A flexible architecture for modeling and simulation of diffusional association

Up to now, it is not possible to obtain analytical solutions for complex molecular association processes (e.g. Molecule recognition in Signaling or catalysis). Instead Brownian Dynamics (BD) simulations are commonly used to estimate the rate of diffusional association, e.g. to be later used in mesoscopic simulations. Meanwhile a portfolio of diffusional association (DA) methods have been developed that exploit BD. However, DA methods do not clearly distinguish between modeling, simulation, and experiment settings. This hampers to classify and compare the existing methods with respect to, for instance model assumptions, simulation approximations or specific optimization strategies for steering the computation of trajectories. To address this deficiency we propose FADA (Flexible Architecture for Diffusional Association) - an architecture that allows the flexible definition of the experiment comprising a formal description of the model in SpacePi, different simulators, as well as validation and analysis methods. Based on the NAM (Northrup-Allison-McCammon) method, which forms the basis of many existing DA methods, we illustrate the structure and functioning of FADA. A discussion of future validation experiments illuminates how the FADA can be exploited in order to estimate reaction rates and how validation techniques may be applied to validate additional features of the model

Transient electrothermal simulation of power semiconductor devices

In this paper, a new thermal model based on the Fourier series solution of heat conduction equation has been introduced in detail. 1-D and 2-D Fourier series thermal models have been programmed in MATLAB/Simulink. Compared with the traditional finite-difference thermal model and equivalent RC thermal network, the new thermal model can provide high simulation speed with high accuracy, which has been proved to be more favorable in dynamic thermal characterization on power semiconductor switches. The complete electrothermal simulation models of insulated gate bipolar transistor (IGBT) and power diodes under inductive load switching condition have been successfully implemented in MATLAB/Simulink. The experimental results on IGBT and power diodes with clamped inductive load switching tests have verified the new electrothermal simulation model. The advantage of Fourier series thermal model over widely used equivalent RC thermal network in dynamic thermal characterization has also been validated by the measured junction temperature

Physics-based visual characterization of molecular interaction forces

Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.Peer ReviewedPostprint (author's final draft

Investigation into intermodulation distortion in HEMTs using a quasi-2-D physical model

The need for both linear and efficient pseudomorphic high electron-mobility transistors (pHEMTs) for modern wireless handsets necessitates a thorough understanding of the origins of intermodulation distortion at the device level. For the first time, the dynamic large-signal internal physical behavior of a pHEMT is examined using a quasi-two-dimensional physical device model. The model accounts fully for device-circuit interaction and is validated experimentally for a two-tone experiment around 5 GHz

Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials