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.

Causes développementales dans la variabilité de l'efficacité et de la toxicité des antalgiques en pédiatrie [Developmental causes in variability of efficacy and toxicity of analgesics in pediatrics]

The intensity of pain perception and its sensibility to analgesic drugs is highly variable and unpredictable between individuals. Drug disposition varies during development due to the physiological maturation of enzymatic systems and physiological processes responsible for the absorption, distribution, elimination and effect at the site of action. Many of those developmental variables are not yet clearly defined, but their consideration is important for avoiding potential risks of ineffective or toxic treatment. Implications of those developmental changes for day-to-day clinical practice depend on the age of the child, on the type of drug, on the underlying disease and on the potential co-administration of other chemicals.

The variability of money velocity in a generalized cash-in-advance model

This paper presents a general equilibrium model of money demand wherethe velocity of money changes in response to endogenous fluctuations in the interest rate. The parameter space can be divided into two subsets: one where velocity is constant and equal to one as in cash-in-advance models, and another one where velocity fluctuates as in Baumol (1952). Despite its simplicity, in terms of paramaters to calibrate, the model performs surprisingly well. In particular, it approximates the variability of money velocity observed in the U.S. for the post-war period. The model is then used to analyze the welfare costs of inflation under uncertainty. This application calculates the errors derived from computing the costs of inflation with deterministic models. It turns out that the size of this difference is small, at least for the levels of uncertainty estimated for the U.S. economy.

Aspects of variability in peruvian coastal waters near 9ºS

Estudia la variabilidad de las aguas costerasen dos transectos cerca de los 8 y 10°S

Genetic variability of a population of Aedes aegypti from Paraná, Brazil, using the mitochondrial ND4 gene

Genetic variability of a population of Aedes aegypti from Paraná, Brazil, using the mitochondrial ND4 gene. To analyze the genetic variability of populations of Aedes aegypti, 156 samples were collected from 10 municipalities in the state of Paraná, Brazil. A 311 base pairs (bp) region of the NADH dehydrogenase subunit 4 (ND4) mitochondrial gene was examined. An analysis of this fragment identified eight distinct haplotypes. The mean genetic diversity was high (h = 0.702; p = 0.01556). AMOVA analysis indicated that most of the variation (67%) occurred within populations and the F ST value (0.32996) was highly significant. F ST values were significant in most comparisons among cities. The isolation by distance was not significant (r = -0.1216 and p = 0, 7550), indicating that genetic distance is not related to geographic distance. Neighbor-joining analysis showed two genetically distinct groups within Paraná. The DNA polymorphism and AMOVA data indicate a decreased gene flow in populations from Paraná, which can result in increased vectorial competence.

Spatial and temporal variability of chlorophyll distributions and geostrophic estimates on the Peru shelf at 9°S

Estudio del perfil de la plataforma del Peru a los 9°S. Datos colectados mediante Batfish en zig zag

Comment on recent modeling studies of astrocyte-neuron metabolic interactions.

Recent years have seen a surge in mathematical modeling of the various aspects of neuron-astrocyte interactions, and the field of brain energy metabolism is no exception in that regard. Despite the advent of biophysical models in the field, the long-lasting debate on the role of lactate in brain energy metabolism is still unresolved. Quite the contrary, it has been ported to the world of differential equations. Here, we summarize the present state of this discussion from the modeler's point of view and bring some crucial points to the attention of the non-mathematically proficient reader.

Modeling complex wells with the multi-scale finite-volume method

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.

Variability of resting energy expenditure in healthy volunteers during fasting and continuous enteral feeding.

The magnitude of variability in resting energy expenditure (REE) during the day was assessed in nine healthy young subjects under two nutritional conditions: 1) mixed nutrient (53% carbohydrate, 30% fat, 17% protein) enteral feeding at an energy level corresponding to 1.44 REE; and 2) enteral fasting, with only water allowed. In each subject, six 30-min measurements of REE were performed using indirect calorimetry (hood system) at 90-min intervals from 9 AM to 5 PM. The mean REE and respiratory quotient were significantly (p less than .01) greater during feeding than during fasting (1.08 +/- 0.07 [SEM] vs. 1.00 +/- 0.06 kcal/min and 0.874 +/- 0.007 vs. 0.829 +/- 0.008 kcal/min, respectively). Mean postprandial thermogenesis was 4.9 +/- 0.4% of metabolizable energy administered. The intraindividual variability of REE throughout the day, expressed as the coefficient of variation, ranged from 0.7% to 2.0% in the fasting condition and from 1.2% to 4.1% in the feeding condition. There was no significant difference between the REE measured in the morning and that determined in the afternoon.

Variability of a peripheral dose among various linac geometries for second cancer risk assessment.

Second cancer risk assessment for radiotherapy is controversial due to the large uncertainties of the dose-response relationship. This could be improved by a better assessment of the peripheral doses to healthy organs in future epidemiological studies. In this framework, we developed a simple Monte Carlo (MC) model of the Siemens Primus 6 MV linac for both open and wedged fields that we then validated with dose profiles measured in a water tank up to 30 cm from the central axis. The differences between the measured and calculated doses were comparable to other more complex MC models and never exceeded 50%. We then compared our simple MC model with the peripheral dose profiles of five different linacs with different collimation systems. We found that the peripheral dose between two linacs could differ up to a factor of 9 for small fields (5 × 5 cm(2)) and up to a factor of 10 for wedged fields. Considering that an uncertainty of 50% in dose estimation could be acceptable in the context of risk assessment, the MC model can be used as a generic model for large open fields (≥10 × 10 cm(2)) only. The uncertainties in peripheral doses should be considered in future epidemiological studies when designing the width of the dose bins to stratify the risk as a function of the dose.

Impact of recombination on genetic variability within Staphylococcus aureus clonal complexes.

The population structure of Staphylococcus aureus is generally described as highly clonal and is consequently subdivided into several clonal complexes (CCs). Recent data suggested that recombination might occur more frequently within than among CCs. To test this hypothesis as well as to understand how genetic diversity is created in S. aureus, we analyzed a collection of 182 isolates with MLST and five highly variable core adhesion (ADH) genes. As expected the polymorphism of ADH genes was higher than MLST genes. However both categories of genes showed low within CCs diversity with a dominant haplotype and its single nucleotide variants. Several recombination events were detected but none involved intra-CC recombination. This did not confirm the hypothesis of higher recombination within CCs. Nevertheless, molecular analyses of variance indicated that these few recombination events have a significant impact on the genetic diversity within CCs. In addition, although most ADH genes were under purifying selection, signs of positive selection associated with a recombinant group were detected. These data highlight the importance of recombination on the evolution of the highly clonal S. aureus and suggest that recombination when combined with demographic mechanisms as well as selection might favor the rapid creation of new clonal complexes.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]