396 research outputs found

    Molecular Dynamics of the Hammerhead Ribozyme

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    CarbBuilder: an adjustable tool for building 3D molecular structures of carbohydrates for molecular simulation.

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    CarbBuilder is a software tool for building 3D structures of carbohydrates, which are the most structurally varied of all molecular classes. CarbBuilder was designed with the dual aims of portability and adaptability, using an iterative software development approach. CarbBuilder employs a simple algorithm, using heuristics based upon experimental data to con- vert a primary structure description of a carbohydrate molecule into a three-dimensional structure file. This straightforward approach means that CarbBuilder can be easily adapted: users can add additional monosaccharide building blocks or alter the conformational defaults to suit specific requirements. The output carbohydrate structure can be used for subsequent molecular simulation investigations. CarbBuilder is freely available and portable: it is a text-based stand-alone program that can run on Windows, Linux and MacOS X systems without installation

    Curation of viral genomes: challenges, applications and the way forward

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    BACKGROUND: Whole genome sequence data is a step towards generating the 'parts list' of life to understand the underlying principles of Biocomplexity. Genome sequencing initiatives of human and model organisms are targeted efforts towards understanding principles of evolution with an application envisaged to improve human health. These efforts culminated in the development of dedicated resources. Whereas a large number of viral genomes have been sequenced by groups or individuals with an interest to study antigenic variation amongst strains and species. These independent efforts enabled viruses to attain the status of 'best-represented taxa' with the highest number of genomes. However, due to lack of concerted efforts, viral genomic sequences merely remained as entries in the public repositories until recently. RESULTS: VirGen is a curated resource of viral genomes and their analyses. Since its first release, it has grown both in terms of coverage of viral families and development of new modules for annotation and analysis. The current release (2.0) includes data for twenty-five families with broad host range as against eight in the first release. The taxonomic description of viruses in VirGen is in accordance with the ICTV nomenclature. A well-characterised strain is identified as a 'representative entry' for every viral species. This non-redundant dataset is used for subsequent annotation and analyses using sequenced-based Bioinformatics approaches. VirGen archives precomputed data on genome and proteome comparisons. A new data module that provides structures of viral proteins available in PDB has been incorporated recently. One of the unique features of VirGen is predicted conformational and sequential epitopes of known antigenic proteins using in-house developed algorithms, a step towards reverse vaccinology. CONCLUSION: Structured organization of genomic data facilitates use of data mining tools, which provides opportunities for knowledge discovery. One of the approaches to achieve this goal is to carry out functional annotations using comparative genomics. VirGen, a comprehensive viral genome resource that serves as an annotation and analysis pipeline has been developed for the curation of public domain viral genome data . Various steps in the curation and annotation of the genomic data and applications of the value-added derived data are substantiated with case studies

    Geometric modeling, simulation, and visualization methods for plasmid DNA molecules

