Magnetohydrodynamic Models of Molecular Tornadoes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Au, Kelvin; Fiege, Jason D., E-mail: fiege@physics.umanitoba.ca

Recent observations near the Galactic Center (GC) have found several molecular filaments displaying striking helically wound morphology that are collectively known as molecular tornadoes. We investigate the equilibrium structure of these molecular tornadoes by formulating a magnetohydrodynamic model of a rotating, helically magnetized filament. A special analytical solution is derived where centrifugal forces balance exactly with toroidal magnetic stress. From the physics of torsional Alfvén waves we derive a constraint that links the toroidal flux-to-mass ratio and the pitch angle of the helical field to the rotation laws, which we find to be an important component in describing the molecularmore » tornado structure. The models are compared to the Ostriker solution for isothermal, nonmagnetic, nonrotating filaments. We find that neither the analytic model nor the Alfvén wave model suffer from the unphysical density inversions noted by other authors. A Monte Carlo exploration of our parameter space is constrained by observational measurements of the Pigtail Molecular Cloud, the Double Helix Nebula, and the GC Molecular Tornado. Observable properties such as the velocity dispersion, filament radius, linear mass, and surface pressure can be used to derive three dimensionless constraints for our dimensionless models of these three objects. A virial analysis of these constrained models is studied for these three molecular tornadoes. We find that self-gravity is relatively unimportant, whereas magnetic fields and external pressure play a dominant role in the confinement and equilibrium radial structure of these objects.« less

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities

PubMed Central

Bardhan, Jaydeep P.

2014-01-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics. PMID:25505358

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities.

PubMed

Bardhan, Jaydeep P

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Open source molecular modeling.

PubMed

Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan

2016-09-01

The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. An updated online version of this catalog can be found at https://opensourcemolecularmodeling.github.io. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Observational Constraints for Modeling Diffuse Molecular Clouds

NASA Astrophysics Data System (ADS)

Federman, S. R.

2014-02-01

Ground-based and space-borne observations of diffuse molecular clouds suggest a number of areas where further improvements to modeling efforts is warranted. I will highlight those that have the widest applicability. The range in CO fractionation caused by selective isotope photodissociation, in particular the large 12C16O/13C16O ratios observed toward stars in Ophiuchus, is not reproduced well by current models. Our ongoing laboratory measurements of oscillator strengths and predissociation rates for Rydberg transitions in CO isotopologues may help clarify the situtation. The CH+ abundance continues to draw attention. Small scale structure seen toward ζ Per may provide additional constraints on the possible synthesis routes. The connection between results from optical transitions and those from radio and sub-millimeter wave transitions requires further effort. A study of OH+ and OH toward background stars reveals that these species favor different environments. This brings to focus the need to model each cloud along the line of sight separately, and to allow the physical conditions to vary within an individual cloud, in order to gain further insight into the chemistry. Now that an extensive set of data on molecular excitation is available, the models should seek to reproduce these data to place further constraints on the modeling results.

Hierarchical modeling of molecular energies using a deep neural network

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

Molecular Dynamics Modeling and Simulation of Diamond Cutting of Cerium.

PubMed

Zhang, Junjie; Zheng, Haibing; Shuai, Maobing; Li, Yao; Yang, Yang; Sun, Tao

2017-12-01

The coupling between structural phase transformations and dislocations induces challenges in understanding the deformation behavior of metallic cerium at the nanoscale. In the present work, we elucidate the underlying mechanism of cerium under ultra-precision diamond cutting by means of molecular dynamics modeling and simulations. The molecular dynamics model of diamond cutting of cerium is established by assigning empirical potentials to describe atomic interactions and evaluating properties of two face-centered cubic cerium phases. Subsequent molecular dynamics simulations reveal that dislocation slip dominates the plastic deformation of cerium under the cutting process. In addition, the analysis based on atomic radial distribution functions demonstrates that there are trivial phase transformations from the γ-Ce to the δ-Ce occurred in both machined surface and formed chip. Following investigations on machining parameter dependence reveal the optimal machining conditions for achieving high quality of machined surface of cerium.

Molecular Dynamics Modeling and Simulation of Diamond Cutting of Cerium

NASA Astrophysics Data System (ADS)

Zhang, Junjie; Zheng, Haibing; Shuai, Maobing; Li, Yao; Yang, Yang; Sun, Tao

2017-07-01

The coupling between structural phase transformations and dislocations induces challenges in understanding the deformation behavior of metallic cerium at the nanoscale. In the present work, we elucidate the underlying mechanism of cerium under ultra-precision diamond cutting by means of molecular dynamics modeling and simulations. The molecular dynamics model of diamond cutting of cerium is established by assigning empirical potentials to describe atomic interactions and evaluating properties of two face-centered cubic cerium phases. Subsequent molecular dynamics simulations reveal that dislocation slip dominates the plastic deformation of cerium under the cutting process. In addition, the analysis based on atomic radial distribution functions demonstrates that there are trivial phase transformations from the γ-Ce to the δ-Ce occurred in both machined surface and formed chip. Following investigations on machining parameter dependence reveal the optimal machining conditions for achieving high quality of machined surface of cerium.

Molecular modelling of protein-protein/protein-solvent interactions

NASA Astrophysics Data System (ADS)

Luchko, Tyler

The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule

Molecular Modeling of Lipid Membrane Curvature Induction by a Peptide: More than Simply Shape

PubMed Central

Sodt, Alexander J.; Pastor, Richard W.

2014-01-01

Molecular dynamics simulations of an amphipathic helix embedded in a lipid bilayer indicate that it will induce substantial positive curvature (e.g., a tube of diameter 20 nm at 16% surface coverage). The induction is twice that of a continuum model prediction that only considers the shape of the inclusion. The discrepancy is explained in terms of the additional presence of specific interactions described only by the molecular model. The conclusion that molecular shape alone is insufficient to quantitatively model curvature is supported by contrasting molecular and continuum models of lipids with large and small headgroups (choline and ethanolamine, respectively), and of the removal of a lipid tail (modeling a lyso-lipid). For the molecular model, curvature propensity is analyzed by computing the derivative of the free energy with respect to bending. The continuum model predicts that the inclusion will soften the bilayer near the headgroup region, an effect that may weaken curvature induction. The all-atom predictions are consistent with experimental observations of the degree of tubulation by amphipathic helices and variation of the free energy of binding to liposomes. PMID:24806928

3D Printing of Molecular Models

ERIC Educational Resources Information Center

Gardner, Adam; Olson, Arthur

2016-01-01

Physical molecular models have played a valuable role in our understanding of the invisible nano-scale world. We discuss 3D printing and its use in producing models of the molecules of life. Complex biomolecular models, produced from 3D printed parts, can demonstrate characteristics of molecular structure and function, such as viral self-assembly,…

Supercomputer applications in molecular modeling.

PubMed

Gund, T M

1988-01-01

An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

A realistic molecular model of cement hydrates.

PubMed

Pellenq, Roland J-M; Kushima, Akihiro; Shahsavari, Rouzbeh; Van Vliet, Krystyn J; Buehler, Markus J; Yip, Sidney; Ulm, Franz-Josef

2009-09-22

Despite decades of studies of calcium-silicate-hydrate (C-S-H), the structurally complex binder phase of concrete, the interplay between chemical composition and density remains essentially unexplored. Together these characteristics of C-S-H define and modulate the physical and mechanical properties of this "liquid stone" gel phase. With the recent determination of the calcium/silicon (C/S = 1.7) ratio and the density of the C-S-H particle (2.6 g/cm(3)) by neutron scattering measurements, there is new urgency to the challenge of explaining these essential properties. Here we propose a molecular model of C-S-H based on a bottom-up atomistic simulation approach that considers only the chemical specificity of the system as the overriding constraint. By allowing for short silica chains distributed as monomers, dimers, and pentamers, this C-S-H archetype of a molecular description of interacting CaO, SiO2, and H2O units provides not only realistic values of the C/S ratio and the density computed by grand canonical Monte Carlo simulation of water adsorption at 300 K. The model, with a chemical composition of (CaO)(1.65)(SiO2)(H2O)(1.75), also predicts other essential structural features and fundamental physical properties amenable to experimental validation, which suggest that the C-S-H gel structure includes both glass-like short-range order and crystalline features of the mineral tobermorite. Additionally, we probe the mechanical stiffness, strength, and hydrolytic shear response of our molecular model, as compared to experimentally measured properties of C-S-H. The latter results illustrate the prospect of treating cement on equal footing with metals and ceramics in the current application of mechanism-based models and multiscale simulations to study inelastic deformation and cracking.

MULTI: a shared memory approach to cooperative molecular modeling.

PubMed

Darden, T; Johnson, P; Smith, H

1991-03-01

A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

Functional Generalized Additive Models.

PubMed

McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

2014-01-01

We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F { X ( t ), t } where F (·,·) is an unknown regression function and X ( t ) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F (·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X ( t ) is a signal from diffusion tensor imaging at position, t , along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.

Chemical insight from density functional modeling of molecular adsorption: Tracking the bonding and diffusion of anthracene derivatives on Cu(111) with molecular orbitals

NASA Astrophysics Data System (ADS)

Wyrick, Jonathan; Einstein, T. L.; Bartels, Ludwig

2015-03-01

We present a method of analyzing the results of density functional modeling of molecular adsorption in terms of an analogue of molecular orbitals. This approach permits intuitive chemical insight into the adsorption process. Applied to a set of anthracene derivates (anthracene, 9,10-anthraquinone, 9,10-dithioanthracene, and 9,10-diselenonanthracene), we follow the electronic states of the molecules that are involved in the bonding process and correlate them to both the molecular adsorption geometry and the species' diffusive behavior. We additionally provide computational code to easily repeat this analysis on any system.

Students' use of atomic and molecular models in learning chemistry

NASA Astrophysics Data System (ADS)

O'Connor, Eileen Ann

1997-09-01

The objective of this study was to investigate the development of introductory college chemistry students' use of atomic and molecular models to explain physical and chemical phenomena. The study was conducted during the first semester of the course at a University and College II. Public institution (Carnegie Commission of Higher Education, 1973). Students' use of models was observed during one-on-one interviews conducted over the course of the semester. The approach to introductory chemistry emphasized models. Students were exposed to over two-hundred and fifty atomic and molecular models during lectures, were assigned text readings that used over a thousand models, and worked interactively with dozens of models on the computer. These models illustrated various features of the spatial organization of valence electrons and nuclei in atoms and molecules. Despite extensive exposure to models in lectures, in textbook, and in computer-based activities, the students in the study based their explanation in large part on a simple Bohr model (electrons arranged in concentric circles around the nuclei)--a model that had not been introduced in the course. Students used visual information from their models to construct their explanation, while overlooking inter-atomic and intra-molecular forces which are not represented explicitly in the models. In addition, students often explained phenomena by adding separate information about the topic without either integrating or logically relating this information into a cohesive explanation. The results of the study demonstrate that despite the extensive use of models in chemistry instruction, students do not necessarily apply them appropriately in explaining chemical and physical phenomena. The results of this study suggest that for the power of models as aids to learning to be more fully realized, chemistry professors must give more attention to the selection, use, integration, and limitations of models in their instruction.

Molecularly imprinted polymers for the detection of illegal drugs and additives: a review.

PubMed

Xiao, Deli; Jiang, Yue; Bi, Yanping

2018-04-04

This review (with 154 refs.) describes the current status of using molecularly imprinted polymers in the extraction and quantitation of illicit drugs and additives. The review starts with an introduction into some synthesis methods (lump MIPs, spherical MIPs, surface imprinting) of MIPs using illicit drugs and additives as templates. The next section covers applications, with subsections on the detection of illegal additives in food, of doping in sports, and of illicit addictive drugs. A particular focus is directed towards current limitations and challenges, on the optimization of methods for preparation of MIPs, their applicability to aqueous samples, the leakage of template molecules, and the identification of the best balance between adsorption capacity and selectivity factor. At last, the need for convincing characterization methods, the lack of uniform parameters for defining selectivity, and the merits and demerits of MIPs prepared using nanomaterials are addressed. Strategies are suggested to solve existing problems, and future developments are discussed with respect to a more widespread use in relevant fields. Graphical abstract This review gives a comprehensive overview of the advances made in molecularly imprinting of polymers for use in the extraction and quantitation of illicit drugs and additives. Methods for syntheses, highlighted applications, limitations and current challenges are specifically addressed.

THE IMPACT OF MOLECULAR GAS ON MASS MODELS OF NEARBY GALAXIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frank, B. S.; Blok, W. J. G. de; Walter, F.

2016-04-15

We present CO velocity fields and rotation curves for a sample of nearby galaxies, based on data from HERACLES. We combine our data with THINGS, SINGS, and KINGFISH results to provide a comprehensive sample of mass models of disk galaxies inclusive of molecular gas. We compare the kinematics of the molecular (CO from HERACLES) and atomic (H i from THINGS) gas distributions to determine the extent to which CO may be used to probe the dynamics in the inner part of galaxies. In general, we find good agreement between the CO and H i kinematics, with small differences in themore » inner part of some galaxies. We add the contribution of the molecular gas to the mass models in our galaxies by using two different conversion factors α{sub CO} to convert CO luminosity to molecular gas mass surface density—the constant Milky Way value and the radially varying profiles determined in recent work based on THINGS, HERACLES, and KINGFISH data. We study the relative effect that the addition of the molecular gas has on the halo rotation curves for Navarro–Frenk–White and the observationally motivated pseudo-isothermal halos. The contribution of the molecular gas varies for galaxies in our sample—for those galaxies where there is a substantial molecular gas content, using different values of α{sub CO} can result in significant differences to the relative contribution of the molecular gas and hence the shape of the dark matter halo rotation curves in the central regions of galaxies.« less

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

PubMed Central

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. PMID:25999313

GPU-Accelerated Molecular Modeling Coming Of Age

PubMed Central

Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

2010-01-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

The cognitive life of mechanical molecular models.

PubMed

Charbonneau, Mathieu

2013-12-01

The use of physical models of molecular structures as research tools has been central to the development of biochemistry and molecular biology. Intriguingly, it has received little attention from scholars of science. In this paper, I argue that these physical models are not mere three-dimensional representations but that they are in fact very special research tools: they are cognitive augmentations. Despite the fact that they are external props, these models serve as cognitive tools that augment and extend the modeler's cognitive capacities and performance in molecular modeling tasks. This cognitive enhancement is obtained because of the way the modeler interacts with these models, the models' materiality contributing to the solving of the molecule's structure. Furthermore, I argue that these material models and their component parts were designed, built and used specifically to serve as cognitive facilitators and cognitive augmentations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nanoindentation of virus capsids in a molecular model

NASA Astrophysics Data System (ADS)

Cieplak, Marek; Robbins, Mark O.

2010-01-01

A molecular-level model is used to study the mechanical response of empty cowpea chlorotic mottle virus (CCMV) and cowpea mosaic virus (CPMV) capsids. The model is based on the native structure of the proteins that constitute the capsids and is described in terms of the Cα atoms. Nanoindentation by a large tip is modeled as compression between parallel plates. Plots of the compressive force versus plate separation for CCMV are qualitatively consistent with continuum models and experiments, showing an elastic region followed by an irreversible drop in force. The mechanical response of CPMV has not been studied, but the molecular model predicts an order of magnitude higher stiffness and a much shorter elastic region than for CCMV. These large changes result from small structural changes that increase the number of bonds by only 30% and would be difficult to capture in continuum models. Direct comparison of local deformations in continuum and molecular models of CCMV shows that the molecular model undergoes a gradual symmetry breaking rotation and accommodates more strain near the walls than the continuum model. The irreversible drop in force at small separations is associated with rupturing nearly all of the bonds between capsid proteins in the molecular model, while a buckling transition is observed in continuum models.

Glioblastoma, a brief review of history, molecular genetics, animal models and novel therapeutic strategies.

PubMed

Agnihotri, Sameer; Burrell, Kelly E; Wolf, Amparo; Jalali, Sharzhad; Hawkins, Cynthia; Rutka, James T; Zadeh, Gelareh

2013-02-01

Glioblastoma (GBM) is the most common and lethal primary brain tumor. Over the past few years tremendous genomic and proteomic characterization along with robust animal models of GBM have provided invaluable data that show that "GBM", although histologically indistinguishable from one another, are comprised of molecularly heterogenous diseases. In addition, robust pre-clinical models and a better understanding of the core pathways disrupted in GBM are providing a renewed optimism for novel strategies targeting these devastating tumors. Here, we summarize a brief history of the disease, our current molecular knowledge, lessons from animal models and emerging concepts of angiogenesis, invasion, and metabolism in GBM that may lend themselves to therapeutic targeting.

GPU-accelerated molecular modeling coming of age.

PubMed

Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

2010-09-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

Computational Process Modeling for Additive Manufacturing

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2014-01-01

Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

Molecular Weight and Molecular Weight Distributions in Synthetic Polymers.

ERIC Educational Resources Information Center

Ward, Thomas Carl

1981-01-01

Focuses on molecular weight and molecular weight distributions (MWD) and models for predicting MWD in a pedagogical way. In addition, instrumental methods used to characterize MWD are reviewed with emphasis on physical chemistry of each, including end-group determination, osmometry, light scattering, solution viscosity, fractionation, and…

Interaction of sucralose with whey protein: Experimental and molecular modeling studies

NASA Astrophysics Data System (ADS)

Zhang, Hongmei; Sun, Shixin; Wang, Yanqing; Cao, Jian

2017-12-01

The objective of this research was to study the interactions of sucralose with whey protein isolate (WPI) by using the three-dimensional fluorescence spectroscopy, circular dichroism spectroscopy and molecular modeling. The results showed that the peptide strands structure of WPI had been changed by sucralose. Sucralose binding induced the secondary structural changes and increased content of aperiodic structure of WPI. Sucralose decreased the thermal stability of WPI and acted as a structure destabilizer during the thermal unfolding process of protein. In addition, the existence of sucralose decreased the reversibility of the unfolding of WPI. Nonetheless, sucralose-WPI complex was less stable than protein alone. The molecular modeling result showed that van der Waals and hydrogen bonding interactions contribute to the complexation free binding energy. There are more than one possible binding sites of WPI with sucralose by surface binding mode.

Uncovering molecular details of urea crystal growth in the presence of additives.

PubMed

Salvalaglio, Matteo; Vetter, Thomas; Giberti, Federico; Mazzotti, Marco; Parrinello, Michele

2012-10-17

Controlling the shape of crystals is of great practical relevance in fields like pharmacology and fine chemistry. Here we examine the paradigmatic case of urea which is known to crystallize from water with a needle-like morphology. To prevent this undesired effect, inhibitors that selectively favor or discourage the growth of specific crystal faces can be used. In urea the most relevant faces are the {001} and the {110} which are known to grow fast and slow, respectively. The relevant growth speed difference between these two crystal faces is responsible for the needle-like structure of crystals grown in water solution. To prevent this effect, additives are used to slow down the growth of one face relative to another, thus controlling the shape of the crystal. We study the growth of fast {001} and slow {110} faces in water solution and the effect of shape controlling inhibitors like biuret. Extensive sampling through molecular dynamics simulations provides a microscopic picture of the growth mechanism and of the role of the additives. We find a continuous growth mechanism on the {001} face, while the slow growing {110} face evolves through a birth and spread process, in which the rate-determining step is the formation on the surface of a two-dimensional crystalline nucleus. On the {001} face, growth inhibitors like biuret compete with urea for the adsorption on surface lattice sites; on the {110} face instead additives cannot interact specifically with surface sites and play a marginal sterical hindrance of the crystal growth. The free energies of adsorption of additives and urea are evaluated with advanced simulation methods (well-tempered metadynamics) allowing a microscopic understanding of the selective effect of additives. Based on this case study, general principles for the understanding of the anisotropic growth of molecular crystals from solutions are laid out. Our work is a step toward a rational development of novel shape-affecting additives.

Multiensemble Markov models of molecular thermodynamics and kinetics.

PubMed

Wu, Hao; Paul, Fabian; Wehmeyer, Christoph; Noé, Frank

2016-06-07

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models-clustering of high-dimensional spaces and modeling of complex many-state systems-with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein-ligand binding model.

Direct calculation of ice homogeneous nucleation rate for a molecular model of water.

PubMed

Haji-Akbari, Amir; Debenedetti, Pablo G

2015-08-25

Ice formation is ubiquitous in nature, with important consequences in a variety of environments, including biological cells, soil, aircraft, transportation infrastructure, and atmospheric clouds. However, its intrinsic kinetics and microscopic mechanism are difficult to discern with current experiments. Molecular simulations of ice nucleation are also challenging, and direct rate calculations have only been performed for coarse-grained models of water. For molecular models, only indirect estimates have been obtained, e.g., by assuming the validity of classical nucleation theory. We use a path sampling approach to perform, to our knowledge, the first direct rate calculation of homogeneous nucleation of ice in a molecular model of water. We use TIP4P/Ice, the most accurate among existing molecular models for studying ice polymorphs. By using a novel topological approach to distinguish different polymorphs, we are able to identify a freezing mechanism that involves a competition between cubic and hexagonal ice in the early stages of nucleation. In this competition, the cubic polymorph takes over because the addition of new topological structural motifs consistent with cubic ice leads to the formation of more compact crystallites. This is not true for topological hexagonal motifs, which give rise to elongated crystallites that are not able to grow. This leads to transition states that are rich in cubic ice, and not the thermodynamically stable hexagonal polymorph. This mechanism provides a molecular explanation for the earlier experimental and computational observations of the preference for cubic ice in the literature.

Direct calculation of ice homogeneous nucleation rate for a molecular model of water

PubMed Central

Haji-Akbari, Amir; Debenedetti, Pablo G.

2015-01-01

Ice formation is ubiquitous in nature, with important consequences in a variety of environments, including biological cells, soil, aircraft, transportation infrastructure, and atmospheric clouds. However, its intrinsic kinetics and microscopic mechanism are difficult to discern with current experiments. Molecular simulations of ice nucleation are also challenging, and direct rate calculations have only been performed for coarse-grained models of water. For molecular models, only indirect estimates have been obtained, e.g., by assuming the validity of classical nucleation theory. We use a path sampling approach to perform, to our knowledge, the first direct rate calculation of homogeneous nucleation of ice in a molecular model of water. We use TIP4P/Ice, the most accurate among existing molecular models for studying ice polymorphs. By using a novel topological approach to distinguish different polymorphs, we are able to identify a freezing mechanism that involves a competition between cubic and hexagonal ice in the early stages of nucleation. In this competition, the cubic polymorph takes over because the addition of new topological structural motifs consistent with cubic ice leads to the formation of more compact crystallites. This is not true for topological hexagonal motifs, which give rise to elongated crystallites that are not able to grow. This leads to transition states that are rich in cubic ice, and not the thermodynamically stable hexagonal polymorph. This mechanism provides a molecular explanation for the earlier experimental and computational observations of the preference for cubic ice in the literature. PMID:26240318

Markov state models and molecular alchemy

NASA Astrophysics Data System (ADS)

Schütte, Christof; Nielsen, Adam; Weber, Marcus

2015-01-01

In recent years, Markov state models (MSMs) have attracted a considerable amount of attention with regard to modelling conformation changes and associated function of biomolecular systems. They have been used successfully, e.g. for peptides including time-resolved spectroscopic experiments, protein function and protein folding , DNA and RNA, and ligand-receptor interaction in drug design and more complicated multivalent scenarios. In this article, a novel reweighting scheme is introduced that allows to construct an MSM for certain molecular system out of an MSM for a similar system. This permits studying how molecular properties on long timescales differ between similar molecular systems without performing full molecular dynamics simulations for each system under consideration. The performance of the reweighting scheme is illustrated for simple test cases, including one where the main wells of the respective energy landscapes are located differently and an alchemical transformation of butane to pentane where the dimension of the state space is changed.

Molecular Modeling of an Electrophilic Addition Reaction with "Unexpected" Regiochemistry

ERIC Educational Resources Information Center

Best, Katherine T.; Li, Diana; Helms, Eric D.

2017-01-01

The electrophilic addition of a hydrohalic acid (HX) to an alkene is often one of the first reactions learned in second-year undergraduate organic chemistry classes. During the ensuing discussion of the mechanism, it is shown that this reaction follows Markovnikov's rule, which states that the hydrogen atom will attach to the carbon with fewer…

Modelling of Cosmic Molecular Masers: Introduction to a Computation Cookbook

NASA Astrophysics Data System (ADS)

Sobolev, Andrej M.; Gray, Malcolm D.

2012-07-01

Numerical modeling of molecular masers is necessary in order to understand their nature and diagnostic capabilities. Model construction requires elaboration of a basic description which allows computation, that is a definition of the parameter space and basic physical relations. Usually, this requires additional thorough studies that can consist of the following stages/parts: relevant molecular spectroscopy and collisional rate coefficients; conditions in and around the masing region (that part of space where population inversion is realized); geometry and size of the masing region (including the question of whether maser spots are discrete clumps or line-of-sight correlations in a much bigger region) and propagation of maser radiation. Output of the maser computer modeling can have the following forms: exploration of parameter space (where do inversions appear in particular maser transitions and their combinations, which parameter values describe a `typical' source, and so on); modeling of individual sources (line flux ratios, spectra, images and their variability); analysis of the pumping mechanism; predictions (new maser transitions, correlations in variability of different maser transitions, and the like). Described schemes (constituents and hierarchy) of the model input and output are based mainly on the experience of the authors and make no claim to be dogmatic.

Molecular modeling: An open invitation for applied mathematics

NASA Astrophysics Data System (ADS)

Mezey, Paul G.

2013-10-01

Molecular modeling methods provide a very wide range of challenges for innovative mathematical and computational techniques, where often high dimensionality, large sets of data, and complicated interrelations imply a multitude of iterative approximations. The physical and chemical basis of these methodologies involves quantum mechanics with several non-intuitive aspects, where classical interpretation and classical analogies are often misleading or outright wrong. Hence, instead of the everyday, common sense approaches which work so well in engineering, in molecular modeling one often needs to rely on rather abstract mathematical constraints and conditions, again emphasizing the high level of reliance on applied mathematics. Yet, the interdisciplinary aspects of the field of molecular modeling also generates some inertia and perhaps too conservative reliance on tried and tested methodologies, that is at least partially caused by the less than up-to-date involvement in the newest developments in applied mathematics. It is expected that as more applied mathematicians take up the challenge of employing the latest advances of their field in molecular modeling, important breakthroughs may follow. In this presentation some of the current challenges of molecular modeling are discussed.

Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.

Multiensemble Markov models of molecular thermodynamics and kinetics

PubMed Central

Wu, Hao; Paul, Fabian; Noé, Frank

2016-01-01

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models—clustering of high-dimensional spaces and modeling of complex many-state systems—with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein–ligand binding model. PMID:27226302

Assessment of Molecular Acoustic Angiography for Combined Microvascular and Molecular Imaging in Preclinical Tumor Models

PubMed Central

Lindsey, Brooks D.; Shelton, Sarah E.; Foster, F. Stuart; Dayton, Paul A.

2017-01-01

Purpose To evaluate a new ultrasound molecular imaging approach in its ability to image a preclinical tumor model and to investigate the capacity to visualize and quantify co-registered microvascular and molecular imaging volumes. Procedures Molecular imaging using the new technique was compared with a conventional ultrasound molecular imaging technique (multi-pulse imaging) by varying the injected microbubble dose and scanning each animal using both techniques. Each of the 14 animals was randomly assigned one of three doses; bolus dose was varied, and the animals were imaged for three consecutive days so that each animal received every dose. A microvascular scan was also acquired for each animal by administering an infusion of non-targeted microbubbles. These scans were paired with co-registered molecular images (VEGFR2-targeted microbubbles), the vessels were segmented, and the spatial relationships between vessels and VEGFR2 targeting locations were analyzed. In 5 animals, an additional scan was performed in which the animal received a bolus of microbubbles targeted to E- and P-selectin. Vessel tortuosity as a function of distance from VEGF and selectin targeting was analyzed in these animals. Results Although resulting differences in image intensity due to varying microbubble dose were not significant between the two lowest doses, superharmonic imaging had significantly higher contrast-to-tissue ratio (CTR) than multi-pulse imaging (mean across all doses: 13.98 dB for molecular acoustic angiography vs. 0.53 dB for multi-pulse imaging; p = 4.9 × 10−10). Analysis of registered microvascular and molecular imaging volumes indicated that vessel tortuosity decreases with increasing distance from both VEGFR2 and selectin targeting sites. Conclusions Molecular acoustic angiography (superharmonic molecular imaging) exhibited a significant increase in CTR at all doses tested due to superior rejection of tissue artifact signals. Due to the high resolution of acoustic

Molecular modeling of the microstructure evolution during carbon fiber processing

NASA Astrophysics Data System (ADS)

Desai, Saaketh; Li, Chunyu; Shen, Tongtong; Strachan, Alejandro

2017-12-01

The rational design of carbon fibers with desired properties requires quantitative relationships between the processing conditions, microstructure, and resulting properties. We developed a molecular model that combines kinetic Monte Carlo and molecular dynamics techniques to predict the microstructure evolution during the processes of carbonization and graphitization of polyacrylonitrile (PAN)-based carbon fibers. The model accurately predicts the cross-sectional microstructure of the fibers with the molecular structure of the stabilized PAN fibers and physics-based chemical reaction rates as the only inputs. The resulting structures exhibit key features observed in electron microcopy studies such as curved graphitic sheets and hairpin structures. In addition, computed X-ray diffraction patterns are in good agreement with experiments. We predict the transverse moduli of the resulting fibers between 1 GPa and 5 GPa, in good agreement with experimental results for high modulus fibers and slightly lower than those of high-strength fibers. The transverse modulus is governed by sliding between graphitic sheets, and the relatively low value for the predicted microstructures can be attributed to their perfect longitudinal texture. Finally, the simulations provide insight into the relationships between chemical kinetics and the final microstructure; we observe that high reaction rates result in porous structures with lower moduli.

Animal Models of Depression: Molecular Perspectives

PubMed Central

Krishnan, Vaishnav; Nestler, Eric J.

2012-01-01

Much of the current understanding about the pathogenesis of altered mood, impaired concentration and neurovegetative symptoms in major depression has come from animal models. However, because of the unique and complex features of human depression, the generation of valid and insightful depression models has been less straightforward than modeling other disabling diseases like cancer or autoimmune conditions. Today’s popular depression models creatively merge ethologically valid behavioral assays with the latest technological advances in molecular biology and automated video-tracking. This chapter reviews depression assays involving acute stress (e.g., forced swim test), models consisting of prolonged physical or social stress (e.g., social defeat), models of secondary depression, genetic models, and experiments designed to elucidate the mechanisms of antidepressant action. These paradigms are critically evaluated in relation to their ease, validity and replicability, the molecular insights that they have provided, and their capacity to offer the next generation of therapeutics for depression. PMID:21225412

Limiting assumptions in molecular modeling: electrostatics.

PubMed

Marshall, Garland R

2013-02-01

Molecular mechanics attempts to represent intermolecular interactions in terms of classical physics. Initial efforts assumed a point charge located at the atom center and coulombic interactions. It is been recognized over multiple decades that simply representing electrostatics with a charge on each atom failed to reproduce the electrostatic potential surrounding a molecule as estimated by quantum mechanics. Molecular orbitals are not spherically symmetrical, an implicit assumption of monopole electrostatics. This perspective reviews recent evidence that requires use of multipole electrostatics and polarizability in molecular modeling.

An Easily Constructed and Versatile Molecular Model

NASA Astrophysics Data System (ADS)

Hernandez, Sandra A.; Rodriguez, Nora M.; Quinzani, Oscar

1996-08-01

Three-dimensional molecular models are powerful tools used in basic courses of general and organic chemistry when the students must visualize the spatial distributions of atoms in molecules and relate them to the physical and chemical properties of such molecules. This article discusses inexpensive, easily carried, and semipermanent molecular models that the students may build by themselves. These models are based upon two different types of arrays of thin flexible wires, like telephone hook-up wires, which may be bent easily but keep their shapes.

Modelling the molecular mechanisms of aging

PubMed Central

Mc Auley, Mark T.; Guimera, Alvaro Martinez; Hodgson, David; Mcdonald, Neil; Mooney, Kathleen M.; Morgan, Amy E.

2017-01-01

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field. PMID:28096317

Informing Mechanistic Toxicology with Computational Molecular Models

EPA Science Inventory

Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo effo...

A model of how different biology experts explain molecular and cellular mechanisms.

PubMed

Trujillo, Caleb M; Anderson, Trevor R; Pelaez, Nancy J

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. © 2015 C. M. Trujillo et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Impact of Low Molecular Weight Poly(3-hexylthiophene)s as Additives in Organic Photovoltaic Devices.

PubMed

Seibers, Zach D; Le, Thinh P; Lee, Youngmin; Gomez, Enrique D; Kilbey, S Michael

2018-01-24

Despite tremendous progress in using additives to enhance the power conversion efficiency of organic photovoltaic devices, significant challenges remain in controlling the microstructure of the active layer, such as at internal donor-acceptor interfaces. Here, we demonstrate that the addition of low molecular weight poly(3-hexylthiophene)s (low-MW P3HT) to the P3HT/fullerene active layer increases device performance up to 36% over an unmodified control device. Low MW P3HT chains ranging in size from 1.6 to 8.0 kg/mol are blended with 77.5 kg/mol P3HT chains and [6,6]-phenyl C 61 butyric acid methyl ester (PCBM) fullerenes while keeping P3HT/PCBM ratio constant. Optimal photovoltaic device performance increases are obtained for each additive when incorporated into the bulk heterojunction blend at loading levels that are dependent upon additive MW. Small-angle X-ray scattering and energy-filtered transmission electron microscopy imaging reveal that domain sizes are approximately invariant at low loading levels of the low-MW P3HT additive, and wide-angle X-ray scattering suggests that P3HT crystallinity is unaffected by these additives. These results suggest that oligomeric P3HTs compatibilize donor-acceptor interfaces at low loading levels but coarsen domain structures at higher loading levels and they are consistent with recent simulations results. Although results are specific to the P3HT/PCBM system, the notion that low molecular weight additives can enhance photovoltaic device performance generally provides a new opportunity for improving device performance and operating lifetimes.

Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics

PubMed Central

Parker, David; Bryant, Zev; Delp, Scott L.

2010-01-01

Experimental and computational approaches are needed to uncover the mechanisms by which molecular motors convert chemical energy into mechanical work. In this article, we describe methods and software to generate structurally realistic models of molecular motor conformations compatible with experimental data from different sources. Coarse-grained models of molecular structures are constructed by combining groups of atoms into a system of rigid bodies connected by joints. Contacts between rigid bodies enforce excluded volume constraints, and spring potentials model system elasticity. This simplified representation allows the conformations of complex molecular motors to be simulated interactively, providing a tool for hypothesis building and quantitative comparisons between models and experiments. In an example calculation, we have used the software to construct atomically detailed models of the myosin V molecular motor bound to its actin track. The software is available at www.simtk.org. PMID:20428469

A Series of Molecular Dynamics and Homology Modeling Computer Labs for an Undergraduate Molecular Modeling Course

ERIC Educational Resources Information Center

Elmore, Donald E.; Guayasamin, Ryann C.; Kieffer, Madeleine E.

