scholarly journals Biomolecular Simulations under Realistic Macroscopic Salt Conditions

2017 ◽  
Author(s):  
Gregory A. Ross ◽  
Ariën S. Rustenburg ◽  
Patrick B. Grinaway ◽  
Josh Fass ◽  
John D. Chodera
Keyword(s):  
Monte Carlo ◽  
Salt Concentration ◽  
Aqueous Environment ◽  
Average Deviation ◽  
Large Reservoir ◽  
Monovalent Ions ◽  
Order Of Magnitude ◽  
Biomolecular Simulations ◽  
Acceptance Rates ◽  
Dna Dodecamer

AbstractBiomolecular simulations are typically performed in an aqueous environment where the number of ions remains fixed for the duration of the simulation, generally with either a minimally neutralizing ion environment or a number of salt pairs intended to match the macroscopic salt concentration. In contrast, real biomolecules experience local ion environments where the salt concentration is dynamic and may differ from bulk. The degree of salt concentration variability and average deviation from the macroscopic concentration remains, as yet, unknown. Here, we describe the theory and implementation of a Monte Carloosmostatthat can be added to explicit solvent molecular dynamics or Monte Carlo simulations to sample from a semigrand canonical ensemble in which the number of salt pairs fluctuates dynamically during the simulation. The osmostat reproduce the correct equilibrium statistics for a simulation volume that can exchange ions with a large reservoir at a defined macroscopic salt concentration. To achieve useful Monte Carlo acceptance rates, the method makes use of nonequilibrium candidate Monte Carlo (NCMC) moves in which monovalent ions and water molecules are alchemically transmuted using short nonequilibrium trajectories, with a modified Metropolis-Hastings criterion ensuring correct equilibrium statistics for an (Δµ, N, p, T) ensemble. We demonstrate how typical protein (DHFR and the tyrosine kinase Src) and nucleic acid (Drew-Dickerson B-DNA dodecamer) systems exhibit salt concentration distributions that significantly differ from fixed-salt bulk simulations and display fluctuations that are on the same order of magnitude as the average.

scholarly journals SOC program for dust continuum radiative transfer

2019 ◽  
Vol 622 ◽  
pp. A79 ◽  
Author(s):  
Mika Juvela
Keyword(s):  
Monte Carlo ◽  
Radiative Transfer ◽  
Convergence Rates ◽  
Dust Emission ◽  
Interstellar Clouds ◽  
Physical Conditions ◽  
Cloud Models ◽  
Order Of Magnitude ◽  
Speed Up ◽  
Run Time

Context. Thermal dust emission carries information on physical conditions and dust properties in many astronomical sources. Because observations represent a sum of emission along the line of sight, their interpretation often requires radiative transfer (RT) modelling. Aims. We describe a new RT program, SOC, for computations of dust emission, and examine its performance in simulations of interstellar clouds with external and internal heating. Methods. SOC implements the Monte Carlo RT method as a parallel program for shared-memory computers. It can be used to study dust extinction, scattering, and emission. We tested SOC with realistic cloud models and examined the convergence and noise of the dust-temperature estimates and of the resulting surface-brightness maps. Results. SOC has been demonstrated to produce accurate estimates for dust scattering and for thermal dust emission. It performs well with both CPUs and GPUs, the latter providing a speed-up of processing time by up to an order of magnitude. In the test cases, accelerated lambda iterations (ALIs) improved the convergence rates but was also sensitive to Monte Carlo noise. Run-time refinement of the hierarchical-grid models did not help in reducing the run times required for a given accuracy of solution. The use of a reference field, without ALI, works more robustly, and also allows the run time to be optimised if the number of photon packages is increased only as the iterations progress. Conclusions. The use of GPUs in RT computations should be investigated further.

scholarly journals On the chemical diversity of the prebiotic ocean of early Earth

2014 ◽  
Vol 14 (3) ◽  
pp. 497-504
Author(s):  
Carlo Canepa
Keyword(s):  
Amino Acid ◽  
Average Length ◽  
Chemical Species ◽  
Catalytic Efficiency ◽  
Chemical Diversity ◽  
Aqueous Environment ◽  
Amino Acid Residues ◽  
Catalytically Active ◽  
Order Of Magnitude ◽  
The Mean

