907 resultados para secondary structure detection
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DNA microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design probes with high specificities, i.e. uniqueness, and also sensitivities, i.e., suitable melting temperature and no secondary structure. We make use of available biology tools to gain necessary sequence information of human chromosome 12, and combined with evolutionary strategy (ES) to find unique subsequences representing all predicted exons. The results are presented and discussed.
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Human CD81 (hCD81) protein has been recombinantly produced in the methylotrophic yeast Pichia pastoris. The purified protein, produced at a yield of 1.75 mg/L of culture, was shown to interact with Hepatitis C virus E2 glycoprotein. Immunofluorescent and flow cytometric staining of P. pastoris protoplasts with monoclonal antibodies specific for the second extracellular loop (EC2) of hCD81 confirmed the antigenicity of the recombinant molecule. Full-length hCD81 was solubilized with an array of detergents and subsequently characterized using circular dichroism (CD) and analytical ultracentrifugation. These biophysical techniques confirmed that the protein solution comprises a homogenous species possessing a highly-defined alpha-helical secondary structure. The predicted alpha-helical content of the protein from CD analysis (77.1%) fits remarkably well with what would be expected (75.2%) from knowledge of the protein sequence together with the data from the crystal structure of the second extracellular loop. This study represents the first biophysical characterization of a full-length recombinant tetraspanin, and opens the way for structure-activity analyses of this ubiquitous family of transmembrane proteins.
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The objective of the work described was to identify and synthesize a range of biodegradable hypercoiling or hydrophobically associating polymers to mimic natural apoproteins, such as those found in lung surfactant or plasma apolipoproteins. Stirred interfacial polymerization was used to synthesize potentially biodegradable aromatic polyamides (Mw of 12,000-26,000) based on L-Iysine, L-Iysine ethyl ester, L-ornithine and DL-diaminopropionic acid, by reaction with isophthaloyl chloride. A similar technique was used to synthesize aliphatic polyamides based on L-Iysine ethyl ester and either adipoyl chloride or glutaryl chloride resulting in the synthesis of poly(lysine ethyl ester adipamide) [PLETESA] or poly(lysine ethyl ester glutaramide) (Mw of 126,000 and 26,000, respectively). PLETESA was found to be soluble in both polar and non-polar solvents and the hydrophobic/hydrophilic balance could be modified by partial saponification (66-75%) of the ethyl ester side chains. Surface or interfacial tension/pH profiles were used to assess the conformation of both the poly(isophthalamides) and partially saponified PLETESA in aqueous solution. The results demonstrated that a loss of charge from the polymer was accompanied by an initial fall in surface activity, followed by a rise in activity, and ultimately, by polymer precipitation. These observations were explained by a collapse of the polymer chains into non-surface active intramolecular coils, followed by a transition to an amphipathic conformation, and finally to a collapsed hydrophobe. 2-Dimensional NMR analysis of polymer conformation in polar and non-polar solvents revealed intramolecular associations between the hydrophobic groups within partially saponified PLETESA. Unsaponified PLETESA appeared to form a coiled structure in polar solvents where the ethyl ester side chains were contained within the polymer coil. The implications of the secondary structure of PLETESA and potential biomedical applications are discussed.
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Background. The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. Results. We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). Conclusions. The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate µ at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of µ, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks. © 2010 Stich et al; licensee BioMed Central Ltd.
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G-protein coupled receptors (GPCRs) constitute the largest class of membrane proteins and are a major drug target. A serious obstacle to studying GPCR structure/function characteristics is the requirement to extract the receptors from their native environment in the plasma membrane, coupled with the inherent instability of GPCRs in the detergents required for their solubilization. In the present study, we report the first solubilization and purification of a functional GPCR [human adenosine A
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Over the years, many reviews of different aspects of diatom biology, ecology and evolution have appeared. Since 1993 many molecular trees have been produced to infer diatom phylogeny. In 2004, Medlin & Kaczmarska revised the systematics of the diatoms based on more than 20 years of consistent recovery of two major clades of diatoms that did not correspond to a traditional concept of centrics and pennates and established three classes of diatoms: Clade 1 = Coscinodiscophyceae (radial centrics) and Clade 2 = Mediophyceae (polar centrics + radial Thalassiosirales) and Bacillariophyceae (pennates). However, under certain analytical conditions, an alternative view of diatom evolution, a grades of clades, has been recovered that suggests a gradual evolution from centric to pennate symmetry. These two schemes of diatom evolution are evaluated in terms of whether or not the criteria advocated by Medlin & Kaczmarska that should be met to recover monophyletic classes have been used. The monophyly of the three diatom classes can only be achieved if (1) a secondary structure of the small subunit (SSU) rRNA gene was used to construct the alignment and not an alignment based on primary structure and (2) multiple outgroups were used. These requirements have not been met in each study of diatom evolution; hence, the grade of clades, which is useful in reconstructing the sequence of evolution, is not useful for accepting the new classification of the diatoms. Evidence for how these two factors affect the recovery of the three monophyletic classes is reviewed here. The three classes have been defined by clear morphological differences primarily based on gametangia and auxospore ontogeny and envelope structure, the presence or absence of a structure (tube process or sternum) associated with the annulus and the location of the cribrum in those genera with loculate areolae. New evidence supporting the three clades is reviewed. Other features of the cell are examined to determine whether they can also be used to support the monophyly of the three classes.
