SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Expanding molecular modeling and design tools to non-natural sidechains.

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.

Local selection rules that can determine specific pathways of DNA unknotting by type II DNA topoisomerases.

We performed numerical simulations of DNA chains to understand how local geometry of juxtaposed segments in knotted DNA molecules can guide type II DNA topoisomerases to perform very efficient relaxation of DNA knots. We investigated how the various parameters defining the geometry of inter-segmental juxtapositions at sites of inter-segmental passage reactions mediated by type II DNA topoisomerases can affect the topological consequences of these reactions. We confirmed the hypothesis that by recognizing specific geometry of juxtaposed DNA segments in knotted DNA molecules, type II DNA topoisomerases can maintain the steady-state knotting level below the topological equilibrium. In addition, we revealed that a preference for a particular geometry of juxtaposed segments as sites of strand-passage reaction enables type II DNA topoisomerases to select the most efficient pathway of relaxation of complex DNA knots. The analysis of the best selection criteria for efficient relaxation of complex knots revealed that local structures in random configurations of a given knot type statistically behave as analogous local structures in ideal geometric configurations of the corresponding knot type.

Rapid prototyping of compliant human aortic roots for assessment of valved stents.

Adequate in-vitro training in valved stents deployment as well as testing of the latter devices requires compliant real-size models of the human aortic root. The casting methods utilized up to now are multi-step, time consuming and complicated. We pursued a goal of building a flexible 3D model in a single-step procedure. We created a precise 3D CAD model of a human aortic root using previously published anatomical and geometrical data and printed it using a novel rapid prototyping system developed by the Fab@Home project. As a material for 3D fabrication we used common house-hold silicone and afterwards dip-coated several models with dispersion silicone one or two times. To assess the production precision we compared the size of the final product with the CAD model. Compliance of the models was measured and compared with native porcine aortic root. Total fabrication time was 3 h and 20 min. Dip-coating one or two times with dispersion silicone if applied took one or two extra days, respectively. The error in dimensions of non-coated aortic root model compared to the CAD design was <3.0% along X, Y-axes and 4.1% along Z-axis. Compliance of a non-coated model as judged by the changes of radius values in the radial direction by 16.39% is significantly different (P<0.001) from native aortic tissue--23.54% at the pressure of 80-100 mmHg. Rapid prototyping of compliant, life-size anatomical models with the Fab@Home 3D printer is feasible--it is very quick compared to previous casting methods.

Epilepsy meets cancer: when, why, and what to do about it?

The lifetime risk of having epileptic seizures is profoundly increased in patients with cancer: about 20% of all patients with systemic cancer may develop brain metastases. These patients and those with primary brain tumours have a lifetime risk of epilepsy of 20-80%. Moreover, exposure to chemotherapy or radiotherapy to the brain, cancer-related metabolic disturbances, stroke, and infection can provoke seizures. The management of epilepsy in patients with cancer includes diagnosis and treatment of the underlying cerebral pathological changes, secondary prophylaxis with antiepileptic drugs, and limiting of the effect of epilepsy and its treatment on the efficacy and tolerability of anticancer treatments, cognitive function, and quality of life. Because of the concern of drug-drug interactions, the pharmacological approach to epilepsy requires a multidisciplinary approach, specifically in a setting of rapidly increasing choices of agents both to treat cancer and cancer-associated epilepsy.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

The population genetics of clonal and partially clonal diploids.

The consequences of variable rates of clonal reproduction on the population genetics of neutral markers are explored in diploid organisms within a subdivided population (island model). We use both analytical and stochastic simulation approaches. High rates of clonal reproduction will positively affect heterozygosity. As a consequence, nearly twice as many alleles per locus can be maintained and population differentiation estimated as F(ST) value is strongly decreased in purely clonal populations as compared to purely sexual ones. With increasing clonal reproduction, effective population size first slowly increases and then points toward extreme values when the reproductive system tends toward strict clonality. This reflects the fact that polymorphism is protected within individuals due to fixed heterozygosity. Contrarily, genotypic diversity smoothly decreases with increasing rates of clonal reproduction. Asexual populations thus maintain higher genetic diversity at each single locus but a lower number of different genotypes. Mixed clonal/sexual reproduction is nearly indistinguishable from strict sexual reproduction as long as the proportion of clonal reproduction is not strongly predominant for all quantities investigated, except for genotypic diversities (both at individual loci and over multiple loci).

