36 resultados para Ligand-steered Modeling Method
em Université de Lausanne, Switzerland
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Résumé La réalisation d'une seconde ligne de métro (M2) dès 2004, passant dans le centre ville de Lausanne, a été l'opportunité de développer une méthodologie concernant des campagnes microgravimétriques dans un environnement urbain perturbé. Les corrections topographiques prennent une dimension particulière dans un tel milieu, car de nombreux objets non géologiques d'origine anthropogénique comme toutes sortes de sous-sols vides viennent perturber les mesures gravimétriques. Les études de génie civil d'avant projet de ce métro nous ont fournis une quantité importante d'informations cadastrales, notamment sur les contours des bâtiments, sur la position prévue du tube du M2, sur des profondeurs de sous-sol au voisinage du tube, mais aussi sur la géologie rencontré le long du corridor du M2 (issue des données lithologiques de forages géotechniques). La planimétrie des sous-sols a été traitée à l'aide des contours des bâtiments dans un SIG (Système d'Information Géographique), alors qu'une enquête de voisinage fut nécessaire pour mesurer la hauteur des sous-sols. Il a été alors possible, à partir d'un MNT (Modèle Numérique de Terrain) existant sur une grille au mètre, de mettre à jour celui ci avec les vides que représentent ces sous-sols. Les cycles de mesures gravimétriques ont été traités dans des bases de données Ac¬cess, pour permettre un plus grand contrôle des données, une plus grande rapidité de traitement, et une correction de relief rétroactive plus facile, notamment lorsque des mises à jour de la topographie ont lieu durant les travaux. Le quartier Caroline (entre le pont Bessières et la place de l'Ours) a été choisi comme zone d'étude. Le choix s'est porté sur ce quartier du fait que, durant ce travail de thèse, nous avions chronologiquement les phases pré et post creusement du tunnel du M2. Cela nous a permis d'effectuer deux campagnes gravimétriques (avant le creu¬sement durant l'été 2005 et après le creusement durant l'été 2007). Ces réitérations nous ont permis de tester notre modélisation du tunnel. En effet, en comparant les mesures des deux campagnes et la réponse gravifique du modèle du tube discrétisé en prismes rectangulaires, nous avons pu valider notre méthode de modélisation. La modélisation que nous avons développée nous permet de construire avec détail la forme de l'objet considéré avec la possibilité de recouper plusieurs fois des interfaces de terrains géologiques et la surface topographique. Ce type de modélisation peut s'appliquer à toutes constructions anthropogéniques de formes linéaires. Abstract The realization of a second underground (M2) in 2004, in downtown Lausanne, was the opportunity to develop a methodology of microgravity in urban environment. Terrain corrections take on special meaning in such environment. Many non-geologic anthropogenic objects like basements act as perturbation of gravity measurements. Civil engineering provided a large amount of cadastral informations, including out¬lines of buildings, M2 tube position, depths of some basements in the vicinity of the M2 corridor, and also on the geology encountered along the M2 corridor (from the lithological data from boreholes). Geometry of basements was deduced from building outlines in a GIS (Geographic Information System). Field investigation was carried out to measure or estimate heights of basements. A DEM (Digital Elevation Model) of the city of Lausanne is updated from voids of basements. Gravity cycles have been processed in Access database, to enable greater control of data, enhance speed processing, and retroactive terrain correction easier, when update of topographic surface are available. Caroline area (between the bridge Saint-Martin and Place de l'Ours) was chosen as the study area. This area was in particular interest because it was before and after digging in this thesis. This allowed us to conduct two gravity surveys (before excavation during summer 2005 and after excavation during summer 2007). These re-occupations enable us to test our modélisation of the tube. Actually, by comparing the difference of measurements between the both surveys and the gravity response of our model (by rectangular prisms), we were able to validate our modeling. The modeling method we developed allows us to construct detailed shape of an object with possibility to cross land geological interfaces and surface topography. This type of modélisation can be applied to all anthropogenic structures.
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In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.
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The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.
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Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.
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PECUBE is a three-dimensional thermal-kinematic code capable of solving the heat production-diffusion-advection equation under a temporally varying surface boundary condition. It was initially developed to assess the effects of time-varying surface topography (relief) on low-temperature thermochronological datasets. Thermochronometric ages are predicted by tracking the time-temperature histories of rock-particles ending up at the surface and by combining these with various age-prediction models. In the decade since its inception, the PECUBE code has been under continuous development as its use became wider and addressed different tectonic-geomorphic problems. This paper describes several major recent improvements in the code, including its integration with an inverse-modeling package based on the Neighborhood Algorithm, the incorporation of fault-controlled kinematics, several different ways to address topographic and drainage change through time, the ability to predict subsurface (tunnel or borehole) data, prediction of detrital thermochronology data and a method to compare these with observations, and the coupling with landscape-evolution (or surface-process) models. Each new development is described together with one or several applications, so that the reader and potential user can clearly assess and make use of the capabilities of PECUBE. We end with describing some developments that are currently underway or should take place in the foreseeable future. (C) 2012 Elsevier B.V. All rights reserved.