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    Plasmid DNA molecules are a special type of DNA molecules that are used, among other applications, in DNA vaccination and gene therapy. These molecules are characterized by, when in their natural state, presenting a closed-circular conformation and by being supercoiled. The production of plasmid DNA using bacteria as hosts implies a purification step where the plasmid DNA molecules are separated from the DNA of the host and other contaminants. This purification process, and all the physical and chemical variations involved, such as temperature changes, may affect the plasmid DNA molecules conformation by uncoiling or even by open them, which makes them useless for therapeutic applications. Because of that, researchers are always searching for new purification techniques that maximize the amount of supercoiled plasmid DNA that is produced. Computer simulations and 3D visualization of plasmid DNA can bring many advantages because they allow researchers to actually see what can happen to the molecules under certain conditions. In this sense, it was necessary to develop reliable and accurate geometric models specific for plasmid DNA simulations. This dissertation presents a new assembling algorithm for B-DNA specifically developed for plasmid DNA assembling. This new assembling algorithm is completely adaptive in the sense that it allows researchers to assemble any plasmid DNA base-pair sequence along any arbitrary conformation that fits the length of the plasmid DNA molecule. This is specially suitable for plasmid DNA simulations, where conformations are generated by simulation procedures and there is the need to assemble the given base-pair sequence over that conformation, what can not be done by conventional predictive DNA assembling methods. Unlike traditional molecular visualization methods that are based on the atomic structure, this new assembling algorithm uses color coded 3D molecular surfaces of the nucleotides as the building blocks for DNA assembling. This new approach, not only reduces the amount of graphical objects and, consequently, makes the rendering faster, but also makes it easier to visually identify the nucleotides in the DNA strands. The algorithm used to triangulate the molecular surfaces of the nucleotides building blocks is also a novelty presented as part of this dissertation. This new triangulation algorithm for Gaussian molecular surfaces introduces a new mechanism that divides the atomic structure of molecules into boxes and spheres. This new space division method is faster because it confines the local calculation of the molecular surface to a specific region of influence of the atomic structure, not taking into account atoms that do not influence the triangulation of the molecular surface in that region. This new method also guarantees the continuity of the molecular surface. Having in mind that the aim of this dissertation is to present a complete set of methods for plasmid DNA visualization and simulation, it is also proposed a new deformation algorithm to be used for plasmid DNA Monte Carlo simulations. This new deformation algorithm uses a 3D polyline to represent the plasmid DNA conformation and performs small deformations on that polyline, keeping the segments length and connectivity. Experiments have been performed in order to compare this new deformation method with deformation methods traditionally used by Monte Carlo plasmid DNA simulations These experiments shown that the new method is more efficient in the sense that its trial acceptance ratio is higher and it converges sooner and faster to the elastic energy equilibrium state of the plasmid DNA molecule. In sum, this dissertation successfully presents an end-to-end set of models and algorithms for plasmid DNA geometric modelling, visualization and simulation

    Minimal model for the secondary structures and conformational conversions in proteins

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    Better understanding of protein folding process can provide physical insights on the function of proteins and makes it possible to benefit from genetic information accumulated so far. Protein folding process normally takes place in less than seconds but even seconds are beyond reach of current computational power for simulations on a system of all-atom detail. Hence, to model and explore protein folding process it is crucial to construct a proper model that can adequately describe the physical process and mechanism for the relevant time scale. We discuss the reduced off-lattice model that can express α-helix and β-hairpin conformations defined solely by a given sequence in order to investigate a protein folding mechanism of conformations such as a β-hairpin and also to investigate conformational conversions in proteins. The first two chapters introduce and review essential concepts in protein folding modelling physical interaction in proteins, various simple models, and also review computational methods, in particular, the Metropolis Monte Carlo method, its dynamic interpretation and thermodynamic Monte Carlo algorithms. Chapter 3 describes the minimalist model that represents both α-helix and β-sheet conformations using simple potentials. The native conformation can be specified by the sequence without particular conformational biases to a reference state. In Chapter 4, the model is used to investigate the folding mechanism of β-hairpins exhaustively using the dynamic Monte Carlo and a thermodynamic Monte Carlo method an effcient combination of the multicanonical Monte Carlo and the weighted histogram analysis method. We show that the major folding pathways and folding rate depend on the location of a hydrophobic. The conformational conversions between α-helix and β-sheet conformations are examined in Chapter 5 and 6. First, the conformational conversion due to mutation in a non-hydrophobic system and then the conformational conversion due to mutation with a hydrophobic pair at a different position at various temperatures are examined

    Understanding protein structure-function relationships in Family 47 α-1,2-mannosidases through computational docking of ligands