SIMULIT : manuel de l'utilisateur

SIMULIT est un programme permettant la simulation de l'occupation des lits des hôpitaux de soins aigus. La mise en oeuvre de SIMULIT et des programmes annexes requiert de l'utilisateur qu'il sache créer et modifier un fichier à l'aide d'un éditeur, et lancer l'exécution d'un programme sur la machine dont il dispose. Le schéma général de la mise en oeuvre se trouve à l'annexe 1 de ce cahier.

Groupes diagnostiques utilisés sur SIMULIT 13

La nomenclature des diagnostics est celle de la Classification internationale des maladies (9e révision), utilisée par la Statistique médicale VESKA depuis 1980. Les trois premiers chiffres du code ont été utilisés; seul le premier diagnostic a été retenu.

Population consequences of environmental sex reversal.

When sex determination in a species is predominantly genetic but environmentally reversible, exposure to (anthropogenic) changes in the environment can lead to shifts in a population's sex ratio. Such scenarios may be common in many fishes and amphibians, yet their ramifications remain largely unexplored. We used a simple model to study the (short-term) population consequences of environmental sex reversal (ESR). We examined the effects on sex ratios, sex chromosome frequencies, and population growth and persistence after exposure to environmental forces with feminizing or masculinizing tendencies. When environmental feminization was strong, X chromosomes were driven to extinction. Analogously, extinction of normally male-linked genetic factors (e.g., Y chromosomes) was caused by continuous environmental masculinization. Although moderate feminization was beneficial for population growth in the absence of large viability effects, our results suggest that the consequences of ESR are generally negative in terms of population size and the persistence of sex chromosomes. Extreme sex ratios resulting from high rates of ESR also reduced effective population sizes considerably. This may limit any evolutionary response to the deleterious effects of ESR. Our findings suggest that ESR changes population growth and sex ratios in some counter-intuitive ways and can change the predominant factor in sex determination from genetic to fully environmental, often within only a few tens of generations. Populations that lose genetic sex determination may quickly go extinct if the environmental forces that cause sex reversal cease.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

Change in defense mechanisms and coping patterns during the course of 2-year-long psychotherapy and psychoanalysis for recurrent depression: a pilot study of a randomized controlled trial.

Very little research has been conducted so far to study the potential mechanisms of change in long-term active psychological treatments of recurrent depression. The present pilot randomized controlled trial aimed to determine the feasibility of studying the change process occurring in patients during the course of 2-year-long dynamic psychotherapy, psychoanalysis, and cognitive therapy, as compared with clinical management. In total, eight outpatients presenting with recurrent depression, two patients per treatment arm, were included. All patients were randomly assigned to one of the four treatment conditions. Defense mechanisms and coping patterns were assessed using validated observer-rated methodology based on transcribed, semistructured follow-along independent dynamic interviews. The results indicated that, whereas some patients in the active treatments changed on the symptomatic levels, some others remained unchanged during the course of their 2-year-long treatment. However, with regard to potential mechanisms of change in these patients, changes in defense mechanisms and coping patterns were revealed to be important processes over time in successful therapies and, to a lesser extent, in less successful treatments. No change was found either on outcome or on the process measure for the control condition, that is, clinical management. These results are discussed along with previous data comparing change in defense mechanisms and coping during the course of treatments.

Quantification of brain glycogen concentration and turnover through localized 13C NMR of both the C1 and C6 resonances.

We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.

Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.