Towards a model of non-equilibrium binding of a metal ion in a biological system

We have used a systems biology approach to address the hitherto insoluble problem of the quantitative analysis of non-equilibrium binding of aqueous metal ions by competitive ligands in heterogeneous media. To-date, the relative proportions of different metal complexes in aqueous media have only been modelled at chemical equilibrium and there are no quantitative analyses of the approach to equilibrium1. While these models have improved our understanding of how metals are used in biological systems they cannot account for the influence of kinetic factors in metal binding, transport and fate2. Here we have modelled the binding of aluminium in blood serum by the iron transport protein transferrin (Tf) as it is widely accepted that the biological fate of this non-essential metal is not adequately described by experiments, in vitro and in silico, which have consistently demonstrated that at equilibrium 90% of serum Al(III) is bound by Tf3-5. We have coined this paradox 'the blood-aluminium problem'6 and herein applied a systems biology approach which utilised well-found assumptions to pare away the complexities of the problem such that it was defined by a comparatively simple set of computational rules and, importantly, its solution assumed significant predictive capabilities. Here we show that our novel computational model successfully described the binding of Al(III) by Tf both at equilibrium and as equilibrium for AlTf was approached. The model provided an explanation of why the distribution of Al(III) in the body cannot be adequately described by its binding and transport by Tf and it highlighted the significance of kinetic in addition to thermodynamic constraints in defining the fate of metal ions in biological systems. This is the first model of non-equilibrium metal binding in a biological system and it should prove to be a valuable predictive tool in furthering our understanding of the bioinorganic chemistry of metals

Model Pembelajaran Kimia Fisika Berbasis Simulasi Dinamika Molekul

Fisika statistik merupakan bidang ilmu alam yang sangat penting dipahami oleh para mahasiswa fisika dan kimia. Bidang kajian fisika statistik termasuk bidang yang abstrak dan sulit dipahami sehingga memerlukan kemampuan analisis matematis yang tinggi. Pada penelitian ini telah dikembangkan sebuah model pembelajaran kimia - fisika berbasis simulasi dinamika molekul sehingga para mahasiswa yang memerlukan konsep-konsep fisika statistik dapat dipelajari dengan baik. Dengan simulasi dinamika molekul ini para mahasiswa dapat memahami perilaku sistem dalam berbagai jenis ensambel secara praktis dan efektif. Berbagai eksperimen yang seharusnya dilakukan dalam laboratorium, namun melalui model pembelajaran ini, kita dapat melakukan simulasi secara mandiri melalui tampilan di layar komputer sehingga dapat membantu pemahaman mahasiswa dengan lebih baik

Parallel simulation of particle dynamics with application to micropolar peridynamic lattice modeling of reinforced concrete Structures

As the first goal of this thesis, we will explain a general purpose parallel particle dynamics code (pdQ2). We describe the re-architecting of pdQ (the MD/PD code that was developed in [Sakhavand 2011]) as pdQ2. pdQ2 is completely non-domain-specific in that user files are clearly separated from non-user files and no #ifdefs exist in the code. Thus, it operates as a particle simulation engine that is capable of executing any parallel particle dynamics model. As in the original pdQ, users can customize their own physical models without having to deal with complexities such as parallelization, but the ease of extensibility has been significantly improved. It is shown that pdQ2 is about four times as fast as pdQ using parallel supercomputers. In the second part of the thesis, we will model reinforced concrete structures based on peridynamic theory [Silling 1998]. We discard the continuum mechanics paradigm completely, and model reinforced concrete by introducing the micropolar peridynamic lattice model (MPLM)\u27. The MPLM models a structure as a close-packed particle lattice. In the MPLM, rather than viewing the structure as collection of truss or beam elements (as with traditional lattice models), the model is viewed as collection of particle masses (as with peridynamic models). The MPLM uses a finite number of equally-spaced interacting particles of finite mass. Thus, it does not need any ad hoc discretization and it is more straightforward to implement computationally. Also, the MPLM is conceptually simpler than both the lattice and peridynamic models [Gerstle et al. 2012]. After defining the MPLM, its application to reinforced concrete structures is investigated through several examples using pdQ2.\u2

Parallel simulation of reinforced concrete sructures using peridynamics

The failure of concrete structures involves many complex mechanisms. Traditional theoretical models are limited to specific problems and are not applicable to many real-life problems. Consequently, design specifications mostly rely on empirical equations derived from laboratory tests at the component level. It is desirable to develop new analysis methods, capable of harnessing material-level test parameters. To overcome limitations and shortcomings of models based on continuum mechanics and fracture mechanics, Stewart Silling introduced the concept of peridynamics in 1998. Similar to molecular dynamics, peridynamic modeling of a physical structure involves simulating interacting particles subjected to an empirical force field. The evolution of interacting particles determines the deformation of the structure at a given time due to the applied boundary condition. As a particle-based model, peridynamics requires the repeated evaluation of many particle interactions which is computationally demanding. However, with todays inexpensive computing hardware, parallel algorithms can be utilized to run such problems on multi-node supercomputers with fast interconnects. However, existing codes tend to be domain-specific with too many built-in physical assumptions. In this work, a novel method for parallelization of any particle-based simulation is presented which is quite general and suitable for simulating diverse physical structures. A scalable parallel code for molecular dynamics and peridynamics simulation, PDQ, is described which implements a novel wall method parallelization algorithm, developed as part of this thesis. PDQ partitions the geometric domain of a problem across multi-nodes while the physics is left open to the user to decide whether to simulate a solvated protein or alloy grain boundary at the atomic scale or to simulate cracking phenomena in concrete via peridynamics. A further extension of PDQ brings more flexibility by allowing the user to define any desired number of degrees of freedom for each particle in a peridynamics simulation. At the end of this thesis, plain, reinforced and prestressed concrete benchmark problems are simulated using PDQ and the results are compared to available design code equations or analytical solutions. This research is a step toward next level of computational modeling of reinforced concrete structures and the revolutionizing of how concrete is analyzed and also how concrete structures are designed.\u2

Parallel Many-Body Simulations Without All-to-All Communication

Simulations of interacting particles are common in science and engineering, appearing in such diverse disciplines as astrophysics, fluid dynamics, molecular physics, and materials science. These simulations are often computationally intensive and so natural candidates for massively parallel computing. Many--body simulations that directly compute interactions between pairs of particles, be they short--range or long--range interactions, have been parallelized in several standard ways. The simplest approaches require all--to--all communication, an expensive communication step. The fastest methods assign a group of nearby particles to a processor, which can lead to load imbalance and be difficult to implement efficiently. We present a new approach, suitable for direct simulations, that avoids all--to--all communication without requiring any geometric clustering. We demonstrate its utility in several parallel molecular dynamics simulations, and compare performance against other parallel app..

Parallel Many-Body Simulations Without All-to-All Communication

Simulations of interacting particles are common in science and engineering, appearing in such diverse disciplines as astrophysics, fluid dynamics, molecular physics, and materials science. These simulations are often computationally intensive and so natural candidates for massively parallel computing. Many-body simulations that directly compute interactions between pairs of particles, be they short-range or long-range interactions, have been parallelized in several standard ways. The simplest approaches require all-to-all communication, an expensive communication step. The fastest methods assign a group of nearby particles to a processor, which can lead to load imbalance and be difficult to implement efficiently. We present a new approach, suitable for direct simulations, that avoids all-to-all communication without requiring any geometric clustering. For some computations we find the new method to be the fastest parallel algorithm available; we demonstrate its utility..