2010-01-01

As computational modeling plays an increasingly central role in biochemical research, it is important to provide students with exposure to common modeling methods in their undergraduate curriculum. This article describes a series of computer labs designed to introduce undergraduate students to energy minimization, molecular dynamics simulations,…

VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS

PubMed Central

Huang, Jian; Horowitz, Joel L.; Wei, Fengrong

2010-01-01

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is “small” relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method. PMID:21127739

Low-molecular-weight model study of peroxide cross-linking of ethylene-propylene-diene rubber using gas chromatography and mass spectrometry II. Addition and combination reactions.

PubMed

Peters, R; van Duin, M; Tonoli, D; Kwakkenbos, G; Mengerink, Y; van Benthem, R A T M; de Koster, C G; Schoenmakers, P J; van der Wal, Sj

2008-08-08

The dicumyl-peroxide-initiated addition and combination reactions of mixtures of alkanes (n-octane, n-decane) and alkenes [5,6-dihydrodicyclopentadiene (DCPDH), 5-ethylidene-2-norbornane (ENBH) and 5-vinylidene-2-norbornane (VNBH)] were studied to mimic the peroxide cross-linking reactions of terpolymerised ethylene, propylene and a diene monomer (EPDM). The reaction products of the mixtures were separated by both gas chromatography (GC) and comprehensive two-dimensional gas chromatography (GCxGC). The separated compounds were identified from their mass spectra and their GC and GCxGC elution pattern. Quantification of the various alkyl/alkyl, alkyl/allyl and allyl/allyl combination products shows that allylic-radicals comprise approximately 60% of the substrate radicals formed. The total concentration of the products formed by combination is found to be independent of the concentration and the type of alkene. The total concentration of the products formed by addition to the alkene increases with increasing concentration of alkene. In addition, the total concentration of the formed addition products depends strongly on the type of the alkene used, viz. VNBH>ENBH approximately DCPDH, which is a consequence of differences in steric hindrance of the unsaturation. The peroxide curing efficiency, defined as the number of moles of cross-linked products formed per mol of peroxide, is 173% using 9% (w/w) 5-vinylidene-2-norbornane (VNBH). This indicates that the addition reaction is recurrent. All these findings are consistent with experimental studies on peroxide curing of EPDM rubber. In addition, the present results provide more-detailed structural information, increasing the understanding of the mechanism of peroxide curing of EPDM. The described approach to use low-molecular-weight model compounds followed by GC-mass spectrometry (MS) and GCxGC-MS analysis is proven to be a very powerful tool to study the cross-linking of EPDM.

Simple model of a coherent molecular photocell

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ernzerhof, Matthias, E-mail: Matthias.Ernzerhof@UMontreal.ca; Bélanger, Marc-André; Mayou, Didier

2016-04-07

Electron transport in molecular electronic devices is often dominated by a coherent mechanism in which the wave function extends from the left contact over the molecule to the right contact. If the device is exposed to light, photon absorption in the molecule might occur, turning the device into a molecular photocell. The photon absorption promotes an electron to higher energy levels and thus modifies the electron transmission probability through the device. A model for such a molecular photocell is presented that minimizes the complexity of the problem while providing a non-trivial description of the device mechanism. In particular, the rolemore » of the molecule in the photocell is investigated. It is described within the Hückel method and the source-sink potential approach [F. Goyer, M. Ernzerhof, and M. Zhuang, J. Chem. Phys. 126, 144104 (2007)] is used to eliminate the contacts in favor of complex-valued potentials. Furthermore, the photons are explicitly incorporated into the model through a second-quantized field. This facilitates the description of the photon absorption process with a stationary state calculation, where eigenvalues and eigenvectors are determined. The model developed is applied to various generic molecular photocells.« less

A consistent transported PDF model for treating differential molecular diffusion

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Zhang, Pei

2016-11-01

Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

Modeling the Hydrogen Bond within Molecular Dynamics

ERIC Educational Resources Information Center

Lykos, Peter

2004-01-01

The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

PubMed

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

PubMed Central

Sing-Long, Carlos A.

2017-01-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

DOE PAGES

Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

2017-06-19

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

Coupling Molecular Modeling to the Traditional "IR-ID" Exercise in the Introductory Organic Chemistry Laboratory

ERIC Educational Resources Information Center

Stokes-Huby, Heather; Vitale, Dale E.

2007-01-01

This exercise integrates the infrared unknown identification ("IR-ID") experiment common to most organic laboratory syllabi with computer molecular modeling. In this modification students are still required to identify unknown compounds from their IR spectra, but must additionally match some of the absorptions with computed frequencies they…

Constructing Molecular Models with Low-Cost Toy Beads

ERIC Educational Resources Information Center

Ng, Pun-hon; Wong, Siu-ling; Mak, Se-yuen

2012-01-01

In teaching the science of the nano world, ball-and-stick molecular models are frequently used as 3D representations of molecules. Unlike a chemical formula, a molecular model allows us to visualise the 3D shape of the molecule and the relative positions of its atoms, the bonds between atoms and why a pair of mirror isomers with the same atoms,…

Exploring the relative reactivities of the hydroxyl groups of monosaccharides by molecular modeling and molecular mechanics

NASA Astrophysics Data System (ADS)

Box, V. G. S.; Evans-Lora, T.

2000-01-01

The molecular modeling program STR3DI.EXE, and its molecular mechanics module, QVBMM, were used to simulate, and evaluate, the stereo-electronic effects in the mono-alkoxides of the 4,6- O-ethylideneglycopyranosides of allose, mannose, galactose and glucose. This study has confirmed the ability of these molecular modeling tools to predict the regiochemistry and reactivity of these sugar derivatives, and holds considerable implications for unraveling the chemistry of the rare monosaccharides.

Modeling molecular mechanisms in the axon

NASA Astrophysics Data System (ADS)

de Rooij, R.; Miller, K. E.; Kuhl, E.

2017-03-01

Axons are living systems that display highly dynamic changes in stiffness, viscosity, and internal stress. However, the mechanistic origin of these phenomenological properties remains elusive. Here we establish a computational mechanics model that interprets cellular-level characteristics as emergent properties from molecular-level events. We create an axon model of discrete microtubules, which are connected to neighboring microtubules via discrete crosslinking mechanisms that obey a set of simple rules. We explore two types of mechanisms: passive and active crosslinking. Our passive and active simulations suggest that the stiffness and viscosity of the axon increase linearly with the crosslink density, and that both are highly sensitive to the crosslink detachment and reattachment times. Our model explains how active crosslinking with dynein motors generates internal stresses and actively drives axon elongation. We anticipate that our model will allow us to probe a wide variety of molecular phenomena—both in isolation and in interaction—to explore emergent cellular-level features under physiological and pathological conditions.

A molecular thermodynamic model for the stability of hepatitis B capsids

NASA Astrophysics Data System (ADS)

Kim, Jehoon; Wu, Jianzhong

2014-06-01

Self-assembly of capsid proteins and genome encapsidation are two critical steps in the life cycle of most plant and animal viruses. A theoretical description of such processes from a physiochemical perspective may help better understand viral replication and morphogenesis thus provide fresh insights into the experimental studies of antiviral strategies. In this work, we propose a molecular thermodynamic model for predicting the stability of Hepatitis B virus (HBV) capsids either with or without loading nucleic materials. With the key components represented by coarse-grained thermodynamic models, the theoretical predictions are in excellent agreement with experimental data for the formation free energies of empty T4 capsids over a broad range of temperature and ion concentrations. The theoretical model predicts T3/T4 dimorphism also in good agreement with the capsid formation at in vivo and in vitro conditions. In addition, we have studied the stability of the viral particles in response to physiological cellular conditions with the explicit consideration of the hydrophobic association of capsid subunits, electrostatic interactions, molecular excluded volume effects, entropy of mixing, and conformational changes of the biomolecular species. The course-grained model captures the essential features of the HBV nucleocapsid stability revealed by recent experiments.

Molecular Modeling of Estrogen Receptor Using Molecular Operating Environment

ERIC Educational Resources Information Center

Roy, Urmi; Luck, Linda A.

2007-01-01

Molecular modeling is pervasive in the pharmaceutical industry that employs many of our students from Biology, Chemistry and the interdisciplinary majors. To expose our students to this important aspect of their education we have incorporated a set of tutorials in our Biochemistry class. The present article describes one of our tutorials where…

Gas-grain chemical models of star-forming molecular clouds as constrained by ISO and SWAS observations

NASA Astrophysics Data System (ADS)

Charnley, S. B.; Rodgers, S. D.; Ehrenfreund, P.

2001-11-01

We have investigated the gaseous and solid state molecular composition of dense interstellar material that periodically experiences processing in the shock waves associated with ongoing star formation. Our motivation is to confront these models with the stringent abundance constraints on CO2, H2O and O2, in both gas and solid phases, that have been set by ISO and SWAS. We also compare our results with the chemical composition of dark molecular clouds as determined by ground-based telescopes. Beginning with the simplest possible model needed to study molecular cloud gas-grain chemistry, we only include additional processes where they are clearly required to satisfy one or more of the ISO-SWAS constraints. When CO, N2 and atoms of N, C and S are efficiently desorbed from grains, a chemical quasi-steady-state develops after about one million years. We find that accretion of CO2 and H2O cannot explain the [CO2/H2O]ice ISO observations; as with previous models, accretion and reaction of oxygen atoms are necessary although a high O atom abundance can still be derived from the CO that remains in the gas. The observational constraints on solid and gaseous molecular oxygen are both met in this model. However, we find that we cannot explain the lowest H2O abundances seen by SWAS or the highest atomic carbon abundances found in molecular clouds; additional chemical processes are required and possible candidates are given. One prediction of models of this type is that there should be some regions of molecular clouds which contain high gas phase abundances of H2O, O2 and NO. A further consequence, we find, is that interstellar grain mantles could be rich in NH2OH and NO2. The search for these regions, as well as NH2OH and NO2 in ices and in hot cores, is an important further test of this scenario. The model can give good agreement with observations of simple molecules in dark molecular clouds such as TMC-1 and L134N. Despite the fact that S atoms are assumed to be continously

Mathematical modeling of molecular diffusion through mucus

PubMed Central

Cu, Yen; Saltzman, W. Mark

2008-01-01

The rate of molecular transport through the mucus gel can be an important determinant of efficacy for therapeutic agents delivered by oral, intranasal, intravaginal/rectal, and intraocular routes. Transport through mucus can be described by mathematical models based on principles of physical chemistry and known characteristics of the mucus gel, its constituents, and of the drug itself. In this paper, we review mathematical models of molecular diffusion in mucus, as well as the techniques commonly used to measure diffusion of solutes in the mucus gel, mucus gel mimics, and mucosal epithelia. PMID:19135488

Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins.

PubMed

Karczyńska, Agnieszka S; Czaplewski, Cezary; Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Liwo, Adam

2017-12-05

Molecular simulations restrained to single or multiple templates are commonly used in protein-structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template-restrained canonical molecular dynamics (MD), multiplexed replica-exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse-grained UNRES force field on nine selected proteins, with pseudo-harmonic log-Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non-ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor-quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Propagation Modeling and Analysis of Molecular Motors in Molecular Communication.

PubMed

Chahibi, Youssef; Akyildiz, Ian F; Balasingham, Ilangko

2016-12-01

Molecular motor networks (MMNs) are networks constructed from molecular motors to enable nanomachines to perform coordinated tasks of sensing, computing, and actuation at the nano- and micro- scales. Living cells are naturally enabled with this same mechanism to establish point-to-point communication between different locations inside the cell. Similar to a railway system, the cytoplasm contains an intricate infrastructure of tracks, named microtubules, interconnecting different internal components of the cell. Motor proteins, such as kinesin and dynein, are able to travel along these tracks directionally, carrying with them large molecules that would otherwise be unreliably transported across the cytoplasm using free diffusion. Molecular communication has been previously proposed for the design and study of MMNs. However, the topological aspects of MMNs, including the effects of branches, have been ignored in the existing studies. In this paper, a physical end-to-end model for MMNs is developed, considering the location of the transmitter node, the network topology, and the receiver nodes. The end-to-end gain and group delay are considered as the performance measures, and analytical expressions for them are derived. The analytical model is validated by Monte-Carlo simulations and the performance of MMNs is analyzed numerically. It is shown that, depending on their nature and position, MMN nodes create impedance effects that are critical for the overall performance. This model could be applied to assist the design of artificial MMNs and to study cargo transport in neurofilaments to elucidate brain diseases related to microtubule jamming.

Some Reflections on the Use and Abuse of Molecular Models

ERIC Educational Resources Information Center

Petersen, Quentin R.

1970-01-01

Describes the historical applications of molecular models and the controversies which they produced. The author discusses types of molecular models from the van't Hoff and Kekule models to the more recently developed ones. He presents a new model which was constructed to overcome the disadvantages of (1) falling apart, (2) inaccurate angles, (3)…

Digital Learning Material for Model Building in Molecular Biology

ERIC Educational Resources Information Center

Aegerter-Wilmsen, Tinri; Janssen, Fred; Hartog, Rob; Bisseling, Ton

2005-01-01

Building models to describe processes forms an essential part of molecular biology research. However, in molecular biology curricula little attention is generally being paid to the development of this skill. In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about…

Additional molecular findings in 11p15-associated imprinting disorders: an urgent need for multi-locus testing.

PubMed

Eggermann, Thomas; Heilsberg, Ann-Kathrin; Bens, Susanne; Siebert, Reiner; Beygo, Jasmin; Buiting, Karin; Begemann, Matthias; Soellner, Lukas

2014-07-01

The chromosomal region 11p15 contains two imprinting control regions (ICRs) and is a key player in molecular processes regulated by genomic imprinting. Genomic as well as epigenetic changes affecting 11p15 are associated either with Silver-Russell syndrome (SRS) or Beckwith-Wiedemann syndrome (BWS). In the last years, a growing number of patients affected by imprinting disorders (IDs) have reported carrying the disease-specific 11p15 hypomethylation patterns as well as methylation changes at imprinted loci at other chromosomal sites (multi-locus methylation defects, MLMD). Furthermore, in several patients, molecular alterations (e.g., uniparental disomies, UPDs) additional to the primary epimutations have been reported. To determine the frequency and distribution of mutations and epimutations in patients referred as SRS or BWS for genetic testing, we retrospectively ascertained our routine patient cohort consisting of 711 patients (SRS, n = 571; BWS, n = 140). As this cohort represents the typical cohort in a routine diagnostic lab without clinical preselection, the detection rates were much lower than those reported from clinically characterized cohorts in the literature (SRS, 19.9%; BWS, 28.6%). Among the molecular subgroups known to be predisposed to MLMD, the frequencies corresponded to that in the literature (SRS, 7.1% in ICR1 hypomethylation carriers; BWS, 20.8% in ICR2 hypomethylation patients). In several patients, more than one epigenetic or genetic disturbance could be identified. Our study illustrates that the complex molecular alterations as well as the overlapping and sometimes unusual clinical findings in patients with imprinting disorders (IDs) often make the decision for a specific imprinting disorder test difficult. We therefore suggest to implement molecular assays in routine ID diagnostics which allow the detection of a broad range of (epi)mutation types (epimutations, UPDs, chromosomal imbalances) and cover the clinically most relevant known ID

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Water models based on a single potential energy surface and different molecular degrees of freedom

NASA Astrophysics Data System (ADS)

Saint-Martin, Humberto; Hernández-Cobos, Jorge; Ortega-Blake, Iván

2005-06-01

Up to now it has not been possible to neatly assess whether a deficient performance of a model is due to poor parametrization of the force field or the lack of inclusion of enough molecular properties. This work compares several molecular models in the framework of the same force field, which was designed to include many-body nonadditive effects: (a) a polarizable and flexible molecule with constraints that account for the quantal nature of the vibration [B. Hess, H. Saint-Martin, and H. J. C. Berendsen, J. Chem. Phys. 116, 9602 (2002), H. Saint-Martin, B. Hess, and H. J. C. Berendsen, J. Chem. Phys. 120, 11133 (2004)], (b) a polarizable and classically flexible molecule [H. Saint-Martin, J. Hernández-Cobos, M. I. Bernal-Uruchurtu, I. Ortega-Blake, and H. J. C. Berendsen, J. Chem. Phys. 113, 10899 (2000)], (c) a polarizable and rigid molecule, and finally (d) a nonpolarizable and rigid molecule. The goal is to determine how significant the different molecular properties are. The results indicate that all factors—nonadditivity, polarizability, and intramolecular flexibility—are important. Still, approximations can be made in order to diminish the computational cost of the simulations with a small decrease in the accuracy of the predictions, provided that those approximations are counterbalanced by the proper inclusion of an effective molecular property, that is, an average molecular geometry or an average dipole. Hence instead of building an effective force field by parametrizing it in order to reproduce the properties of a specific phase, a building approach is proposed that is based on adequately restricting the molecular flexibility and/or polarizability of a model potential fitted to unimolecular properties, pair interactions, and many-body nonadditive contributions. In this manner, the same parental model can be used to simulate the same substance under a wide range of thermodynamic conditions. An additional advantage of this approach is that, as the force

Modeling and Bio molecular Self-assembly via Molecular Dynamics and Dissipative Particle Dynamics

NASA Astrophysics Data System (ADS)

Rakesh, L.

2009-09-01

Surfactants like materials can be used to increase the solubility of poorly soluble drugs in water and to increase drug bioavailability. A typical case study will be demonstrated using DPD simulation to model the distribution of anti-inflammatory drug molecules. Computer simulation is a convenient approach to understand drug distribution and solubility concepts without much wastage and costly experiments in the laboratory. Often in molecular dynamics (MD) the atoms are represented explicitly and the equation of motion as described by Newtonian dynamics is integrated explicitly. MD has been used to study spontaneous formation of micelles by hydrophobic molecules with amphiphilic head groups in bulk water, as well as stability of pre-configured micelles and membranes. DPD is a state-of the- art mesoscale simulation, it is a more recent molecular dynamics technique, originally developed for simulating complex fluids but lately also applied to membrane dynamics, hemodynamic in biomedical applications. Such fluids pervade industrial research from paints to pharmaceuticals and from cosmetics to the controlled release of drugs. Dissipative particle dynamics (DPD) can provide structural and dynamic properties of fluids in equilibrium, under shear or confined to narrow cavities, at length- and time-scales beyond the scope of traditional atomistic molecular dynamics simulation methods. Mesoscopic particles are used to represent clusters of molecules. The interaction conserves mass and momentum and as a consequence the dynamics is consistent with Navier-Stokes equations. In addition to the conservative forces, stochastic drive and dissipation is introduced to represent internal degrees of freedom in the mesoscopic particles. In this research, an initial study is being conducted using the aqueous solubilization of the nonsteroidal, anti-inflammatory drug is studied theoretically in micellar solution of nonionic (dodecyl hexa(ethylene oxide), C12E6) surfactants possessing the

Extending rule-based methods to model molecular geometry and 3D model resolution.

PubMed

Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

2016-08-01

Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models

The effect of tailor-made additives on crystal growth of methyl paraben: Experiments and modelling

NASA Astrophysics Data System (ADS)

Cai, Zhihui; Liu, Yong; Song, Yang; Guan, Guoqiang; Jiang, Yanbin

2017-03-01

In this study, methyl paraben (MP) was selected as the model component, and acetaminophen (APAP), p-methyl acetanilide (PMAA) and acetanilide (ACET), which share the similar molecular structure as MP, were selected as the three tailor-made additives to study the effect of tailor-made additives on the crystal growth of MP. HPLC results indicated that the MP crystals induced by the three additives contained MP only. Photographs of the single crystals prepared indicated that the morphology of the MP crystals was greatly changed by the additives, but PXRD and single crystal diffraction results illustrated that the MP crystals were the same polymorph only with different crystal habits, and no new crystal form was found compared with other references. To investigate the effect of the additives on the crystal growth, the interaction between additives and facets was discussed in detail using the DFT methods and MD simulations. The results showed that APAP, PMAA and ACET would be selectively adsorbed on the growth surfaces of the crystal facets, which induced the change in MP crystal habits.

Realistic molecular model of kerogen's nanostructure

NASA Astrophysics Data System (ADS)

Bousige, Colin; Ghimbeu, Camélia Matei; Vix-Guterl, Cathie; Pomerantz, Andrew E.; Suleimenova, Assiya; Vaughan, Gavin; Garbarino, Gaston; Feygenson, Mikhail; Wildgruber, Christoph; Ulm, Franz-Josef; Pellenq, Roland J.-M.; Coasne, Benoit

2016-05-01

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp2/sp3 hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.

Realistic molecular model of kerogen's nanostructure.

PubMed

Bousige, Colin; Ghimbeu, Camélia Matei; Vix-Guterl, Cathie; Pomerantz, Andrew E; Suleimenova, Assiya; Vaughan, Gavin; Garbarino, Gaston; Feygenson, Mikhail; Wildgruber, Christoph; Ulm, Franz-Josef; Pellenq, Roland J-M; Coasne, Benoit

2016-05-01

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp(2)/sp(3) hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.

Skeletal dosimetry models for alpha-particles for use in molecular radiotherapy

NASA Astrophysics Data System (ADS)

Watchman, Christopher J.

Molecular radiotherapy is a cancer treatment methodology whereby a radionuclide is combined with a biologically active molecule to preferentially target cancer cells. Alpha-particle emitting radionuclides show significant potential for use in molecular radiotherapy due to the short range of the alpha-particles in tissue and their high rates of energy deposition. Current radiation dosimetry models used to assess alpha emitter dose in the skeleton were developed originally for occupational applications. In medical dosimetry, individual variability in uptake, translocation and other biological factors can result in poor correlation of clinical outcome with marrow dose estimates determined using existing skeletal models. Methods presented in this work were developed in response to the need for dosimetry models which account for these biological and patient-specific factors. Dosimetry models are presented for trabecular bone alpha particle dosimetry as well as a model for cortical bone dosimetry. These radiation transport models are the 3D chord-based infinite spongiosa transport model (3D-CBIST) and the chord-based infinite cortical transport model (CBICT), respectively. Absorbed fraction data for several skeletal tissues for several subjects are presented. Each modeling strategy accounts for biological parameters, such as bone marrow cellularity, not previously incorporated into alpha-particle skeletal dosimetry models used in radiation protection. Using these data a study investigating the variability in alpha-particle absorbed fractions in the human skeleton is also presented. Data is also offered relating skeletal tissue masses in individual bone sites for a range of ages. These data are necessary for dose calculations and have previously only been available as whole body tissue masses. A revised 3D-CBIST model is also presented which allows for changes in endosteum thickness to account for revised target cell location of tissues involved in the radiological

Insight into the interaction mechanism of human SGLT2 with its inhibitors: 3D-QSAR studies, homology modeling, and molecular docking and molecular dynamics simulations.

PubMed

Dong, Lili; Feng, Ruirui; Bi, Jiawei; Shen, Shengqiang; Lu, Huizhe; Zhang, Jianjun

2018-03-06

Human sodium-dependent glucose co-transporter 2 (hSGLT2) is a crucial therapeutic target in the treatment of type 2 diabetes. In this study, both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to generate three-dimensional quantitative structure-activity relationship (3D-QSAR) models. In the most accurate CoMFA-based and CoMSIA-based QSAR models, the cross-validated coefficients (r 2 cv ) were 0.646 and 0.577, respectively, while the non-cross-validated coefficients (r 2 ) were 0.997 and 0.991, respectively, indicating that both models were reliable. In addition, we constructed a homology model of hSGLT2 in the absence of a crystal structure. Molecular docking was performed to explore the bonding mode of inhibitors to the active site of hSGLT2. Molecular dynamics (MD) simulations and binding free energy calculations using MM-PBSA and MM-GBSA were carried out to further elucidate the interaction mechanism. With regards to binding affinity, we found that hydrogen-bond interactions of Asn51 and Glu75, located in the active site of hSGLT2, with compound 40 were critical. Hydrophobic and electrostatic interactions were shown to enhance activity, in agreement with the results obtained from docking and 3D-QSAR analysis. Our study results shed light on the interaction mode between inhibitors and hSGLT2 and may aid in the development of C-aryl glucoside SGLT2 inhibitors.

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E.

2014-01-01

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand the structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as means to sample conformational space for a better understanding of the relevance of a given model. From this discussion, the major limitations with modeling, in general, were highlighted. These are the difficult issues in sampling conformational space effectively—the multiple minima or conformational sampling problems—and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These are discussed in detail in this unit. PMID:18428877

Phaser.MRage: automated molecular replacement.

PubMed

Bunkóczi, Gábor; Echols, Nathaniel; McCoy, Airlie J; Oeffner, Robert D; Adams, Paul D; Read, Randy J

2013-11-01

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement.

Exploring Organic Mechanistic Puzzles with Molecular Modeling

ERIC Educational Resources Information Center

Horowitz, Gail; Schwartz, Gary

2004-01-01

The molecular modeling was used to reinforce more general skills such as deducing and drawing reaction mechanisms, analyzing reaction kinetics and thermodynamics and drawing reaction coordinate energy diagrams. This modeling was done through the design of mechanistic puzzles, involving reactions not familiar to the students.

A collaborative molecular modeling environment using a virtual tunneling service.

PubMed

Lee, Jun; Kim, Jee-In; Kang, Lin-Woo

2012-01-01

Collaborative researches of three-dimensional molecular modeling can be limited by different time zones and locations. A networked virtual environment can be utilized to overcome the problem caused by the temporal and spatial differences. However, traditional approaches did not sufficiently consider integration of different computing environments, which were characterized by types of applications, roles of users, and so on. We propose a collaborative molecular modeling environment to integrate different molecule modeling systems using a virtual tunneling service. We integrated Co-Coot, which is a collaborative crystallographic object-oriented toolkit, with VRMMS, which is a virtual reality molecular modeling system, through a collaborative tunneling system. The proposed system showed reliable quantitative and qualitative results through pilot experiments.

A Collaborative Molecular Modeling Environment Using a Virtual Tunneling Service

PubMed Central

Lee, Jun; Kim, Jee-In; Kang, Lin-Woo

2012-01-01

Collaborative researches of three-dimensional molecular modeling can be limited by different time zones and locations. A networked virtual environment can be utilized to overcome the problem caused by the temporal and spatial differences. However, traditional approaches did not sufficiently consider integration of different computing environments, which were characterized by types of applications, roles of users, and so on. We propose a collaborative molecular modeling environment to integrate different molecule modeling systems using a virtual tunneling service. We integrated Co-Coot, which is a collaborative crystallographic object-oriented toolkit, with VRMMS, which is a virtual reality molecular modeling system, through a collaborative tunneling system. The proposed system showed reliable quantitative and qualitative results through pilot experiments. PMID:22927721

Manipulating crystallization with molecular additives.

PubMed

Shtukenberg, Alexander G; Lee, Stephanie S; Kahr, Bart; Ward, Michael D

2014-01-01

Given the importance of organic crystals in a wide range of industrial applications, the chemistry, biology, materials science, and chemical engineering communities have focused considerable attention on developing methods to control crystal structure, size, shape, and orientation. Tailored additives have been used to control crystallization to great effect, presumably by selectively binding to particular crystallographic surfaces and sites. However, substantial knowledge gaps still exist in the fundamental mechanisms that govern the formation and growth of organic crystals in both the absence and presence of additives. In this review, we highlight research discoveries that reveal the role of additives, either introduced by design or present adventitiously, on various stages of formation and growth of organic crystals, including nucleation, dislocation spiral growth mechanisms, growth inhibition, and nonclassical crystal morphologies. The insights from these investigations and others of their kind are likely to guide the development of innovative methods to manipulate crystallization for a wide range of materials and applications.

Uncovering molecular processes in crystal nucleation and growth by using molecular simulation.

PubMed

Anwar, Jamshed; Zahn, Dirk

2011-02-25

Exploring nucleation processes by molecular simulation provides a mechanistic understanding at the atomic level and also enables kinetic and thermodynamic quantities to be estimated. However, whilst the potential for modeling crystal nucleation and growth processes is immense, there are specific technical challenges to modeling. In general, rare events, such as nucleation cannot be simulated using a direct "brute force" molecular dynamics approach. The limited time and length scales that are accessible by conventional molecular dynamics simulations have inspired a number of advances to tackle problems that were considered outside the scope of molecular simulation. While general insights and features could be explored from efficient generic models, new methods paved the way to realistic crystal nucleation scenarios. The association of single ions in solvent environments, the mechanisms of motif formation, ripening reactions, and the self-organization of nanocrystals can now be investigated at the molecular level. The analysis of interactions with growth-controlling additives gives a new understanding of functionalized nanocrystals and the precipitation of composite materials. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ridge, Lasso and Bayesian additive-dominance genomic models.

PubMed

Azevedo, Camila Ferreira; de Resende, Marcos Deon Vilela; E Silva, Fabyano Fonseca; Viana, José Marcelo Soriano; Valente, Magno Sávio Ferreira; Resende, Márcio Fernando Ribeiro; Muñoz, Patricio

2015-08-25

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Two-Dimensional Model of Scrolled Packings of Molecular Nanoribbons

NASA Astrophysics Data System (ADS)

Savin, A. V.; Mazo, M. A.

2018-04-01

A simplified model of the in-plane molecular chain, allowing the description of folded and scrolled packings of molecular nanoribbons of different structures, is proposed. Using this model, possible steady states of single-layer nanoribbons scrolls of graphene, graphane, fluorographene, and fluorographane (graphene hydrogenated on the one side and fluorinated on the other side) are obtained. Their stability is demonstrated and their energy is calculated as a function of the nanoribbon length. It is shown that the scrolled packing is the most energetically favorable nanoribbon conformation at long lengths. The existences of scrolled packings for fluorographene nanoribbons and the existence of two different scroll types corresponding to left- and right-hand Archimedean spirals for fluorographane nanoribbons in the chain model are shown for the first time. The simplicity of the proposed model makes it possible to consider the dynamics of scrolls of rather long molecular nanoribbons at long enough time intervals.

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

Modeling inelastic phonon scattering in atomic- and molecular-wire junctions

NASA Astrophysics Data System (ADS)

Paulsson, Magnus; Frederiksen, Thomas; Brandbyge, Mads

2005-11-01

Computationally inexpensive approximations describing electron-phonon scattering in molecular-scale conductors are derived from the nonequilibrium Green’s function method. The accuracy is demonstrated with a first-principles calculation on an atomic gold wire. Quantitative agreement between the full nonequilibrium Green’s function calculation and the newly derived expressions is obtained while simplifying the computational burden by several orders of magnitude. In addition, analytical models provide intuitive understanding of the conductance including nonequilibrium heating and provide a convenient way of parameterizing the physics. This is exemplified by fitting the expressions to the experimentally observed conductances through both an atomic gold wire and a hydrogen molecule.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

ERIC Educational Resources Information Center

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

3D-Lab: a collaborative web-based platform for molecular modeling.

PubMed

Grebner, Christoph; Norrby, Magnus; Enström, Jonatan; Nilsson, Ingemar; Hogner, Anders; Henriksson, Jonas; Westin, Johan; Faramarzi, Farzad; Werner, Philip; Boström, Jonas

2016-09-01

The use of 3D information has shown impact in numerous applications in drug design. However, it is often under-utilized and traditionally limited to specialists. We want to change that, and present an approach making 3D information and molecular modeling accessible and easy-to-use 'for the people'. A user-friendly and collaborative web-based platform (3D-Lab) for 3D modeling, including a blazingly fast virtual screening capability, was developed. 3D-Lab provides an interface to automatic molecular modeling, like conformer generation, ligand alignments, molecular dockings and simple quantum chemistry protocols. 3D-Lab is designed to be modular, and to facilitate sharing of 3D-information to promote interactions between drug designers. Recent enhancements to our open-source virtual reality tool Molecular Rift are described. The integrated drug-design platform allows drug designers to instantaneously access 3D information and readily apply advanced and automated 3D molecular modeling tasks, with the aim to improve decision-making in drug design projects.

Understanding DNA under oxidative stress and sensitization: the role of molecular modeling

PubMed Central

Dumont, Elise; Monari, Antonio

2015-01-01

DNA is constantly exposed to damaging threats coming from oxidative stress, i.e., from the presence of free radicals and reactive oxygen species. Sensitization from exogenous and endogenous compounds that strongly enhance the frequency of light-induced lesions also plays an important role. The experimental determination of DNA lesions, though a difficult subject, is somehow well established and allows to elucidate even extremely rare DNA lesions. In parallel, molecular modeling has become fundamental to clearly understand the fine mechanisms related to DNA defects induction. Indeed, it offers an unprecedented possibility to get access to an atomistic or even electronic resolution. Ab initio molecular dynamics may also describe the time-evolution of the molecular system and its reactivity. Yet the modeling of DNA (photo-)reactions does necessitate elaborate multi-scale methodologies to tackle a damage induction reactivity that takes place in a complex environment. The double-stranded DNA environment is first characterized by a very high flexibility, but also a strongly inhomogeneous electrostatic embedding. Additionally, one aims at capturing more subtle effects, such as the sequence selectivity which is of critical important for DNA damage. The structure and dynamics of the DNA/sensitizers complexes, as well as the photo-induced electron- and energy-transfer phenomena taking place upon sensitization, should be carefully modeled. Finally the factors inducing different repair ratios for different lesions should also be rationalized. In this review we will critically analyze the different computational strategies used to model DNA lesions. A clear picture of the complex interplay between reactivity and structural factors will be sketched. The use of proper multi-scale modeling leads to the in-depth comprehension of DNA lesions mechanisms and also to the rational design of new chemo-therapeutic agents. PMID:26236706

The activation strain model and molecular orbital theory

PubMed Central

Wolters, Lando P; Bickelhaupt, F Matthias

2015-01-01

The activation strain model is a powerful tool for understanding reactivity, or inertness, of molecular species. This is done by relating the relative energy of a molecular complex along the reaction energy profile to the structural rigidity of the reactants and the strength of their mutual interactions: ΔE(ζ) = ΔEstrain(ζ) + ΔEint(ζ). We provide a detailed discussion of the model, and elaborate on its strong connection with molecular orbital theory. Using these approaches, a causal relationship is revealed between the properties of the reactants and their reactivity, e.g., reaction barriers and plausible reaction mechanisms. This methodology may reveal intriguing parallels between completely different types of chemical transformations. Thus, the activation strain model constitutes a unifying framework that furthers the development of cross-disciplinary concepts throughout various fields of chemistry. We illustrate the activation strain model in action with selected examples from literature. These examples demonstrate how the methodology is applied to different research questions, how results are interpreted, and how insights into one chemical phenomenon can lead to an improved understanding of another, seemingly completely different chemical process. WIREs Comput Mol Sci 2015, 5:324–343. doi: 10.1002/wcms.1221 PMID:26753009

Combined proportional and additive residual error models in population pharmacokinetic modelling.

PubMed

Proost, Johannes H

2017-11-15

In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking. The theoretical background of the methods is described. Method VAR assumes that the variance of the residual error is the sum of the statistically independent proportional and additive components; this method can be coded in three ways. Method SD assumes that the standard deviation of the residual error is the sum of the proportional and additive components. Using datasets from literature and simulations based on these datasets, the methods are compared using NONMEM. The different coding of methods VAR yield identical results. Using method SD, the values of the parameters describing residual error are lower than for method VAR, but the values of the structural parameters and their inter-individual variability are hardly affected by the choice of the method. Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Agronomic Traits and Molecular Marker Identification of Wheat–Aegilops caudata Addition Lines

PubMed Central

Gong, Wenping; Han, Ran; Li, Haosheng; Song, Jianmin; Yan, Hongfei; Li, Genying; Liu, Aifeng; Cao, Xinyou; Guo, Jun; Zhai, Shengnan; Cheng, Dungong; Zhao, Zhendong; Liu, Cheng; Liu, Jianjun

2017-01-01

Aegilops caudata is an important gene source for wheat breeding. Intensive evaluation of its utilization value is an essential first step prior to its application in breeding. In this research, the agronomical and quality traits of Triticum aestivum-Ae. caudata additions B–G (homoeologous groups not identified) were analyzed and evaluated. Disease resistance tests showed that chromosome D of Ae. caudata might possess leaf rust resistance, and chromosome E might carry stem rust and powdery mildew resistance genes. Investigations into agronomical traits suggested that the introduction of the Ae. caudata chromosome in addition line F could reduce plant height. Grain quality tests showed that the introduction of chromosomes E or F into wheat could increase its protein and wet gluten content. Therefore, wheat-Ae. caudata additions D–F are all potentially useful candidates for chromosome engineering activities to create useful wheat-alien chromosome introgressions. A total of 55 EST-based molecular markers were developed and then used to identify the chromosome homoeologous group of each of the Ae. caudata B–G chromosomes. Marker analysis indicated that the Ae. caudata chromosomes in addition lines B to G were structurally altered, therefore, a large population combined with intensive screening pressure should be taken into consideration when inducing and screening for wheat-Ae. caudata compensating translocations. Marker data also indicated that the Ae. caudata chromosomes in addition lines C–F were 5C, 6C, 7C, and 3C, respectively, while the homoeologous group of chromosomes B and G of Ae. caudata are as yet undetermined and need further research. PMID:29075275

Phaser.MRage: automated molecular replacement

PubMed Central

Bunkóczi, Gábor; Echols, Nathaniel; McCoy, Airlie J.; Oeffner, Robert D.; Adams, Paul D.; Read, Randy J.

2013-01-01

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement. PMID:24189240

New cytotoxic benzosuberene analogs. Synthesis, molecular modeling and biological evaluation.

PubMed

Chen, Zecheng; Maderna, Andreas; Sukuru, Sai Chetan K; Wagenaar, Melissa; O'Donnell, Christopher J; Lam, My-Hanh; Musto, Sylvia; Loganzo, Frank

2013-12-15

In this Letter we describe the synthesis and biological evaluation of new benzosuberene analogs with structural modifications on the B-ring. The focus was initially to probe the chemical space around the B-ring C-8 position. This position was readily available for derivatization chemistry using our recently developed new synthesis for this compound class. Furthermore, we describe two new B-ring analogs, one containing a diene and the other a cyclic ether group. Both new analogs show excellent potencies in tumor cell proliferation assays. In addition, we describe molecular modeling studies that provide a binding rationale for reference compound 8 in the colchicine binding site using the known colchicine crystal structure. We also examine whether the cell based potency data obtained with selected new analogs are supported by modeling results. Copyright © 2013 Elsevier Ltd. All rights reserved.

Novel thrombopoietin mimetic peptides bind c-Mpl receptor: Synthesis, biological evaluation and molecular modeling.

PubMed

Liu, Yaquan; Tian, Fang; Zhi, Dejuan; Wang, Haiqing; Zhao, Chunyan; Li, Hongyu

2017-02-01

Thrombopoietin (TPO) acts in promoting the proliferation of hematopoietic stem cells and by initiating specific maturation events in megakaryocytes. Now, TPO-mimetic peptides with amino acid sequences unrelated to TPO are of considerable pharmaceutical interest. In the present paper, four new TPO mimetic peptides that bind and activate c-Mpl receptor have been identified, synthesized and tested by Dual-Luciferase reporter gene assay for biological activities. The molecular modeling research was also approached to understand key molecular mechanisms and structural features responsible for peptide binding with c-Mpl receptor. The results presented that three of four mimetic peptides showed significant activities. In addition, the molecular modeling approaches proved hydrophobic interactions were the driven positive forces for binding behavior between peptides and c-Mpl receptor. TPO peptide residues in P7, P13 and P7' positions were identified by the analysis of hydrogen bonds and energy decompositions as the key ones for benefiting better biological activities. Our data suggested the synthesized peptides have considerable potential for the future development of stable and highly active TPO mimetic peptides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification.

PubMed

Gao, Jing; Zhong, Shaoyun; Zhou, Yanting; He, Han; Peng, Shuying; Zhu, Zhenyun; Liu, Xing; Zheng, Jing; Xu, Bin; Zhou, Hu

2017-06-06

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

A molecular model for proflavine-DNA intercalation.

PubMed Central

Neidle, S; Pearl, L H; Herzyk, P; Berman, H M

1988-01-01

A molecular model has been derived for the intercalation of proflavine into the CpG site of the decamer duplex of d(GATACGATAC). The starting geometry of the intercalation site was taken from previous crystallographic studies on the d(CpG)-proflavine complex, and molecular mechanics used to obtain a stereochemically acceptable structure. This has widened grooves compared to standard A- or B- double helices, as well as distinct conformational, roll, twist and tilt features. PMID:3174439

Nonmetallic electronegativity equalization and point-dipole interaction model including exchange interactions for molecular dipole moments and polarizabilities.

PubMed

Smalø, Hans S; Astrand, Per-Olof; Jensen, Lasse

2009-07-28

The electronegativity equalization model (EEM) has been combined with a point-dipole interaction model to obtain a molecular mechanics model consisting of atomic charges, atomic dipole moments, and two-atom relay tensors to describe molecular dipole moments and molecular dipole-dipole polarizabilities. The EEM has been phrased as an atom-atom charge-transfer model allowing for a modification of the charge-transfer terms to avoid that the polarizability approaches infinity for two particles at infinite distance and for long chains. In the present work, these shortcomings have been resolved by adding an energy term for transporting charges through individual atoms. A Gaussian distribution is adopted for the atomic charge distributions, resulting in a damping of the electrostatic interactions at short distances. Assuming that an interatomic exchange term may be described as the overlap between two electronic charge distributions, the EEM has also been extended by a short-range exchange term. The result is a molecular mechanics model where the difference of charge transfer in insulating and metallic systems is modeled regarding the difference in bond length between different types of system. For example, the model is capable of modeling charge transfer in both alkanes and alkenes with alternating double bonds with the same set of carbon parameters only relying on the difference in bond length between carbon sigma- and pi-bonds. Analytical results have been obtained for the polarizability of a long linear chain. These results show that the model is capable of describing the polarizability scaling both linearly and nonlinearly with the size of the system. Similarly, a linear chain with an end atom with a high electronegativity has been analyzed analytically. The dipole moment of this model system can either be independent of the length or increase linearly with the length of the chain. In addition, the model has been parametrized for alkane and alkene chains with data

Clinical, Morphological, and Molecular Evaluations of Bone Regeneration With an Additive Manufactured Osteosynthesis Plate.

PubMed

Thor, Andreas; Palmquist, Anders; Hirsch, Jan-Michaél; Rännar, Lars-Erik; Dérand, Per; Omar, Omar

2016-10-01

There is limited information on the biological status of bone regenerated with microvascular fibula flap combined with biomaterials. This paper describes the clinical, histological, ultrastructural, and molecular picture of bone regenerated with patient-customized plate, used for mandibular reconstruction in combination with microvascular osteomyocutaneous fibula flap. The plate was virtually planned and additively manufactured using electron beam melting. This plate was retrieved from the patient after 33 months. Microcomputed tomography, backscattered-scanning electron microscopy, histology, and quantitative-polymerase chain reaction were employed to evaluate the regenerated bone and the flap bone associated with the retrieved plate. At retrieval, the posterior two-thirds of the plate were in close adaptation with the underlying flap, whereas soft tissue was observed between the native mandible and the anterior one-third. The histological and structural analyses showed new bone regeneration, ingrowth, and osseointegration of the posterior two-thirds. The histological observations were supported by the gene expression analysis showing higher expression of bone formation and remodeling genes under the posterior two-thirds compared with the anterior one-third of the plate. The observation of osteocytes in the flap indicated its viability. The present data endorse the suitability of the customized, additively manufactured plate for the vascularized fibula mandibular reconstruction. Furthermore, the combination of the analytical techniques provides possibilities to deduce the structural and molecular characteristics of bone regenerated using this procedure.

Mobile modeling in the molecular sciences

EPA Science Inventory

The art of modeling in the molecular sciences is highly dependent on both the available computational technology, underlying data, and ability to collaborate. With the ever increasing market share of mobile devices, it is assumed by many that tablets will overtake laptops as the...

Reasoning with Atomic-Scale Molecular Dynamic Models

ERIC Educational Resources Information Center

Pallant, Amy; Tinker, Robert F.

2004-01-01

The studies reported in this paper are an initial effort to explore the applicability of computational models in introductory science learning. Two instructional interventions are described that use a molecular dynamics model embedded in a set of online learning activities with middle and high school students in 10 classrooms. The studies indicate…

Tangible Models and Haptic Representations Aid Learning of Molecular Biology Concepts

ERIC Educational Resources Information Center

Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Polyimide processing additives

NASA Technical Reports Server (NTRS)

Fletcher, James C. (Inventor); Pratt, J. Richard (Inventor); St.clair, Terry L. (Inventor); Stoakley, Diane M. (Inventor); Burks, Harold D. (Inventor)

1992-01-01

A process for preparing polyimides having enhanced melt flow properties is described. The process consists of heating a mixture of a high molecular weight poly-(amic acid) or polyimide with a low molecular weight amic acid or imide additive in the range of 0.05 to 15 percent by weight of additive. The polyimide powders so obtained show improved processability, as evidenced by lower melt viscosity by capillary rheometry. Likewise, films prepared from mixtures of polymers with additives show improved processability with earlier onset of stretching by TMA.

Polyimide processing additives

NASA Technical Reports Server (NTRS)

Pratt, J. Richard (Inventor); St.clair, Terry L. (Inventor); Stoakley, Diane M. (Inventor); Burks, Harold D. (Inventor)

1993-01-01

A process for preparing polyimides having enhanced melt flow properties is described. The process consists of heating a mixture of a high molecular weight poly-(amic acid) or polyimide with a low molecular weight amic acid or imide additive in the range of 0.05 to 15 percent by weight of the additive. The polyimide powders so obtained show improved processability, as evidenced by lower melt viscosity by capillary rheometry. Likewise, films prepared from mixtures of polymers with additives show improved processability with earlier onset of stretching by TMA.

Introducing Molecular Life Science Students to Model Building Using Computer Simulations

ERIC Educational Resources Information Center

Aegerter-Wilmsen, Tinri; Kettenis, Dik; Sessink, Olivier; Hartog, Rob; Bisseling, Ton; Janssen, Fred

2006-01-01

Computer simulations can facilitate the building of models of natural phenomena in research, such as in the molecular life sciences. In order to introduce molecular life science students to the use of computer simulations for model building, a digital case was developed in which students build a model of a pattern formation process in…

Additive mixed effect model for recurrent gap time data.

PubMed

Ding, Jieli; Sun, Liuquan

2017-04-01

Gap times between recurrent events are often of primary interest in medical and observational studies. The additive hazards model, focusing on risk differences rather than risk ratios, has been widely used in practice. However, the marginal additive hazards model does not take the dependence among gap times into account. In this paper, we propose an additive mixed effect model to analyze gap time data, and the proposed model includes a subject-specific random effect to account for the dependence among the gap times. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite sample behavior of the proposed methods is evaluated through simulation studies, and an application to a data set from a clinic study on chronic granulomatous disease is provided.

Molecular modeling studies of substrate binding by penicillin acylase.

PubMed

Chilov, G G; Stroganov, O V; Svedas, V K

2008-01-01

Molecular modeling has revealed intimate details of the mechanism of binding of natural substrate, penicillin G (PG), in the penicillin acylase active center and solved questions raised by analysis of available X-ray structures, mimicking Michaelis complex, which substantially differ in the binding pattern of the PG leaving group. Three MD trajectories were launched, starting from PDB complexes of the inactive mutant enzyme with PG (1FXV) and native penicillin acylase with sluggishly hydrolyzed substrate analog penicillin G sulfoxide (1GM9), or from the complex obtained by PG docking. All trajectories converged to a similar PG binding mode, which represented the near-to-attack conformation, consistent with chemical criteria of how reactive Michaelis complex should look. Simulated dynamic structure of the enzyme-substrate complex differed significantly from 1FXV, resembling rather 1GM9; however, additional contacts with residues bG385, bS386, and bN388 have been found, which were missing in X-ray structures. Combination of molecular docking and molecular dynamics also clarified the nature of extremely effective phenol binding in the hydrophobic pocket of penicillin acylase, which lacked proper explanation from crystallographic experiments. Alternative binding modes of phenol were probed, and corresponding trajectories converged to a single binding pattern characterized by a hydrogen bond between the phenol hydroxyl and the main chain oxygen of bS67, which was not evident from the crystal structure. Observation of the trajectory, in which phenol moved from its steady bound to pre-dissociation state, mapped the consequence of molecular events governing the conformational transitions in a coil region a143-a146 coupled to substrate binding and release of the reaction products. The current investigation provided information on dynamics of the conformational transitions accompanying substrate binding and significance of poorly structured and flexible regions in

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

Applications of molecular modeling in coal research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, G.A.; Faulon, J.L.

Over the past several years, molecular modeling has been applied to study various characteristics of coal molecular structures. Powerful workstations coupled with molecular force-field-based software packages have been used to study coal and coal-related molecules. Early work involved determination of the minimum-energy three-dimensional conformations of various published coal structures (Given, Wiser, Solomon and Shinn), and the dominant role of van der Waals and hydrogen bonding forces in defining the energy-minimized structures. These studies have been extended to explore various physical properties of coal structures, including density, microporosity, surface area, and fractal dimension. Other studies have related structural characteristics to cross-linkmore » density and have explored small molecule interactions with coal. Finally, recent studies using a structural elucidation (molecular builder) technique have constructed statistically diverse coal structures based on quantitative and qualitative data on coal and its decomposition products. This technique is also being applied to study coalification processes based on postulated coalification chemistry.« less

Molecular Modeling and Computational Chemistry at Humboldt State University.

ERIC Educational Resources Information Center

Paselk, Richard A.; Zoellner, Robert W.

2002-01-01

Describes a molecular modeling and computational chemistry (MM&CC) facility for undergraduate instruction and research at Humboldt State University. This facility complex allows the introduction of MM&CC throughout the chemistry curriculum with tailored experiments in general, organic, and inorganic courses as well as a new molecular modeling…

Polarization models of filamentary molecular clouds.

NASA Astrophysics Data System (ADS)

Carlqvist, P.; Kristen, H.

1997-08-01

We study numerically the linear polarization and extinction of light from background stars in three types of models of elongated molecular clouds by following the development of the Stokes parameters. The clouds are assumed to be of cylindrical shape and penetrated by a helical magnetic field {vec}(B). In the first two models we study only the relative magnitude of the polarization assuming that the polarization is proportional to Bmu^, where primarily μ=2. Provided there is no background/foreground polarization present we find from the cylindrically symmetric Model I that the angle of polarization has a bimodal character with the polarization being either parallel with or perpendicular to the axis of the filament. For some magnetic-field geometries both angles may exist in one and the same filament. It is concluded that it is not a straightforward task to find the magnetic-field-line pattern from the polarization pattern. If a background/foreground polarization exists or, as in Model II, the filament is not cylindrically symmetric, the bimodal character of the angle of polarization is lost. By means of Model III we have, using semi-empirical methods based on the Davis-Greenstein mechanism, estimated the absolute degree of polarization in the filamentary molecular cloud L204. It is found that the polarization produced by the model is much less than the polarization observed. We therefore conclude that most of the polarization measured in the L204 cloud is not produced in the cloud itself but is constituted by a large-scale background/foreground polarization.

The emerging role of cloud computing in molecular modelling.

PubMed

Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W

2013-07-01

There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.

Molecular dynamics simulations of theoretical cellulose nanotube models.

PubMed

Uto, Takuya; Kodama, Yuta; Miyata, Tatsuhiko; Yui, Toshifumi

2018-06-15

Nanotubes are remarkable nanoscale architectures for a wide range of potential applications. In the present paper, we report a molecular dynamics (MD) study of the theoretical cellulose nanotube (CelNT) models to evaluate their dynamic behavior in solution (either chloroform or benzene). Based on the one-quarter chain staggering relationship, we constructed six CelNT models by combining the two chain polarities (parallel (P) and antiparallel (AP)) and three symmetry operations (helical right (H R ), helical left (H L ), and rotation (R)) to generate a circular arrangement of molecular chains. Among the four models that retained the tubular form (P-H R , P-H L , P-R, and AP-R), the P-R and AP-R models have the lowest steric energies in benzene and chloroform, respectively. The structural features of the CelNT models were characterized in terms of the hydroxymethyl group conformation and intermolecular hydrogen bonds. Solvent structuring more clearly occurred with benzene than chloroform, suggesting that the CelNT models may disperse in benzene. Copyright © 2018 Elsevier Ltd. All rights reserved.

Molecular dynamics simulations on discoidal HDL particles suggest a mechanism for rotation in the apo A-I belt model.

PubMed

Klon, Anthony E; Segrest, Jere P; Harvey, Stephen C

2002-12-06

Apolipoprotein A-I (apo A-I) is the major protein component of high-density lipoprotein (HDL) particles. Elevated levels of HDL in the bloodstream have been shown to correlate strongly with a reduced risk factor for atherosclerosis. Molecular dynamics simulations have been carried out on three separate model discoidal high-density lipoprotein particles (HDL) containing two monomers of apo A-I and 160 molecules of palmitoyloleoylphosphatidylcholine (POPC), to a time-scale of 1ns. The starting structures were on the basis of previously published molecular belt models of HDL consisting of the lipid-binding C-terminal domain (residues 44-243) wrapped around the circumference of a discoidal HDL particle. Subtle changes between two of the starting structures resulted in significantly different behavior during the course of the simulation. The results provide support for the hypothesis of Segrest et al. that helical registration in the molecular belt model of apo A-I is modulated by intermolecular salt bridges. In addition, we propose an explanation for the presence of proline punctuation in the molecular belt model, and for the presence of two 11-mer helical repeats interrupting the otherwise regular pattern of 22-mer helical repeats in the lipid-binding domain of apo A-I.

Molecular aspects of aromatic C additions to soils: Implications of char quality for ecosystem functionality

NASA Astrophysics Data System (ADS)

Keiluweit, M.; Nico, P. S.; Johnson, M. G.; Kleber, M.

2009-12-01

Solid residues of incomplete combustion (biochar or char) are continuously being added to soils due to natural vegetation fires in many ecosystems. However, new strategies for carbon sequestration in soils are likely to include the active addition of biochar to soils. Since biochar is a highly aromatic organic material such additions will modify the native molecular structure of soil organic matter and thus alter interactions with the global atmosphere and hydrosphere. Here we present a molecular level assessment of the physical organization and chemical complexity of biomass-derived chars and, specifically, that of aromatic carbon in char structures. Differences among wood and grass charred at temperatures from 100 to 700°C are investigated. BET-N2 surface area, X-ray diffraction (XRD), synchrotron-based Near-edge X-ray Absorption Fine Structure (NEXAFS) and Fourier transform infrared (FT-IR) spectroscopy results demonstrate how the two plant precursor materials undergo analogous, but quantitatively different physical-chemical transitions as charring intensity increases. These changes suggest the existence of four distinct physical and chemical categories of char. We find that each category of char consists of a unique mixture of chemical phases and physical states: (i) in transition chars the crystalline character of the precursor materials is preserved, (ii) in amorphous chars the heat-altered molecules and incipient aromatic polycondensates are randomly mixed, (iii) composite chars consist of poorly ordered graphene stacks embedded in amorphous phases, and (iv) turbostratic chars are dominated by turbostratic (disordered) graphitic crystallites. There is wide variation in both the chemical and the physical nature of aromatic carbon among these char categories. In this presentation we will point out how molecular variations among the aromatic components of the different char categories translate into differences in their ability to: (i) persist in the

Molecular Dynamics implementation of BN2D or 'Mercedes Benz' water model

NASA Astrophysics Data System (ADS)

Scukins, Arturs; Bardik, Vitaliy; Pavlov, Evgen; Nerukh, Dmitry

2015-05-01

Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.

Molecular model for the diffusion of associating telechelic polymer networks

NASA Astrophysics Data System (ADS)

Ramirez, Jorge; Dursch, Thomas; Olsen, Bradley

Understanding the mechanisms of motion and stress relaxation of associating polymers at the molecular level is critical for advanced technological applications such as enhanced oil-recovery, self-healing materials or drug delivery. In associating polymers, the strength and rates of association/dissociation of the reversible physical crosslinks govern the dynamics of the network and therefore all the macroscopic properties, like self-diffusion and rheology. Recently, by means of forced Rayleigh scattering experiments, we have proved that associating polymers of different architectures show super-diffusive behavior when the free motion of single molecular species is slowed down by association/dissociation kinetics. Here we discuss a new molecular picture for unentangled associating telechelic polymers that considers concentration, molecular weight, number of arms of the molecules and equilibrium and rate constants of association/dissociation. The model predicts super-diffusive behavior under the right combination of values of the parameters. We discuss some of the predictions of the model using scaling arguments, show detailed results from Brownian dynamics simulations of the FRS experiments, and attempt to compare the predictions of the model to experimental data.

The Influence of Sintering Method on Kaolin-Based Geopolymer Ceramics with Addition of Ultra High Molecular Weight Polyethylene as Binder

NASA Astrophysics Data System (ADS)

Romisuhani, A.; AlBakri, M. M.; Kamarudin, H.; Andrei, S. V.

2017-11-01

The influence of sintering method on kaolin-based geopolymer ceramics with addition of Ultra High Molecular Weight Polyethylene as binder were studied. Geopolymer were formed at room temperature from kaolin and sodium silicate in a highly alkaline medium, followed by curing and drying at 80 °C. 12 M of sodium hydroxide solution were mixed with sodium silicate at a ratio of 0.24 to form alkaline activator. Powder metallurgy technique were used in order to produce kaolin geopolymer ceramics with addition of Ultra High Molecular Weight Polyethylene. The samples were heated at temperature of 1200 °C with two different sintering method which are conventional method and two-step sintering method. The strength and density were tested.

Study of clathrate hydrates via equilibrium molecular-dynamics simulation employing polarisable and non-polarisable, rigid and flexible water models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnham, Christian J., E-mail: christian.burnham@ucd.ie, E-mail: niall.english@ucd.ie; English, Niall J., E-mail: christian.burnham@ucd.ie, E-mail: niall.english@ucd.ie

Equilibrium molecular-dynamics (MD) simulations have been performed on metastable sI and sII polymorphs of empty hydrate lattices, in addition to liquid water and ice Ih. The non-polarisable TIP4P-2005, simple point charge model (SPC), and polarisable Thole-type models (TTM): TTM2, TTM3, and TTM4 water models were used in order to survey the differences between models and to see what differences can be expected when polarisability is incorporated. Rigid and flexible variants were used of each model to gauge the effects of flexibility. Power spectra are calculated and compared to density-of-states spectra inferred from inelastic neutron scattering (INS) measurements. Thermodynamic properties weremore » also calculated, as well as molecular-dipole distributions. It was concluded that TTM models offer optimal fidelity vis-à-vis INS spectra, together with thermodynamic properties, with the flexible TTM2 model offering optimal placement of vibrational modes.« less

Validation analysis of probabilistic models of dietary exposure to food additives.

PubMed

Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

2003-10-01

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Melting Behavior of a Model Molecular Crystalline GeI4

NASA Astrophysics Data System (ADS)

Fuchizaki, Kazuhiro; Asano, Yuta

2015-06-01

A model molecular crystalline GeI4 was examined using molecular dynamics simulation. The model was constructed in such a way that rigid tetrahedral molecules interact with each other via Lennard-Jones potentials whose centers are located at the vertices of a tetrahedron. Because no other interaction that can "soften" the intermolecular interaction was introduced, the melting curve of the model crystalline material does not exhibit the anomaly that was found for the real substance. However, the current investigation is useful in that it could settle the upper bound of pressure below which the model can predict properties of the molecular liquid. Moreover, singularity-free nature of the melting curve allowed us to analytically treat the melting curve in the light of the Kumari-Dass-Kechin equation. As a result, we could definitely conclude that the well-known Simon equation for the melting curve is merely an approximate expression. The condition for the validity of Simon's equation was identified.

Dynamic, mechanistic, molecular-level modelling of cyanobacteria: Anabaena and nitrogen interaction.

PubMed

Hellweger, Ferdi L; Fredrick, Neil D; McCarthy, Mark J; Gardner, Wayne S; Wilhelm, Steven W; Paerl, Hans W

2016-09-01

Phytoplankton (eutrophication, biogeochemical) models are important tools for ecosystem research and management, but they generally have not been updated to include modern biology. Here, we present a dynamic, mechanistic, molecular-level (i.e. gene, transcript, protein, metabolite) model of Anabaena - nitrogen interaction. The model was developed using the pattern-oriented approach to model definition and parameterization of complex agent-based models. It simulates individual filaments, each with individual cells, each with genes that are expressed to yield transcripts and proteins. Cells metabolize various forms of N, grow and divide, and differentiate heterocysts when fixed N is depleted. The model is informed by observations from 269 laboratory experiments from 55 papers published from 1942 to 2014. Within this database, we identified 331 emerging patterns, and, excluding inconsistencies in observations, the model reproduces 94% of them. To explore a practical application, we used the model to simulate nutrient reduction scenarios for a hypothetical lake. For a 50% N only loading reduction, the model predicts that N fixation increases, but this fixed N does not compensate for the loading reduction, and the chlorophyll a concentration decreases substantially (by 33%). When N is reduced along with P, the model predicts an additional 8% reduction (compared to P only). © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Carbohydrate-protein interactions: molecular modeling insights.

PubMed

Pérez, Serge; Tvaroška, Igor

2014-01-01

The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses. © 2014 Elsevier Inc. All rights reserved.

Quantum mechanics/molecular mechanics modeling of covalent addition between EGFR-cysteine 797 and N-(4-anilinoquinazolin-6-yl) acrylamide.

PubMed

Capoferri, Luigi; Lodola, Alessio; Rivara, Silvia; Mor, Marco

2015-03-23

Irreversible epidermal growth factor receptor (EGFR) inhibitors can circumvent resistance to first-generation ATP-competitive inhibitors in the treatment of nonsmall-cell lung cancer. They covalently bind a noncatalytic cysteine (Cys797) at the surface of EGFR active site by an acrylamide warhead. Herein, we used a hybrid quantum mechanics/molecular mechanics (QM/MM) potential in combination with umbrella sampling in the path-collective variable space to investigate the mechanism of alkylation of Cys797 by the prototypical covalent inhibitor N-(4-anilinoquinazolin-6-yl) acrylamide. Calculations show that Cys797 reacts with the acrylamide group of the inhibitor through a direct addition mechanism, with Asp800 acting as a general base/general acid in distinct steps of the reaction. The obtained reaction free energy is negative (ΔA = -12 kcal/mol) consistent with the spontaneous and irreversible alkylation of Cys797 by N-(4-anilinoquinazolin-6-yl) acrylamide. Our calculations identify desolvation of Cys797 thiolate anion as a key step of the alkylation process, indicating that changes in the intrinsic reactivity of the acrylamide would have only a minor impact on the inhibitor potency.

Diamond-like nanoparticles influence on flavonoids transport: molecular modelling

NASA Astrophysics Data System (ADS)

Plastun, Inna L.; Agandeeva, Ksenia E.; Bokarev, Andrey N.; Zenkin, Nikita S.

2017-03-01

Intermolecular interaction of diamond-like nanoparticles and flavonoids is investigated by numerical simulation. Using molecular modelling by the density functional theory method, we analyze hydrogen bonds formation and their influence on IR - spectra and structure of molecular complex which is formed due to interaction between flavonoids and nanodiamonds surrounded with carboxylic groups. Enriched adamantane (1,3,5,7 - adamantanetetracarboxylic acid) is used as an example of diamond-like nanoparticles. Intermolecular forces and structure of hydrogen bonds are investigated. IR - spectra and structure parameters of quercetin - adamantanetetracarboxylic acid molecular complex are obtained by numerical simulation using the Gaussian software complex. Received data coincide well with experimental results. Intermolecular interactions and hydrogen bonding structure in the obtained molecular complex are examined. Possibilities of flavonoids interaction with DNA at the molecular level are also considered.

Does anesthetic additivity imply a similar molecular mechanism of anesthetic action at N-methyl-D-aspartate receptors?

PubMed

Brosnan, Robert J; Pham, Trung L

2011-03-01

Isoflurane and carbon dioxide (CO(2)) negatively modulate N-methyl-d-aspartate (NMDA) receptors, but via different mechanisms. Isoflurane is a competitive antagonist at the NMDA receptor glycine binding site, whereas CO(2) inhibits NMDA receptor current through extracellular acidification. Isoflurane and CO(2) exhibit additive minimum alveolar concentration effects in rats, but we hypothesized that they would not additively inhibit NMDA receptor currents in vitro because they act at different molecular sites. NMDA receptors were expressed in frog oocytes and studied using 2-electrode voltage clamp techniques. A glycine concentration response for NMDA was measured in the presence and absence of CO(2). Concentration-response curves for isoflurane, H(+), CO(2), and ketamine as a function of NMDA inhibition were measured, and a Hill equation was used to calculate the EC(50) for each compound. Binary drug combinations containing ½ EC(50) were additive if NMDA current inhibition was not statistically different from 50%. The ½ EC(50) binary drug combinations decreased the percentage baseline NMDA receptor current as follows (mean ± SD, n = 5 to 6 oocytes each): CO(2)+ H(+) (51% ± 5%), CO(2 )+ isoflurane (54% ± 5%), H(+) + isoflurane (51% ± 3%), CO(2)+ ketamine (67% ± 8%), and H(+) + ketamine (64% ± 2%). In contrast to our hypothesis, NMDA receptor inhibition by CO(2) and isoflurane is additive. Possibly, CO(2) acidification modulates a pH-sensitive loop on the NMDA receptor that in turn alters glycine binding affinity on the GluN1 subunit. However, ketamine plus either CO(2) or H(+) synergistically inhibits NMDA receptor currents. Drugs acting via different mechanisms can thus exhibit additive or synergistic receptor effects. Additivity may not robustly indicate commonality between molecular anesthetic mechanisms.

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Multi-scale modelling of supercapacitors: From molecular simulations to a transmission line model

NASA Astrophysics Data System (ADS)

Pean, C.; Rotenberg, B.; Simon, P.; Salanne, M.

2016-09-01

We perform molecular dynamics simulations of a typical nanoporous-carbon based supercapacitor. The organic electrolyte consists in 1-ethyl-3-methylimidazolium and hexafluorophosphate ions dissolved in acetonitrile. We simulate systems at equilibrium, for various applied voltages. This allows us to determine the relevant thermodynamic (capacitance) and transport (in-pore resistivities) properties. These quantities are then injected in a transmission line model for testing its ability to predict the charging properties of the device. The results from this macroscopic model are in good agreement with non-equilibrium molecular dynamics simulations, which validates its use for interpreting electrochemical impedance experiments.

Phenomenological and molecular-level Petri net modeling and simulation of long-term potentiation.

PubMed

Hardy, S; Robillard, P N

2005-10-01

Petri net-based modeling methods have been used in many research projects to represent biological systems. Among these, the hybrid functional Petri net (HFPN) was developed especially for biological modeling in order to provide biologists with a more intuitive Petri net-based method. In the literature, HFPNs are used to represent kinetic models at the molecular level. We present two models of long-term potentiation previously represented by differential equations which we have transformed into HFPN models: a phenomenological synapse model and a molecular-level model of the CaMKII regulation pathway. Through simulation, we obtained results similar to those of previous studies using these models. Our results open the way to a new type of modeling for systems biology where HFPNs are used to combine different levels of abstraction within one model. This approach can be useful in fully modeling a system at the molecular level when kinetic data is missing or when a full study of a system at the molecular level it is not within the scope of the research.

Molecular Modeling of Water Interfaces: From Molecular Spectroscopy to Thermodynamics.

PubMed

Nagata, Yuki; Ohto, Tatsuhiko; Backus, Ellen H G; Bonn, Mischa

2016-04-28

Understanding aqueous interfaces at the molecular level is not only fundamentally important, but also highly relevant for a variety of disciplines. For instance, electrode-water interfaces are relevant for electrochemistry, as are mineral-water interfaces for geochemistry and air-water interfaces for environmental chemistry; water-lipid interfaces constitute the boundaries of the cell membrane, and are thus relevant for biochemistry. One of the major challenges in these fields is to link macroscopic properties such as interfacial reactivity, solubility, and permeability as well as macroscopic thermodynamic and spectroscopic observables to the structure, structural changes, and dynamics of molecules at these interfaces. Simulations, by themselves, or in conjunction with appropriate experiments, can provide such molecular-level insights into aqueous interfaces. In this contribution, we review the current state-of-the-art of three levels of molecular dynamics (MD) simulation: ab initio, force field, and coarse-grained. We discuss the advantages, the potential, and the limitations of each approach for studying aqueous interfaces, by assessing computations of the sum-frequency generation spectra and surface tension. The comparison of experimental and simulation data provides information on the challenges of future MD simulations, such as improving the force field models and the van der Waals corrections in ab initio MD simulations. Once good agreement between experimental observables and simulation can be established, the simulation can be used to provide insights into the processes at a level of detail that is generally inaccessible to experiments. As an example we discuss the mechanism of the evaporation of water. We finish by presenting an outlook outlining four future challenges for molecular dynamics simulations of aqueous interfacial systems.

Modeling Molecular Hydrogen Emission in M-Dwarf Exoplanetary Systems

NASA Astrophysics Data System (ADS)

Evonosky, W. R.; France, K.; Kruczek, N.; Youngblood, A.

2016-12-01

Exoplanets orbiting low-mass stars are prime candidates for atmospheric characterization due to their astronomical abundance and short orbital periods. These planets orbit stars that are often more active than main sequence solar-type stars. They are exposed to differing levels of ultraviolet radiation which can cause traditional "biosignature" gases to be generated abiotically, potentially causing false-positive identifications of life. We modeled the recently discovered molecular hydrogen emission in the ultraviolet spectra (1350 - 1650 Å) as arising from the stellar surface, excited by radiation generated in the upper chromosphere. The model was compared with observed hydrogen emission from the "Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars" (MUSCLES) survey by conducting a grid search and implementing a chi-squared minimization routine. We considered only progressions from the [1, 4] and [1, 7] first excited electronic levels. Our modeling procedure varied the atomic hydrogen column density (in the chromosphere) as well as the photospheric molecular hydrogen column density and temperature. The model required as an input a reconstructed intrinsic Lyman α profile which served as the pumping radiation for the molecular hydrogen. We found that an atomic hydrogen column density of log10N(H I) = 14.13 ± 0.16 cm-2 represents a breaking point above which there is not enough Lyman α flux available to excite a significant molecular hydrogen population into the [1, 7] state. We also present H2 temperatures which may suggest that star spots on low mass stars persist longer, and encompass more area than star spots on solar-type stars.

