934 resultados para Computer Simulation


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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

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In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.

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A new type of high avidity binding molecule, termed "peptabody" was created by harnessing the effect of multivalent interaction. A short peptide ligand was fused via a semi-rigid hinge region with the coiled-coil assembly domain of the cartilage oligomeric matrix protein, resulting in a pentameric multivalent binding molecule. In the first peptabody (Pab-S) described here, a peptide (S) specific for the mouse B-cell lymphoma BCL1 surface Ig idiotype, was selected from a phage display library. A fusion gene was constructed encoding peptide S, followed by the 24 aa hinge region from camel IgG and a modified 55 aa cartilage oligomeric matrix protein pentamerization domain. The Pab-S fusion protein was expressed in Escherichia coli in a soluble form at high levels and purified in a single step by metal-affinity chromatography. Pab-S specifically bound the BCL1 surface idiotype with an avidity of about 1 nM, which corresponds to a 2 x 10(5)-fold increase compared with the affinity of the synthetic peptide S itself. Biochemical characterization showed that Pab-S is a stable homopentamer of about 85 kDa, with interchain disulfide bonds. Pab-S can be dissociated under denaturing and reducing conditions and reassociated as a pentamer with full-binding activity. This intrinsic feature provides an easy way to combine Pab molecules with two different peptide specificities, thus producing heteropentamers with bispecific and/or chelating properties.

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Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.

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In mammography, the image contrast and dose delivered to the patient are determined by the x-ray spectrum and the scatter to primary ratio S/P. Thus the quality of the mammographic procedure is highly dependent on the choice of anode and filter material and on the method used to reduce the amount of scattered radiation reaching the detector. Synchrotron radiation is a useful tool to study the effect of beam energy on the optimization of the mammographic process because it delivers a high flux of monochromatic photons. Moreover, because the beam is naturally flat collimated in one direction, a slot can be used instead of a grid for scatter reduction. We have measured the ratio S/P and the transmission factors for grids and slots for monoenergetic synchrotron radiation. In this way the effect of beam energy and scatter rejection method were separated, and their respective importance for image quality and dose analyzed. Our results show that conventional mammographic spectra are not far from optimum and that the use of a slot instead of a grid has an important effect on the optimization of the mammographic process. We propose a simple numerical model to quantify this effect.

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Pallido-pyramidal syndromes combine dystonia with or without parkinsonism and spasticity as part of a mixed neurodegenerative disorder. Several causative genes have been shown to lead to pallido-pyramidal syndromes, including FBXO7, ATP13A2, PLA2G6, PRKN and SPG11. Among these, ATP13A2 and PLA2G6 are inconsistently associated with brain iron deposition. Using homozygosity mapping and direct sequencing in a multiplex consanguineous Saudi Arabian family with a pallido-pyramidal syndrome, iron deposition and cerebellar atrophy, we identified a homozygous p.G53R mutation in C19orf12. Our findings add to the phenotypic spectrum associated with C19orf12 mutations.

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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

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How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

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Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

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Ami, ou ennemi, le soleil ? Qui n'a jamais maudit un petit excès de bain de soleil sanctionné par une peau brûlée ? Mais en hiver, quand il se fait rare, l'huile de foie de morue est la panacée que prescrit la sagesse de nos grands-mères pour remplacer la vitamine D qu'en temps normal il nous aide à synthétiser. Pour pouvoir faire le point sur les dangers et les bénéfices du rayonnement solaire, il faut connaître son intensité et en particulier celle du rayonnement ultraviolet (UV) qui a une forte influence sur la santé.Durant ces dernières décades, une forte augmentation des cancers de la peau a été constatée dans les pays développés. La communauté médicale suppose que cette augmentation est liée à une plus forte exposition aux UV, qui serait elle-même due à des changements d'habitudes de la population (engouement pour les loisirs en plein air, pour les vacances sous les tropiques, popularité du bronzage, etc.) et éventuellement à un accroissement du rayonnement UV. [Auteurs]

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We present a novel and straightforward method for estimating recent migration rates between discrete populations using multilocus genotype data. The approach builds upon a two-step sampling design, where individual genotypes are sampled before and after dispersal. We develop a model that estimates all pairwise backwards migration rates (m(ij), the probability that an individual sampled in population i is a migrant from population j) between a set of populations. The method is validated with simulated data and compared with the methods of BayesAss and Structure. First, we use data for an island model and then we consider more realistic data simulations for a metapopulation of the greater white-toothed shrew (Crocidura russula). We show that the precision and bias of estimates primarily depend upon the proportion of individuals sampled in each population. Weak sampling designs may particularly affect the quality of the coverage provided by 95% highest posterior density intervals. We further show that it is relatively insensitive to the number of loci sampled and the overall strength of genetic structure. The method can easily be extended and makes fewer assumptions about the underlying demographic and genetic processes than currently available methods. It allows backwards migration rates to be estimated across a wide range of realistic conditions.