AbstractThis work investigates the consequences on the diverse number of chemical species in a pre-biotic terrestrial aqueous environment endowed with an amino acid source induced by the spontaneous build-up of catalytically active polypeptides from amino acid monomers. The assumed probability that a randomly formed polypeptide exhibits catalytic properties is dependent on constraining both the chemical identity and the position of a fraction of the amino acid residues. Within this hypothesis, and using values of the average length n of the catalytic polypeptides about one half of the present-day enzymes, the stationary-state concentration of the catalytically active polypeptides is ≈10−30 −10−19 M, and the ratio of the concentration of a product of a catalytic process to the initial concentration of the corresponding substrate is predicted to be ≈10−6−105. Matching the mean life of each catalytic polypeptide to the mean life of its substrate (λ ≈ ω) is only possible by significantly raising the intensity of the source of the amino acid monomers. Under these hypothetical optimal conditions, the mean lives of the catalytic polypeptides and their substrates have values ω−1 ≈ λ−1 ≈10 yr and the asymptotic concentration of each product is of the same order of magnitude as the concentration of the substrate. In all cases the catalytic efficiency necessary to form the active peptides takes the typical values of present-day enzymes.

scholarly journals Salt-Induced Swelling and Volume Phase Transition of Polyelectrolyte Gels

2017 ◽  
Vol 84 (5) ◽  
Author(s):  
Yalin Yu ◽  
Chad M. Landis ◽  
Rui Huang
Keyword(s):  
Phase Transitions ◽  
Salt Concentration ◽  
Volume Fraction ◽  
External Solution ◽  
Quantitative Agreement ◽  
Continuous Transition ◽  
Volume Phase ◽  
Polyelectrolyte Gels ◽  
Monovalent Ions ◽  
Polymer Solvent

A theoretical model of polyelectrolyte gels is presented to study continuous and discontinuous volume phase transitions induced by changing salt concentration in the external solution. Phase diagrams are constructed in terms of the polymer–solvent interaction parameters, external salt concentration, and concentration of fixed charges. Comparisons with previous experiments for an ionized acrylamide gel in mixed water–acetone solvents are made with good quantitative agreement for a monovalent salt (NaCl) but fair qualitative agreement for a divalent salt (MgCl2), using a simple set of parameters for both cases. The effective polymer–solvent interactions vary with the volume fraction of acetone in the mixed solvent, leading to either continuous or discontinuous volume transitions. The presence of divalent ions (Mg2+) in addition to monovalent ions in the external solution reduces the critical salt concentration for the discontinuous transition by several orders of magnitude. Moreover, a secondary continuous transition is predicted between two highly swollen states for the case of a divalent salt. The present model may be further extended to study volume phase transitions of polyelectrolyte gels in response to other stimuli such as temperature, pH and electrical field.

scholarly journals Swelling of ionic microgel particles in the presence of excluded-volume interactions: a density functional approach

2016 ◽  
Vol 18 (7) ◽  
pp. 5372-5385 ◽  
Author(s):  
Arturo Moncho-Jordá ◽  
Joachim Dzubiella
Keyword(s):  
Density Functional Theory ◽  
Salt Concentration ◽  
Density Functional ◽  
Functional Approach ◽  
Excluded Volume ◽  
Local Concentration ◽  
Functional Theory ◽  
Monovalent Ions ◽  
Microgel Particles ◽  
Theory Framework

In this work a new density functional theory framework is developed to predict the salt-concentration dependent swelling state of charged microgels and the local concentration of monovalent ions inside and outside the microgel.

The Monte Carlo Independent Column Approximation’s Conditional Random Noise: Impact on Simulated Climate

2005 ◽  
Vol 18 (22) ◽  
pp. 4715-4730 ◽  
Author(s):  
P. Räisänen ◽  
H. W. Barker ◽  
J. N. S. Cole
Keyword(s):  
Monte Carlo ◽  
Global Climate ◽  
Random Noise ◽  
Radiative Heating ◽  
Time Interval ◽  
Additional Time ◽  
Time Step ◽  
Order Of Magnitude ◽  
Independent Column ◽  
The Impact

