Monte Carlo studies of N-methylformamide-dimethyl sulfoxide mixtures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monte Carlo thermodynamic and structural properties of the TIP4P water model: dependence on the computational conditions

Classical Monte Carlo simulations were carried out on the NPT ensemble at 25°C and 1 atm, aiming to investigate the ability of the TIP4P water model [Jorgensen, Chandrasekhar, Madura, Impey and Klein; J. Chem. Phys., 79 (1983) 926] to reproduce the newest structural picture of liquid water. The results were compared with recent neutron diffraction data [Soper; Bruni and Ricci; J. Chem. Phys., 106 (1997) 247]. The influence of the computational conditions on the thermodynamic and structural results obtained with this model was also analyzed. The findings were compared with the original ones from Jorgensen et al [above-cited reference plus Mol. Phys., 56 (1985) 1381]. It is notice that the thermodynamic results are dependent on the boundary conditions used, whereas the usual radial distribution functions g(O/O(r)) and g(O/H(r)) do not depend on them.

Efeitos da transformação de uma variável com distribuição normal em sua inversa sobre os parâmetros de sua distribuição usando técnicas de Monte Carlo

Foram realizados quatro estudos de simulação para verificar a distribuição de inversas de variáveis com distribuição normal, em função de diferentes variâncias, médias, pontos de truncamentos e tamanhos amostrais. As variáveis simuladas foram GMD, com distribuição normal, representando o ganho médio diário e DIAS, obtido a partir da inversa de GMD, representando dias para se obter determinado peso. em todos os estudos, foi utilizado o sistema SAS® (1990) para simulação dos dados e para posterior análise dos resultados. As médias amostrais de DIAS foram dependentes dos desvios-padrão utilizados na simulação. As análises de regressão mostraram redução da média e do desvio-padrão de DIAS em função do aumento na média de GMD. A inclusão de um ponto de truncamento entre 10 e 25% do valor da média de GMD reduziu a média de GMD e aumentou a de DIAS, quando o coeficiente de variação de GMD foi superior a 25%. O efeito do tamanho dos grupos nas médias de GMD e DIAS não foi significativo, mas o desvio-padrão e CV amostrais médios de GMD aumentaram com o tamanho do grupo. em virtude da dependência entre a média e o desvio-padrão e da variação observada nos desvios-padrão de DIAS em função do tamanho do grupo, a utilização de DIAS como critério de seleção pode diminuir a acurácia da variação. Portanto, para a substituição de GMD por DIAS, é necessária a utilização de um método de análise robusto o suficiente para a eliminação da heterogeneidade de variância.

Protein-Ion Binding Process on Finite Macromolecular Concentration. A Poisson-Boltzmann and Monte Carlo Study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Percolation of Monte Carlo clusters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monte Carlo renormalization group with evolution in the space of parameters

Using data from a single simulation we obtain Monte Carlo renormalization-group information in a finite region of parameter space by adapting the Ferrenberg-Swendsen histogram method. Several quantities are calculated in the two-dimensional N 2 Ashkin-Teller and Ising models to show the feasibility of the method. We show renormalization-group Hamiltonian flows and critical-point location by matching of correlations by doing just two simulations at a single temperature in lattices of different sizes to partially eliminate finite-size effects.

C-H center dot center dot center dot O and N-H center dot center dot center dot O hydrogen bonds in liquid amides investigated by Monte Carlo simulation

Monte Carlo simulations of liquid formamide, N-methylformamide (MF), and N,N-dimethylformamide (DMF) have been performed in the isothermal and isobaric ensemble at 298 K and 1 atm, aiming to investigate the C-H ... O and N-H ... O hydrogen bonds. The interaction energy was calculated using the classical 6-12 Lennard-Jones pairwise potential plus a Coulomb term on a rigid six-site molecular model with the potential parameters being optimized in this work. Theoretical values obtained for heat of vaporization and liquid densities are in good agreement with the experimental data. The radial distribution function [RDF, g(r)] obtained compare well with R-X diffraction data available. The RDF and molecular mechanics (MM2) minimization show that the C-H ... O interaction has a significant role in the structure of the three liquids. These results are supported by ab initio calculations. This Interaction is particularly important in the structure of MF. The intensity of the N-H ... O hydrogen bond is greater in the MF than formamide. This could explain some anomalous properties verified in MF. (C) 1997 John Wiley & Sons, Inc.