Binding of carbendazim to bovine serum albumin: Insights from experimental and molecular modeling studies

NASA Astrophysics Data System (ADS)

Li, Jinhua; Zhang, Yulei; Hu, Lin; Kong, Yaling; Jin, Changqing; Xi, Zengzhe

2017-07-01

Carbendazim (CBZ) is a widely used benzimidazole fungicide in agriculture to control a wide range of fruit and vegetable pathogens, which may lead to potential health hazards. To evaluate the potential toxicity of CBZ, the binding mechanism of bovine serum albumin (BSA) with CBZ was investigated by the fluorescence quenching technology, UV absorbance spectra, circular dichroism (CD), and molecular modeling. The fluorescence titration and UV absorbance spectra revealed that the fluorescence quenching mechanism of BSA by CBZ was a combined quenching process. In addition, the studies of CD spectra suggested that the binding of CBZ to BSA changed the secondary structure of protein. Furthermore, the thermodynamic functions of enthalpy change (ΔH0) and entropy change (ΔS0) for the reaction were calculated to be 24.87 kJ mol-1 and 162.95 J mol-1 K-1 according to Van't Hoff equation. These data suggested that hydrophobic interaction play a major role in the binding of CBZ to BSA, which was in good agreement with the result of molecular modeling study.

Molecular Imprinting of Silica Nanoparticle Surfaces via Reversible Addition-Fragmentation Polymerization for Optical Biosensing Applications

NASA Astrophysics Data System (ADS)

Oluz, Zehra; Nayab, Sana; Kursun, Talya Tugana; Caykara, Tuncer; Yameen, Basit; Duran, Hatice

Azo initiator modified surface of silica nanoparticles were coated via reversible addition-fragmentation polymerization (RAFT) of methacrylic acid and ethylene glycol dimethacrylate using 2-phenylprop 2-yl dithobenzoate as chain transfer agent. Using L-phenylalanine anilide as template during polymerization led molecularly imprinted nanoparticles. RAFT polymerization offers an efficient control of grafting process, while molecularly imprinted polymers shows enhanced capacity as sensor. L-phenylalanine anilide imprinted silica particles were characterized by X-Ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM). Performances of the particles were followed by surface plasmon resonance spectroscopy (SPR) after coating the final product on gold deposited glass substrate against four different analogous of analyte molecules: D-henylalanine anilide, L-tyrosine, L-tryptophan and L-phenylalanine. Characterizations indicated that silica particles coated with polymer layer do contain binding sites for L-phenylalanine anilide, and are highly selective for the molecule of interest. This project was supported by TUBITAK (Project No:112M804).

Molecular modeling and identification of novel glucokinase activators through stepwise virtual screening.

PubMed

Behera, Pabitra Mohan; Behera, Deepak Kumar; Satpati, Suresh; Agnihotri, Geetanjali; Nayak, Sanghamitra; Padhi, Payodhar; Dixit, Anshuman

2015-04-01

The glucose phosphorylating enzyme glucokinase (GK) is a 50kD monomeric protein having 465 amino acids. It maintains glucose homeostasis inside cells, acts as a glucose sensor in pancreatic β-cells and as a rate controlling enzyme for hepatic glucose clearance and glycogen synthesis. It has two binding sites, one for binding d-glucose and the other for a putative allosteric activator named glucokinase activator (GKA). The GKAs interact with the same region of the GK enzyme that is commonly affected by naturally occurring mutations in humans. However, many GKAs do not bind to GK in the absence of glucose. Recently, it has been reported that GKAs are highly effective in patients with type 2 diabetes mellitus. In this milieu a molecular modeling study has been carried out on three natural variants of GK that lie in the GKA binding site and are known to cause maturity onset diabetes of young (MODY). Additionally, a 10ns molecular dynamics simulation was done on each of the modeled variant in order to explore the flexibility of this site. Subsequently, a systematic virtual screening study was done to identify compounds which can bind with high affinity at GKA binding site of mutant GK. Copyright © 2015 Elsevier Inc. All rights reserved.

A simple model for molecular hydrogen chemistry coupled to radiation hydrodynamics

NASA Astrophysics Data System (ADS)

Nickerson, Sarah; Teyssier, Romain; Rosdahl, Joakim

2018-06-01

We introduce non-equilibrium molecular hydrogen chemistry into the radiation-hydrodynamics code RAMSES-RT. This is an adaptive mesh refinement grid code with radiation hydrodynamics that couples the thermal chemistry of hydrogen and helium to moment-based radiative transfer with the Eddington tensor closure model. The H2 physics that we include are formation on dust grains, gas phase formation, formation by three-body collisions, collisional destruction, photodissociation, photoionisation, cosmic ray ionisation and self-shielding. In particular, we implement the first model for H2 self-shielding that is tied locally to moment-based radiative transfer by enhancing photo-destruction. This self-shielding from Lyman-Werner line overlap is critical to H2 formation and gas cooling. We can now track the non-equilibrium evolution of molecular, atomic, and ionised hydrogen species with their corresponding dissociating and ionising photon groups. Over a series of tests we show that our model works well compared to specialised photodissociation region codes. We successfully reproduce the transition depth between molecular and atomic hydrogen, molecular cooling of the gas, and a realistic Strömgren sphere embedded in a molecular medium. In this paper we focus on test cases to demonstrate the validity of our model on small scales. Our ultimate goal is to implement this in large-scale galactic simulations.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when

Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

PubMed Central

2013-01-01

hydrolysis and degree of synergism among enzymes. Conclusions The model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Simulations were in qualitative and quantitative agreement with experimental data. Several experimentally observed phenomena were simulated without the need for any additional assumptions or parameter changes and confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis. PMID:23638989

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Geometric and electrostatic modeling using molecular rigidity functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Lin; Xia, Kelin; Wei, Guowei

Geometric and electrostatic modeling is an essential component in computational biophysics and molecular biology. Commonly used geometric representations admit geometric singularities such as cusps, tips and self-intersecting facets that lead to computational instabilities in the molecular modeling. Our present work explores the use of flexibility and rigidity index (FRI), which has a proved superiority in protein B-factor prediction, for biomolecular geometric representation and associated electrostatic analysis. FRI rigidity surfaces are free of geometric singularities. We propose a rigidity based Poisson–Boltzmann equation for biomolecular electrostatic analysis. These approaches to surface and electrostatic modeling are validated by a set of 21 proteins.more » Our results are compared with those of established methods. Finally, being smooth and analytically differentiable, FRI rigidity functions offer excellent curvature analysis, which characterizes concave and convex regions on protein surfaces. Polarized curvatures constructed by using the product of minimum curvature and electrostatic potential is shown to predict potential protein–ligand binding sites.« less

Geometric and electrostatic modeling using molecular rigidity functions

DOE PAGES

Mu, Lin; Xia, Kelin; Wei, Guowei

2017-03-01

Geometric and electrostatic modeling is an essential component in computational biophysics and molecular biology. Commonly used geometric representations admit geometric singularities such as cusps, tips and self-intersecting facets that lead to computational instabilities in the molecular modeling. Our present work explores the use of flexibility and rigidity index (FRI), which has a proved superiority in protein B-factor prediction, for biomolecular geometric representation and associated electrostatic analysis. FRI rigidity surfaces are free of geometric singularities. We propose a rigidity based Poisson–Boltzmann equation for biomolecular electrostatic analysis. These approaches to surface and electrostatic modeling are validated by a set of 21 proteins.more » Our results are compared with those of established methods. Finally, being smooth and analytically differentiable, FRI rigidity functions offer excellent curvature analysis, which characterizes concave and convex regions on protein surfaces. Polarized curvatures constructed by using the product of minimum curvature and electrostatic potential is shown to predict potential protein–ligand binding sites.« less

Effects of additional food in a delayed predator-prey model.

PubMed

Sahoo, Banshidhar; Poria, Swarup

2015-03-01

We examine the effects of supplying additional food to predator in a gestation delay induced predator-prey system with habitat complexity. Additional food works in favor of predator growth in our model. Presence of additional food reduces the predatory attack rate to prey in the model. Supplying additional food we can control predator population. Taking time delay as bifurcation parameter the stability of the coexisting equilibrium point is analyzed. Hopf bifurcation analysis is done with respect to time delay in presence of additional food. The direction of Hopf bifurcations and the stability of bifurcated periodic solutions are determined by applying the normal form theory and the center manifold theorem. The qualitative dynamical behavior of the model is simulated using experimental parameter values. It is observed that fluctuations of the population size can be controlled either by supplying additional food suitably or by increasing the degree of habitat complexity. It is pointed out that Hopf bifurcation occurs in the system when the delay crosses some critical value. This critical value of delay strongly depends on quality and quantity of supplied additional food. Therefore, the variation of predator population significantly effects the dynamics of the model. Model results are compared with experimental results and biological implications of the analytical findings are discussed in the conclusion section. Copyright © 2015 Elsevier Inc. All rights reserved.

A Comparative Study of Successful Central Nervous System Drugs Using Molecular Modeling

ERIC Educational Resources Information Center

Kim, Hyosub; Sulaimon, Segun; Menezes, Sandra; Son, Anne; Menezes, Warren J. C.

2011-01-01

Molecular modeling is a powerful tool used for three-dimensional visualization and for exploring electrostatic forces involved in drug transport. This tool enhances student understanding of structure-property relationships, as well as actively engaging them in class. Molecular modeling of several central nervous system (CNS) drugs is used to…

Modeling molecular hydrogen emission in M dwarf exoplanetary systems

NASA Astrophysics Data System (ADS)

Evonosky, William; France, Kevin; Kruczek, Nick E.; Youngblood, Allison; Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars (MUSCLES)

2017-01-01

Exoplanets orbiting low-mass stars are prime candidates for atmospheric characterization due to their astronomical abundance and short orbital periods. These planets orbit stars that are often more active than main sequence solar-type stars. They are exposed to differing levels of ultraviolet radiation which can cause traditional “biosignature” gases to be generated abiotically, potentially causing false-positive identifications of life. We modeled the recently discovered molecular hydrogen emission in the ultraviolet spectra (1350 - 1650 Å) as arising from the stellar surface, excited by radiation generated in the upper chromosphere. The model was compared with observed hydrogen emission from the “Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars” (MUSCLES) survey by conducting a grid search and implementing a chi-squared minimization routine. We considered only progressions from the [1, 4] and [1, 7] first excited electronic levels. Our modeling procedure varied the atomic hydrogen column density (in the chromosphere) as well as the photospheric molecular hydrogen column density and temperature. The model required as an input a reconstructed intrinsic Lyman α profile which served as the pumping radiation for the molecular hydrogen. We found that an atomic hydrogen column density of log10N(H I) = 14.13 ± 0.16 cm-2 represents a breaking point above which there is not enough Lyman α flux available to excite a significant molecular hydrogen population into the [1, 7] state. We also present H2 temperatures which may suggest that star spots on low mass stars persist longer, and encompass more area than star spots on solar-type stars.

Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.

PubMed

Xue, Hongqi; Wu, Shuang; Wu, Yichao; Ramirez Idarraga, Juan C; Wu, Hulin

2018-05-02

Mechanism-driven low-dimensional ordinary differential equation (ODE) models are often used to model viral dynamics at cellular levels and epidemics of infectious diseases. However, low-dimensional mechanism-based ODE models are limited for modeling infectious diseases at molecular levels such as transcriptomic or proteomic levels, which is critical to understand pathogenesis of diseases. Although linear ODE models have been proposed for gene regulatory networks (GRNs), nonlinear regulations are common in GRNs. The reconstruction of large-scale nonlinear networks from time-course gene expression data remains an unresolved issue. Here, we use high-dimensional nonlinear additive ODEs to model GRNs and propose a 4-step procedure to efficiently perform variable selection for nonlinear ODEs. To tackle the challenge of high dimensionality, we couple the 2-stage smoothing-based estimation method for ODEs and a nonlinear independence screening method to perform variable selection for the nonlinear ODE models. We have shown that our method possesses the sure screening property and it can handle problems with non-polynomial dimensionality. Numerical performance of the proposed method is illustrated with simulated data and a real data example for identifying the dynamic GRN of Saccharomyces cerevisiae. Copyright © 2018 John Wiley & Sons, Ltd.

Comprehensive European dietary exposure model (CEDEM) for food additives.

PubMed

Tennant, David R

2016-05-01

European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

Nonadiabatic excited-state molecular dynamics: modeling photophysics in organic conjugated materials.

PubMed

Nelson, Tammie; Fernandez-Alberti, Sebastian; Roitberg, Adrian E; Tretiak, Sergei

2014-04-15

To design functional photoactive materials for a variety of technological applications, researchers need to understand their electronic properties in detail and have ways to control their photoinduced pathways. When excited by photons of light, organic conjugated materials (OCMs) show dynamics that are often characterized by large nonadiabatic (NA) couplings between multiple excited states through a breakdown of the Born-Oppenheimer (BO) approximation. Following photoexcitation, various nonradiative intraband relaxation pathways can lead to a number of complex processes. Therefore, computational simulation of nonadiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons. Over the years, we have developed a nonadiabatic excited-state molecular dynamics (NA-ESMD) framework that efficiently and accurately describes photoinduced phenomena in extended conjugated molecular systems. We use the fewest-switches surface hopping (FSSH) algorithm to treat quantum transitions among multiple adiabatic excited state potential energy surfaces (PESs). Extended molecular systems often contain hundreds of atoms and involve large densities of excited states that participate in the photoinduced dynamics. We can achieve an accurate description of the multiple excited states using the configuration interaction single (CIS) formalism with a semiempirical model Hamiltonian. Analytical techniques allow the trajectory to be propagated "on the fly" using the complete set of NA coupling terms and remove computational bottlenecks in the evaluation of excited-state gradients and NA couplings. Furthermore, the use of state-specific gradients for propagation of nuclei on the native excited-state PES eliminates the need for simplifications such as the classical path approximation (CPA), which only uses ground-state gradients. Thus, the NA-ESMD methodology

Assessing High School Chemistry Students' Modeling Sub-Skills in a Computerized Molecular Modeling Learning Environment

ERIC Educational Resources Information Center

Dori, Yehudit Judy; Kaberman, Zvia

2012-01-01

Much knowledge in chemistry exists at a molecular level, inaccessible to direct perception. Chemistry instruction should therefore include multiple visual representations, such as molecular models and symbols. This study describes the implementation and assessment of a learning unit designed for 12th grade chemistry honors students. The organic…

Molecular-orbital model for metal-sapphire interfacial strength

NASA Technical Reports Server (NTRS)

Johnson, K. H.; Pepper, S. V.

1982-01-01

Self-consistent-field X-Alpha scattered-wave cluster molecular-orbital models have been constructed for transition and noble metals (Fe, Ni, Cu, and Ag) in contact with a sapphire (Al2O3) surface. It is found that a chemical bond is established between the metal d-orbital electrons and the nonbonding 2p-orbital electrons of the oxygen anions on the Al2O3 surface. An increasing number of occupied metal-sapphire antibonding molecular orbitals explains qualitatively the observed decrease of contact shear strength through the series Fe, Ni, Cu, and Ag.

A Model of In vitro Plasticity at the Parallel Fiber—Molecular Layer Interneuron Synapses

PubMed Central

Lennon, William; Yamazaki, Tadashi; Hecht-Nielsen, Robert

2015-01-01

Theoretical and computational models of the cerebellum typically focus on the role of parallel fiber (PF)—Purkinje cell (PKJ) synapses for learned behavior, but few emphasize the role of the molecular layer interneurons (MLIs)—the stellate and basket cells. A number of recent experimental results suggest the role of MLIs is more important than previous models put forth. We investigate learning at PF—MLI synapses and propose a mathematical model to describe plasticity at this synapse. We perform computer simulations with this form of learning using a spiking neuron model of the MLI and show that it reproduces six in vitro experimental results in addition to simulating four novel protocols. Further, we show how this plasticity model can predict the results of other experimental protocols that are not simulated. Finally, we hypothesize what the biological mechanisms are for changes in synaptic efficacy that embody the phenomenological model proposed here. PMID:26733856

Dielectric properties of organic solvents from non-polarizable molecular dynamics simulation with electronic continuum model and density functional theory.

PubMed

Lee, Sanghun; Park, Sung Soo

2011-11-03

Dielectric constants of electrolytic organic solvents are calculated employing nonpolarizable Molecular Dynamics simulation with Electronic Continuum (MDEC) model and Density Functional Theory. The molecular polarizabilities are obtained by the B3LYP/6-311++G(d,p) level of theory to estimate high-frequency refractive indices while the densities and dipole moment fluctuations are computed using nonpolarizable MD simulations. The dielectric constants reproduced from these procedures are evaluated to provide a reliable approach for estimating the experimental data. An additional feature, two representative solvents which have similar molecular weights but are different dielectric properties, i.e., ethyl methyl carbonate and propylene carbonate, are compared using MD simulations and the distinctly different dielectric behaviors are observed at short times as well as at long times.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

ERIC Educational Resources Information Center

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do…

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

A molecular model for ice nucleation and growth, attachment 1

NASA Technical Reports Server (NTRS)

Plummer, P. L. M.

1981-01-01

The quantum mechanical technique is used to study ionic, configurational, and impurity defects in the ice surface. In addition to static calculations of the energetics of the water monomer-ice surface interactions, molecular dynamics studies were initiated. The calculations of the monomer-ice surface interaction, molecular dynamics studies were initiated. The calculations of monomer-ice surface interactions indicate that many adsorption sites exist on the ice surfaces and that the barriers between bonding sites are relatively low. Bonding on the prism face of ice is preferentially above lattice sites.

Molecular Model of a Quantum Dot Beyond the Constant Interaction Approximation

NASA Astrophysics Data System (ADS)

Temirov, Ruslan; Green, Matthew F. B.; Friedrich, Niklas; Leinen, Philipp; Esat, Taner; Chmielniak, Pawel; Sarwar, Sidra; Rawson, Jeff; Kögerler, Paul; Wagner, Christian; Rohlfing, Michael; Tautz, F. Stefan

2018-05-01

We present a physically intuitive model of molecular quantum dots beyond the constant interaction approximation. It accurately describes their charging behavior and allows the extraction of important molecular properties that are otherwise experimentally inaccessible. The model is applied to data recorded with a noncontact atomic force microscope on three different molecules that act as a quantum dot when attached to the microscope tip. The results are in excellent agreement with first-principles simulations.

Ionic imbalance, in addition to molecular crowding, abates cytoskeletal dynamics and vesicle motility during hypertonic stress

PubMed Central

Nunes, Paula; Roth, Isabelle; Meda, Paolo; Féraille, Eric; Brown, Dennis; Hasler, Udo

2015-01-01

Cell volume homeostasis is vital for the maintenance of optimal protein density and cellular function. Numerous mammalian cell types are routinely exposed to acute hypertonic challenge and shrink. Molecular crowding modifies biochemical reaction rates and decreases macromolecule diffusion. Cell volume is restored rapidly by ion influx but at the expense of elevated intracellular sodium and chloride levels that persist long after challenge. Although recent studies have highlighted the role of molecular crowding on the effects of hypertonicity, the effects of ionic imbalance on cellular trafficking dynamics in living cells are largely unexplored. By tracking distinct fluorescently labeled endosome/vesicle populations by live-cell imaging, we show that vesicle motility is reduced dramatically in a variety of cell types at the onset of hypertonic challenge. Live-cell imaging of actin and tubulin revealed similar arrested microfilament motility upon challenge. Vesicle motility recovered long after cell volume, a process that required functional regulatory volume increase and was accelerated by a return of extracellular osmolality to isosmotic levels. This delay suggests that, although volume-induced molecular crowding contributes to trafficking defects, it alone cannot explain the observed effects. Using fluorescent indicators and FRET-based probes, we found that intracellular ATP abundance and mitochondrial potential were reduced by hypertonicity and recovered after longer periods of time. Similar to the effects of osmotic challenge, isovolumetric elevation of intracellular chloride concentration by ionophores transiently decreased ATP production by mitochondria and abated microfilament and vesicle motility. These data illustrate how perturbed ionic balance, in addition to molecular crowding, affects membrane trafficking. PMID:26045497

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

PubMed

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Modelling the behaviour of additives in gun barrels

NASA Astrophysics Data System (ADS)

Rhodes, N.; Ludwig, J. C.

1986-01-01

A mathematical model which predicts the flow and heat transfer in a gun barrel is described. The model is transient, two-dimensional and equations are solved for velocities and enthalpies of a gas phase, which arises from the combustion of propellant and cartridge case, for particle additives which are released from the case; volume fractions of the gas and particles. Closure of the equations is obtained using a two-equation turbulence model. Preliminary calculations are described in which the proportions of particle additives in the cartridge case was altered. The model gives a good prediction of the ballistic performance and the gas to wall heat transfer. However, the expected magnitude of reduction in heat transfer when particles are present is not predicted. The predictions of gas flow invalidate some of the assumptions made regarding case and propellant behavior during combustion and further work is required to investigate these effects and other possible interactions, both chemical and physical, between gas and particles.

Spectroscopic and molecular modeling studies of the interaction between cytidine and human serum albumin and its analytical application.

PubMed

Cui, Fengling; Wang, Junli; Yao, Xiaojun; Wang, Li; Zhang, Qiangzhai; Qu, Guirong

In this study, the interaction between cytidine and human serum albumin (HSA) was investigated for the first time by fluorescence spectroscopy in combination with UV absorption spectrum and molecular modeling under simulative physiological conditions. Experimental results indicated that cytidine had a strong ability to quench the intrinsic fluorescence of human serum albumin. The binding constants (K) at different temperatures, thermodynamic parameter enthalpy changes (DeltaH) and entropy changes (DeltaS) of HSA-cytidine had been calculated according to the relevant fluorescence data, which indicated that the hydrophobic and electrostatic interactions played a major role, which was in agreement with the results of molecular modeling study. In addition, the effects of other ions on the binding constants were also studied. Furthermore, synchronous fluorescence technology was successfully applied to the determination of human serum albumin added into the cytidine solution.

A log-normal distribution model for the molecular weight of aquatic fulvic acids

USGS Publications Warehouse

Cabaniss, S.E.; Zhou, Q.; Maurice, P.A.; Chin, Y.-P.; Aiken, G.R.

2000-01-01

The molecular weight of humic substances influences their proton and metal binding, organic pollutant partitioning, adsorption onto minerals and activated carbon, and behavior during water treatment. We propose a lognormal model for the molecular weight distribution in aquatic fulvic acids to provide a conceptual framework for studying these size effects. The normal curve mean and standard deviation are readily calculated from measured M(n) and M(w) and vary from 2.7 to 3 for the means and from 0.28 to 0.37 for the standard deviations for typical aquatic fulvic acids. The model is consistent with several types of molecular weight data, including the shapes of high- pressure size-exclusion chromatography (HP-SEC) peaks. Applications of the model to electrostatic interactions, pollutant solubilization, and adsorption are explored in illustrative calculations.The molecular weight of humic substances influences their proton and metal binding, organic pollutant partitioning, adsorption onto minerals and activated carbon, and behavior during water treatment. We propose a log-normal model for the molecular weight distribution in aquatic fulvic acids to provide a conceptual framework for studying these size effects. The normal curve mean and standard deviation are readily calculated from measured Mn and Mw and vary from 2.7 to 3 for the means and from 0.28 to 0.37 for the standard deviations for typical aquatic fulvic acids. The model is consistent with several type's of molecular weight data, including the shapes of high-pressure size-exclusion chromatography (HP-SEC) peaks. Applications of the model to electrostatic interactions, pollutant solubilization, and adsorption are explored in illustrative calculations.

Diffusion-controlled interface kinetics-inclusive system-theoretic propagation models for molecular communication systems

NASA Astrophysics Data System (ADS)

Chude-Okonkwo, Uche A. K.; Malekian, Reza; Maharaj, B. T.

2015-12-01

Inspired by biological systems, molecular communication has been proposed as a new communication paradigm that uses biochemical signals to transfer information from one nano device to another over a short distance. The biochemical nature of the information transfer process implies that for molecular communication purposes, the development of molecular channel models should take into consideration diffusion phenomenon as well as the physical/biochemical kinetic possibilities of the process. The physical and biochemical kinetics arise at the interfaces between the diffusion channel and the transmitter/receiver units. These interfaces are herein termed molecular antennas. In this paper, we present the deterministic propagation model of the molecular communication between an immobilized nanotransmitter and nanoreceiver, where the emission and reception kinetics are taken into consideration. Specifically, we derived closed-form system-theoretic models and expressions for configurations that represent different communication systems based on the type of molecular antennas used. The antennas considered are the nanopores at the transmitter and the surface receptor proteins/enzymes at the receiver. The developed models are simulated to show the influence of parameters such as the receiver radius, surface receptor protein/enzyme concentration, and various reaction rate constants. Results show that the effective receiver surface area and the rate constants are important to the system's output performance. Assuming high rate of catalysis, the analysis of the frequency behavior of the developed propagation channels in the form of transfer functions shows significant difference introduce by the inclusion of the molecular antennas into the diffusion-only model. It is also shown that for t > > 0 and with the information molecules' concentration greater than the Michaelis-Menten kinetic constant of the systems, the inclusion of surface receptors proteins and enzymes in the models

Testing the Use of Implicit Solvent in the Molecular Dynamics Modelling of DNA Flexibility

NASA Astrophysics Data System (ADS)

Mitchell, J.; Harris, S.

DNA flexibility controls packaging, looping and in some cases sequence specific protein binding. Molecular dynamics simulations carried out with a computationally efficient implicit solvent model are potentially a powerful tool for studying larger DNA molecules than can be currently simulated when water and counterions are represented explicitly. In this work we compare DNA flexibility at the base pair step level modelled using an implicit solvent model to that previously determined from explicit solvent simulations and database analysis. Although much of the sequence dependent behaviour is preserved in implicit solvent, the DNA is considerably more flexible when the approximate model is used. In addition we test the ability of the implicit solvent to model stress induced DNA disruptions by simulating a series of DNA minicircle topoisomers which vary in size and superhelical density. When compared with previously run explicit solvent simulations, we find that while the levels of DNA denaturation are similar using both computational methodologies, the specific structural form of the disruptions is different.

Modeling stochastic kinetics of molecular machines at multiple levels: from molecules to modules.

PubMed

Chowdhury, Debashish

2013-06-04

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Modeling Stochastic Kinetics of Molecular Machines at Multiple Levels: From Molecules to Modules

PubMed Central

Chowdhury, Debashish

2013-01-01

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. PMID:23746505

Structural Biology and Molecular Modeling in the Design of Novel DPP-4 Inhibitors

NASA Astrophysics Data System (ADS)

Scapin, Giovanna

Inhibition of dipeptidyl peptidase IV (DPP-4) is a promising new approach for the treatment of type 2 diabetes. DPP-4 is the enzyme responsible for inactivating the incretin hormones glucagon-like peptide 1 (GLP-1) and glucose dependent insulinotropic polypeptide (GIP), two hormones that play important roles in glucose homeostasis. The potent, orally bioavailable and highly selective small molecule DPP-4 inhibitor sitagliptin has been approved by the FDA as novel drug for the treatment of type 2 diabetes. The comparison between the binding mode of sitagliptin (a β-amino acid) and that of a second class of inhibitors (α-amino acid-based) initially led to the successful identification and design of structurally diverse and highly potent DPP-4 inhibitors. Further analysis of the crystal structure of sitagliptin bound to DPP-4 suggested that the central β-amino butanoyl moiety could be replaced by a rigid group. This was confirmed by molecular modeling, and the resulting cyclohexylamine analogs were synthesized and found to be potent DPP-4 inhibitors. However, the triazolopyrazine was predicted to be distorted in order to fit in the binding pocket, and the crystal structure showed that multiple conformations exist for this moiety. Additional molecular modeling studies were then used to improve potency of the cyclohexylamine series. In addition, a 3-D QSAR method was used to gain insight for reducing off-target DPP-8/9 activities. Novel compounds were thus synthesized and found to be potent DPP-4 inhibitors. Two compounds in particular were designed to be highly selective against off-target "DPP-4 Activity- and/or Structure Homologues" (DASH) enzymes while maintaining potency against DPP-4.

Molecular Imaging of Vulnerable Atherosclerotic Plaques in Animal Models

PubMed Central

Gargiulo, Sara; Gramanzini, Matteo; Mancini, Marcello

2016-01-01

Atherosclerosis is characterized by intimal plaques of the arterial vessels that develop slowly and, in some cases, may undergo spontaneous rupture with subsequent heart attack or stroke. Currently, noninvasive diagnostic tools are inadequate to screen atherosclerotic lesions at high risk of acute complications. Therefore, the attention of the scientific community has been focused on the use of molecular imaging for identifying vulnerable plaques. Genetically engineered murine models such as ApoE−/− and ApoE−/−Fbn1C1039G+/− mice have been shown to be useful for testing new probes targeting biomarkers of relevant molecular processes for the characterization of vulnerable plaques, such as vascular endothelial growth factor receptor (VEGFR)-1, VEGFR-2, intercellular adhesion molecule (ICAM)-1, P-selectin, and integrins, and for the potential development of translational tools to identify high-risk patients who could benefit from early therapeutic interventions. This review summarizes the main animal models of vulnerable plaques, with an emphasis on genetically altered mice, and the state-of-the-art preclinical molecular imaging strategies. PMID:27618031

Systematic study of 16O-induced fusion with the improved quantum molecular dynamics model

NASA Astrophysics Data System (ADS)

Wang, Ning; Zhao, Kai; Li, Zhuxia

2014-11-01

The heavy-ion fusion reactions with 16O bombarding on 62Ni,65Cu,74Ge,148Nd,180Hf,186W,208Pb,238U are systematically investigated with the improved quantum molecular dynamics model. The fusion cross sections at energies near and above the Coulomb barriers can be reasonably well reproduced by using this semiclassical microscopic transport model with the parameter sets SkP* and IQ3a. The dynamical nucleus-nucleus potentials and the influence of Fermi constraint on the fusion process are also studied simultaneously. In addition to the mean field, the Fermi constraint also plays a key role for the reliable description of the fusion process and for improving the stability of fragments in heavy-ion collisions.

Molecular Modeling of Ammonium, Calcium, Sulfur, and Sodium Lignosulphonates in Acid and Basic Aqueous Environments

NASA Astrophysics Data System (ADS)

Salazar Valencia, P. J.; Bolívar Marinez, L. E.; Pérez Merchancano, S. T.

2015-12-01

Lignosulphonates (LS), also known as lignin sulfonates or sulfite lignin, are lignins in sulfonated forms, obtained from the "sulfite liquors," a residue of the wood pulp extraction process. Their main utility lies in its wide range of properties, they can be used as additives, dispersants, binders, fluxing, binder agents, etc. in fields ranging from food to fertilizer manufacture and even as agents in the preparation of ion exchange membranes. Since they can be manufactured relatively easy and quickly, and that its molecular size can be manipulated to obtain fragments of very low molecular weight, they are used as transport agents in the food industry, cosmetics, pharmaceutical and drug development, and as molecular elements for the treatment of health problems. In this paper, we study the electronic structural and optical characteristics of LS incorporating ammonium, sulfur, calcium, and sodium ions in acidic and basic aqueous media in order to gain a better understanding of their behavior and the very interesting properties exhibit. The studies were performed using the molecular modeling program HyperChem 5 using the semiempirical method PM3 of the NDO Family (neglect of differential overlap), to calculate the structural properties. We calculated the electronic and optical properties using the semiempirical method ZINDO / CI.

Molecular weight kinetics and chain scission models for dextran polymers during ultrasonic degradation.

PubMed

Pu, Yuanyuan; Zou, Qingsong; Hou, Dianzhi; Zhang, Yiping; Chen, Shan

2017-01-20

Ultrasonic degradation of six dextran samples with different initial molecular weights (IMW) has been performed to investigate the degradation behavior and chain scission mechanism of dextrans. The weight-average molecular weight (Mw) and polydispersity index (D value) were monitored by High Performance Gel Permeation Chromatography (HPGPC). Results showed that Mw and D value decreased with increasing ultrasonic time, resulting in a more homologous dextran solution with lower molecular weight. A significant degradation occurred in dextrans with higher IMW, particularly at the initial stage of the ultrasonic treatment. The Malhotra model was found to well describe the molecular weight kinetics for all dextran samples. Experimental data was fitted into two chain scission models to study dextran chain scission mechanism and the model performance was compared. Results indicated that the midpoint scission model agreed well with experimental results, with a linear regression factor of R 2 >0.99. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of computer-assisted molecular modeling for immunoassay of low molecular weight food contaminants: A review.

PubMed

Xu, Zhen-Lin; Shen, Yu-Dong; Beier, Ross C; Yang, Jin-Yi; Lei, Hong-Tao; Wang, Hong; Sun, Yuan-Ming

2009-08-11

Immunoassay for low molecular weight food contaminants, such as pesticides, veterinary drugs, and mycotoxins is now a well-established technique which meets the demand for a rapid, reliable, and cost-effective analytical method. However, due to limited understanding of the molecular structure of antibody binding sites and antigenic epitopes, as well as the intermolecular binding forces that come into play, the traditional 'trial and error' method used to develop antibodies still remains the method of choice. Therefore, development of enhanced immunochemical techniques for specific- and generic-assays, requires new approaches for antibody design that will improve affinity and specificity of the antibody in a more rapid and economic manner. Computer-assisted molecular modeling (CAMM) has been demonstrated to be a useful tool to help the immunochemist develop immunoassays. CAMM methods can be used to help direct improvements to important antibody features, and can provide insights into the effects of molecular structure on biological activity that are difficult or impossible to obtain in any other way. In this review, we briefly summarize applications of CAMM in immunoassay development, including assisting in hapten design, explaining cross-reactivity, modeling antibody-antigen interactions, and providing insights into the effects of the mouse body temperature on the three-dimensional conformation of a hapten during antibody production. The fundamentals and theory, programs and software, limitations, and prospects of CAMM in immunoassay development were also discussed.

Genomic Model with Correlation Between Additive and Dominance Effects.

PubMed

Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

2018-05-09

Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant

Multipole correction of atomic monopole models of molecular charge distribution. I. Peptides

NASA Technical Reports Server (NTRS)

Sokalski, W. A.; Keller, D. A.; Ornstein, R. L.; Rein, R.

1993-01-01

The defects in atomic monopole models of molecular charge distribution have been analyzed for several model-blocked peptides and compared with accurate quantum chemical values. The results indicate that the angular characteristics of the molecular electrostatic potential around functional groups capable of forming hydrogen bonds can be considerably distorted within various models relying upon isotropic atomic charges only. It is shown that these defects can be corrected by augmenting the atomic point charge models by cumulative atomic multipole moments (CAMMs). Alternatively, sets of off-center atomic point charges could be automatically derived from respective multipoles, providing approximately equivalent corrections. For the first time, correlated atomic multipoles have been calculated for N-acetyl, N'-methylamide-blocked derivatives of glycine, alanine, cysteine, threonine, leucine, lysine, and serine using the MP2 method. The role of the correlation effects in the peptide molecular charge distribution are discussed.

Unraveling additive from nonadditive effects using genomic relationship matrices.

PubMed

Muñoz, Patricio R; Resende, Marcio F R; Gezan, Salvador A; Resende, Marcos Deon Vilela; de Los Campos, Gustavo; Kirst, Matias; Huber, Dudley; Peter, Gary F

2014-12-01

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies. Copyright © 2014 by the Genetics Society of America.