Resumo:
Over the years, many reviews of different aspects of diatom biology, ecology and evolution have appeared. Since 1993 many molecular trees have been produced to infer diatom phylogeny. In 2004, Medlin & Kaczmarska revised the systematics of the diatoms based on more than 20 years of consistent recovery of two major clades of diatoms that did not correspond to a traditional concept of centrics and pennates and established three classes of diatoms: Clade 1 = Coscinodiscophyceae (radial centrics) and Clade 2 = Mediophyceae (polar centrics + radial Thalassiosirales) and Bacillariophyceae (pennates). However, under certain analytical conditions, an alternative view of diatom evolution, a grades of clades, has been recovered that suggests a gradual evolution from centric to pennate symmetry. These two schemes of diatom evolution are evaluated in terms of whether or not the criteria advocated by Medlin & Kaczmarska that should be met to recover monophyletic classes have been used. The monophyly of the three diatom classes can only be achieved if (1) a secondary structure of the small subunit (SSU) rRNA gene was used to construct the alignment and not an alignment based on primary structure and (2) multiple outgroups were used. These requirements have not been met in each study of diatom evolution; hence, the grade of clades, which is useful in reconstructing the sequence of evolution, is not useful for accepting the new classification of the diatoms. Evidence for how these two factors affect the recovery of the three monophyletic classes is reviewed here. The three classes have been defined by clear morphological differences primarily based on gametangia and auxospore ontogeny and envelope structure, the presence or absence of a structure (tube process or sternum) associated with the annulus and the location of the cribrum in those genera with loculate areolae. New evidence supporting the three clades is reviewed. Other features of the cell are examined to determine whether they can also be used to support the monophyly of the three classes.
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ABSTRACT. – Phylogenies and molecular clocks of the diatoms have largely been inferred from SSU rDNA sequences. A new phylogeny of diatoms was estimated using four gene markers SSU and LSU rDNA rbcL and psbA (total 4352 bp) with 42 diatom species. The four gene trees analysed with a maximum likelihood (ML) and Baysian (BI) analysis recovered a monophyletic origin of the new diatom classes with high bootstrap support, which has been controversial with single gene markers using single outgroups and alignments that do not take secondary structure of the SSU gene into account. The divergence time of the classes were calculated from a ML tree in the MultliDiv Time program using a Bayesian estimation allowing for simultaneous constraints from the fossil record and varying rates of molecular evolution of different branches in the phylogenetic tree. These divergence times are generally in agreement with those proposed by other clocks using single genes with the exception that the pennates appear much earlier and suggest a longer Cretaceous fossil record that has yet to be sampled. Ghost lineages (i.e. the discrepancy between first appearance (FA) and molecular clock age of origin from an extant taxon) were revealed in the pennate lineage, whereas those ghost lineages in the centric lineages previously reported by others are reviewed and referred to earlier literature.
Resumo:
ABSTRACT. – Phylogenies and molecular clocks of the diatoms have largely been inferred from SSU rDNA sequences. A new phylogeny of diatoms was estimated using four gene markers SSU and LSU rDNA rbcL and psbA (total 4352 bp) with 42 diatom species. The four gene trees analysed with a maximum likelihood (ML) and Baysian (BI) analysis recovered a monophyletic origin of the new diatom classes with high bootstrap support, which has been controversial with single gene markers using single outgroups and alignments that do not take secondary structure of the SSU gene into account. The divergence time of the classes were calculated from a ML tree in the MultliDiv Time program using a Bayesian estimation allowing for simultaneous constraints from the fossil record and varying rates of molecular evolution of different branches in the phylogenetic tree. These divergence times are generally in agreement with those proposed by other clocks using single genes with the exception that the pennates appear much earlier and suggest a longer Cretaceous fossil record that has yet to be sampled. Ghost lineages (i.e. the discrepancy between first appearance (FA) and molecular clock age of origin from an extant taxon) were revealed in the pennate lineage, whereas those ghost lineages in the centric lineages previously reported by others are reviewed and referred to earlier literature.
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Functionalized diphenylalkynes provide a template for the presentation of protein-like surfaces composed of multistrand β-sheets. The conformational properties of three-, four-, and seven-stranded systems have been investigated in the solid- and solution-state. This class of molecule may be suitable for the mediation of therapeutically relevant protein-protein interactions.