Abstract The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. Results for five experiments are used to assess the impact of McICA-related noise on simulations of global climate made by the NCAR Community Atmosphere Model (CAM). The experiment with the least noise (an order of magnitude below that of basic McICA) is taken as the reference. Two additional experiments help demonstrate how the impact of noise depends on the time interval between calls to the radiation code. Each experiment is an ensemble of seven 15-month simulations. Experiments with very high noise levels feature significant reductions to cloudiness in the lowermost model layer over tropical oceans as well as changes in highly related quantities. This bias appears immediately, stabilizes after a couple of model days, and appears to stem from nonlinear interactions between clouds and radiative heating. Outside the Tropics, insignificant differences prevail. When McICA sampling is confined to cloudy subcolumns and when, on average, 50% more samples, relative to basic McICA, are drawn for selected spectral intervals, McICA noise is much reduced and the results of the simulation are almost statistically indistinguishable from the reference. This is true both for mean fields and for the nature of fluctuations on scales ranging from 1 day to at least 30 days. While calling the radiation code once every 3 h instead of every hour allows the CAM additional time to incorporate McICA-related noise, the impact of noise is enhanced only slightly. In contrast, changing the radiative time step by itself produces effects that generally exceed the impact of McICA’s noise.

scholarly journals Diffusion of CH4 in amorphous solid water

2020 ◽  
Vol 643 ◽  
pp. A163
Author(s):  
Belén Maté ◽  
Stéphanie Cazaux ◽  
Miguel Ángel Satorre ◽  
Germán Molpeceres ◽  
Juan Ortigoso ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Diffusion Coefficients ◽  
Amorphous Solid ◽  
Amorphous Solid Water ◽  
Water Ice ◽  
Cometary Material ◽  
Order Of Magnitude ◽  
Diffusion Rates ◽  
Solid Water

Context. The diffusion of volatile species on amorphous solid water ice affects the chemistry on dust grains in the interstellar medium as well as the trapping of gases enriching planetary atmospheres or present in cometary material. Aims. The aim of the work is to provide diffusion coefficients of CH4 on amorphous solid water (ASW) and to understand how they are affected by the ASW structure. Methods. Ice mixtures of H2O and CH4 were grown in different conditions and the sublimation of CH4 was monitored via infrared spectroscopy or via the mass loss of a cryogenic quartz crystal microbalance. Diffusion coefficients were obtained from the experimental data assuming the systems obey Fick’s law of diffusion. Monte Carlo simulations were used to model the different amorphous solid water ice structures investigated and were used to reproduce and interpret the experimental results. Results. Diffusion coefficients of methane on amorphous solid water have been measured to be between 10−12 and 10−13 cm2 s−1 for temperatures ranging between 42 K and 60 K. We show that diffusion can differ by one order of magnitude depending on the morphology of amorphous solid water. The porosity within water ice and the network created by pore coalescence enhance the diffusion of species within the pores. The diffusion rates derived experimentally cannot be used in our Monte Carlo simulations to reproduce the measurements. Conclusions. We conclude that Fick’s laws can be used to describe diffusion at the macroscopic scale, while Monte Carlo simulations describe the microscopic scale where trapping of species in the ices (and their movement) is considered.

scholarly journals Squeeze-and-breathe evolutionary Monte Carlo optimization with local search acceleration and its application to parameter fitting

2012 ◽  
Vol 9 (73) ◽  
pp. 1925-1933 ◽  
Author(s):  
Mariano Beguerisse-Díaz ◽  
Baojun Wang ◽  
Radhika Desikan ◽  
Mauricio Barahona
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
A Priori ◽  
Monte Carlo Optimization ◽  
Parameter Fitting ◽  
Search Optimization ◽  
Order Of Magnitude ◽  
Complex Optimization ◽  
Real Experimental Data ◽  
Modelling Process

Estimating parameters from data is a key stage of the modelling process, particularly in biological systems where many parameters need to be estimated from sparse and noisy datasets. Over the years, a variety of heuristics have been proposed to solve this complex optimization problem, with good results in some cases yet with limitations in the biological setting. In this work, we develop an algorithm for model parameter fitting that combines ideas from evolutionary algorithms, sequential Monte Carlo and direct search optimization. Our method performs well even when the order of magnitude and/or the range of the parameters is unknown. The method refines iteratively a sequence of parameter distributions through local optimization combined with partial resampling from a historical prior defined over the support of all previous iterations. We exemplify our method with biological models using both simulated and real experimental data and estimate the parameters efficiently even in the absence of a priori knowledge about the parameters.

The diameter of the DNA superhelix decreases with salt concentration: SANS measurements and Monte Carlo simulations

2000 ◽  
Vol 33 (3) ◽  
pp. 526-529 ◽  
Author(s):  
M. Hammermann ◽  
N. Brun ◽  
K.V. Klenin ◽  
R. P. May ◽  
K. Tóth ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Salt Concentration
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