Monte Carlo and modified Tanford-Kirkwood results for macromolecular electrostatics calculations

The understanding of electrostatic interactions is an essential aspect of the complex correlation between structure and function of biological macromolecules. It is also important in protein engineering and design. Theoretical studies of such interactions are predominantly done within the framework of Debye-Huckel theory. A classical example is the Tanford-Kirkwood (TK) model. Besides other limitations, this model assumes an infinitesimally small macromolecule concentration. By comparison to Monte Carlo (MC) simulations, it is shown that TK predictions for the shifts in ion binding constants upon addition of salt become less reliable even at moderately macromolecular concentrations. A simple modification based on colloidal literature is suggested to the TK scheme. The modified TK models suggested here satisfactorily predict MC and experimental shifts in the calcium binding constant as a function of protein concentration for the calbindin D-9k mutant and calmodulin.

A critical investigation of the Tanford-Kirkwood scheme by means of Monte Carlo simulations

Monte Carlo simulations are used to assess the adequacy of the Tanford-Kirkwood prescription for electrostatic interactions in macromolecules. Within a continuum dielectric framework, the approach accurately describes salt screening of electrostatic interactions for moderately charged systems consistent with common proteins at physiological conditions. The limitations of the Debye-Huckel theory, which forms the statistical mechanical basis for the Tanford-Kirkwood result, become apparent for highly charged systems. It is shown, both by an analysis of the Debye-Huckel theory and by numerical simulations, that the difference in dielectric permittivity between macromolecule and surrounding solvent does not play a significant role for salt effects if the macromolecule is highly charged. By comparison to experimental data, the continuum dielectric model (combined with either an approximate effective Hamiltonian as in the Tanford-Kirkwood treatment or with exact Monte Carlo simulations) satisfactorily predicts the effects of charge mutation on metal ion binding constants, but only if the macromolecule and solvent are assigned the same or similar permittivities.

Economic design of two-stage (X)over-bar charts: the Markov chain approach

When the (X) over bar chart is in use, samples are regularly taken from the process, and their means are plotted on the chart. In some cases, it is too expensive to obtain the X values, but not the values of a correlated variable Y. This paper presents a model for the economic design of a two-stage control chart, that is. a control chart based on both performance (X) and surrogate (Y) variables. The process is monitored by the surrogate variable until it signals an out-of-control behavior, and then a switch is made to the (X) over bar chart. The (X) over bar chart is built with central, warning. and action regions. If an X sample mean falls in the central region, the process surveillance returns to the (Y) over bar chart. Otherwise. The process remains under the (X) over bar chart's surveillance until an (X) over bar sample mean falls outside the control limits. The search for an assignable cause is undertaken when the performance variable signals an out-of-control behavior. In this way, the two variables, are used in an alternating fashion. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A study is performed to examine the economic advantages of using performance and surrogate variables. (C) 2003 Elsevier B.V. All rights reserved.

Application of a new reverse Monte Carlo algorithm to polyatomic molecular systems. I. Liquid water

Using a new reverse Monte Carlo algorithm, we present simulations that reproduce very well several structural and thermodynamic properties of liquid water. Both Monte Carlo, molecular dynamics simulations and experimental radial distribution functions used as input are accurately reproduced using a small number of molecules and no external constraints. Ad hoc energy and hydrogen bond analysis show the physical consistency and limitations of the generated RMC configurations. (C) 2001 American Institute of Physics.

Economic design of (X)over-bar charts with variable parameters: the Markov chain approach

This paper presents an economic design of (X) over bar control charts with variable sample sizes, variable sampling intervals, and variable control limits. The sample size n, the sampling interval h, and the control limit coefficient k vary between minimum and maximum values, tightening or relaxing the control. The control is relaxed when an (X) over bar value falls close to the target and is tightened when an (X) over bar value falls far from the target. A cost model is constructed that involves the cost of false alarms, the cost of finding and eliminating the assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A comprehensive study is performed to examine the economic advantages of varying the (X) over bar chart parameters.