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The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.
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We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism.
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Purpose: Mutations in the ligand-binding domain (LBD) of NR2E3 cause recessively inherited enhanced short wavelength sensitive (S-) cone syndrome (ESCS), Goldmann-Favre syndrome (GFS) and clumped pigmentary retinal degeneration (CPRD). In addition to ligand binding, the LBD contains also essential amino acid sequences for the oligomerization of nuclear receptors. The aim of our studies is to characterize the impact of mutations in the LBD on receptor oligomerization and transcriptional activity of NR2E3. Methods: The different NR2E3 mutants were generated by QuickChange mutagenesis and analyzed in 293T-based transactivation studies and BRET2 (bioluminescence resonance electron transfer) assays. In silico homology modeling of mutant proteins was also performed using available crystallographic data of related nuclear receptors. Results: The mutants p.W234S, p.A256V, p.A256E, p.L263P, p.R309G, p.R311Q, p.R334G, p.L336P, p.L353V, p.R385P and p.M407K, all located in the LBD, showed impaired receptor dimerization at various degrees. Impaired repressor dimerization as assessed by BRET2 assays did not always correlate with impaired repressor function of NR2E3 as assessed by cell-based reporter assays. There were minor differences of transcriptional activity of mutant proteins on mouse S-opsin (opn1sw), mouse cone arrestin (arr3) and human cone arrestin, suggesting that the effect of LBD mutations was independent of the promoter context. Conclusions: Mutational analysis and homology modeling allowed the characterization of potential oligomerization interfaces of the NR2E3 LBD. Additionally, mutations in NR2E3 LBD may cause recessive retinal degenerations by different molecular mechanisms.
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To study the interaction of T cell receptor with its ligand, a complex of a major histocompatibility complex molecule and a peptide, we derived H-2Kd-restricted cytolytic T lymphocyte clones from mice immunized with a Plasmodium berghei circumsporozoite peptide (PbCS) 252-260 (SYIPSAEKI) derivative containing photoreactive Nepsilon-[4-azidobenzoyl] lysine in place of Pro-255. This residue and Lys-259 were essential parts of the epitope recognized by these clones. Most of the clones expressed BV1S1A1 encoded beta chains along with specific complementary determining region (CDR) 3beta regions but diverse alpha chain sequences. Surprisingly, all T cell receptors were preferentially photoaffinity labeled on the alpha chain. For a representative T cell receptor, the photoaffinity labeled site was located in the Valpha C-strand. Computer modeling suggested the presence of a hydrophobic pocket, which is formed by parts of the Valpha/Jalpha C-, F-, and G-strands and adjacent CDR3alpha residues and structured to be able to avidly bind the photoreactive ligand side chain. We previously found that a T cell receptor specific for a PbCS peptide derivative containing this photoreactive side chain in position 259 similarly used a hydrophobic pocket located between the junctional CDR3 loops. We propose that this nonpolar domain in these locations allow T cell receptors to avidly and specifically bind epitopes containing non-peptidic side chains.
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To study the interaction of the TCR with its ligand, the complex of a MHC molecule and an antigenic peptide, we modified a TCR contact residue of a H-2Kd-restricted antigenic peptide with photoreactive 4-azidobenzoic acid. The photoreactive group was a critical component of the epitope recognized by CTL clones derived from mice immunized with such a peptide derivative. The majority of these clones expressed V beta 1-encoded beta chains that were paired with J alpha TA28-encoded alpha chains. For one of these TCR, the photoaffinity labeled sites were mapped on the alpha chain as a J alpha TA28-encoded tryptophan and on the beta chain as a residue of the C' strand of V beta 1. Molecular modeling of this TCR suggested the presence of a hydrophobic pocket that harbors this tryptophan as well as a tyrosine on the C' strand of V beta 1 between which the photoreactive side chain inserts. It is concluded that this avid binding principle may account for the preferential selection of V beta 1 and J alpha TA28-encoded TCR.