Molecular gearing systems

DOE PAGES

Gakh, Andrei A.; Sachleben, Richard A.; Bryan, Jeff C.

1997-11-01

The race to create smaller devices is fueling much of the research in electronics. The competition has intensified with the advent of microelectromechanical systems (MEMS), in which miniaturization is already reaching the dimensional limits imposed by physics of current lithographic techniques. Also, in the realm of biochemistry, evidence is accumulating that certain enzyme complexes are capable of very sophisticated modes of motion. Complex synergistic biochemical complexes driven by sophisticated biomechanical processes are quite common. Their biochemical functions are based on the interplay of mechanical and chemical processes, including allosteric effects. In addition, the complexity of this interplay far exceeds thatmore » of typical chemical reactions. Understanding the behavior of artificial molecular devices as well as complex natural molecular biomechanical systems is difficult. Fortunately, the problem can be successfully resolved by direct molecular engineering of simple molecular systems that can mimic desired mechanical or electronic devices. These molecular systems are called technomimetics (the name is derived, by analogy, from biomimetics). Several classes of molecular systems that can mimic mechanical, electronic, or other features of macroscopic devices have been successfully synthesized by conventional chemical methods during the past two decades. In this article we discuss only one class of such model devices: molecular gearing systems.« less

An electrical circuit model for additive-modified SnO2 ceramics

NASA Astrophysics Data System (ADS)

Karami Horastani, Zahra; Alaei, Reza; Karami, Amirhossein

2018-05-01

In this paper an electrical circuit model for additive-modified metal oxide ceramics based on their physical structures and electrical resistivities is presented. The model predicts resistance of the sample at different additive concentrations and different temperatures. To evaluate the model two types of composite ceramics, SWCNT/SnO2 with SWCNT concentrations of 0.3, 0.6, 1.2, 2.4 and 3.8%wt, and Ag/SnO2 with Ag concentrations of 0.3, 0.5, 0.8 and 1.5%wt, were prepared and their electrical resistances versus temperature were experimentally measured. It is shown that the experimental data are in good agreement with the results obtained from the model. The proposed model can be used in the design process of ceramic-based gas sensors, and it also clarifies the role of additive in gas sensing process of additive-modified metal oxide gas sensors. Furthermore the model can be used in the system level modeling of designs in which these sensors are also present.

Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

NASA Astrophysics Data System (ADS)

Endah Saraswati, Teguh; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

2017-01-01

Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH3). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory.

Cross-Link Guided Molecular Modeling with ROSETTA

PubMed Central

Leitner, Alexander; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2013-01-01

Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods. PMID:24069194

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Moving Contact Lines: Linking Molecular Dynamics and Continuum-Scale Modeling.

PubMed

Smith, Edward R; Theodorakis, Panagiotis E; Craster, Richard V; Matar, Omar K

2018-05-17

Despite decades of research, the modeling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily life applications. On the one hand, molecular dynamics (MD) simulation has the ability to provide unique insight into the microscopic details that determine the dynamic behavior of the contact line, which is not possible with either continuum-scale simulations or experiments. On the other hand, continuum-based models provide a link to the macroscopic description of the system. In this Feature Article, we explore the complex range of physical factors, including the presence of surfactants, which governs the contact line motion through MD simulations. We also discuss links between continuum- and molecular-scale modeling and highlight the opportunities for future developments in this area.

Modeling Natural Anti-Inflammatory Compounds by Molecular Topology

PubMed Central

Galvez-Llompart, María; Zanni, Riccardo; García-Domenech, Ramón

2011-01-01

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds. PMID:22272145

Temperature effects on multiphase reactions of organic molecular markers: A modeling study

NASA Astrophysics Data System (ADS)

Pratap, Vikram; Chen, Ying; Yao, Guangming; Nakao, Shunsuke

2018-04-01

Various molecular markers are used in source apportionment studies. In early studies, molecular markers were assumed to be inert. However, recent studies suggest that molecular markers can decay rapidly through multiphase reactions, which makes interpretation of marker measurements challenging. This study presents a simplified model to account for the effects of temperature and relative humidity on the lifetime of molecular markers through a shift in gas-particle partitioning as well as a change in viscosity of the condensed phase. As a model case, this study examines the stability of levoglucosan, a key marker species of biomass burning, over a wide temperature range relevant to summertime and wintertime. Despite the importance of wood combustion for space heating in winter, the lifetime of levoglucosan in wintertime is not well understood. The model predicts that in low-temperature conditions, levoglucosan predominantly remains in the particle phase, and therefore its loss due to gas-phase oxidation reactions is significantly reduced. Furthermore, the movement of the levoglucosan from the bulk of the particle to the particle surface is reduced due to low diffusivity in the semi-solid state. The simplified model developed in this study reasonably reproduces upper and lower bounds of the lifetime of levoglucosan investigated in previous studies. The model results show that the levoglucosan depletion after seven days reduces significantly from ∼98% at 25 °C to <1% at 0 °C under dry conditions. The depletion of levoglucosan increases at higher relative humidities. However, at temperatures below 0 °C, levoglucosan appears to be a useful marker (lifetime > 1 week) even at 60% relative humidity irrespective of the assumed fragility parameter D that controls estimated diffusivity. The model shows that lifetime of an organic molecular marker strongly depends on assumed D especially when a semi-volatile marker is in semi-solid organic aerosol.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

NASA Technical Reports Server (NTRS)

Pisani, William A.; Radue, Matthew; Chinkanjanarot, Sorayot; Bednarcyk, Brett A.; Pineda, Evan J.; King, Julia A.; Odegard, Gregory M.

2018-01-01

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

Prediction of triple-charm molecular pentaquarks

NASA Astrophysics Data System (ADS)

Chen, Rui; Hosaka, Atsushi; Liu, Xiang

2017-12-01

In a one-boson-exchange model, we study molecular states of double-charm baryon [Ξc c(3621 )] and a charmed meson (D and D*). Our model indicates that there exist two possible triple-charm molecular pentaquarks, a Ξc cD state with I (JP)=0 (1 /2-), and a Ξc cD* state with I (JP)=0 (3 /2-), and we do not find bound solutions for isotriplet states. In addition, we also extend our formula to explore Ξc cB¯(*), Ξc cD¯(*), and Ξc cB(*) systems and find more possible heavy flavor molecular pentaquarks, a Ξc cB ¯ state with I (JP)=0 (1 /2-), a Ξc cB¯* state with I (JP)=0 (3 /2-), and Ξc cD¯*/Ξc cB* states with I (JP)=0 (1 /2-). Experimental research for these predicted triple-charm molecular pentaquarks is encouraged.

Molecular dynamics modelling of solidification in metals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boercker, D.B.; Belak, J.; Glosli, J.

1997-12-31

Molecular dynamics modeling is used to study the solidification of metals at high pressure and temperature. Constant pressure MD is applied to a simulation cell initially filled with both solid and molten metal. The solid/liquid interface is tracked as a function of time, and the data are used to estimate growth rates of crystallites at high pressure and temperature in Ta and Mg.

Quantum ring-polymer contraction method: Including nuclear quantum effects at no additional computational cost in comparison to ab initio molecular dynamics

NASA Astrophysics Data System (ADS)

John, Christopher; Spura, Thomas; Habershon, Scott; Kühne, Thomas D.

2016-04-01

We present a simple and accurate computational method which facilitates ab initio path-integral molecular dynamics simulations, where the quantum-mechanical nature of the nuclei is explicitly taken into account, at essentially no additional computational cost in comparison to the corresponding calculation using classical nuclei. The predictive power of the proposed quantum ring-polymer contraction method is demonstrated by computing various static and dynamic properties of liquid water at ambient conditions using density functional theory. This development will enable routine inclusion of nuclear quantum effects in ab initio molecular dynamics simulations of condensed-phase systems.

Simple model for molecular scattering

NASA Astrophysics Data System (ADS)

Mehta, Nirav; Ticknor, Christopher; Hazzard, Kaden

2017-04-01

The collisions of ultracold molecules are qualitatively different from the collisions of ultracold atoms due to the high density of bimolecular resonances near the collision energy. We present results from a simple N-channel scattering model with square-well channel potentials and constant channel couplings (inside the well) designed to reproduce essential features of chaotic molecular scattering. The potential depths and channel splittings are tuned to reproduce the appropriate density of states for the short-range bimolecular collision complex (BCC), which affords a direct comparison of the resulting level-spacing distribution to that expected from random matrix theory (RMT), namely the so-called Wigner surmise. The density of states also sets the scale for the rate of dissociation from the BCC to free molecules, as approximated by transition state theory (TST). Our model affords a semi-analytic solution for the scattering amplitude in the open channel, and a determinantal equation for the eigenenergies of the short-ranged BCC. It is likely the simplest finite-ranged scattering model that can be compared to expectations from the approximations of RMT, and TST. The validity of these approximations has implications for the many-channel Hubbard model recently developed. This research was funded in part by the National Science Foundation under Grant No. NSF PHY-1125915.

Molecular Analysis Research at Community College of Philadelphia

DTIC Science & Technology

2015-09-21

projects presented below fall under the category of "molecular genetics ", as presented in ARO Solicitation Number W911NF-12-R-0012-01. These projects...role of the GADD45 family of genes in innate immunity and sepsis. In addition to studying genetic components of the molecular response of myeloid...Equipment in left  column, procedure in right column.  kinetics of these molecular signaling pathways in genetic variants (gene KO models) has yet to

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Hybrid quantum and molecular mechanics embedded cluster models for chemistry on silicon and silicon carbide surfaces

NASA Astrophysics Data System (ADS)

Shoemaker, James Richard

Fabrication of silicon carbide (SiC) semiconductor devices are of interest for aerospace applications because of their high-temperature tolerance. Growth of an insulating SiO2 layer on SiC by oxidation is a poorly understood process, and sometimes produces interface defects that degrade device performance. Accurate theoretical models of surface chemistry, using quantum mechanics (QM), do not exist because of the huge computational cost of solving Schrodinger's equation for a molecular cluster large enough to represent a surface. Molecular mechanics (MM), which describes a molecule as a collection of atoms interacting through classical potentials, is a fast computational method, good at predicting molecular structure, but cannot accurately model chemical reactions. A new hybrid QM/MM computational method for surface chemistry was developed and applied to silicon and SiC surfaces. The addition of MM steric constraints was shown to have a large effect on the energetics of O atom adsorption on SiC. Adsorption of O atoms on Si-terminated SiC(111) favors above surface sites, in contrast to Si(111), but favors subsurface adsorption sites on C- terminated SiC(111). This difference, and the energetics of C atom etching via CO2 desorption, can explain the observed poor performance of SiC devices in which insulating layers were grown on C-terminated surfaces.

Modeling of molecular diffusion and thermal conduction with multi-particle interaction in compressible turbulence

NASA Astrophysics Data System (ADS)

Tai, Y.; Watanabe, T.; Nagata, K.

2018-03-01

A mixing volume model (MVM) originally proposed for molecular diffusion in incompressible flows is extended as a model for molecular diffusion and thermal conduction in compressible turbulence. The model, established for implementation in Lagrangian simulations, is based on the interactions among spatially distributed notional particles within a finite volume. The MVM is tested with the direct numerical simulation of compressible planar jets with the jet Mach number ranging from 0.6 to 2.6. The MVM well predicts molecular diffusion and thermal conduction for a wide range of the size of mixing volume and the number of mixing particles. In the transitional region of the jet, where the scalar field exhibits a sharp jump at the edge of the shear layer, a smaller mixing volume is required for an accurate prediction of mean effects of molecular diffusion. The mixing time scale in the model is defined as the time scale of diffusive effects at a length scale of the mixing volume. The mixing time scale is well correlated for passive scalar and temperature. Probability density functions of the mixing time scale are similar for molecular diffusion and thermal conduction when the mixing volume is larger than a dissipative scale because the mixing time scale at small scales is easily affected by different distributions of intermittent small-scale structures between passive scalar and temperature. The MVM with an assumption of equal mixing time scales for molecular diffusion and thermal conduction is useful in the modeling of the thermal conduction when the modeling of the dissipation rate of temperature fluctuations is difficult.

A Mouse Ependymoma Model Provides Molecular Insights into Tumor Formation.

PubMed

Pajtler, Kristian W; Pfister, Stefan M

2018-06-26

Ozawa et al. present a murine tumor model resembling the most frequent molecular group of human supratentorial ependymoma, ST-EPN-RELA. Their model shows RELA-fusion-based de novo ependymoma tumorigenesis in the forebrain derived from neural stem cells. Copyright © 2018. Published by Elsevier Inc.

The ALI-ARMS Code for Modeling Atmospheric non-LTE Molecular Band Emissions: Current Status and Applications

NASA Technical Reports Server (NTRS)

Kutepov, A. A.; Feofilov, A. G.; Manuilova, R. O.; Yankovsky, V. A.; Rezac, L.; Pesnell, W. D.; Goldberg, R. A.

2008-01-01

The Accelerated Lambda Iteration (ALI) technique was developed in stellar astrophysics at the beginning of 1990s for solving the non-LTE radiative transfer problem in atomic lines and multiplets in stellar atmospheres. It was later successfully applied to modeling the non-LTE emissions and radiative cooling/heating in the vibrational-rotational bands of molecules in planetary atmospheres. Similar to the standard lambda iterations ALI operates with the matrices of minimal dimension. However, it provides higher convergence rate and stability due to removing from the iterating process the photons trapped in the optically thick line cores. In the current ALI-ARMS (ALI for Atmospheric Radiation and Molecular Spectra) code version additional acceleration of calculations is provided by utilizing the opacity distribution function (ODF) approach and "decoupling". The former allows replacing the band branches by single lines of special shape, whereas the latter treats non-linearity caused by strong near-resonant vibration-vibrational level coupling without additional linearizing the statistical equilibrium equations. Latest code application for the non-LTE diagnostics of the molecular band emissions of Earth's and Martian atmospheres as well as for the non-LTE IR cooling/heating calculations are discussed.

Insights from molecular modeling and dynamics simulation of pathogen resistance (R) protein from brinjal.

PubMed

Shrivastava, Dipty; Nain, Vikrant; Sahi, Shakti; Verma, Anju; Sharma, Priyanka; Sharma, Prakash Chand; Kumar, Polumetla Ananda

2011-01-22

Resistance (R) protein recognizes molecular signature of pathogen infection and activates downstream hypersensitive response signalling in plants. R protein works as a molecular switch for pathogen defence signalling and represent one of the largest plant gene family. Hence, understanding molecular structure and function of R proteins has been of paramount importance for plant biologists. The present study is aimed at predicting structure of R proteins signalling domains (CC-NBS) by creating a homology model, refining and optimising the model by molecular dynamics simulation and comparing ADP and ATP binding. Based on sequence similarity with proteins of known structures, CC-NBS domains were initially modelled using CED- 4 (cell death abnormality protein) and APAF-1 (apoptotic protease activating factor) as multiple templates. The final CC-NBS structural model was built and optimized by molecular dynamic simulation for 5 nanoseconds (ns). Docking of ADP and ATP at active site shows that both ligand bind specifically with same residues and with minor difference (1 Kcal/mol) in binding energy. Sharing of binding site by ADP and ATP and low difference in their binding site makes CC-NBS suitable for working as molecular switch. Furthermore, structural superimposition elucidate that CC-NBS and CARD (caspase recruitment domains) domain of CED-4 have low RMSD value of 0.9 A° Availability of 3D structural model for both CC and NBS domains will . help in getting deeper insight in these pathogen defence genes.

Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

PubMed Central

Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

2014-01-01

Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

Molecular envelope and atomic model of an anti-terminated glyQS T-box regulator in complex with tRNAGly

PubMed Central

Chetnani, Bhaskar

2017-01-01

Abstract A T-box regulator or riboswitch actively monitors the levels of charged/uncharged tRNA and participates in amino acid homeostasis by regulating genes involved in their utilization or biosynthesis. It has an aptamer domain for cognate tRNA recognition and an expression platform to sense the charge state and modulate gene expression. These two conserved domains are connected by a variable linker that harbors additional secondary structural elements, such as Stem III. The structural basis for specific tRNA binding is known, but the structural basis for charge sensing and the role of other elements remains elusive. To gain new structural insights on the T-box mechanism, a molecular envelope was calculated from small angle X-ray scattering data for the Bacillus subtilis glyQS T-box riboswitch in complex with an uncharged tRNAGly. A structural model of an anti-terminated glyQS T-box in complex with its cognate tRNAGly was derived based on the molecular envelope. It shows the location and relative orientation of various secondary structural elements. The model was validated by comparing the envelopes of the wild-type complex and two variants. The structural model suggests that in addition to a possible regulatory role, Stem III could aid in preferential stabilization of the T-box anti-terminated state allowing read-through of regulated genes. PMID:28531275

Molecular dynamics-based model of VEGF-A and its heparin interactions.

PubMed

Uciechowska-Kaczmarzyk, Urszula; Babik, Sándor; Zsila, Ferenc; Bojarski, Krzysztof Kamil; Beke-Somfai, Tamás; Samsonov, Sergey A

2018-06-01

We present a computational model of the Vascular Endothelial Growth Factor (VEGF), an important regulator of blood vessels formation, which function is affected by its heparin interactions. Although structures of a receptor binding (RBD) and a heparin binding domain (HBD) of VEGF are known, there are structural data neither on the 12 amino acids interdomain linker nor on its complexes with heparin. We apply molecular docking and molecular dynamics techniques combined with circular dichroism spectroscopy to model the full structure of the dimeric VEGF and to propose putative molecular mechanisms underlying the function of VEGF/VEGF receptors/heparin system. We show that both the conformational flexibility of the linker and the formation of HBD-heparin-HBD sandwich-like structures regulate the mutual disposition of HBDs and so affect the VEGF-mediated signalling. Copyright © 2018 Elsevier Inc. All rights reserved.

Effect of phospholipids and their molecular species on cholesterol solubility and nucleation in human and model biles.

PubMed Central

Halpern, Z; Moshkowitz, M; Laufer, H; Peled, Y; Gilat, T

1993-01-01

Much research in the pathophysiology of gall stones has been devoted to various molecular species of bile salts. Recent findings have shown the importance of phospholipids in biliary pathophysiology. In the present study the addition of increasing doses of egg lecithin to human and model biles progressively prolonged the nucleation time. Concurrently biliary cholesterol was shifted from the vesicular to the non-vesicular carrier(s) while the cholesterol/phospholipid ratio of the remaining vesicles was progressively lowered. Model bile solutions of identical lipid concentration were prepared using phosphatidylcholine, phosphatidylserine, and phosphatidylethanolamine as the only phospholipid. With phosphatidylethanolamine most of the cholesterol was shifted to the vesicular carrier while phosphatidylserine shifted most of the cholesterol to the non-vesicular carrier(s). With phosphatidylcholine the cholesterol was distributed in both carriers. Phosphatidyl choline species composed of various acyl fatty acids in the sn-1 and sn-2 positions were used as the sole phospholipid in otherwise identical model bile solutions. With palmitic acid in the sn-1 position and arachidonic acid in the sn-2 position most of the cholesterol was found in the non-vesicular carrier. When stearic acid was used in sn-2 position instead of arachidonic acid most of the cholesterol was found in the vesicular carrier. These and other variations in phospholipid molecular species shifted cholesterol among its carriers and also modified the nucleation time of model biles. Most of these effects were also found upon addition of the various phospholipid species to human biles. These findings show the importance of phospholipid species in biliary pathophysiology and may be useful when trying to manipulate cholesterol carriers and solubility in bile. PMID:8432440

Molecular modeling of polymer composite-analyte interactions in electronic nose sensors

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K. S.

2003-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.

Many Molecular Properties from One Kernel in Chemical Space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

We introduce property-independent kernels for machine learning modeling of arbitrarily many molecular properties. The kernels encode molecular structures for training sets of varying size, as well as similarity measures sufficiently diffuse in chemical space to sample over all training molecules. Corresponding molecular reference properties provided, they enable the instantaneous generation of ML models which can systematically be improved through the addition of more data. This idea is exemplified for single kernel based modeling of internal energy, enthalpy, free energy, heat capacity, polarizability, electronic spread, zero-point vibrational energy, energies of frontier orbitals, HOMOLUMO gap, and the highest fundamental vibrational wavenumber. Modelsmore » of these properties are trained and tested using 112 kilo organic molecules of similar size. Resulting models are discussed as well as the kernels’ use for generating and using other property models.« less

Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines.

PubMed

Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z

2017-04-18

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2 , and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2 -rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

PubMed Central

Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

2016-01-01

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

Molecular Modeling of Interfacial Behaviors of Nanomaterials

DTIC Science & Technology

2007-05-01

potential was originally designed for the modeling of mixed covalent- ionic bonding and was successfully used to describe oxides in crystalline, glassy, and...is separates from the bulk liquid polymer, i.e., the structure of this layer, as influenced by that of the meatal surface, is significantly more...Striolo, J. Kieffer, and P. Cummings, ’Evaluation of Force- fields for molecular simulation of polyhedral oligomeric silsesquioxanes,’ J. Phys. Chem

Molecular imaging assessment of periodontitis lesions in an experimental mouse model.

PubMed

Ideguchi, Hidetaka; Yamashiro, Keisuke; Yamamoto, Tadashi; Shimoe, Masayuki; Hongo, Shoichi; Kochi, Shinsuke; Yoshihara-Hirata, Chiaki; Aoyagi, Hiroaki; Kawamura, Mari; Takashiba, Shogo

2018-06-06

We aimed to evaluate molecular imaging as a novel diagnostic tool for mice periodontitis model induced by ligature and Porphyromonas gingivalis (Pg) inoculation. Twelve female mice were assigned to the following groups: no treatment as control group (n = 4); periodontitis group induced by ligature and Pg as Pg group (n = 4); and Pg group treated with glycyrrhizinic acid (GA) as Pg + GA group (n = 4). All mice were administered a myeloperoxidase (MPO) activity-specific luminescent probe and observed using a charge-coupled device camera on day 14. Image analysis on all mice was conducted using software to determine the signal intensity of inflammation. Additionally, histological and radiographic evaluation for periodontal inflammation and bone resorption at the site of periodontitis, and quantitative enzyme-linked immunosorbent assay (ELISA) were conducted on three mice for each group. Each experiment was performed three times. Levels of serum IgG antibody against P. gingivalis were significantly higher in the Pg than in the Pg + GA group. Histological analyses indicated that the number of osteoclasts and neutrophils were significantly lower in the Pg + GA than in the Pg group. Micro-CT image analysis indicated no difference in bone resorption between the Pg and Pg + GA groups. The signal intensity of MPO activity was detected on the complete craniofacial image; moreover, strong signal intensity was localized specifically at the periodontitis site in the ex vivo palate, with group-wise differences. Molecular imaging analysis based on MPO activity showed high sensitivity of detection of periodontal inflammation in mice. Molecular imaging analysis based on MPO activity has potential as a diagnostic tool for periodontitis.

Molecular modeling and SPRi investigations of interleukin 6 (IL6) protein and DNA aptamers.

PubMed

Rhinehardt, Kristen L; Vance, Stephen A; Mohan, Ram V; Sandros, Marinella; Srinivas, Goundla

2018-06-01

Interleukin 6 (IL6), an inflammatory response protein has major implications in immune-related inflammatory diseases. Identification of aptamers for the IL6 protein aids in diagnostic, therapeutic, and theranostic applications. Three different DNA aptamers and their interactions with IL6 protein were extensively investigated in a phosphate buffed saline (PBS) solution. Molecular-level modeling through molecular dynamics provided insights of structural, conformational changes and specific binding domains of these protein-aptamer complexes. Multiple simulations reveal consistent binding region for all protein-aptamer complexes. Conformational changes coupled with quantitative analysis of center of mass (COM) distance, radius of gyration (R g ), and number of intermolecular hydrogen bonds in each IL6 protein-aptamer complex was used to determine their binding performance strength and obtain molecular configurations with strong binding. A similarity comparison of the molecular configurations with strong binding from molecular-level modeling concurred with Surface Plasmon Resonance imaging (SPRi) for these three aptamer complexes, thus corroborating molecular modeling analysis findings. Insights from the natural progression of IL6 protein-aptamer binding modeled in this work has identified key features such as the orientation and location of the aptamer in the binding event. These key features are not readily feasible from wet lab experiments and impact the efficacy of the aptamers in diagnostic and theranostic applications.

Mechanochemical models of processive molecular motors

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Sun, Sean X.

2012-05-01

Motor proteins are the molecular engines powering the living cell. These nanometre-sized molecules convert chemical energy, both enthalpic and entropic, into useful mechanical work. High resolution single molecule experiments can now observe motor protein movement with increasing precision. The emerging data must be combined with structural and kinetic measurements to develop a quantitative mechanism. This article describes a modelling framework where quantitative understanding of motor behaviour can be developed based on the protein structure. The framework is applied to myosin motors, with emphasis on how synchrony between motor domains give rise to processive unidirectional movement. The modelling approach shows that the elasticity of protein domains are important in regulating motor function. Simple models of protein domain elasticity are presented. The framework can be generalized to other motor systems, or an ensemble of motors such as muscle contraction. Indeed, for hundreds of myosins, our framework can be reduced to the Huxely-Simmons description of muscle movement in the mean-field limit.

Diffusion-Based Model for Synaptic Molecular Communication Channel.

PubMed

Khan, Tooba; Bilgin, Bilgesu A; Akan, Ozgur B

2017-06-01

Computational methods have been extensively used to understand the underlying dynamics of molecular communication methods employed by nature. One very effective and popular approach is to utilize a Monte Carlo simulation. Although it is very reliable, this method can have a very high computational cost, which in some cases renders the simulation impractical. Therefore, in this paper, for the special case of an excitatory synaptic molecular communication channel, we present a novel mathematical model for the diffusion and binding of neurotransmitters that takes into account the effects of synaptic geometry in 3-D space and re-absorption of neurotransmitters by the transmitting neuron. Based on this model we develop a fast deterministic algorithm, which calculates expected value of the output of this channel, namely, the amplitude of excitatory postsynaptic potential (EPSP), for given synaptic parameters. We validate our algorithm by a Monte Carlo simulation, which shows total agreement between the results of the two methods. Finally, we utilize our model to quantify the effects of variation in synaptic parameters, such as position of release site, receptor density, size of postsynaptic density, diffusion coefficient, uptake probability, and number of neurotransmitters in a vesicle, on maximum number of bound receptors that directly affect the peak amplitude of EPSP.

Naumovozyma castellii: an alternative model for budding yeast molecular biology.

PubMed

Karademir Andersson, Ahu; Cohn, Marita

2017-03-01

Naumovozyma castellii (Saccharomyces castellii) is a member of the budding yeast family Saccharomycetaceae. It has been extensively used as a model organism for telomere biology research and has gained increasing interest as a budding yeast model for functional analyses owing to its amenability to genetic modifications. Owing to the suitable phylogenetic distance to S. cerevisiae, the whole genome sequence of N. castellii has provided unique data for comparative genomic studies, and it played a key role in the establishment of the timing of the whole genome duplication and the evolutionary events that took place in the subsequent genomic evolution of the Saccharomyces lineage. Here we summarize the historical background of its establishment as a laboratory yeast species, and the development of genetic and molecular tools and strains. We review the research performed on N. castellii, focusing on areas where it has significantly contributed to the discovery of new features of molecular biology and to the advancement of our understanding of molecular evolution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Energetics using the single point IMOMO (integrated molecular orbital+molecular orbital) calculations: Choices of computational levels and model system

NASA Astrophysics Data System (ADS)

Svensson, Mats; Humbel, Stéphane; Morokuma, Keiji

1996-09-01

The integrated MO+MO (IMOMO) method, recently proposed for geometry optimization, is tested for accurate single point calculations. The principle idea of the IMOMO method is to reproduce results of a high level MO calculation for a large ``real'' system by dividing it into a small ``model'' system and the rest and applying different levels of MO theory for the two parts. Test examples are the activation barrier of the SN2 reaction of Cl-+alkyl chlorides, the C=C double bond dissociation of olefins and the energy of reaction for epoxidation of benzene. The effects of basis set and method in the lower level calculation as well as the effects of the choice of model system are investigated in detail. The IMOMO method gives an approximation to the high level MO energetics on the real system, in most cases with very small errors, with a small additional cost over the low level calculation. For instance, when the MP2 (Møller-Plesset second-order perturbation) method is used as the lower level method, the IMOMO method reproduces the results of very high level MO method within 2 kcal/mol, with less than 50% of additional computer time, for the first two test examples. When the HF (Hartree-Fock) method is used as the lower level method, it is less accurate and depends more on the choice of model system, though the improvement over the HF energy is still very significant. Thus the IMOMO single point calculation provides a method for obtaining reliable local energetics such as bond energies and activation barriers for a large molecular system.

Unicellular eukaryotes as models in cell and molecular biology: critical appraisal of their past and future value.

PubMed

Simon, Martin; Plattner, Helmut

2014-01-01

Unicellular eukaryotes have been appreciated as model systems for the analysis of crucial questions in cell and molecular biology. This includes Dictyostelium (chemotaxis, amoeboid movement, phagocytosis), Tetrahymena (telomere structure, telomerase function), Paramecium (variant surface antigens, exocytosis, phagocytosis cycle) or both ciliates (ciliary beat regulation, surface pattern formation), Chlamydomonas (flagellar biogenesis and beat), and yeast (S. cerevisiae) for innumerable aspects. Nowadays many problems may be tackled with "higher" eukaryotic/metazoan cells for which full genomic information as well as domain databases, etc., were available long before protozoa. Established molecular tools, commercial antibodies, and established pharmacology are additional advantages available for higher eukaryotic cells. Moreover, an increasing number of inherited genetic disturbances in humans have become elucidated and can serve as new models. Among lower eukaryotes, yeast will remain a standard model because of its peculiarities, including its reduced genome and availability in the haploid form. But do protists still have a future as models? This touches not only the basic understanding of biology but also practical aspects of research, such as fund raising. As we try to scrutinize, due to specific advantages some protozoa should and will remain favorable models for analyzing novel genes or specific aspects of cell structure and function. Outstanding examples are epigenetic phenomena-a field of rising interest. © 2014 Elsevier Inc. All rights reserved.

Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

PubMed

van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

2012-01-01

This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

Characterization, phase solubility and molecular modeling of α-cyclodextrin/pyrimethamine inclusion complex

NASA Astrophysics Data System (ADS)

Araujo, Marcia Valeria Gaspar de; Macedo, Osmir F. L.; Nascimento, Cristiane da Cunha; Conegero, Leila Souza; Barreto, Ledjane Silva; Almeida, Luis Eduardo; Costa, Nivan Bezerra da; Gimenez, Iara F.

2009-02-01

An inclusion complex between the dihydrofolate reductase inhibitor pyrimethamine (PYR) and α-cyclodextrin (α-CD) was prepared and characterized. From the phase-solubility diagram, a linear increase of PYR solubility was verified as a function of α-CD concentration, suggesting the formation of a soluble complex. A 1:1 host-guest stoichiometry can be proposed according to the Job's plot, obtained from the difference of PYR fluorescence intensity in the presence and absence of α-CD. Differential scanning calorimetry (DSC) measurements provided additional evidences of complexation such as the absence of the endothermic peak assigned to the melting of the drug. The inclusion mode characterized by two-dimensional 1H NMR spectroscopy (ROESY) involves penetration of the p-chlorophenyl ring into the α-CD cavity, in agreement to the orientation optimized by molecular modeling methods.

Molecular Sticker Model Stimulation on Silicon for a Maximum Clique Problem

PubMed Central

Ning, Jianguo; Li, Yanmei; Yu, Wen

2015-01-01

Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time. PMID:26075867

Modeling the nanoscale viscoelasticity of fluids by bridging non-Markovian fluctuating hydrodynamics and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Voulgarakis, Nikolaos K.; Satish, Siddarth; Chu, Jhih-Wei

2009-12-01

A multiscale computational method is developed to model the nanoscale viscoelasticity of fluids by bridging non-Markovian fluctuating hydrodynamics (FHD) and molecular dynamics (MD) simulations. To capture the elastic responses that emerge at small length scales, we attach an additional rheological model parallel to the macroscopic constitutive equation of a fluid. The widely used linear Maxwell model is employed as a working choice; other models can be used as well. For a fluid that is Newtonian in the macroscopic limit, this approach results in a parallel Newtonian-Maxwell model. For water, argon, and an ionic liquid, the power spectrum of momentum field autocorrelation functions of the parallel Newtonian-Maxwell model agrees very well with those calculated from all-atom MD simulations. To incorporate thermal fluctuations, we generalize the equations of FHD to work with non-Markovian rheological models and colored noise. The fluctuating stress tensor (white noise) is integrated in time in the same manner as its dissipative counterpart and numerical simulations indicate that this approach accurately preserves the set temperature in a FHD simulation. By mapping position and velocity vectors in the molecular representation onto field variables, we bridge the non-Markovian FHD with atomistic MD simulations. Through this mapping, we quantitatively determine the transport coefficients of the parallel Newtonian-Maxwell model for water and argon from all-atom MD simulations. For both fluids, a significant enhancement in elastic responses is observed as the wave number of hydrodynamic modes is reduced to a few nanometers. The mapping from particle to field representations and the perturbative strategy of developing constitutive equations provide a useful framework for modeling the nanoscale viscoelasticity of fluids.

Molecular modeling of polycarbonate materials: Glass transition and mechanical properties

NASA Astrophysics Data System (ADS)

Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim

2017-09-01

Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.

Targeting CYP51 for drug design by the contributions of molecular modeling.

PubMed

Rabelo, Vitor W; Santos, Taísa F; Terra, Luciana; Santana, Marcos V; Castro, Helena C; Rodrigues, Carlos R; Abreu, Paula A

2017-02-01

CYP51 is an enzyme of sterol biosynthesis pathway present in animals, plants, protozoa and fungi. This enzyme is described as an important drug target that is still of interest. Therefore, in this work, we reviewed the structure and function of CYP51 and explored the molecular modeling approaches for the development of new antifungal and antiprotozoans that target this enzyme. Crystallographic structures of CYP51 of some organisms have already been described in the literature, which enable the construction of homology models of other organisms' enzymes and molecular docking studies of new ligands. The binding mode and interactions of some new series of azoles with antifungal or antiprotozoan activities has been studied and showed important residues of the active site. Molecular modeling is an important tool to be explored for the discovery and optimization of CYP51 inhibitors with better activities, pharmacokinetics, and toxicological profiles. © 2016 Société Française de Pharmacologie et de Thérapeutique.

Rational molecular dynamics scheme for predicting optimum concentration loading of nano-additive in phase change materials

NASA Astrophysics Data System (ADS)

Rastogi, Monisha; Vaish, Rahul; Madhar, Niyaz Ahamad; Shaikh, Hamid; Al-Zahrani, S. M.

2015-10-01

The present study deals with the diffusion and phase transition behaviour of paraffin reinforced with carbon nano-additives namely graphene oxide (GO) and surface functionalized single walled carbon nanotubes (SWCNT). Bulk disordered systems of paraffin hydrocarbons impregnated with carbon nano-additives have been generated in realistic equilibrium conformations for potential application as latent heat storage systems. Ab initio molecular dynamics(MD) in conjugation with COMPASS forcefield has been implemented using periodic boundary conditions. The proposed scheme allows determination of optimum nano-additive loading for improving thermo-physical properties through analysis of mass, thermal and transport properties; and assists in determination of composite behaviour and related performance from microscopic point of view. It was observed that nanocomposites containing 7.8 % surface functionalised SWCNT and 55% GO loading corresponds to best latent heat storage system. The propounded methodology could serve as a by-pass route for economically taxing and iterative experimental procedures required to attain the optimum composition for best performance. The results also hint at the large unexplored potential of ab-initio classical MD techniques for predicting performance of new nanocomposites for potential phase change material applications.

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

PubMed

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Molecular simulations of self-assembly processes in metal-organic frameworks: Model dependence

NASA Astrophysics Data System (ADS)

Biswal, Debasmita; Kusalik, Peter G.

2017-07-01

Molecular simulation is a powerful tool for investigating microscopic behavior in various chemical systems, where the use of suitable models is critical to successfully reproduce the structural and dynamic properties of the real systems of interest. In this context, molecular dynamics simulation studies of self-assembly processes in metal-organic frameworks (MOFs), a well-known class of porous materials with interesting chemical and physical properties, are relatively challenging, where a reasonably accurate representation of metal-ligand interactions is anticipated to play an important role. In the current study, we both investigate the performance of some existing models and introduce and test new models to help explore the self-assembly in an archetypal Zn-carboxylate MOF system. To this end, the behavior of six different Zn-ion models, three solvent models, and two ligand models was examined and validated against key experimental structural parameters. To explore longer time scale ordering events during MOF self-assembly via explicit solvent simulations, it is necessary to identify a suitable combination of simplified model components representing metal ions, organic ligands, and solvent molecules. It was observed that an extended cationic dummy atom (ECDA) Zn-ion model combined with an all-atom carboxylate ligand model and a simple dipolar solvent model can reproduce characteristic experimental structures for the archetypal MOF system. The successful use of these models in extensive sets of molecular simulations, which provide key insights into the self-assembly mechanism of this archetypal MOF system occurring during the early stages of this process, has been very recently reported.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE PAGES

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

2017-02-24

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase

Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

PubMed Central

Crawford, Alasdair O.; Hamerton, Ian; Cavalli, Gabriel; Howlin, Brendan J.

2012-01-01

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties. PMID:22970230

Matching mice to malignancy: molecular subgroups and models of medulloblastoma

PubMed Central

Lau, Jasmine; Schmidt, Christin; Markant, Shirley L.; Taylor, Michael D.; Wechsler-Reya, Robert J.

2012-01-01

Introduction Medulloblastoma, the largest group of embryonal brain tumors, has historically been classified into five variants based on histopathology. More recently, epigenetic and transcriptional analyses of primary tumors have sub-classified medulloblastoma into four to six subgroups, most of which are incongruous with histopathological classification. Discussion Improved stratification is required for prognosis and development of targeted treatment strategies, to maximize cure and minimize adverse effects. Several mouse models of medulloblastoma have contributed both to an improved understanding of progression and to developmental therapeutics. In this review, we summarize the classification of human medulloblastoma subtypes based on histopathology and molecular features. We describe existing genetically engineered mouse models, compare these to human disease, and discuss the utility of mouse models for developmental therapeutics. Just as accurate knowledge of the correct molecular subtype of medulloblastoma is critical to the development of targeted therapy in patients, we propose that accurate modeling of each subtype of medulloblastoma in mice will be necessary for preclinical evaluation and optimization of those targeted therapies. PMID:22315164

Conformation of kainic acid in solution from molecular modelling and NMR spectra.

PubMed

Falk, M; Sidhu, P; Walter, J A

1998-01-01

Conformational behaviour of kainic acid in aqueous solution was elucidated by molecular mechanics and dynamics. The pucker of the five-membered ring in kainic acid was examined and compared with that of model compounds. In cyclopentane there is no barrier to pseudorotation, so that all puckered states coexist. In pyrrolidinium, the presence of a hetero-atom in the ring introduces a small barrier (about 0.6 kcal mol(-1)) to pseudorotation, separating two stable regions, A and B, which are equivalent by symmetry. In proline, the presence of the carboxylate group on C2 removes the symmetry but two stable conformational minima, A and B, remain. In kainic acid, the presence of side-chains on C3 and C4 introduces complications resulting in additional sub-minima in both regions, A and B. In solution, kainic acid is a complex mixture of conformers with comparable energies, because of the combination of several stable states of the pyrrolidinium ring with the torsional degrees of freedom arising from the two side-chains. The individual geometries, energies, and estimates of relative populations of these conformers were obtained from molecular dynamics simulations. The calculations were validated by a comparison of predicted inter-proton distances and vicinal proton coupling constants with the experimental quantities derived from NMR spectra.

Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates

NASA Astrophysics Data System (ADS)

Rahimi, Ehsan; Nejad, Shahram Mohammad

2012-05-01

Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices.

Isoscalar giant monopole resonance in Sn isotopes using a quantum molecular dynamics model

NASA Astrophysics Data System (ADS)

Tao, C.; Ma, Y. G.; Zhang, G. Q.; Cao, X. G.; Fang, D. Q.; Wang, H. W.; Xu, J.

2013-12-01

The isoscalar giant monopole resonance (GMR) in Sn isotopes and other nuclei is investigated in the framework of the isospin-dependent quantum molecular dynamics (IQMD) model. The spectrum of GMR is calculated by taking the rms radius of a nucleus as its monopole moment. The peak energy, the FWHM, and the strength of the GMR extracted by a Gaussian fit to the spectrum have been studied. The GMR peak energies for Sn isotopes from the calculations using a mass-number-dependent Gaussian wave-packet width σr for nucleons are found to be overestimated and show a weak dependence on the mass number compared with the experimental data. However, it is found that experimental data of the GMR peak energies for 56Ni, 90Zr, and 208Pb as well as Sn isotopes can be nicely reproduced after taking into account the isospin dependence in isotope chains in addition to the mass-number dependence of σr for nucleons in the IQMD model calculation.

Electron Transport Modeling of Molecular Nanoscale Bridges Used in Energy Conversion Schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunietz, Barry D

2016-08-09

The goal of the research program is to reliably describe electron transport and transfer processes at the molecular level. Such insight is essential for improving molecular applications of solar and thermal energy conversion. We develop electronic structure models to study (1) photoinduced electron transfer and transport processes in organic semiconducting materials, and (2) charge and heat transport through molecular bridges. We seek fundamental understanding of key processes, which lead to design new experiments and ultimately to achieve systems with improved properties.

Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

NASA Astrophysics Data System (ADS)

Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

2008-07-01

The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

Digital Learning Material for Student-Directed Model Building in Molecular Biology

ERIC Educational Resources Information Center

Aegerter-Wilmsen, Tinri; Coppens, Marjolijn; Janssen, Fred; Hartog, Rob; Bisseling, Ton

2005-01-01

The building of models to explain data and make predictions constitutes an important goal in molecular biology research. To give students the opportunity to practice such model building, two digital cases had previously been developed in which students are guided to build a model step by step. In this article, the development and initial…

Physical re-examination of parameters on a molecular collisions-based diffusion model for diffusivity prediction in polymers.

PubMed

Ohashi, Hidenori; Tamaki, Takanori; Yamaguchi, Takeo

2011-12-29

Molecular collisions, which are the microscopic origin of molecular diffusive motion, are affected by both the molecular surface area and the distance between molecules. Their product can be regarded as the free space around a penetrant molecule defined as the "shell-like free volume" and can be taken as a characteristic of molecular collisions. On the basis of this notion, a new diffusion theory has been developed. The model can predict molecular diffusivity in polymeric systems using only well-defined single-component parameters of molecular volume, molecular surface area, free volume, and pre-exponential factors. By consideration of the physical description of the model, the actual body moved and which neighbor molecules are collided with are the volume and the surface area of the penetrant molecular core. In the present study, a semiempirical quantum chemical calculation was used to calculate both of these parameters. The model and the newly developed parameters offer fairly good predictive ability. © 2011 American Chemical Society

Molecular Modeling Studies of 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitors through Receptor-Based 3D-QSAR and Molecular Dynamics Simulations.

PubMed

Qian, Haiyan; Chen, Jiongjiong; Pan, Youlu; Chen, Jianzhong

2016-09-19

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a potential target for the treatment of numerous human disorders, such as diabetes, obesity, and metabolic syndrome. In this work, molecular modeling studies combining molecular docking, 3D-QSAR, MESP, MD simulations and free energy calculations were performed on pyridine amides and 1,2,4-triazolopyridines as 11β-HSD1 inhibitors to explore structure-activity relationships and structural requirement for the inhibitory activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by docking strategy. The derived pharmacophoric features were further supported by MESP and Mulliken charge analyses using density functional theory. In addition, MD simulations and free energy calculations were employed to determine the detailed binding process and to compare the binding modes of inhibitors with different bioactivities. The binding free energies calculated by MM/PBSA showed a good correlation with the experimental biological activities. Free energy analyses and per-residue energy decomposition indicated the van der Waals interaction would be the major driving force for the interactions between an inhibitor and 11β-HSD1. These unified results may provide that hydrogen bond interactions with Ser170 and Tyr183 are favorable for enhancing activity. Thr124, Ser170, Tyr177, Tyr183, Val227, and Val231 are the key amino acid residues in the binding pocket. The obtained results are expected to be valuable for the rational design of novel potent 11β-HSD1 inhibitors.

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101

Molecular modeling of human neutral sphingomyelinase provides insight into its molecular interactions.

PubMed

Dinesh; Goswami, Angshumala; Suresh, Panneer Selvam; Thirunavukkarasu, Chinnasamy; Weiergräber, Oliver H; Kumar, Muthuvel Suresh

2011-01-01

The neutral sphingomyelinase (N-SMase) is considered a major candidate for mediating the stress-induced production of ceramide, and it plays an important role in cell-cycle arrest, apoptosis, inflammation, and eukaryotic stress responses. Recent studies have identified a small region at the very N-terminus of the 55 kDa tumour necrosis factor receptor (TNF-R55), designated the neutral sphingomyelinase activating domain (NSD) that is responsible for the TNF-induced activation of N-SMase. There is no direct association between TNF-R55 NSD and N-SMase; instead, a protein named factor associated with N-SMase activation (FAN) has been reported to couple the TNF-R55 NSD to N-SMase. Since the three-dimensional fold of N-SMase is still unknown, we have modeled the structure using the protein fold recognition and threading method. Moreover, we propose models for the TNF-R55 NSD as well as the FAN protein in order to study the structural basis of N-SMase activation and regulation. Protein-protein interaction studies suggest that FAN is crucially involved in mediating TNF-induced activation of the N-SMase pathway, which in turn regulates mitogenic and proinflammatory responses. Inhibition of N-SMase may lead to reduction of ceramide levels and hence may provide a novel therapeutic strategy for inflammation and autoimmune diseases. Molecular dynamics (MD) simulations were performed to check the stability of the predicted model and protein-protein complex; indeed, stable RMS deviations were obtained throughout the simulation. Furthermore, in silico docking of low molecular mass ligands into the active site of N-SMase suggests that His135, Glu48, Asp177, and Asn179 residues play crucial roles in this interaction. Based on our results, these ligands are proposed to be potent and selective N-SMase inhibitors, which may ultimately prove useful as lead compounds for drug development.

Molecular envelope and atomic model of an anti-terminated glyQS T-box regulator in complex with tRNAGly.

PubMed

Chetnani, Bhaskar; Mondragón, Alfonso

2017-07-27

A T-box regulator or riboswitch actively monitors the levels of charged/uncharged tRNA and participates in amino acid homeostasis by regulating genes involved in their utilization or biosynthesis. It has an aptamer domain for cognate tRNA recognition and an expression platform to sense the charge state and modulate gene expression. These two conserved domains are connected by a variable linker that harbors additional secondary structural elements, such as Stem III. The structural basis for specific tRNA binding is known, but the structural basis for charge sensing and the role of other elements remains elusive. To gain new structural insights on the T-box mechanism, a molecular envelope was calculated from small angle X-ray scattering data for the Bacillus subtilis glyQS T-box riboswitch in complex with an uncharged tRNAGly. A structural model of an anti-terminated glyQS T-box in complex with its cognate tRNAGly was derived based on the molecular envelope. It shows the location and relative orientation of various secondary structural elements. The model was validated by comparing the envelopes of the wild-type complex and two variants. The structural model suggests that in addition to a possible regulatory role, Stem III could aid in preferential stabilization of the T-box anti-terminated state allowing read-through of regulated genes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Molecular models of alginic acid: Interactions with calcium ions and calcite surfaces

NASA Astrophysics Data System (ADS)

Perry, Thomas D.; Cygan, Randall T.; Mitchell, Ralph

2006-07-01

Cation binding by polysaccharides is observed in many environments and is important for predictive environmental modeling, and numerous industrial and food technology applications. The complexities of these cation-organic interactions are well suited for predictive molecular modeling and the analysis of conformation and configuration of polysaccharides and their influence on cation binding. In this study, alginic acid was chosen as a model polymer system and representative disaccharide and polysaccharide subunits were developed. Molecular dynamics simulation of the torsion angles of the ether linkage between various monomeric subunits identified local and global energy minima for selected disaccharides. The simulations indicate stable disaccharide configurations and a common global energy minimum for all disaccharide models at Φ = 274 ± 7°, Ψ = 227 ± 5°, where Φ and Ψ are the torsion angles about the ether linkage. The ability of disaccharide subunits to bind calcium ions and to associate with the (101¯4) surface of calcite was also investigated. Molecular models of disaccharide interactions with calcite provide binding energy differences for conformations that are related to the proximity and residence densities of the electron-donating moieties with calcium ions on the calcite surface, which are controlled, in part, by the torsion of the ether linkage between monosaccharide units. Dynamically optimized configurations for polymer alginate models with calcium ions were also derived.

The Effect of Different Molecular Models on High School Students' Conceptions of Molecular Genetics

ERIC Educational Resources Information Center

Rotbain, Yosi; Stavy, Ruth; Marbach-Ad, Gili

2008-01-01

Our main goal in this study was to explore whether the use of models in high school molecular genetics instruction can contribute to students' understanding of concepts and processes in genetics. Three hundred and nineteen students from four comparable groups of 11th- and 12th-grade students participated. The control group (116 students) was…

Collective effects in models for interacting molecular motors and motor-microtubule mixtures

NASA Astrophysics Data System (ADS)

Menon, Gautam I.

2006-12-01

Three problems in the statistical mechanics of models for an assembly of molecular motors interacting with cytoskeletal filaments are reviewed. First, a description of the hydrodynamical behaviour of density-density correlations in fluctuating ratchet models for interacting molecular motors is outlined. Numerical evidence indicates that the scaling properties of dynamical behaviour in such models belong to the KPZ universality class. Second, the generalization of such models to include boundary injection and removal of motors is provided. In common with known results for the asymmetric exclusion processes, simulations indicate that such models exhibit sharp boundary driven phase transitions in the thermodynamic limit. In the third part of this paper, recent progress towards a continuum description of pattern formation in mixtures of motors and microtubules is described, and a non-equilibrium “phase-diagram” for such systems discussed.

Coarse-Grained Models Reveal Functional Dynamics – II. Molecular Dynamics Simulation at the Coarse-Grained Level – Theories and Biological Applications

PubMed Central

Chng, Choon-Peng; Yang, Lee-Wei

2008-01-01

Molecular dynamics (MD) simulation has remained the most indispensable tool in studying equilibrium/non-equilibrium conformational dynamics since its advent 30 years ago. With advances in spectroscopy accompanying solved biocomplexes in growing sizes, sampling their dynamics that occur at biologically interesting spatial/temporal scales becomes computationally intractable; this motivated the use of coarse-grained (CG) approaches. CG-MD models are used to study folding and conformational transitions in reduced resolution and can employ enlarged time steps due to the absence of some of the fastest motions in the system. The Boltzmann-Inversion technique, heavily used in parameterizing these models, provides a smoothed-out effective potential on which molecular conformation evolves at a faster pace thus stretching simulations into tens of microseconds. As a result, a complete catalytic cycle of HIV-1 protease or the assembly of lipid-protein mixtures could be investigated by CG-MD to gain biological insights. In this review, we survey the theories developed in recent years, which are categorized into Folding-based and Molecular-Mechanics-based. In addition, physical bases in the selection of CG beads/time-step, the choice of effective potentials, representation of solvent, and restoration of molecular representations back to their atomic details are systematically discussed. PMID:19812774

Molecular modeling of field-driven ion emission from ionic liquids

NASA Astrophysics Data System (ADS)

Zhang, Fei; He, Yadong; Qiao, Rui

2017-11-01

Traditionally, operating electrosprays in the purely ionic mode is challenging, but recent experiments confirmed that such operation can be achieved using room-temperature ionic liquids as working electrolytes. Such electrosprays have shown promise in applications including chemical analysis, nanomanufacturing, and space propulsion. The mechanistic and quantitative understanding of such electrosprays at the molecular level, however, remain limited at present. In this work, we simulated ion emission from EMIM-PF6 ionic liquid films using the molecular dynamics method. We show that, when the surface electric field is smaller than 1.5V/nm, the ion emission current predicted using coarse-grained ionic liquid model observes the classical scaling law by J. V. Iribarne and B. A. Thomson, i.e., ln(Je/ σ) En1/2. These simulations, however, cannot capture the co-emission of cations and anions from ionic liquid surface observed in some experiments. Such co-emission was successfully captured when united-atom models were adopted for the ionic liquids. By examining the co-emission events with picosecond, sub-angstrom resolution, we clarified the origins of the co-emission phenomenon and delineate the molecular events leading to ion emission.

Additions to Mars Global Reference Atmospheric Model (MARS-GRAM)

NASA Technical Reports Server (NTRS)

Justus, C. G.; James, Bonnie

1992-01-01

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification was also made which allows heights to go 'below' local terrain height and return 'realistic' pressure, density, and temperature, and not the surface values, as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local 'valley' areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch versions of Mars-GRAM are presented.

Additions to Mars Global Reference Atmospheric Model (Mars-GRAM)

NASA Technical Reports Server (NTRS)

Justus, C. G.

1991-01-01

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification has also been made which allows heights to go below local terrain height and return realistic pressure, density, and temperature (not the surface values) as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local valley areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch version of Mars-GRAM are presented.

Dynamic properties of molecular motors in burnt-bridge models

NASA Astrophysics Data System (ADS)

Artyomov, Maxim N.; Morozov, Alexander Yu; Pronina, Ekaterina; Kolomeisky, Anatoly B.

2007-08-01

Dynamic properties of molecular motors that fuel their motion by actively interacting with underlying molecular tracks are studied theoretically via discrete-state stochastic 'burnt-bridge' models. The transport of the particles is viewed as an effective diffusion along one-dimensional lattices with periodically distributed weak links. When an unbiased random walker passes the weak link it can be destroyed ('burned') with probability p, providing a bias in the motion of the molecular motor. We present a theoretical approach that allows one to calculate exactly all dynamic properties of motor proteins, such as velocity and dispersion, under general conditions. It is found that dispersion is a decreasing function of the concentration of bridges, while the dependence of dispersion on the burning probability is more complex. Our calculations also show a gap in dispersion for very low concentrations of weak links or for very low burning probabilities which indicates a dynamic phase transition between unbiased and biased diffusion regimes. Theoretical findings are supported by Monte Carlo computer simulations.

Improving a Lecture-Size Molecular Model Set by Repurposing Used Whiteboard Markers

ERIC Educational Resources Information Center

Dragojlovic, Veljko

2015-01-01

Preparation of an inexpensive model set from whiteboard markers and either HGS molecular model set or atoms made of wood is described. The model set is relatively easy to prepare and is sufficiently large to be suitable as an instructor set for use in lectures.

Molecular line emission models of Herbig-Haro objects. II - HCO(+) emission

NASA Technical Reports Server (NTRS)

Wolfire, Mark G.; Koenigl, Arieh

1993-01-01

We present time-dependent models of the chemistry and temperature of interstellar molecular gas clumps that are exposed to the radiation from propagating stellar-jet shocks. The X-ray, EUV, and FUV radiation from the shock initiates ion chemistry and also heats the gas in the clumps. Using representative parameters, we show that, on the shock transit time between the clumps, the abundances of the ionized molecular species that are produced in the clumps can exceed the values determined from steady state models by several orders of magnitude. Collisional excitation by the heated gas can lead to measurable line emission from several ionized species; as in previous investigations of X-ray-irradiated molecular gas, we find that electron impacts contribute significantly to this process. We apply these results to the interpretation of the HCO(+) line emission that has already been detected in several Herbig-Haro objects. We demonstrate that this picture provides a natural explanation of the fact that the line intensity typically peaks ahead of the associated shock, as well as of the reported low line-center velocities and narrow line widths. We tabulate several diagnostic line intensities of HCO(+) and other molecular species that may be used to infer the physical conditions in the emitting gas.

A Self-Assisting Protein Folding Model for Teaching Structural Molecular Biology.

PubMed

Davenport, Jodi; Pique, Michael; Getzoff, Elizabeth; Huntoon, Jon; Gardner, Adam; Olson, Arthur

2017-04-04

Structural molecular biology is now becoming part of high school science curriculum thus posing a challenge for teachers who need to convey three-dimensional (3D) structures with conventional text and pictures. In many cases even interactive computer graphics does not go far enough to address these challenges. We have developed a flexible model of the polypeptide backbone using 3D printing technology. With this model we have produced a polypeptide assembly kit to create an idealized model of the Triosephosphate isomerase mutase enzyme (TIM), which forms a structure known as TIM barrel. This kit has been used in a laboratory practical where students perform a step-by-step investigation into the nature of protein folding, starting with the handedness of amino acids to the formation of secondary and tertiary structure. Based on the classroom evidence we collected, we conclude that these models are valuable and inexpensive resource for teaching structural molecular biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Molecular Dynamic Modeling of Hemoglobin-Hemoglobin Interactions

NASA Astrophysics Data System (ADS)

Wu, Tao; Yang, Ye; Sheldon Wang, X.; Cohen, Barry; Ge, Hongya

2010-05-01

In this paper, we present a study of hemoglobin-hemoglobin interaction with model reduction methods. We begin with a simple spring-mass system with given parameters (mass and stiffness). With this known system, we compare the mode superposition method with Singular Value Decomposition (SVD) based Principal Component Analysis (PCA). Through PCA we are able to recover the principal direction of this system, namely the model direction. This model direction will be matched with the eigenvector derived from mode superposition analysis. The same technique will be implemented in a much more complicated hemoglobin-hemoglobin molecule interaction model, in which thousands of atoms in hemoglobin molecules are coupled with tens of thousands of T3 water molecule models. In this model, complex inter-atomic and inter-molecular potentials are replaced by nonlinear springs. We employ the same method to get the most significant modes and their frequencies of this complex dynamical system. More complex physical phenomena can then be further studied by these coarse grained models.

On the coalescence-dispersion modeling of turbulent molecular mixing

NASA Technical Reports Server (NTRS)

Givi, Peyman; Kosaly, George

1987-01-01

The general coalescence-dispersion (C/D) closure provides phenomenological modeling of turbulent molecular mixing. The models of Curl and Dopazo and O'Brien appear as two limiting C/D models that bracket the range of results one can obtain by various models. This finding is used to investigate the sensitivtiy of the results to the choice of the model. Inert scalar mixing is found to be less model-sensitive than mixing accompanied by chemical reaction. Infinitely fast chemistry approximation is used to relate the C/D approach to Toor's earlier results. Pure mixing and infinite rate chemistry calculations are compared to study further a recent result of Hsieh and O'Brien who found that higher concentration moments are not sensitive to chemistry.

Fischer and Schrock Carbene Complexes: A Molecular Modeling Exercise

ERIC Educational Resources Information Center

Montgomery, Craig D.

2015-01-01

An exercise in molecular modeling that demonstrates the distinctive features of Fischer and Schrock carbene complexes is presented. Semi-empirical calculations (PM3) demonstrate the singlet ground electronic state, restricted rotation about the C-Y bond, the positive charge on the carbon atom, and hence, the electrophilic nature of the Fischer…

Variational Implicit Solvation with Solute Molecular Mechanics: From Diffuse-Interface to Sharp-Interface Models.

PubMed

Li, Bo; Zhao, Yanxiang

2013-01-01

Central in a variational implicit-solvent description of biomolecular solvation is an effective free-energy functional of the solute atomic positions and the solute-solvent interface (i.e., the dielectric boundary). The free-energy functional couples together the solute molecular mechanical interaction energy, the solute-solvent interfacial energy, the solute-solvent van der Waals interaction energy, and the electrostatic energy. In recent years, the sharp-interface version of the variational implicit-solvent model has been developed and used for numerical computations of molecular solvation. In this work, we propose a diffuse-interface version of the variational implicit-solvent model with solute molecular mechanics. We also analyze both the sharp-interface and diffuse-interface models. We prove the existence of free-energy minimizers and obtain their bounds. We also prove the convergence of the diffuse-interface model to the sharp-interface model in the sense of Γ-convergence. We further discuss properties of sharp-interface free-energy minimizers, the boundary conditions and the coupling of the Poisson-Boltzmann equation in the diffuse-interface model, and the convergence of forces from diffuse-interface to sharp-interface descriptions. Our analysis relies on the previous works on the problem of minimizing surface areas and on our observations on the coupling between solute molecular mechanical interactions with the continuum solvent. Our studies justify rigorously the self consistency of the proposed diffuse-interface variational models of implicit solvation.

Imaging molecular dynamics in vivo--from cell biology to animal models.

PubMed

Timpson, Paul; McGhee, Ewan J; Anderson, Kurt I

2011-09-01

Advances in fluorescence microscopy have enabled the study of membrane diffusion, cell adhesion and signal transduction at the molecular level in living cells grown in culture. By contrast, imaging in living organisms has primarily been restricted to the localization and dynamics of cells in tissues. Now, imaging of molecular dynamics is on the cusp of progressing from cell culture to living tissue. This transition has been driven by the understanding that the microenvironment critically determines many developmental and pathological processes. Here, we review recent progress in fluorescent protein imaging in vivo by drawing primarily on cancer-related studies in mice. We emphasize the need for techniques that can be easily combined with genetic models and complement fluorescent protein imaging by providing contextual information about the cellular environment. In this Commentary we will consider differences between in vitro and in vivo experimental design and argue for an approach to in vivo imaging that is built upon the use of intermediate systems, such as 3-D and explant culture models, which offer flexibility and control that is not always available in vivo. Collectively, these methods present a paradigm shift towards the molecular-level investigation of disease and therapy in animal models of disease.

A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA.

PubMed

Zhang, Tao; Wei, Dong-Qing; Chou, Kuo-Chen

2012-03-01

Comparative molecular field analysis (CoMFA) is a widely used 3D-QSAR method by which we can investigate the potential relation between biological activity of compounds and their structural features. In this study, a new application of this approach is presented by combining the molecular modeling with a new developed pharmacophore model specific to CYP1A2 active site. During constructing the model, we used the molecular dynamics simulation and molecular docking method to select the sensible binding conformations for 17 CYP1A2 substrates based on the experimental data. Subsequently, the results obtained via the alignment of binding conformations of substrates were projected onto the active- site residues, upon which a simple blueprint of active site was produced. It was validated by the experimental and computational results that the model did exhibit the high degree of rationality and provide useful insights into the substrate binding. It is anticipated that our approach can be extended to investigate the protein-ligand interactions for many other enzyme-catalyzed systems as well.

Modeling of capacitively and inductively coupled plasma for molecular decontamination

NASA Astrophysics Data System (ADS)

Mihailova, Diana; Hagelaar, Gerjan; Belenguer, Philippe; Laurent, Christopher; Lo, Juslan; Caillier, Bruno; Therese, Laurent; Guillot, Philippe

2013-09-01

This project aims to study and to develop new technology bricks for next generation of molecular decontamination systems, including plasma solution, for various applications. The contamination control in the processing stages is a major issue for the industrial performance as well as for the development of new technologies in the surface treatment area. The main task is to create uniform low temperature plasma inside a reactor containing the object to be treated. Different plasma sources are modeled with the aim of finding the most efficient one for surface decontamination: inductively coupled plasma, capacitively coupled plasma and combination of both. The model used for testing the various plasma sources is a time dependent two-dimensional multi-fluid model. The model is applied to a simplified cylindrically symmetric geometry in pure argon gas. The modeling results are validated by comparison with experimental results and observations based on optical and physical diagnostic tools. The influence of various parameters (power, pressure, flow) is studied and the corresponding results are presented, compared and discussed. This work has been performed in the frame of the collaborative program PAUD (Plasma Airborne molecular contamination Ultra Desorption) funded by the French agency OSEO and certified by French global competitive clusters Minalogic and Trimatec.

QSAR, DFT and molecular modeling studies of peptides from HIV-1 to describe their recognition properties by MHC-I.

PubMed

Andrade-Ochoa, S; García-Machorro, J; Bello, Martiniano; Rodríguez-Valdez, L M; Flores-Sandoval, C A; Correa-Basurto, J

2017-08-03

Human immunodeficiency virus type-1 (HIV-1) has infected more than 40 million people around the world. HIV-1 treatment still has several side effects, and the development of a vaccine, which is another potential option for decreasing human infections, has faced challenges. This work presents a computational study that includes a quantitative structure activity relationship(QSAR) using density functional theory(DFT) for reported peptides to identify the principal quantum mechanics descriptors related to peptide activity. In addition, the molecular recognition properties of these peptides are explored on major histocompatibility complex I (MHC-I) through docking and molecular dynamics (MD) simulations accompanied by the Molecular Mechanics Generalized Born Surface Area (MMGBSA) approach for correlating peptide activity reported elsewhere vs. theoretical peptide affinity. The results show that the carboxylic acid and hydroxyl groups are chemical moieties that have an inverse relationship with biological activity. The number of sulfides, pyrroles and imidazoles from the peptide structure are directly related to biological activity. In addition, the HOMO orbital energy values of the total absolute charge and the Ghose-Crippen molar refractivity of peptides are descriptors directly related to the activity and affinity on MHC-I. Docking and MD simulation studies accompanied by an MMGBSA analysis show that the binding free energy without considering the entropic contribution is energetically favorable for all the complexes. Furthermore, good peptide interaction with the most affinity is evaluated experimentally for three proteins. Overall, this study shows that the combination of quantum mechanics descriptors and molecular modeling studies could help describe the immunogenic properties of peptides from HIV-1.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

On interfacial properties of tetrahydrofuran: Atomistic and coarse-grained models from molecular dynamics simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garrido, J. M.; Algaba, J.; Blas, F. J., E-mail: felipe@uhu.es

2016-04-14

We have determined the interfacial properties of tetrahydrofuran (THF) from direct simulation of the vapor-liquid interface. The molecules are modeled using six different molecular models, three of them based on the united-atom approach and the other three based on a coarse-grained (CG) approach. In the first case, THF is modeled using the transferable parameters potential functions approach proposed by Chandrasekhar and Jorgensen [J. Chem. Phys. 77, 5073 (1982)] and a new parametrization of the TraPPE force fields for cyclic alkanes and ethers [S. J. Keasler et al., J. Phys. Chem. B 115, 11234 (2012)]. In both cases, dispersive and coulombicmore » intermolecular interactions are explicitly taken into account. In the second case, THF is modeled as a single sphere, a diatomic molecule, and a ring formed from three Mie monomers according to the SAFT-γ Mie top-down approach [V. Papaioannou et al., J. Chem. Phys. 140, 054107 (2014)]. Simulations were performed in the molecular dynamics canonical ensemble and the vapor-liquid surface tension is evaluated from the normal and tangential components of the pressure tensor along the simulation box. In addition to the surface tension, we have also obtained density profiles, coexistence densities, critical temperature, density, and pressure, and interfacial thickness as functions of temperature, paying special attention to the comparison between the estimations obtained from different models and literature experimental data. The simulation results obtained from the three CG models as described by the SAFT-γ Mie approach are able to predict accurately the vapor-liquid phase envelope of THF, in excellent agreement with estimations obtained from TraPPE model and experimental data in the whole range of coexistence. However, Chandrasekhar and Jorgensen model presents significant deviations from experimental results. We also compare the predictions for surface tension as obtained from simulation results for all the models with

Molecular modeling the microstructure and phase behavior of bulk and inhomogeneous complex fluids

NASA Astrophysics Data System (ADS)

Bymaster, Adam

Accurate prediction of the thermodynamics and microstructure of complex fluids is contingent upon a model's ability to capture the molecular architecture and the specific intermolecular and intramolecular interactions that govern fluid behavior. This dissertation makes key contributions to improving the understanding and molecular modeling of complex bulk and inhomogeneous fluids, with an emphasis on associating and macromolecular molecules (water, hydrocarbons, polymers, surfactants, and colloids). Such developments apply broadly to fields ranging from biology and medicine, to high performance soft materials and energy. In the bulk, the perturbed-chain statistical associating fluid theory (PC-SAFT), an equation of state based on Wertheim's thermodynamic perturbation theory (TPT1), is extended to include a crossover correction that significantly improves the predicted phase behavior in the critical region. In addition, PC-SAFT is used to investigate the vapor-liquid equilibrium of sour gas mixtures, to improve the understanding of mercaptan/sulfide removal via gas treating. For inhomogeneous fluids, a density functional theory (DFT) based on TPT1 is extended to problems that exhibit radially symmetric inhomogeneities. First, the influence of model solutes on the structure and interfacial properties of water are investigated. The DFT successfully describes the hydrophobic phenomena on microscopic and macroscopic length scales, capturing structural changes as a function of solute size and temperature. The DFT is used to investigate the structure and effective forces in nonadsorbing polymer-colloid mixtures. A comprehensive study is conducted characterizing the role of polymer concentration and particle/polymer size ratio on the structure, polymer induced depletion forces, and tendency towards colloidal aggregation. The inhomogeneous form of the association functional is used, for the first time, to extend the DFT to associating polymer systems, applicable to any

Use of Molecular Models for Active Learning in Biochemistry Lecture Courses

ERIC Educational Resources Information Center

Hageman, James H.

2010-01-01

The pedagogical value of having biochemistry and organic chemistry students build and manipulate physical models of chemical species is well established in the literature. Nevertheless, for the most part, the use of molecular models is generally limited to several laboratory exercises or to demonstrations in the classroom setting. A simple…

Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

NASA Astrophysics Data System (ADS)

Hehr, Adam; Dapino, Marcelo J.

2016-04-01

Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

PubMed

Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

2016-12-01

High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Modeling process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-02-01

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

The structure of PX3 (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling.

PubMed

Pothoczki, Szilvia; Temleitner, László; Pusztai, László

2014-02-07

Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr3 electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl3 and PI3 are largely driven by steric effects.

The interaction of 2-mercaptobenzimidazole with human serum albumin as determined by spectroscopy, atomic force microscopy and molecular modeling.

PubMed

Li, Yuqin; Jia, Baoxiu; Wang, Hao; Li, Nana; Chen, Gaopan; Lin, Yuejuan; Gao, Wenhua

2013-04-01

The interaction of 2-mercaptobenzimidazole (MBI) with human serum albumin (HSA) was studied in vitro by equilibrium dialysis under normal physiological conditions. This study used fluorescence, ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared (FT-IR), circular dichroism (CD) and Raman spectroscopy, atomic force microscopy (AFM) and molecular modeling techniques. Association constants, the number of binding sites and basic thermodynamic parameters were used to investigate the quenching mechanism. Based on the fluorescence resonance energy transfer, the distance between the HSA and MBI was 2.495 nm. The ΔG(0), ΔH(0), and ΔS(0) values across temperature indicated that the hydrophobic interaction was the predominant binding Force. The UV, FT-IR, CD and Raman spectra confirmed that the HSA secondary structure was altered in the presence of MBI. In addition, the molecular modeling showed that the MBI-HSA complex was stabilized by hydrophobic forces, which resulted from amino acid residues. The AFM results revealed that the individual HSA molecule dimensions were larger after interaction with MBI. Overall, this study suggested a method for characterizing the weak intermolecular interaction. In addition, this method is potentially useful for elucidating the toxigenicity of MBI when it is combined with the biomolecular function effect, transmembrane transport, toxicological testing and other experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

Molecular epidemiology of acute leukemia in children: causal model, interaction of three factors-susceptibility, environmental exposure and vulnerability period.

PubMed

Mejía-Aranguré, Juan Manuel

Acute leukemias have a huge morphological, cytogenetic and molecular heterogeneity and genetic polymorphisms associated with susceptibility. Every leukemia presents causal factors associated with the development of the disease. Particularly, when three factors are present, they result in the development of acute leukemia. These phenomena are susceptibility, environmental exposure and a period that, for this model, has been called the period of vulnerability. This framework shows how the concepts of molecular epidemiology have established a reference from which it is more feasible to identify the environmental factors associated with the development of leukemia in children. Subsequently, the arguments show that only susceptible children are likely to develop leukemia once exposed to an environmental factor. For additional exposure, if the child is not susceptible to leukemia, the disease does not develop. In addition, this exposure should occur during a time window when hematopoietic cells and their environment are more vulnerable to such interaction, causing the development of leukemia. This model seeks to predict the time when the leukemia develops and attempts to give a context in which the causality of childhood leukemia should be studied. This information can influence and reduce the risk of a child developing leukemia. Copyright © 2016 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Fine-tuning molecular acoustic models: sensitivity of the predicted attenuation to the Lennard-Jones parameters

NASA Astrophysics Data System (ADS)

Petculescu, Andi G.; Lueptow, Richard M.

2005-01-01

In a previous paper [Y. Dain and R. M. Lueptow, J. Acoust. Soc. Am. 109, 1955 (2001)], a model of acoustic attenuation due to vibration-translation and vibration-vibration relaxation in multiple polyatomic gas mixtures was developed. In this paper, the model is improved by treating binary molecular collisions via fully pairwise vibrational transition probabilities. The sensitivity of the model to small variations in the Lennard-Jones parameters-collision diameter (σ) and potential depth (ɛ)-is investigated for nitrogen-water-methane mixtures. For a N2(98.97%)-H2O(338 ppm)-CH4(1%) test mixture, the transition probabilities and acoustic absorption curves are much more sensitive to σ than they are to ɛ. Additionally, when the 1% methane is replaced by nitrogen, the resulting mixture [N2(99.97%)-H2O(338 ppm)] becomes considerably more sensitive to changes of σwater. The current model minimizes the underprediction of the acoustic absorption peak magnitudes reported by S. G. Ejakov et al. [J. Acoust. Soc. Am. 113, 1871 (2003)]. .

Thermal conductivity of molten salt mixtures: Theoretical model supported by equilibrium molecular dynamics simulations.

PubMed

Gheribi, Aïmen E; Chartrand, Patrice

2016-02-28

A theoretical model for the description of thermal conductivity of molten salt mixtures as a function of composition and temperature is presented. The model is derived by considering the classical kinetic theory and requires, for its parametrization, only information on thermal conductivity of pure compounds. In this sense, the model is predictive. For most molten salt mixtures, no experimental data on thermal conductivity are available in the literature. This is a hindrance for many industrial applications (in particular for thermal energy storage technologies) as well as an obvious barrier for the validation of the theoretical model. To alleviate this lack of data, a series of equilibrium molecular dynamics (EMD) simulations has been performed on several molten chloride systems in order to determine their thermal conductivity in the entire range of composition at two different temperatures: 1200 K and 1300 K. The EMD simulations are first principles type, as the potentials used to describe the interactions have been parametrized on the basis of first principle electronic structure calculations. In addition to the molten chlorides system, the model predictions are also compared to a recent similar EMD study on molten fluorides and with the few reliable experimental data available in the literature. The accuracy of the proposed model is within the reported numerical and/or experimental errors.

Preparation of core-shell molecularly imprinted polymer via the combination of reversible addition-fragmentation chain transfer polymerization and click reaction.

PubMed

Chang, Limin; Li, Ying; Chu, Jia; Qi, Jingyao; Li, Xin

2010-11-08

In this paper, we demonstrated an efficient and robust route to the preparation of well-defined molecularly imprinted polymer based on reversible addition-fragmentation chain transfer (RAFT) polymerization and click chemistry. The alkyne terminated RAFT chain transfer agent was first synthesized, and then click reaction was used to graft RAFT agent onto the surface of silica particles which was modified by azide. Finally, imprinted thin film was prepared in the presence of 2,4-dichlorophenol as the template. The imprinted beads were demonstrated with a homogeneous polymer films (thickness of about 2.27 nm), and exhibited thermal stability under 255°C. The as-synthesized product showed obvious molecular imprinting effects towards the template, fast template rebinding kinetics and an appreciable selectivity over structurally related compounds. Copyright © 2010 Elsevier B.V. All rights reserved.

Mass accommodation of water: bridging the gap between molecular dynamics simulations and kinetic condensation models.

PubMed

Julin, Jan; Shiraiwa, Manabu; Miles, Rachael E H; Reid, Jonathan P; Pöschl, Ulrich; Riipinen, Ilona

2013-01-17

The condensational growth of submicrometer aerosol particles to climate relevant sizes is sensitive to their ability to accommodate vapor molecules, which is described by the mass accommodation coefficient. However, the underlying processes are not yet fully understood. We have simulated the mass accommodation and evaporation processes of water using molecular dynamics, and the results are compared to the condensation equations derived from the kinetic gas theory to shed light on the compatibility of the two. Molecular dynamics simulations were performed for a planar TIP4P-Ew water surface at four temperatures in the range 268-300 K as well as two droplets, with radii of 1.92 and 4.14 nm at T = 273.15 K. The evaporation flux from molecular dynamics was found to be in good qualitative agreement with that predicted by the simple kinetic condensation equations. Water droplet growth was also modeled with the kinetic multilayer model KM-GAP of Shiraiwa et al. [Atmos. Chem. Phys. 2012, 12, 2777]. It was found that, due to the fast transport across the interface, the growth of a pure water droplet is controlled by gas phase diffusion. These facts indicate that the simple kinetic treatment is sufficient in describing pure water condensation and evaporation. The droplet size was found to have minimal effect on the value of the mass accommodation coefficient. The mass accommodation coefficient was found to be unity (within 0.004) for all studied surfaces, which is in agreement with previous simulation work. Additionally, the simulated evaporation fluxes imply that the evaporation coefficient is also unity. Comparing the evaporation rates of the mass accommodation and evaporation simulations indicated that the high collision flux, corresponding to high supersaturation, present in typical molecular dynamics mass accommodation simulations can under certain conditions lead to an increase in the evaporation rate. Consequently, in such situations the mass accommodation coefficient

Mass Accommodation of Water: Bridging the Gap Between Molecular Dynamics Simulations and Kinetic Condensation Models

PubMed Central

2012-01-01

The condensational growth of submicrometer aerosol particles to climate relevant sizes is sensitive to their ability to accommodate vapor molecules, which is described by the mass accommodation coefficient. However, the underlying processes are not yet fully understood. We have simulated the mass accommodation and evaporation processes of water using molecular dynamics, and the results are compared to the condensation equations derived from the kinetic gas theory to shed light on the compatibility of the two. Molecular dynamics simulations were performed for a planar TIP4P-Ew water surface at four temperatures in the range 268–300 K as well as two droplets, with radii of 1.92 and 4.14 nm at T = 273.15 K. The evaporation flux from molecular dynamics was found to be in good qualitative agreement with that predicted by the simple kinetic condensation equations. Water droplet growth was also modeled with the kinetic multilayer model KM-GAP of Shiraiwa et al. [Atmos. Chem. Phys.2012, 117, 2777]. It was found that, due to the fast transport across the interface, the growth of a pure water droplet is controlled by gas phase diffusion. These facts indicate that the simple kinetic treatment is sufficient in describing pure water condensation and evaporation. The droplet size was found to have minimal effect on the value of the mass accommodation coefficient. The mass accommodation coefficient was found to be unity (within 0.004) for all studied surfaces, which is in agreement with previous simulation work. Additionally, the simulated evaporation fluxes imply that the evaporation coefficient is also unity. Comparing the evaporation rates of the mass accommodation and evaporation simulations indicated that the high collision flux, corresponding to high supersaturation, present in typical molecular dynamics mass accommodation simulations can under certain conditions lead to an increase in the evaporation rate. Consequently, in such situations the mass accommodation

Molecular pathogenesis of viral hemorrhagic fever.

PubMed

Basler, Christopher F

2017-07-01

The clinical syndrome referred to as viral hemorrhagic fever (VHF) can be caused by several different families of RNA viruses, including select members of the arenaviruses, bunyaviruses, filoviruses, and flaviviruses. VHF is characterized by malaise, fever, vascular permeability, decreased plasma volume, coagulation abnormalities, and varying degrees of hemorrhage. Study of the filovirus Ebola virus has demonstrated a critical role for suppression of innate antiviral defenses in viral pathogenesis. Additionally, antigen-presenting cells are targets of productive infection and immune dysregulation. Among these cell populations, monocytes and macrophages are proposed to produce damaging inflammatory cytokines, while infected dendritic cells fail to undergo proper maturation, potentially impairing adaptive immunity. Uncontrolled virus replication and accompanying inflammatory responses are thought to promote vascular leakage and coagulopathy. However, the specific molecular pathways that underlie these features of VHF remain poorly understood. The arenavirus Lassa virus and the flavivirus yellow fever virus exhibit similar molecular pathogenesis suggesting common underlying mechanisms. Because non-human primate models that closely mimic VHF are available for Ebola, Lassa, and yellow fever viruses, we propose that comparative molecular studies using these models will yield new insights into the molecular underpinnings of VHF and suggest new therapeutic approaches.

Characterization of the molecular defect in a feline model for type II GM2-gangliosidosis (Sandhoff disease).

PubMed

Muldoon, L L; Neuwelt, E A; Pagel, M A; Weiss, D L

1994-05-01

The Korat cat provides an animal model for type II GM2-gangliosidosis (Sandhoff disease) that may be suitable for tests of gene replacement therapy with the HEXB gene encoding the beta subunit of the beta-hexosaminidases. In the present report, we examined the brain and liver pathology of a typical Sandhoff-affected cat. We characterized the feline HEXB complementary DNA (cDNA) and determined the molecular defect in this feline model. cDNA libraries were produced from one normal and one affected animal, and cDNA clones homologous to human HEXB were sequenced. In the affected cDNA clone, the deletion of a cytosine residue at position +39 of the putative coding region results in a frame shift and a stop codon at base +191. This disease-related deletion was consistently detected by sequencing of cloned polymerase chain reaction amplified reverse transcribed messenger RNA from one more normal Korat and two additional affected animals. The defect was further demonstrated using single-strand conformational polymorphism analysis of the polymerase chain reaction products. In addition, alternative splicing of both normal and affected messenger RNAs was demonstrated. These results should facilitate the use of this animal model to assess gene therapy.

Equivalent Discrete-Time Channel Modeling for Molecular Communication With Emphasize on an Absorbing Receiver.

PubMed

Damrath, Martin; Korte, Sebastian; Hoeher, Peter Adam

2017-01-01

This paper introduces the equivalent discrete-time channel model (EDTCM) to the area of diffusion-based molecular communication (DBMC). Emphasis is on an absorbing receiver, which is based on the so-called first passage time concept. In the wireless communications community the EDTCM is well known. Therefore, it is anticipated that the EDTCM improves the accessibility of DBMC and supports the adaptation of classical wireless communication algorithms to the area of DBMC. Furthermore, the EDTCM has the capability to provide a remarkable reduction of computational complexity compared to random walk based DBMC simulators. Besides the exact EDTCM, three approximations thereof based on binomial, Gaussian, and Poisson approximation are proposed and analyzed in order to further reduce computational complexity. In addition, the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is adapted to all four channel models. Numerical results show the performance of the exact EDTCM, illustrate the performance of the adapted BCJR algorithm, and demonstrate the accuracy of the approximations.

Modeling of Ti-W Solidification Microstructures Under Additive Manufacturing Conditions

NASA Astrophysics Data System (ADS)

Rolchigo, Matthew R.; Mendoza, Michael Y.; Samimi, Peyman; Brice, David A.; Martin, Brian; Collins, Peter C.; LeSar, Richard

2017-07-01

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper.

Modeling Complex Workflow in Molecular Diagnostics

PubMed Central

Gomah, Mohamed E.; Turley, James P.; Lu, Huimin; Jones, Dan

2010-01-01

One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency. PMID:20007844

Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations

NASA Astrophysics Data System (ADS)

Wu, Hao; Nüske, Feliks; Paul, Fabian; Klus, Stefan; Koltai, Péter; Noé, Frank

2017-04-01

Markov state models (MSMs) and master equation models are popular approaches to approximate molecular kinetics, equilibria, metastable states, and reaction coordinates in terms of a state space discretization usually obtained by clustering. Recently, a powerful generalization of MSMs has been introduced, the variational approach conformation dynamics/molecular kinetics (VAC) and its special case the time-lagged independent component analysis (TICA), which allow us to approximate slow collective variables and molecular kinetics by linear combinations of smooth basis functions or order parameters. While it is known how to estimate MSMs from trajectories whose starting points are not sampled from an equilibrium ensemble, this has not yet been the case for TICA and the VAC. Previous estimates from short trajectories have been strongly biased and thus not variationally optimal. Here, we employ the Koopman operator theory and the ideas from dynamic mode decomposition to extend the VAC and TICA to non-equilibrium data. The main insight is that the VAC and TICA provide a coefficient matrix that we call Koopman model, as it approximates the underlying dynamical (Koopman) operator in conjunction with the basis set used. This Koopman model can be used to compute a stationary vector to reweight the data to equilibrium. From such a Koopman-reweighted sample, equilibrium expectation values and variationally optimal reversible Koopman models can be constructed even with short simulations. The Koopman model can be used to propagate densities, and its eigenvalue decomposition provides estimates of relaxation time scales and slow collective variables for dimension reduction. Koopman models are generalizations of Markov state models, TICA, and the linear VAC and allow molecular kinetics to be described without a cluster discretization.

Materials Testing and Cost Modeling for Composite Parts Through Additive Manufacturing

DTIC Science & Technology

2016-04-30

FDM include plastic jet printing (PJP), fused filament modeling ( FFM ), and fused filament fabrication (FFF). FFF was coined by the RepRap project to...additive manufacturing processes? • Fused deposition modeling (FDM) trademarked by Stratasys • Fused filament modeling ( FFM ) and fused filament

Validating clustering of molecular dynamics simulations using polymer models.

PubMed

Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

2011-11-14

Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers

Validating clustering of molecular dynamics simulations using polymer models

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the

A Langevin model for fluctuating contact angle behaviour parametrised using molecular dynamics.

PubMed

Smith, E R; Müller, E A; Craster, R V; Matar, O K

2016-12-06

Molecular dynamics simulations are employed to develop a theoretical model to predict the fluid-solid contact angle as a function of wall-sliding speed incorporating thermal fluctuations. A liquid bridge between counter-sliding walls is studied, with liquid-vapour interface-tracking, to explore the impact of wall-sliding speed on contact angle. The behaviour of the macroscopic contact angle varies linearly over a range of capillary numbers beyond which the liquid bridge pinches off, a behaviour supported by experimental results. Nonetheless, the liquid bridge provides an ideal test case to study molecular scale thermal fluctuations, which are shown to be well described by Gaussian distributions. A Langevin model for contact angle is parametrised to incorporate the mean, fluctuation and auto-correlations over a range of sliding speeds and temperatures. The resulting equations can be used as a proxy for the fully-detailed molecular dynamics simulation allowing them to be integrated within a continuum-scale solver.

PyEvolve: a toolkit for statistical modelling of molecular evolution.

PubMed

Butterfield, Andrew; Vedagiri, Vivek; Lang, Edward; Lawrence, Cath; Wakefield, Matthew J; Isaev, Alexander; Huttley, Gavin A

2004-01-05

Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences - ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from approximately 10 days to approximately 6 hours. PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used

Molecular modeling on structure-function analysis of human progesterone receptor modulators.

PubMed

Pal, Ria; Islam, Md Ataul; Hossain, Tabassum; Saha, Achintya

2011-01-01

Considering the significance of progesterone receptor (PR) modulators, the present study is explored to envisage the biophoric signals for binding to selective PR subtype-A using ligand-based quantitative structure activity relationship (QSAR) and pharmacophore space modeling studies on nonsteroidal substituted quinoline and cyclocymopol monomethyl ether derivatives. Consensus QSAR models (Training set (Tr): n(Tr)=100, R(2) (pred)=0.702; test set (Ts): n(Ts)=30, R(2) (pred)=0.705, R(2) (m)=0.635; validation set (Vs): n(Vs)=40, R(2) (pred)=0.715, R(2) (m)=0.680) suggest that molecular topology, atomic polarizability and electronegativity, atomic mass and van der Waals volume of the ligands have influence on the presence of functional atoms (F, Cl, N and O) and consequently contribute significant relations on ligand binding affinity. Receptor independent space modeling study (Tr: n(Tr)=26, Q(2)=0.927; Ts: n(Ts)=60, R(2) (pred)=0.613, R(2) (m)=0.545; Vs: n(Vs)=84, R(2) (pred)=0.611, R(2) (m)=0.507) indicates the importance of aromatic ring, hydrogen bond donor, molecular hydrophobicity and steric influence for receptor binding. The structure-function characterization is adjudged with the receptor-based docking study, explaining the significance of the mapped molecular attributes for ligand-receptor interaction in the catalytic cleft of PR-A.

A computational kinetic model of diffusion for molecular systems.

PubMed

Teo, Ivan; Schulten, Klaus

2013-09-28

Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.

Hidden Markov models and other machine learning approaches in computational molecular biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

ePMV Embeds Molecular Modeling into Professional Animation Software Environments

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2011-01-01

SUMMARY Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers, we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. PMID:21397181

Growth and modelling of spherical crystalline morphologies of molecular materials

NASA Astrophysics Data System (ADS)

Shalev, O.; Biswas, S.; Yang, Y.; Eddir, T.; Lu, W.; Clarke, R.; Shtein, M.

2014-10-01

Crystalline, yet smooth, sphere-like morphologies of small molecular compounds are desirable in a wide range of applications but are very challenging to obtain using common growth techniques, where either amorphous films or faceted crystallites are the norm. Here we show solvent-free, guard flow-assisted organic vapour jet printing of non-faceted, crystalline microspheroids of archetypal small molecular materials used in organic electronic applications. We demonstrate how process parameters control the size distribution of the spheroids and propose an analytical model and a phase diagram predicting the surface morphology evolution of different molecules based on processing conditions, coupled with the thermophysical and mechanical properties of the molecules. This experimental approach opens a path for exciting applications of small molecular organic compounds in optical coatings, textured surfaces with controlled wettability, pharmaceutical and food substance printing and others, where thick organic films and particles with high surface area are needed.

In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors.

PubMed

Mahapatra, Manoj Kumar; Bera, Krishnendu; Singh, Durg Vijay; Kumar, Rajnish; Kumar, Manoj

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

NASA Astrophysics Data System (ADS)

Bröer, Britta M.; Gurrath, Marion; Höltje, Hans-Dieter

2003-11-01

The ORL1 ( opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.

Analysis of molecular interactions in solid dosage forms; challenge to molecular pharmaceutics.

PubMed

Yamamoto, Keiji; Limwikrant, Waree; Moribe, Kunikazu

2011-01-01

The molecular states of active pharmaceutical ingredients (APIs) in pharmaceutical dosage forms strongly affect the properties and quality of a drug. Various important fundamental physicochemical studies were reviewed from the standpoint of molecular pharmaceutics. Mechanochemical effects were evaluated in mixtures of APIs and pharmaceutical additives. Amorphization, complex formation and nanoparticle formation are observed after grinding process depending on the combination of APIs and pharmaceutical additives. Sealed-heating method and mesoporous materials have been used to investigate drug molecular interactions in dosage forms. Molecular states have been investigated using powder X-ray diffraction, thermal analysis, IR, solid state fluorometry, and NMR. © 2011 Pharmaceutical Society of Japan

Learning Molecular Behaviour May Improve Student Explanatory Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Harris, Sara E.; Gold, Anne U.

2018-01-01

We assessed undergraduates' representations of the greenhouse effect, based on student-generated concept sketches, before and after a 30-min constructivist lesson. Principal component analysis of features in student sketches revealed seven distinct and coherent explanatory models including a new "Molecular Details" model. After the…

Flood loss model transfer: on the value of additional data

NASA Astrophysics Data System (ADS)

Schröter, Kai; Lüdtke, Stefan; Vogel, Kristin; Kreibich, Heidi; Thieken, Annegret; Merz, Bruno

2017-04-01

The transfer of models across geographical regions and flood events is a key challenge in flood loss estimation. Variations in local characteristics and continuous system changes require regional adjustments and continuous updating with current evidence. However, acquiring data on damage influencing factors is expensive and therefore assessing the value of additional data in terms of model reliability and performance improvement is of high relevance. The present study utilizes empirical flood loss data on direct damage to residential buildings available from computer aided telephone interviews that were carried out after the floods in 2002, 2005, 2006, 2010, 2011 and 2013 mainly in the Elbe and Danube catchments in Germany. Flood loss model performance is assessed for incrementally increased numbers of loss data which are differentiated according to region and flood event. Two flood loss modeling approaches are considered: (i) a multi-variable flood loss model approach using Random Forests and (ii) a uni-variable stage damage function. Both model approaches are embedded in a bootstrapping process which allows evaluating the uncertainty of model predictions. Predictive performance of both models is evaluated with regard to mean bias, mean absolute and mean squared errors, as well as hit rate and sharpness. Mean bias and mean absolute error give information about the accuracy of model predictions; mean squared error and sharpness about precision and hit rate is an indicator for model reliability. The results of incremental, regional and temporal updating demonstrate the usefulness of additional data to improve model predictive performance and increase model reliability, particularly in a spatial-temporal transfer setting.

SHAPEMOL: Modelling molecular line emission in protoplanetary and planetary nebulae with SHAPE

NASA Astrophysics Data System (ADS)

Santander-García, M.; Bujarrabal, V.; Steffen, W.; Koning, N.

2014-04-01

Modern instrumentation in radioastronomy constitutes a valuable tool for studying the Universe: ALMA will reach unprecedented sensitivities and spatial resolution, while Herschel/HIFI has opened a new window for probing molecular warm gas (˜50-1000 K). On the other hand, the SHAPE software has emerged in the last few years as the standard tool for determining the morphology and velocity field of different kinds of gaseous emission nebulae via spatio-kinematical modelling. Standard SHAPE implements radiative transfer solving, but it is only available for atomic species and not for molecules. Being aware of the growing importance of the development of tools for easying the analyses of molecular data from new era observatories, we introduce the computer code shapemol, a plug-in for SHAPE v5.0 with which we intend to fill the so far empty molecular niche. Shapemol enables spatio-kinematic modeling with accurate non-LTE calculations of line excitation and radiative transfer in molecular species. This code has been succesfully tested in the study of the excitation conditions of the molecular envelope of the young planetary nebula NGC 7027 using data from Herschel/HIFI and IRAM 30m. Currently, it allows radiative transfer solving in the 12CO and 13CO J=1-0 to J=17-16 lines. Shapemol, used along SHAPE, allows to easily generate synthetic maps to test against interferometric observations, as well as synthetic line profiles to match single-dish observations.

Using Set Model for Learning Addition of Integers

ERIC Educational Resources Information Center

Lestari, Umi Puji; Putri, Ratu Ilma Indra; Hartono, Yusuf

2015-01-01

This study aims to investigate how set model can help students' understanding of addition of integers in fourth grade. The study has been carried out to 23 students and a teacher of IVC SD Iba Palembang in January 2015. This study is a design research that also promotes PMRI as the underlying design context and activity. Results showed that the…

Molecular and Kinetic Models for High-rate Thermal Degradation of Polyethylene

DOE PAGES

Lane, J. Matthew; Moore, Nathan W.

2018-02-01

Thermal degradation of polyethylene is studied under the extremely high rate temperature ramps expected in laser-driven and X-ray ablation experiments—from 10 10 to 10 14 K/s in isochoric, condensed phases. The molecular evolution and macroscopic state variables are extracted as a function of density from reactive molecular dynamics simulations using the ReaxFF potential. The enthalpy, dissociation onset temperature, bond evolution, and observed cross-linking are shown to be rate dependent. These results are used to parametrize a kinetic rate model for the decomposition and coalescence of hydrocarbons as a function of temperature, temperature ramp rate, and density. In conclusion, the resultsmore » are contrasted to first-order random-scission macrokinetic models often assumed for pyrolysis of linear polyethylene under ambient conditions.« less

Molecular and Kinetic Models for High-rate Thermal Degradation of Polyethylene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lane, J. Matthew; Moore, Nathan W.

Thermal degradation of polyethylene is studied under the extremely high rate temperature ramps expected in laser-driven and X-ray ablation experiments—from 10 10 to 10 14 K/s in isochoric, condensed phases. The molecular evolution and macroscopic state variables are extracted as a function of density from reactive molecular dynamics simulations using the ReaxFF potential. The enthalpy, dissociation onset temperature, bond evolution, and observed cross-linking are shown to be rate dependent. These results are used to parametrize a kinetic rate model for the decomposition and coalescence of hydrocarbons as a function of temperature, temperature ramp rate, and density. In conclusion, the resultsmore » are contrasted to first-order random-scission macrokinetic models often assumed for pyrolysis of linear polyethylene under ambient conditions.« less

CHARMM additive and polarizable force fields for biophysics and computer-aided drug design

PubMed Central

Vanommeslaeghe, K.

2014-01-01

Background Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance. Scope of Review As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular bimolecular force fields. Additionally, we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields’ parametrization philosophy and methodology. Major Conclusions Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approximation is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1 microsecond on proteins, DNA, lipids and carbohydrates. General Significance Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calculations that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers a model that is an inherently more accurate model of the underlying physical forces driving macromolecular structures and dynamics. PMID:25149274

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

PubMed Central

Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

2013-01-01

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be

Molecular Sieve Bench Testing and Computer Modeling

NASA Technical Reports Server (NTRS)

Mohamadinejad, Habib; DaLee, Robert C.; Blackmon, James B.

1995-01-01

The design of an efficient four-bed molecular sieve (4BMS) CO2 removal system for the International Space Station depends on many mission parameters, such as duration, crew size, cost of power, volume, fluid interface properties, etc. A need for space vehicle CO2 removal system models capable of accurately performing extrapolated hardware predictions is inevitable due to the change of the parameters which influences the CO2 removal system capacity. The purpose is to investigate the mathematical techniques required for a model capable of accurate extrapolated performance predictions and to obtain test data required to estimate mass transfer coefficients and verify the computer model. Models have been developed to demonstrate that the finite difference technique can be successfully applied to sorbents and conditions used in spacecraft CO2 removal systems. The nonisothermal, axially dispersed, plug flow model with linear driving force for 5X sorbent and pore diffusion for silica gel are then applied to test data. A more complex model, a non-darcian model (two dimensional), has also been developed for simulation of the test data. This model takes into account the channeling effect on column breakthrough. Four FORTRAN computer programs are presented: a two-dimensional model of flow adsorption/desorption in a packed bed; a one-dimensional model of flow adsorption/desorption in a packed bed; a model of thermal vacuum desorption; and a model of a tri-sectional packed bed with two different sorbent materials. The programs are capable of simulating up to four gas constituents for each process, which can be increased with a few minor changes.

Modelling of additive manufacturing processes: a review and classification

NASA Astrophysics Data System (ADS)

Stavropoulos, Panagiotis; Foteinopoulos, Panagis

2018-03-01

Additive manufacturing (AM) is a very promising technology; however, there are a number of open issues related to the different AM processes. The literature on modelling the existing AM processes is reviewed and classified. A categorization of the different AM processes in process groups, according to the process mechanism, has been conducted and the most important issues are stated. Suggestions are made as to which approach is more appropriate according to the key performance indicator desired to be modelled and a discussion is included as to the way that future modelling work can better contribute to improving today's AM process understanding.

Efficient heterologous expression, functional characterization and molecular modeling of annular seabream digestive phospholipase A2.

PubMed

Smichi, Nabil; Othman, Houcemeddine; Achouri, Neila; Noiriel, Alexandre; Triki, Soumaya; Arondel, Vincent; Srairi-Abid, Najet; Abousalham, Abdelkarim; Gargouri, Youssef; Miled, Nabil; Fendri, Ahmed

2018-03-01

Here we report the cDNA cloning of a phospholipase A 2 (PLA 2 ) from five Sparidae species. The deduced amino acid sequences show high similarity with pancreatic PLA 2 . In addition, a phylogenetic tree derived from alignment of various available sequences revealed that Sparidae PLA 2 are closer to avian PLA 2 group IB than to mammals' ones. In order to understand the structure-function relationships of these enzymes, we report here the recombinant expression in E.coli, the refolding and characterization of His-tagged annular seabream PLA 2 (AsPLA 2 ). A single Ni-affinity chromatography step was used to obtain a highly purified recombinant AsPLA 2 with a molecular mass of 15kDa as attested by gel electrophoresis and MALDI-TOF mass spectrometry data. The enzyme has a specific activity of 400U.mg -1 measured on phosphatidylcholine at pH 8.5 and 50°C. The enzyme high thermo-activity and thermo-stability make it a potential candidate in various biological applications. The 3D structure models of these enzymes were compared with structures of phylogenetically related pancreatic PLA 2 . By following these models and utilizing molecular dynamics simulations, the resistance of the AsPLA 2 at high temperatures was explained. Using the monomolecular film technique, AsPLA 2 was found to be active on various phospholipids spread at the air/water interface at a surface pressure between 12 and 25dyncm -1 . Interestingly, this enzyme was shown to be mostly active on dilauroyl-phosphatidylglycerol monolayers and this behavior was confirmed by molecular docking and dynamics simulations analysis. The discovery of a thermo-active new member of Sparidae PLA 2 , provides new insights on structure-activity relationships of fish PLA 2 . Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular and cellular alterations in Down syndrome: toward the identification of targets for therapeutics.

PubMed

Créau, Nicole

2012-01-01

Down syndrome is a complex disease that has challenged molecular and cellular research for more than 50 years. Understanding the molecular bases of morphological, cellular, and functional alterations resulting from the presence of an additional complete chromosome 21 would aid in targeting specific genes and pathways for rescuing some phenotypes. Recently, progress has been made by characterization of brain alterations in mouse models of Down syndrome. This review will highlight the main molecular and cellular findings recently described for these models, particularly with respect to their relationship to Down syndrome phenotypes.

Phase computations and phase models for discrete molecular oscillators.

PubMed

Suvak, Onder; Demir, Alper

2012-06-11

Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations.

Mechanism of molecular recognition on molecular imprinted monolith by capillary electrochromatography.

PubMed

Liu, Zhao-Sheng; Xu, Yan-Li; Yan, Chao; Gao, Ru-Yu

2005-09-16

The recognition mechanism of molecularly imprinted polymer (MIP) in capillary electrochromatography (CEC) is complicated since it possesses a hybrid process, which comprises the features of chromatographic retention, electrophoretic migration and molecular imprinting. For an understanding of the molecular recognition of MIP in CEC, a monolithic MIP in a capillary with 1,1'-binaphthyl-2,2'-diamine (BNA) imprinting was prepared by in situ copolymerization of imprinted molecule, methacrylic acid and ethylene glycol dimethacrylate in porogenic solvent, a mixture of toluene-isooctane. Strong recognition ability and high column performance (theory plates was 43,000 plates/m) of BNA were achieved on this monolithic MIP in CEC mode. In addition, BNA and its structural analogue, 1,1'-bi-2, 2'-naphthol, differing in functional groups, were used as model compounds to study imprinting effect on the resultant BNA-imprinted monolithic column, a reference column without imprinting of BNA and a open capillary. The effects of organic modifier concentration, pH value of buffer, salt concentration of buffer and column temperature on the retention and recognition of two compounds were investigated. The results showed that the molecular recognition on MIP monolith in CEC mode mainly derived from imprinting cavities on BNA-imprinted polymer other than chromatographic retention and electrophoretic migration.

Combined molecular modelling and 3D-QSAR study for understanding the inhibition of NQO1 by heterocyclic quinone derivatives.

PubMed

López-Lira, Claudia; Alzate-Morales, Jans H; Paulino, Margot; Mella-Raipán, Jaime; Salas, Cristian O; Tapia, Ricardo A; Soto-Delgado, Jorge

2018-01-01

A combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular modelling methods were used to understand the potent inhibitory NAD(P)H:quinone oxidoreductase 1 (NQO1) activity of a set of 52 heterocyclic quinones. Molecular docking results indicated that some favourable interactions of key amino acid residues at the binding site of NQO1 with these quinones would be responsible for an improvement of the NQO1 activity of these compounds. The main interactions involved are hydrogen bond of the amino group of residue Tyr128, π-stacking interactions with Phe106 and Phe178, and electrostatic interactions with flavin adenine dinucleotide (FADH) cofactor. Three models were prepared by 3D-QSAR analysis. The models derived from Model I and Model III, shown leave-one-out cross-validation correlation coefficients (q 2 LOO ) of .75 and .73 as well as conventional correlation coefficients (R 2 ) of .93 and .95, respectively. In addition, the external predictive abilities of these models were evaluated using a test set, producing the predicted correlation coefficients (r 2 pred ) of .76 and .74, respectively. The good concordance between the docking results and 3D-QSAR contour maps provides helpful information about a rational modification of new molecules based in quinone scaffold, in order to design more potent NQO1 inhibitors, which would exhibit highly potent antitumor activity. © 2017 John Wiley & Sons A/S.

Terminal addition in a cellular world.

PubMed

Torday, J S; Miller, William B

2018-07-01

Recent advances in our understanding of evolutionary development permit a reframed appraisal of Terminal Addition as a continuous historical process of cellular-environmental complementarity. Within this frame of reference, evolutionary terminal additions can be identified as environmental induction of episodic adjustments to cell-cell signaling patterns that yield the cellular-molecular pathways that lead to differing developmental forms. Phenotypes derive, thereby, through cellular mutualistic/competitive niche constructions in reciprocating responsiveness to environmental stresses and epigenetic impacts. In such terms, Terminal Addition flows according to a logic of cellular needs confronting environmental challenges over space-time. A reconciliation of evolutionary development and Terminal Addition can be achieved through a combined focus on cell-cell signaling, molecular phylogenies and a broader understanding of epigenetic phenomena among eukaryotic organisms. When understood in this manner, Terminal Addition has an important role in evolutionary development, and chronic disease might be considered as a form of 'reverse evolution' of the self-same processes. Copyright © 2017. Published by Elsevier Ltd.