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We present an agent-based model with the aim of studying how macro-level dynamics of spatial distances among interacting individuals in a closed space emerge from micro-level dyadic and local interactions. Our agents moved on a lattice (referred to as a room) using a model implemented in a computer program called P-Space in order to minimize their dissatisfaction, defined as a function of the discrepancy between the real distance and the ideal, or desired, distance between agents. Ideal distances evolved in accordance with the agent's personal and social space, which changed throughout the dynamics of the interactions among the agents. In the first set of simulations we studied the effects of the parameters of the function that generated ideal distances, and in a second set we explored how group macrolevel behavior depended on model parameters and other variables. We learned that certain parameter values yielded consistent patterns in the agents' personal and social spaces, which in turn led to avoidance and approaching behaviors in the agents. We also found that the spatial behavior of the group of agents as a whole was influenced by the values of the model parameters, as well as by other variables such as the number of agents. Our work demonstrates that the bottom-up approach is a useful way of explaining macro-level spatial behavior. The proposed model is also shown to be a powerful tool for simulating the spatial behavior of groups of interacting individuals.

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The Iowa Department of Transportation has been using the Bureau of Public Roads (BPR) Roughometer as part of its detour analysis process for more than 20 years. Advances in technology have made the BPR Roughometer obsolete for ride quality testing. High-speed profilers that can collect the profile of the road at highway speeds are the standard ride instruments for determining ride quality on pavements. The objective of the project was to develop a correlation between the BPR Roughometer and the high-speed laser South Dakota type Profiler (SD Profiler). Nineteen pavement sections were chosen to represent the range of types and conditions for detours. Three computer simulation models were tested on the profiler profiles. The first model is the International Ride Index (IRI) which is considered the standard index for reporting ride quality in the United States. The second model is the Ride Number (RN) developed by the University of Michigan Transportation Research Institute and the third model used is a quarter-car simulation of the BPR Roughometer (ASTM E-1170) which should match the speed and range of roadway features experienced by Iowa's BPR Roughometer Unit. The BPR Roughometer quarter-car model provided the best overall correlation with Iowa's BPR Roughometer.

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FGFR1 mutations have been identified in both Kallmann syndrome and normosmic HH (nIHH). To date, few mutations in the FGFR1 gene have been structurally or functionally characterized in vitro to identify molecular mechanisms that contribute to the disease pathogenesis. We attempted to define the in vitro functionality of two FGFR1 mutants (R254W and R254Q), resulting from two different amino acid substitutions of the same residue, and to correlate the in vitro findings to the patient phenotypes. Two unrelated GnRH deficient probands were found to harbor mutations in FGFR1 (R254W and R254Q). Mutant signaling activity and expression levels were evaluated in vitro and compared to a wild type (WT) receptor. Signaling activity was determined by a FGF2/FGFR1 dependent transcription reporter assay. Receptor total expression levels were assessed by Western blot and cell surface expression was measured by a radiolabeled antibody binding assay. The R254W maximal receptor signaling capacity was reduced by 45% (p<0.01) while R254Q activity was not different from WT. However, both mutants displayed diminished total protein expression levels (40 and 30% reduction relative to WT, respectively), while protein maturation was unaffected. Accordingly, cell surface expression levels of the mutant receptors were also significantly reduced (35% p<0.01 and 15% p<0.05, respectively). The p.R254W and p.R254Q are both loss-of-function mutations as demonstrated by their reduced overall and cell surface expression levels suggesting a deleterious effect on receptor folding and stability. It appears that a tryptophan substitution at R254 is more disruptive to receptor structure than the more conserved glutamine substitution. No clear correlation between the severity of in vitro loss-of-function and phenotypic presentation could be assigned.

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We analyze the short-time dynamical behavior of a colloidal suspension in a confined geometry. We analyze the relevant dynamical response of the solvent, and derive the temporal behavior of the velocity autocorrelation function, which exhibits an asymptotic negative algebraic decay. We are able to compare quantitatively with theoretical expressions, and analyze the effects of confinement on the diffusive behavior of the suspension.