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PURPOSE: Aerodynamic drag plays an important role in performance for athletes practicing sports that involve high-velocity motions. In giant slalom, the skier is continuously changing his/her body posture, and this affects the energy dissipated in aerodynamic drag. It is therefore important to quantify this energy to understand the dynamic behavior of the skier. The aims of this study were to model the aerodynamic drag of alpine skiers in giant slalom simulated conditions and to apply these models in a field experiment to estimate energy dissipated through aerodynamic drag. METHODS: The aerodynamic characteristics of 15 recreational male and female skiers were measured in a wind tunnel while holding nine different skiing-specific postures. The drag and the frontal area were recorded simultaneously for each posture. Four generalized and two individualized models of the drag coefficient were built, using different sets of parameters. These models were subsequently applied in a field study designed to compare the aerodynamic energy losses between a dynamic and a compact skiing technique. RESULTS: The generalized models estimated aerodynamic drag with an accuracy of between 11.00% and 14.28%, and the individualized models estimated aerodynamic drag with an accuracy between 4.52% and 5.30%. The individualized model used for the field study showed that using a dynamic technique led to 10% more aerodynamic drag energy loss than using a compact technique. DISCUSSION: The individualized models were capable of discriminating different techniques performed by advanced skiers and seemed more accurate than the generalized models. The models presented here offer a simple yet accurate method to estimate the aerodynamic drag acting upon alpine skiers while rapidly moving through the range of positions typical to turning technique.
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We implemented Biot-type porous wave equations in a pseudo-spectral numerical modeling algorithm for the simulation of Stoneley waves in porous media. Fourier and Chebyshev methods are used to compute the spatial derivatives along the horizontal and vertical directions, respectively. To prevent from overly short time steps due to the small grid spacing at the top and bottom of the model as a consequence of the Chebyshev operator, the mesh is stretched in the vertical direction. As a large benefit, the Chebyshev operator allows for an explicit treatment of interfaces. Boundary conditions can be implemented with a characteristics approach. The characteristic variables are evaluated at zero viscosity. We use this approach to model seismic wave propagation at the interface between a fluid and a porous medium. Each medium is represented by a different mesh and the two meshes are connected through the above described characteristics domain-decomposition method. We show an experiment for sealed pore boundary conditions, where we first compare the numerical solution to an analytical solution. We then show the influence of heterogeneity and viscosity of the pore fluid on the propagation of the Stoneley wave and surface waves in general.
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We present a novel numerical approach for the comprehensive, flexible, and accurate simulation of poro-elastic wave propagation in 2D polar coordinates. An important application of this method and its extensions will be the modeling of complex seismic wave phenomena in fluid-filled boreholes, which represents a major, and as of yet largely unresolved, computational problem in exploration geophysics. In view of this, we consider a numerical mesh, which can be arbitrarily heterogeneous, consisting of two or more concentric rings representing the fluid in the center and the surrounding porous medium. The spatial discretization is based on a Chebyshev expansion in the radial direction and a Fourier expansion in the azimuthal direction and a Runge-Kutta integration scheme for the time evolution. A domain decomposition method is used to match the fluid-solid boundary conditions based on the method of characteristics. This multi-domain approach allows for significant reductions of the number of grid points in the azimuthal direction for the inner grid domain and thus for corresponding increases of the time step and enhancements of computational efficiency. The viability and accuracy of the proposed method has been rigorously tested and verified through comparisons with analytical solutions as well as with the results obtained with a corresponding, previously published, and independently bench-marked solution for 2D Cartesian coordinates. Finally, the proposed numerical solution also satisfies the reciprocity theorem, which indicates that the inherent singularity associated with the origin of the polar coordinate system is adequately handled.