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    Family 47 [Alpha]-1,2-mannosidases are crucial enzymes involved in N-glycan maturation in the endoplasmic reticulum (ER) and the Golgi apparatus of eukaryotic cells. They have also been implicated in playing a role in the quality control of newly synthesized proteins in the ER, by indirectly supplying the signal necessary for targeting misfolded proteins for degradation. High-resolution crystal structures of the human and yeast ER [Alpha]-1,2-mannosidases have been recently determined by others. In the crystal structure of the yeast enzyme, the N-glycan from one molecule extends into the active-site cavity of the adjacent symmetry-related molecule, forming what is believed to be the enzyme-substrate complex. However, due to the absence in the crystal structure of the terminal mannosyl residue that is cleaved by the enzyme, it has not been possible to unambiguously identify the catalytic proton donor and the nucleophile involved in the glycoside bond hydrolysis. The human [Alpha]-1,2-mannosidase crystal structure was determined by others in complex with inhibitors 1-deoxy-mannojirimycin and kifunensine, both of which bind in the active site in the unusual 1C4 conformation. In this work, [Alpha]-galactose, [Alpha]-glucose, and [Alpha]-mannose were docked in the active site in the energetically stable 4C1 conformation as well as in the 1C4 conformation to compare the energetics of interaction. From these docked structures, a model for substrate selectivity and conformer selectivity based on the dimensions of the active site was proposed. Specifically, the proposal was that the opening of the active-site neck is too narrow for the flatter and more extended 4C1 conformation to enter the-1 site of the catalytic domain, while the more compact 1C4 conformation can enter this site. [Alpha]-D-Galactopyranosyl-(l[Right pointing arrow]2)-[Alpha]-D-mannopyranose, [Alpha]-D-glucopyranosyl-(1Right pointing arrow]2)-[Alpha]-D-mannopyranose, and [Alpha]-D-mannopyranosyl-(1[Right pointing arrow]2)-[Alpha]-D-mannopyranose were also docked into the active site with the nonreducing-end residue in the 1C4 and E4 (representing the transition state) conformations. The results of these docking runs clearly show how this enzyme achieves transition-state stabilization. Based on the docked structure of [Alpha]-D-mannopyranosyl-E4-(1[Right pointing arrow]2)-[Alpha]-D-mannopyranose, the catalytic acid and base are Glu132 and Glu435, respectively

    Ensemble-Based Virtual Screening Reveals Potential Novel Antiviral Compounds for Avian Influenza Neuraminidase

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    Avian influenza virus subtype H5N1 is a potential pandemic threat with human-adapted strains resistant to antiviral drugs. Although virtual screening (VS) against a crystal or relaxed receptor structure is an established method to identify potential inhibitors, the more dynamic changes within binding sites are neglected. To accommodate full receptor flexibility, we use AutoDock4 to screen the NCI diversity set against representative receptor ensembles extracted from explicitly solvated molecular dynamics simulations of the neuraminidase system. The top hits are redocked to the entire nonredundant receptor ensemble and rescored using the relaxed complex scheme (RCS). Of the 27 top hits reported, half ranked very poorly if only crystal structures are used. These compounds target the catalytic cavity as well as the newly identified 150- and 430-cavities, which exhibit dynamic properties in electrostatic surface and geometric shape. This ensemble-based VS and RCS approach may offer improvement over existing strategies for structure-based drug discovery

    Structural aspects of molecular recognition

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    This thesis describes the design, implementation and application of a novel docking algorithm. Chapter 1 reviews some important facts about proteins and protein structure. Several molecular recognition systems are examined in detail. This Chapter also reviews a representative set of recent protein/protein docking methods and discusses their relative merits. Chapter 2 sets out the aims of the new docking algorithm, called DAPMatch, and gives full details of its implementation on a parallel architecture computer. The testing of the algorithm is also discussed. Subsequent chapters describe the application of the DAPMatch algorithm to a number of docking problems. DAPMatch is used to reconstruct the known structures of three antibody/lysozyme complexes, using the unbound structure of lysozyme. For the first time a model of the D1.3 antibody is used as a target molecule for a docking algorithm. These results are presented in Chapter 3 and analysed in detail to demonstrate their significance; non-native solutions are also examined. Chapter 4 describes the practical use of the DAPMatch algorithm in a modelling situation, to construct a hypothetical structure for the high molecular weight epidermal growth factor complex. Chapter 5 describes the adaptation of the DAPMatch algorithm to investigate α-helix/α-helix docking, and presents the results obtained. Chapter 6 explains the conclusions that were derived from this work, and suggests possible future enhancements to the algorithm

    Infrared Spectroscopy

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    This informative and state-of-the-art book on Infrared Spectroscopy is addressed to Researchers in Medicine as well as to Pharmaceutical Industry and Agriculture. It features 7 specialized chapters of MIRS and NIRS covering applications in proteins and biopolymers; food quality research and food safety applications; and medical applications, such as Down syndrome disorders of tooth, probing of brain oxygen, the role of CO2 in blood pressure and diagnosis of metastatic cancer. This book highlights the span of modern Infrared applications
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