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The protein folding problem has been one of the most challenging subjects in biological physics due to its complexity. Energy landscape theory based on statistical mechanics provides a thermodynamic interpretation of the protein folding process. We have been working to answer fundamental questions about protein-protein and protein-water interactions, which are very important for describing the energy landscape surface of proteins correctly. At first, we present a new method for computing protein-protein interaction potentials of solvated proteins directly from SAXS data. An ensemble of proteins was modeled by Metropolis Monte Carlo and Molecular Dynamics simulations, and the global X-ray scattering of the whole model ensemble was computed at each snapshot of the simulation. The interaction potential model was optimized and iterated by a Levenberg-Marquardt algorithm. Secondly, we report that terahertz spectroscopy directly probes hydration dynamics around proteins and determines the size of the dynamical hydration shell. We also present the sequence and pH-dependence of the hydration shell and the effect of the hydrophobicity. On the other hand, kinetic terahertz absorption (KITA) spectroscopy is introduced to study the refolding kinetics of ubiquitin and its mutants. KITA results are compared to small angle X-ray scattering, tryptophan fluorescence, and circular dichroism results. We propose that KITA monitors the rearrangement of hydrogen bonding during secondary structure formation. Finally, we present development of the automated single molecule operating system (ASMOS) for a high throughput single molecule detector, which levitates a single protein molecule in a 10 µm diameter droplet by the laser guidance. I also have performed supporting calculations and simulations with my own program codes.
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Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.
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Phosphorylation is amongst the most crucial and well-studied post-translational modifications. It is involved in multiple cellular processes which makes phosphorylation prediction vital for understanding protein functions. However, wet-lab techniques are labour and time intensive. Thus, computational tools are required for efficiency. This project aims to provide a novel way to predict phosphorylation sites from protein sequences by adding flexibility and Sezerman Grouping amino acid similarity measure to previous methods, as discovering new protein sequences happens at a greater rate than determining protein structures. The predictor – NOPAY - relies on Support Vector Machines (SVMs) for classification. The features include amino acid encoding, amino acid grouping, predicted secondary structure, predicted protein disorder, predicted protein flexibility, solvent accessibility, hydrophobicity and volume. As a result, we have managed to improve phosphorylation prediction accuracy for Homo sapiens by 3% and 6.1% for Mus musculus. Sensitivity at 99% specificity was also increased by 6% for Homo sapiens and for Mus musculus by 5% on independent test sets. In this study, we have managed to increase phosphorylation prediction accuracy for Homo sapiens and Mus musculus. When there is enough data, future versions of the software may also be able to predict other organisms.
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Turnip crinkle virus (TCV) and Pea enation mosaic virus (PEMV) are two positive (+)-strand RNA viruses that are used to investigate the regulation of translation and replication due to their small size and simple genomes. Both viruses contain cap-independent translation elements (CITEs) within their 3´ untranslated regions (UTRs) that fold into tRNA-shaped structures (TSS) according to nuclear magnetic resonance and small angle x-ray scattering analysis (TCV) and computational prediction (PEMV). Specifically, the TCV TSS can directly associate with ribosomes and participates in RNA-dependent RNA polymerase (RdRp) binding. The PEMV kissing-loop TSS (kl-TSS) can simultaneously bind to ribosomes and associate with the 5´ UTR of the viral genome. Mutational analysis and chemical structure probing methods provide great insight into the function and secondary structure of the two 3´ CITEs. However, lack of 3-D structural information has limited our understanding of their functional dynamics. Here, I report the folding dynamics for the TCV TSS using optical tweezers (OT), a single molecule technique. My study of the unfolding/folding pathways for the TCV TSS has provided an unexpected unfolding pathway, confirmed the presence of Ψ3 and hairpin elements, and suggested an interconnection between the hairpins and pseudoknots. In addition, this study has demonstrated the importance of the adjacent upstream adenylate-rich sequence for the formation of H4a/Ψ3 along with the contribution of magnesium to the stability of the TCV TSS. In my second project, I report on the structural analysis of the PEMV kl-TSS using NMR and SAXS. This study has re-confirmed the base-pair pattern for the PEMV kl-TSS and the proposed interaction of the PEMV kl-TSS with its interacting partner, hairpin 5H2. The molecular envelope of the kl-TSS built from SAXS analysis suggests the kl-TSS has two functional conformations, one of which has a different shape from the previously predicted tRNA-shaped form. Along with applying biophysical methods to study the structural folding dynamics of RNAs, I have also developed a technique that improves the production of large quantities of recombinant RNAs in vivo for NMR study. In this project, I report using the wild-type and mutant E.coli strains to produce cost-effective, site-specific labeled, recombinant RNAs. This technique was validated with four representative RNAs of different sizes and complexity to produce milligram amounts of RNAs. The benefit of using site-specific labeled RNAs made from E.coli was demonstrated with several NMR techniques.
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Wydział Biologii: Instytut Biologii Molekularnej i Biotechnologii