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The activation of the specific immune response against tumor cells is based on the recognition by the CD8+ Cytotoxic Τ Lymphocytes (CTL), of antigenic peptides (p) presented at the surface of the cell by the class I major histocompatibility complex (MHC). The ability of the so-called T-Cell Receptors (TCR) to discriminate between self and non-self peptides constitutes the most important specific control mechanism against infected cells. The TCR/pMHC interaction has been the subject of much attention in cancer therapy since the design of the adoptive transfer approach, in which Τ lymphocytes presenting an interesting response against tumor cells are extracted from the patient, expanded in vitro, and reinfused after immunodepletion, possibly leading to cancer regression. In the last decade, major progress has been achieved by the introduction of engineered lypmhocytes. In the meantime, the understanding of the molecular aspects of the TCRpMHC interaction has become essential to guide in vitro and in vivo studies. In 1996, the determination of the first structure of a TCRpMHC complex by X-ray crystallography revealed the molecular basis of the interaction. Since then, molecular modeling techniques have taken advantage of crystal structures to study the conformational space of the complex, and understand the specificity of the recognition of the pMHC by the TCR. In the meantime, experimental techniques used to determine the sequences of TCR that bind to a pMHC complex have been used intensively, leading to the collection of large repertoires of TCR sequences that are specific for a given pMHC. There is a growing need for computational approaches capable of predicting the molecular interactions that occur upon TCR/pMHC binding without relying on the time consuming resolution of a crystal structure. This work presents new approaches to analyze the molecular principles that govern the recognition of the pMHC by the TCR and the subsequent activation of the T-cell. We first introduce TCRep 3D, a new method to model and study the structural properties of TCR repertoires, based on homology and ab initio modeling. We discuss the methodology in details, and demonstrate that it outperforms state of the art modeling methods in predicting relevant TCR conformations. Two successful applications of TCRep 3D that supported experimental studies on TCR repertoires are presented. Second, we present a rigid body study of TCRpMHC complexes that gives a fair insight on the TCR approach towards pMHC. We show that the binding mode of the TCR is correctly described by long-distance interactions. Finally, the last section is dedicated to a detailed analysis of an experimental hydrogen exchange study, which suggests that some regions of the constant domain of the TCR are subject to conformational changes upon binding to the pMHC. We propose a hypothesis of the structural signaling of TCR molecules leading to the activation of the T-cell. It is based on the analysis of correlated motions in the TCRpMHC structure. - L'activation de la réponse immunitaire spécifique dirigée contre les cellules tumorales est basée sur la reconnaissance par les Lymphocytes Τ Cytotoxiques (CTL), d'un peptide antigénique (p) présenté à la suface de la cellule par le complexe majeur d'histocompatibilité de classe I (MHC). La capacité des récepteurs des lymphocytes (TCR) à distinguer les peptides endogènes des peptides étrangers constitue le mécanisme de contrôle le plus important dirigé contre les cellules infectées. L'interaction entre le TCR et le pMHC est le sujet de beaucoup d'attention dans la thérapie du cancer, depuis la conception de la méthode de transfer adoptif: les lymphocytes capables d'une réponse importante contre les cellules tumorales sont extraits du patient, amplifiés in vitro, et réintroduits après immunosuppression. Il peut en résulter une régression du cancer. Ces dix dernières années, d'importants progrès ont été réalisés grâce à l'introduction de lymphocytes modifiés par génie génétique. En parallèle, la compréhension du TCRpMHC au niveau moléculaire est donc devenue essentielle pour soutenir les études in vitro et in vivo. En 1996, l'obtention de la première structure du complexe TCRpMHC à l'aide de la cristallographie par rayons X a révélé les bases moléculaires de l'interaction. Depuis lors, les techniques de modélisation moléculaire ont exploité les structures expérimentales pour comprendre la spécificité de la reconnaissance du pMHC par le TCR. Dans le même temps, de nouvelles techniques expérimentales permettant de déterminer la séquence de TCR spécifiques envers un pMHC donné, ont été largement exploitées. Ainsi, d'importants répertoires de TCR sont devenus disponibles, et il est plus que jamais nécessaire de développer des approches informatiques capables de prédire les interactions moléculaires qui ont lieu lors de la liaison du TCR au pMHC, et ce sans dépendre systématiquement de la résolution d'une structure cristalline. Ce mémoire présente une nouvelle approche pour analyser les principes moléculaires régissant la reconnaissance du pMHC par le TCR, et l'activation du lymphocyte qui en résulte. Dans un premier temps, nous présentons TCRep 3D, une nouvelle méthode basée sur les modélisations par homologie et ab initio, pour l'étude de propriétés structurales des répertoires de TCR. Le procédé est discuté en détails et comparé à des approches standard. Nous démontrons ainsi que TCRep 3D est le plus performant pour prédire des conformations pertinentes du TCR. Deux applications à des études expérimentales des répertoires TCR sont ensuite présentées. Dans la seconde partie de ce travail nous présentons une étude de complexes TCRpMHC qui donne un aperçu intéressant du mécanisme d'approche du pMHC par le TCR. Finalement, la dernière section se concentre sur l'analyse détaillée d'une étude expérimentale basée sur les échanges deuterium/hydrogène, dont les résultats révèlent que certaines régions clés du domaine constant du TCR sont sujettes à un changement conformationnel lors de la liaison au pMHC. Nous proposons une hypothèse pour la signalisation structurelle des TCR, menant à l'activation du lymphocyte. Celle-ci est basée sur l'analyse des mouvements corrélés observés dans la structure du TCRpMHC.
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Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.