emerging trend. The predominant MRSA strains changed over time and place, but two internationally spread epidemic strains of MRSA, FIN-16 and FIN-21, were related to the increase detected most recently. Those strains were also one cause of the strikingly increasing invasive MRSA findings. The rise of MRSA strains with SCCmec types IV or V, possible community-acquired MRSA was also detected. With questionnaires, the diagnostic methods used for MRSA identification in Finnish microbiology laboratories and the number of MRSA screening specimens studied were reviewed. Surveys, which focused on the MRSA situation in long-term facilities in 2001 and on the background information of MRSA-positive persons in 2001-2003, were also carried out. The rates of MRSA and screening practices varied widely across geographic regions. Part of the NMDR MRSA strains could remain undetected in some laboratories because of insufficient diagnostic techniques used. The increasing proportion of elderly population carrying MRSA suggests that MRSA is an emerging problem in Finnish long-term facilities. Among the patients, 50% of the specimens were taken on a clinical basis, 43% on a screening basis after exposure to MRSA, 3% on a screening basis because of hospital contact abroad, and 4% for other reasons. In response to an outbreak of MRSA possessing a new genotype that occurred in a health care ward and in an associated nursing home of a small municipality in Northern Finland in autumn 2003, a point-prevalence survey was performed six months later. In the same study, the molecular epidemiology of MRSA and methicillin-sensitive S. aureus (MSSA) strains were also assessed, the results to the national strain collection compared, and the difficulties of MRSA screening with low-level oxacillin-resistant isolates encountered. The original MRSA outbreak in LTF, which consisted of isolates possessing a nationally new PFGE profile (FIN-22) and internationally rare MLST type (ST-27), was confined. Another previously unrecognized MRSA strain was found with additional screening, possibly indicating that current routine MRSA screening methods may be insufficiently sensitive for strains possessing low-level oxacillin resistance. Most of the MSSA strains found were genotypically related to the epidemic MRSA strains, but only a few of them had received the SCCmec element, and all those strains possessed the new SCCmec type V. In the second largest nursing home in Finland, the colonization of S. aureus and MRSA, and the role of screening sites along with broth enrichment culture on the sensitivity to detect S. aureus were studied. Combining the use of enrichment broth and perineal swabbing, in addition to nostrils and skin lesions swabbing, may be an alternative for throat swabs in the nursing home setting, especially when residents are uncooperative. Finally, in order to evaluate adequate phenotypic and genotypic methods needed for reliable laboratory diagnostics of MRSA, oxacillin disk diffusion and MIC tests to the cefoxitin disk diffusion method at both +35°C and +30°C, both with or without an addition of sodium chloride (NaCl) to the Müller Hinton test medium, and in-house PCR to two commercial molecular methods (the GenoType® MRSA test and the EVIGENETM MRSA Detection test) with different bacterial species in addition to S. aureus were compared. The cefoxitin disk diffusion method was superior to that of oxacillin disk diffusion and to the MIC tests in predicting mecA-mediated resistance in S. aureus when incubating at +35°C with or without the addition of NaCl to the test medium. Both the Geno Type® MRSA and EVIGENETM MRSA Detection tests are usable, accurate, cost-effective, and sufficiently fast methods for rapid MRSA confirmation from a pure culture.