Lacosamide derivatives with anticonvulsant activity as carbonic anhydrase inhibitors. Molecular modeling, docking and QSAR analysis.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Duchowicz, Pablo R; Torrens, Francisco; Estrada, Mario R

2014-01-01

Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.

State-space reduction and equivalence class sampling for a molecular self-assembly model.

PubMed

Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

2016-07-01

Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.

CREATION OF THE MODEL ADDITIONAL PROTOCOL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Houck, F.; Rosenthal, M.; Wulf, N.

In 1991, the international nuclear nonproliferation community was dismayed to discover that the implementation of safeguards by the International Atomic Energy Agency (IAEA) under its NPT INFCIRC/153 safeguards agreement with Iraq had failed to detect Iraq's nuclear weapon program. It was now clear that ensuring that states were fulfilling their obligations under the NPT would require not just detecting diversion but also the ability to detect undeclared materials and activities. To achieve this, the IAEA initiated what would turn out to be a five-year effort to reappraise the NPT safeguards system. The effort engaged the IAEA and its Member Statesmore » and led to agreement in 1997 on a new safeguards agreement, the Model Protocol Additional to the Agreement(s) between States and the International Atomic Energy Agency for the Application of Safeguards. The Model Protocol makes explicit that one IAEA goal is to provide assurance of the absence of undeclared nuclear material and activities. The Model Protocol requires an expanded declaration that identifies a State's nuclear potential, empowers the IAEA to raise questions about the correctness and completeness of the State's declaration, and, if needed, allows IAEA access to locations. The information required and the locations available for access are much broader than those provided for under INFCIRC/153. The negotiation was completed in quite a short time because it started with a relatively complete draft of an agreement prepared by the IAEA Secretariat. This paper describes how the Model Protocol was constructed and reviews key decisions that were made both during the five-year period and in the actual negotiation.« less

ePMV embeds molecular modeling into professional animation software environments.

PubMed

Johnson, Graham T; Autin, Ludovic; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2011-03-09

Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties, and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology. Copyright © 2011 Elsevier Ltd. All rights reserved.

A molecular dynamics implementation of the 3D Mercedes-Benz water model

NASA Astrophysics Data System (ADS)

Hynninen, T.; Dias, C. L.; Mkrtchyan, A.; Heinonen, V.; Karttunen, M.; Foster, A. S.; Ala-Nissila, T.

2012-02-01

The three-dimensional Mercedes-Benz model was recently introduced to account for the structural and thermodynamic properties of water. It treats water molecules as point-like particles with four dangling bonds in tetrahedral coordination, representing H-bonds of water. Its conceptual simplicity renders the model attractive in studies where complex behaviors emerge from H-bond interactions in water, e.g., the hydrophobic effect. A molecular dynamics (MD) implementation of the model is non-trivial and we outline here the mathematical framework of its force-field. Useful routines written in modern Fortran are also provided. This open source code is free and can easily be modified to account for different physical context. The provided code allows both serial and MPI-parallelized execution. Program summaryProgram title: CASHEW (Coarse Approach Simulator for Hydrogen-bonding Effects in Water) Catalogue identifier: AEKM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKM_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 20 501 No. of bytes in distributed program, including test data, etc.: 551 044 Distribution format: tar.gz Programming language: Fortran 90 Computer: Program has been tested on desktop workstations and a Cray XT4/XT5 supercomputer. Operating system: Linux, Unix, OS X Has the code been vectorized or parallelized?: The code has been parallelized using MPI. RAM: Depends on size of system, about 5 MB for 1500 molecules. Classification: 7.7 External routines: A random number generator, Mersenne Twister ( http://www.math.sci.hiroshima-u.ac.jp/m-mat/MT/VERSIONS/FORTRAN/mt95.f90), is used. A copy of the code is included in the distribution. Nature of problem: Molecular dynamics simulation of a new geometric water model. Solution method: New force-field for

The Use of Molecular Modeling Programs in Medicinal Chemistry Instruction.

ERIC Educational Resources Information Center

Harrold, Marc W.

1992-01-01

This paper describes and evaluates the use of a molecular modeling computer program (Alchemy II) in a pharmaceutical education program. Provided are the hardware requirements and basic program features as well as several examples of how this program and its features have been applied in the classroom. (GLR)

Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

PubMed

Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

2014-05-01

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

NASA Astrophysics Data System (ADS)

Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

2017-12-01

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

The Molecular Mechanisms of Anesthetic Action: Updates and Cutting Edge Developments from the Field of Molecular Modeling.

PubMed

Bertaccini, Edward J

2010-07-08

For over 160 years, general anesthetics have been given for the relief of pain and suffering. While many theories of anesthetic action have been purported, it has become increasingly apparent that a significant molecular focus of anesthetic action lies within the family of ligand-gated ion channels (LGIC's). These protein channels have a transmembrane region that is composed of a pentamer of four helix bundles, symmetrically arranged around a central pore for ion passage. While initial and some current models suggest a possible cavity for binding within this four helix bundle, newer calculations postulate that the actual cavity for anesthetic binding may exist between four helix bundles. In either scenario, these cavities have a transmembrane mode of access and may be partially bordered by lipid moieties. Their physicochemical nature is amphiphilic. Anesthetic binding may alter the overall motion of a ligand-gated ion channel by a "foot-in-door" motif, resulting in the higher likelihood of and greater time spent in a specific channel state. The overall gating motion of these channels is consistent with that shown in normal mode analyses carried out both in vacuo as well as in explicitly hydrated lipid bilayer models. Molecular docking and large scale molecular dynamics calculations may now begin to show a more exact mode by which anesthetic molecules actually localize themselves and bind to specific protein sites within LGIC's, making the design of future improvements to anesthetic ligands a more realizable possibility.

Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories.

PubMed

Chikalov, Igor; Yao, Peggy; Moshkov, Mikhail; Latombe, Jean-Claude

2011-02-15

Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. They form and break while a protein deforms, for instance during the transition from a non-functional to a functional state. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor. This paper describes inductive learning methods to train protein-independent probabilistic models of H-bond stability from molecular dynamics (MD) simulation trajectories of various proteins. The training data contains 32 input attributes (predictors) that describe an H-bond and its local environment in a conformation c and the output attribute is the probability that the H-bond will be present in an arbitrary conformation of this protein achievable from c within a time duration Δ. We model dependence of the output variable on the predictors by a regression tree. Several models are built using 6 MD simulation trajectories containing over 4000 distinct H-bonds (millions of occurrences). Experimental results demonstrate that such models can predict H-bond stability quite well. They perform roughly 20% better than models based on H-bond energy alone. In addition, they can accurately identify a large fraction of the least stable H-bonds in a conformation. In most tests, about 80% of the 10% H-bonds predicted as the least stable are actually among the 10% truly least stable. The important attributes identified during the tree construction are consistent with previous findings. We use inductive learning methods to build protein-independent probabilistic models to study H-bond stability, and demonstrate that the models perform better than H-bond energy alone.

Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems

NASA Astrophysics Data System (ADS)

Stanton, L. G.; Glosli, J. N.; Murillo, M. S.

2018-04-01

Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.

An original traffic additional emission model and numerical simulation on a signalized road

NASA Astrophysics Data System (ADS)

Zhu, Wen-Xing; Zhang, Jing-Yu

2017-02-01

Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.

Ab Initio Modeling of Molecular Radiation

NASA Technical Reports Server (NTRS)

Jaffe, Richard; Schwenke, David

2014-01-01

Radiative emission from excited states of atoms and molecules can comprise a significant fraction of the total heat flux experienced by spacecraft during atmospheric entry at hypersonic speeds. For spacecraft with ablating heat shields, some of this radiative flux can be absorbed by molecular constituents in the boundary layer that are formed by the ablation process. Ab initio quantum mechanical calculations are carried out to predict the strengths of these emission and absorption processes. This talk will describe the methods used in these calculations using, as examples, the 4th positive emission bands of CO and the 1g+ 1u+ absorption in C3. The results of these calculations are being used as input to NASA radiation modeling codes like NeqAir, HARA and HyperRad.

Charge Transport Processes in Molecular Junctions

NASA Astrophysics Data System (ADS)

Smith, Christopher Eugene

Molecular electronics (ME) has evolved into a rich area of exploration that combines the fields of chemistry, materials, electronic engineering and computational modeling to explore the physics behind electronic conduction at the molecular level. Through studying charge transport properties of single molecules and nanoscale molecular materials the field has gained the potential to bring about new avenues for the miniaturization of electrical components where quantum phenomena are utilized to achieve solid state molecular device functionality. Molecular junctions are platforms that enable these studies and consist of a single molecule or a small group of molecules directly connected to electrodes. The work presented in this thesis has built upon the current understanding of the mechanisms of charge transport in ordered junctions using self-assembled monolayer (SAM) molecular thin films. Donor and acceptor compounds were synthesized and incorporated into SAMs grown on metal substrates then the transport properties were measured with conducting probe atomic force microscopy (CP-AFM). In addition to experimentally measured current-voltage (I-V) curves, the transport properties were addressed computationally and modeled theoretically. The key objectives of this project were to 1) investigate the impact of molecular structure on hole and electron charge transport, 2) understand the nature of the charge carriers and their structure-transport properties through long (<4 nm) conjugated molecular wires, and 3) quantitatively extract interfacial properties characteristic to macroscopic junctions, such as energy level alignment and molecule-contact electronic coupling from experimental I-V curves. Here, we lay ground work for creating a more complete picture of charge transport in macroscopically ordered molecular junctions of controlled architecture, length and charge carrier. The polaronic nature of hopping transport has been predicted in long, conjugated molecular wires

A model of early formation of uranium molecular oxides in laser-ablated plasmas

NASA Astrophysics Data System (ADS)

Finko, Mikhail S.; Curreli, Davide; Weisz, David G.; Crowhurst, Jonathan C.; Rose, Timothy P.; Koroglu, Batikan; Radousky, Harry B.; Armstrong, Michael R.

2017-12-01

In this work, we present a newly constructed U x O y reaction mechanism that consists of 30 reaction channels (21 of which are reversible channels) for 11 uranium molecular species (including ions). Both the selection of reaction channels and calculation of corresponding rate coefficients is accomplished via a comprehensive literature review and application of basic reaction rate theory. The reaction mechanism is supplemented by a detailed description of oxygen plasma chemistry (19 species and 142 reaction channels) and is used to model an atmospheric laser ablated uranium plume via a 0D (global) model. The global model is used to analyze the evolution of key uranium molecular species predicted by the reaction mechanism, and the initial stage of formation of uranium oxide species.

Research on Capacity Addition using Market Model with Transmission Congestion under Competitive Environment

NASA Astrophysics Data System (ADS)

Katsura, Yasufumi; Attaviriyanupap, Pathom; Kataoka, Yoshihiko

In this research, the fundamental premises for deregulation of the electric power industry are reevaluated. The authors develop a simple model to represent wholesale electricity market with highly congested network. The model is developed by simplifying the power system and market in New York ISO based on available data of New York ISO in 2004 with some estimation. Based on the developed model and construction cost data from the past, the economic impact of transmission line addition on market participants and the impact of deregulation on power plant additions under market with transmission congestion are studied. Simulation results show that the market signals may fail to facilitate proper capacity additions and results in the undesirable over-construction and insufficient-construction cycle of capacity addition.

Warm neutral halos around molecular clouds. VI - Physical and chemical modeling

NASA Technical Reports Server (NTRS)

Andersson, B.-G.; Wannier, P. G.

1993-01-01

A combined physical and chemical modeling of the halos around molecular clouds is presented, with special emphasis on the H-to-H2 transition. On the basis of H I 21 cm observations, it is shown that the halos are extended. A physical model is employed in conjunction with a chemistry code to provide a self-consistent description of the gas. The radiative transfer code provides a check with H I, CO, and OH observations. It is concluded that the warm neutral halos are not gravitationally bound to the underlying molecular clouds and are isobaric. It is inferred from the observed extent of the H I envelopes and the large observed abundance of OH in them that the generally accepted rate for H2 information on grains is too large by a factor of two to three.

Activities of mixtures of soil-applied herbicides with different molecular targets.

PubMed

Kaushik, Shalini; Streibig, Jens Carl; Cedergreen, Nina

2006-11-01

The joint action of soil-applied herbicide mixtures with similar or different modes of action has been assessed by using the additive dose model (ADM). The herbicides chlorsulfuron, metsulfuron-methyl, pendimethalin and pretilachlor, applied either singly or in binary mixtures, were used on rice (Oryza sativa L.). The growth (shoot) response curves were described by a logistic dose-response model. The ED50 values and their corresponding standard errors obtained from the response curves were used to test statistically if the shape of the isoboles differed from the reference model (ADM). Results showed that mixtures of herbicides with similar molecular targets, i.e. chlorsulfuron and metsulfuron (acetolactate synthase (ALS) inhibitors), and with different molecular targets, i.e. pendimethalin (microtubule assembly inhibitor) and pretilachlor (very long chain fatty acids (VLCFAs) inhibitor), followed the ADM. Mixing herbicides with different molecular targets gave different results depending on whether pretilachlor or pendimethalin was involved. In general, mixtures of pretilachlor and sulfonylureas showed synergistic interactions, whereas mixtures of pendimethalin and sulfonylureas exhibited either antagonistic or additive activities. Hence, there is a large potential for both increasing the specificity of herbicides by using mixtures and lowering the total dose for weed control, while at the same time delaying the development of herbicide resistance by using mixtures with different molecular targets. Copyright (c) 2006 Society of Chemical Industry.

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations.

PubMed

Anandakrishnan, Ramu; Aguilar, Boris; Onufriev, Alexey V

2012-07-01

The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.

Modeling of molecular nitrogen collisions and dissociation processes for direct simulation Monte Carlo.

PubMed

Parsons, Neal; Levin, Deborah A; van Duin, Adri C T; Zhu, Tong

2014-12-21

The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N2(Σg+1)-N2(Σg+1) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections.

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

Effects of molecular and particle scatterings on the model parameter for remote-sensing reflectance.

PubMed

Lee, ZhongPing; Carder, Kendall L; Du, KePing

2004-09-01

For optically deep waters, remote-sensing reflectance (r(rs)) is traditionally expressed as the ratio of the backscattering coefficient (b(b)) to the sum of absorption and backscattering coefficients (a + b(b)) that multiples a model parameter (g, or the so-called f'/Q). Parameter g is further expressed as a function of b(b)/(a + b(b)) (or b(b)/a) to account for its variation that is due to multiple scattering. With such an approach, the same g value will be derived for different a and b(b) values that provide the same ratio. Because g is partially a measure of the angular distribution of upwelling light, and the angular distribution from molecular scattering is quite different from that of particle scattering; g values are expected to vary with different scattering distributions even if the b(b)/a ratios are the same. In this study, after numerically demonstrating the effects of molecular and particle scatterings on the values of g, an innovative r(rs) model is developed. This new model expresses r(rs) in two separate terms: one governed by the phase function of molecular scattering and one governed by the phase function of particle scattering, with a model parameter introduced for each term. In this way the phase function effects from molecular and particle scatterings are explicitly separated and accounted for. This new model provides an analytical tool to understand and quantify the phase-function effects on r(rs), and a platform to calculate r(rs) spectrum quickly and accurately that is required for remote-sensing applications.

Computational Process Modeling for Additive Manufacturing (OSU)

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2015-01-01

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

Effect of molecular weight, temperature, and additives on the moisture sorption properties of polyethylene glycol.

PubMed

Baird, Jared A; Olayo-Valles, Roberto; Rinaldi, Carlos; Taylor, Lynne S

2010-01-01

Polyethylene glycol (PEG) is a hygroscopic polymer that undergoes the phenomenon of deliquescence once a critical relative humidity (RH(0)) is reached. The purpose of this study was to test the hypothesis that the deliquescence behavior of PEG will be affected by the polymer molecular weight, temperature, and the presence of additives. The deliquescence relative humidity for single component (RH(0)) and binary mixtures (RH(0,mix)) were measured using an automated gravimetric moisture analyzer at 25 and 40 degrees C. Changes in PEG crystallinity after exposure to moisture were qualitatively assessed using powder X-ray diffraction (PXRD). Optical microscopy was used to visually observe the deliquescence phenomenon. For single component systems, decreasing PEG MW and elevating the temperature resulted in a decrease in the observed RH(0). Physical mixtures of acetaminophen and anhydrous citric acid with both PEG 3350 and PEG 100,000 exhibited deliquescence (RH(0,mix)) at a relative humidity below that of either individual component. Qualitative changes in crystallinity were observed from the X-ray diffractograms for each PEG MW grade at high relative humidities, indicating that phase transformation (deliquescence) of the samples had occurred. In conclusion, it was found that the deliquescence behavior of PEG was affected by the polymer MW, temperature, and the presence of additives. This phenomenon may have important implications for the stability of PEG containing formulations.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to

Charge transfer in model peptides: obtaining Marcus parameters from molecular simulation.

PubMed

Heck, Alexander; Woiczikowski, P Benjamin; Kubař, Tomáš; Giese, Bernd; Elstner, Marcus; Steinbrecher, Thomas B

2012-02-23

Charge transfer within and between biomolecules remains a highly active field of biophysics. Due to the complexities of real systems, model compounds are a useful alternative to study the mechanistic fundamentals of charge transfer. In recent years, such model experiments have been underpinned by molecular simulation methods as well. In this work, we study electron hole transfer in helical model peptides by means of molecular dynamics simulations. A theoretical framework to extract Marcus parameters of charge transfer from simulations is presented. We find that the peptides form stable helical structures with sequence dependent small deviations from ideal PPII helices. We identify direct exposure of charged side chains to solvent as a cause of high reorganization energies, significantly larger than typical for electron transfer in proteins. This, together with small direct couplings, makes long-range superexchange electron transport in this system very slow. In good agreement with experiment, direct transfer between the terminal amino acid side chains can be dicounted in favor of a two-step hopping process if appropriate bridging groups exist. © 2012 American Chemical Society

Phase computations and phase models for discrete molecular oscillators

PubMed Central

2012-01-01

Background Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. Results In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. Conclusions The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations. PMID:22687330

Characterization of the molecular defect in a feline model for type II GM2-gangliosidosis (Sandhoff disease).

PubMed Central

Muldoon, L. L.; Neuwelt, E. A.; Pagel, M. A.; Weiss, D. L.

1994-01-01

The Korat cat provides an animal model for type II GM2-gangliosidosis (Sandhoff disease) that may be suitable for tests of gene replacement therapy with the HEXB gene encoding the beta subunit of the beta-hexosaminidases. In the present report, we examined the brain and liver pathology of a typical Sandhoff-affected cat. We characterized the feline HEXB complementary DNA (cDNA) and determined the molecular defect in this feline model. cDNA libraries were produced from one normal and one affected animal, and cDNA clones homologous to human HEXB were sequenced. In the affected cDNA clone, the deletion of a cytosine residue at position +39 of the putative coding region results in a frame shift and a stop codon at base +191. This disease-related deletion was consistently detected by sequencing of cloned polymerase chain reaction amplified reverse transcribed messenger RNA from one more normal Korat and two additional affected animals. The defect was further demonstrated using single-strand conformational polymorphism analysis of the polymerase chain reaction products. In addition, alternative splicing of both normal and affected messenger RNAs was demonstrated. These results should facilitate the use of this animal model to assess gene therapy. Images Figure 1 Figure 3 Figure 4 Figure 5 PMID:8178934

Molecular modeling of calmodulin: a comparison with crystallographic data

NASA Technical Reports Server (NTRS)

McDonald, J. J.; Rein, R.

1989-01-01

Two methods of side-chain placement on a modeled protein have been examined. Two molecular models of calmodulin were constructed that differ in the treatment of side chains prior to optimization of the molecule. A virtual bond analysis program developed by Purisima and Scheraga was used to determine the backbone conformation based on 2.2 angstroms resolution C alpha coordinates for the molecules. In the first model, side chains were initially constructed in an extended conformation. In the second model, a conformational grid search technique was employed. Calcium ions were treated explicitly during energy optimization using CHARMM. The models are compared to a recently published refined crystal structure of calmodulin. The results indicate that the initial choices for side-chains, but also significant effects on the main-chain conformation and supersecondary structure. The conformational differences are discussed. Analysis of these and other methods makes possible the formulation of a methodology for more appropriate side-chain placement in modeled proteins.

CHARMM additive and polarizable force fields for biophysics and computer-aided drug design.

PubMed

Vanommeslaeghe, K; MacKerell, A D

2015-05-01

Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance. As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomolecular force fields. Additionally, we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodology. Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approximation is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1μs on proteins, DNA, lipids and carbohydrates. Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calculations that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying physical forces driving macromolecular structures and dynamics. This article is part of a Special Issue entitled "Recent developments of molecular dynamics". Copyright © 2014 Elsevier B.V. All rights reserved.

On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis.

PubMed

Li, Bing; Chun, Hyonho; Zhao, Hongyu

2014-09-01

We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis.

Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

NASA Technical Reports Server (NTRS)

Seufzer, William J.

2014-01-01

Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

On an additive partial correlation operator and nonparametric estimation of graphical models.

PubMed

Lee, Kuang-Yao; Li, Bing; Zhao, Hongyu

2016-09-01

We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance.

On an additive partial correlation operator and nonparametric estimation of graphical models

PubMed Central

Li, Bing; Zhao, Hongyu

2016-01-01

Abstract We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance. PMID:29422689

Analysis of conjugation of chloramphenicol and hemoglobin by fluorescence, circular dichroism and molecular modeling

NASA Astrophysics Data System (ADS)

Ding, Fei; Liu, Wei; Sun, Ye; Yang, Xin-Ling; Sun, Ying; Zhang, Li

2012-01-01

Chloramphenicol is a low cost, broad spectrum, highly active antibiotic, and widely used in the treatment of serious infections, including typhoid fever and other life-threatening infections of the central nervous system and respiratory tract. The purpose of the present study was to examine the conjugation of chloramphenicol with hemoglobin (Hb) and compared with albumin at molecular level, utilizing fluorescence, UV/vis absorption, circular dichroism (CD) as well as molecular modeling. Fluorescence data indicate that drug bind Hb generate quenching via static mechanism, this corroborates UV/vis absorption measurements that the ground state complex formation with an affinity of 10 4 M -1, and the driving forces in the Hb-drug complex are hydrophilic interactions and hydrogen bonds, as derived from computational model. The accurate binding site of drug has been identified from the analysis of fluorescence and molecular modeling, α1β2 interface of Hb was assigned to possess high-affinity for drug, which located at the β-37 Trp nearby. The structural investigation of the complexed Hb by synchronous fluorescence, UV/vis absorption, and CD observations revealed some degree of Hb structure unfolding upon complexation. Based on molecular modeling, we can draw the conclusion that the binding affinity of drug with albumin is superior, compared with Hb. These phenomena can provide salient information on the absorption, distribution, pharmacology, and toxicity of chloramphenicol and other drugs which have analogous configuration with chloramphenicol.

High-excitation lines of molecular hydrogen: A discriminant between shock models

NASA Technical Reports Server (NTRS)

Burton, M.; Brand, P.; Moorhouse, A.; Geballe, T.

1989-01-01

The results of column densities of molecular hydrogen, calculated from nineteen infrared line intensities, are discussed. They were measured at peak 1 of the outflow of the Orion molecular cloud OMC-1. The 1-0 O(7) and 0-0 S(13) lines of H2, at 3.8 microns, are mapped over the source. Their intensity ratio is found to be independent of position in the outflow. These observations are well fitted by a simple cooling-flow model of the line emitting region, but seem to be at variance with predictions of C-shocks current in the literature.

Static dielectric constant of water within a bilayer using recent water models: a molecular dynamics study

NASA Astrophysics Data System (ADS)

Meneses-Juárez, Efrain; Rivas-Silva, Juan Francisco; González-Melchor, Minerva

2018-05-01

The water confined within a surfactant bilayer is studied using different water models via molecular dynamics simulations. We considered four representative rigid models of water: the SPC/E and the TIP4P/2005, which are commonly used in numerical calculations and the more recent TIP4Q and SPC/ε models, developed to reproduce the dielectric behaviour of pure water. The static dielectric constant of the confined water was analyzed as a function of the temperature for the four models. In all cases it decreases as the temperature increases. Additionally, the static dielectric constant of the bilayer-water system was estimated through its expression in terms of the fluctuations in the total dipole moment, usually applied for isotropic systems. The estimated dielectric was compared with the available experimental data. We found that the TIP4Q and the SPC/ε produce closer values to the experimental data than the other models, particularly at room temperature. It was found that the probability of finding the sodium ion close to the head of the surfactant decreases as the temperature increases, thus the head of the surfactant is more exposed to the interaction with water when the temperature is higher.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

PubMed

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2013-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

PubMed Central

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2012-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

PubMed

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

Expanding the clinical and molecular spectrum of PRMT7 mutations: 3 additional patients and review.

PubMed

Agolini, E; Dentici, M L; Bellacchio, E; Alesi, V; Radio, F C; Torella, A; Musacchia, F; Tartaglia, M; Dallapiccola, B; Nigro, V; Digilio, M C; Novelli, A

2018-03-01

Protein arginine methyltransferase 7 (PRMT7) is a member of a family of enzymes that catalyze the transfer of methyl groups from S-adenosyl-l-methionine to nitrogen atoms on arginine residues. Arginine methylation is involved in multiple biological processes, such as signal transduction, mRNA splicing, transcriptional control, DNA repair, and protein translocation. Currently, 7 patients have been described harboring compound heterozygous or homozygous variants in the PRMT7 gene, causing a novel intellectual disability syndrome, known as SBIDDS syndrome (Short Stature, Brachydactyly, Intellectual Developmental Disability, and Seizures). We report on 3 additional patients from 2 consanguineous families with severe/moderate intellectual disability, short stature, brachydactyly and dysmorphisms. Exome sequencing revealed 2 novel homozygous mutations in PRMT7. Our findings expand the clinical and molecular spectrum of homozygous PRMT7 mutations, associated to the SBIDDS syndrome, showing a possible correlation between the type of mutation and the severity of the phenotype. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparative study of the molecularly imprinted polymers prepared by reversible addition-fragmentation chain transfer "bulk" polymerization and traditional radical "bulk" polymerization.

PubMed

Ma, Yue; Pan, Guoqing; Zhang, Ying; Guo, Xianzhi; Zhang, Huiqi

2013-05-01

Bisphenol A (BPA) and propranolol-imprinted polymers have been prepared via both reversible addition-fragmentation chain transfer "bulk" polymerization (RAFTBP) and traditional radical "bulk" polymerization (TRBP) under similar reaction conditions, and their equilibrium binding properties were compared in detail for the first time. The chemical compositions, specific surface areas, equilibrium bindings, and selectivity of the obtained molecularly imprinted polymers (MIPs) were systematically characterized. The experimental results showed that the MIPs with molecular imprinting effects and quite fast binding kinetics could be readily prepared via RAFTBP, but they did not show improved template binding properties in comparison with those prepared via TRBP, which is in sharp contrast to many previous reports. This could be attributed to the heavily interrupted equilibrium between the dormant species and active radicals in the RAFT mechanism because of the occurrence of fast gelation during RAFTBP. The findings presented here strongly demonstrates that the application of controlled radical polymerizations (CRPs) in molecular imprinting does not always benefit the binding properties of the resultant MIPs, which is of significant importance for the rational use of CRPs in generating MIPs with improved properties. Copyright © 2013 John Wiley & Sons, Ltd.

Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

Coestimation of recombination, substitution and molecular adaptation rates by approximate Bayesian computation.

PubMed

Lopes, J S; Arenas, M; Posada, D; Beaumont, M A

2014-03-01

The estimation of parameters in molecular evolution may be biased when some processes are not considered. For example, the estimation of selection at the molecular level using codon-substitution models can have an upward bias when recombination is ignored. Here we address the joint estimation of recombination, molecular adaptation and substitution rates from coding sequences using approximate Bayesian computation (ABC). We describe the implementation of a regression-based strategy for choosing subsets of summary statistics for coding data, and show that this approach can accurately infer recombination allowing for intracodon recombination breakpoints, molecular adaptation and codon substitution rates. We demonstrate that our ABC approach can outperform other analytical methods under a variety of evolutionary scenarios. We also show that although the choice of the codon-substitution model is important, our inferences are robust to a moderate degree of model misspecification. In addition, we demonstrate that our approach can accurately choose the evolutionary model that best fits the data, providing an alternative for when the use of full-likelihood methods is impracticable. Finally, we applied our ABC method to co-estimate recombination, substitution and molecular adaptation rates from 24 published human immunodeficiency virus 1 coding data sets.

SketchBio: a scientist's 3D interface for molecular modeling and animation.

PubMed

Waldon, Shawn M; Thompson, Peter M; Hahn, Patrick J; Taylor, Russell M

2014-10-30

Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides opportunities for miscommunication. Working with multiple collaborators, a tool was developed (based on a set of design goals) to enable them to directly construct models and animations. SketchBio is presented, a tool that incorporates state-of-the-art bimanual interaction and drop shadows to enable rapid construction of molecular structures and animations. It includes three novel features: crystal-by-example, pose-mode physics, and spring-based layout that accelerate operations common in the formation of molecular models. Design decisions and their consequences are presented, including cases where iterative design was required to produce effective approaches. The design decisions, novel features, and inclusion of state-of-the-art techniques enabled SketchBio to meet all of its design goals. These features and decisions can be incorporated into existing and new tools to improve their effectiveness.

A model of early formation of uranium molecular oxides in laser-ablated plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finko, Mikhail S.; Curreli, Davide; Weisz, David G.

Here, in this work, we present a newly constructed U xO y reaction mechanism that consists of 30 reaction channels (21 of which are reversible channels) for 11 uranium molecular species (including ions). Both the selection of reaction channels and calculation of corresponding rate coefficients is accomplished via a comprehensive literature review and application of basic reaction rate theory. The reaction mechanism is supplemented by a detailed description of oxygen plasma chemistry (19 species and 142 reaction channels) and is used to model an atmospheric laser ablated uranium plume via a 0D (global) model. Finally, the global model is usedmore » to analyze the evolution of key uranium molecular species predicted by the reaction mechanism, and the initial stage of formation of uranium oxide species.« less

A model of early formation of uranium molecular oxides in laser-ablated plasmas

DOE PAGES

Finko, Mikhail S.; Curreli, Davide; Weisz, David G.; ...

2017-10-12

Here, in this work, we present a newly constructed U xO y reaction mechanism that consists of 30 reaction channels (21 of which are reversible channels) for 11 uranium molecular species (including ions). Both the selection of reaction channels and calculation of corresponding rate coefficients is accomplished via a comprehensive literature review and application of basic reaction rate theory. The reaction mechanism is supplemented by a detailed description of oxygen plasma chemistry (19 species and 142 reaction channels) and is used to model an atmospheric laser ablated uranium plume via a 0D (global) model. Finally, the global model is usedmore » to analyze the evolution of key uranium molecular species predicted by the reaction mechanism, and the initial stage of formation of uranium oxide species.« less

A model of lipid-free Apolipoprotein A-I revealed by iterative molecular dynamics simulation

DOE PAGES

Zhang, Xing; Lei, Dongsheng; Zhang, Lei; ...

2015-03-20

Apolipoprotein A-I (apo A-I), the major protein component of high-density lipoprotein, has been proven inversely correlated to cardiovascular risk in past decades. The lipid-free state of apo A-I is the initial stage which binds to lipids forming high-density lipoprotein. Molecular models of lipid-free apo A-I have been reported by methods like X-ray crystallography and chemical cross-linking/mass spectrometry (CCL/MS). Through structural analysis we found that those current models had limited consistency with other experimental results, such as those from hydrogen exchange with mass spectrometry. Through molecular dynamics simulations, we also found those models could not reach a stable equilibrium state. Therefore,more » by integrating various experimental results, we proposed a new structural model for lipidfree apo A-I, which contains a bundled four-helix N-terminal domain (1–192) that forms a variable hydrophobic groove and a mobile short hairpin C-terminal domain (193–243). This model exhibits an equilibrium state through molecular dynamics simulation and is consistent with most of the experimental results known from CCL/MS on lysine pairs, fluorescence resonance energy transfer and hydrogen exchange. This solution-state lipid-free apo A-I model may elucidate the possible conformational transitions of apo A-I binding with lipids in high-density lipoprotein formation.« less

Molecular modeling studies of 1,4-dihydro-4-oxoquinoline ribonucleosides with anti-HSV-1 activity

NASA Astrophysics Data System (ADS)

Yoneda, Julliane Diniz; Albuquerque, Magaly Girão; Leal, Kátia Zaccur; Seidl, Peter Rudolf; de Alencastro, Ricardo Bicca

2011-12-01

Eight human herpes viruses ( e.g., herpes simplex, varicella-zoster, Epstein-Barr, cytomegalovirus, Kaposi's sarcoma) are responsible for several diseases from sub-clinic manifestations to fatal infections, mostly in immunocompromised patients. The major limitations of the currently available antiviral drug therapy are drug resistance, host toxicity, and narrow spectrum of activity. However, some non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives ( e.g., PNU-183792) [4] shows broad spectrum antiviral activity. We have developed molecular modeling studies, including molecular docking and molecular dynamics simulations, based on a model proposed by Liu and co-workers [14] in order to understand the mechanism of action of a 6-chloro substituted 1,4-dihydro-4-oxoquinoline ribonucleoside, synthesized by the synthetic group, which showed anti-HSV-1 activity [9]. The molecular docking simulations confirmed the Liu's model showing that the ligand needs to dislocate template residues from the active site in order to interact with the viral DNA polymerase enzyme, reinforcing that the interaction with the Val823 residue is pivotal for the inhibitory activity of non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives, such as PNU-183792, with the HSV-1. The molecular dynamics simulations showed that the 6-chloro-benzyl group of PNU-183792 maintains its interaction with residues of the HSV-1 DNA polymerase hydrophobic pocket, considered important according to the Liu's model, and also showed that the methyl group bounded to the nitrogen atom from PNU-183792 is probably contributing to a push-pull effect with the carbonyl group.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

DOE PAGES

Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

2017-12-21

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Mechanical-Kinetic Modeling of a Molecular Walker from a Modular Design Principle

NASA Astrophysics Data System (ADS)

Hou, Ruizheng; Loh, Iong Ying; Li, Hongrong; Wang, Zhisong

2017-02-01

Artificial molecular walkers beyond burnt-bridge designs are complex nanomachines that potentially replicate biological walkers in mechanisms and functionalities. Improving the man-made walkers up to performance for widespread applications remains difficult, largely because their biomimetic design principles involve entangled kinetic and mechanical effects to complicate the link between a walker's construction and ultimate performance. Here, a synergic mechanical-kinetic model is developed for a recently reported DNA bipedal walker, which is based on a modular design principle, potentially enabling many directional walkers driven by a length-switching engine. The model reproduces the experimental data of the walker, and identifies its performance-limiting factors. The model also captures features common to the underlying design principle, including counterintuitive performance-construction relations that are explained by detailed balance, entropy production, and bias cancellation. While indicating a low directional fidelity for the present walker, the model suggests the possibility of improving the fidelity above 90% by a more powerful engine, which may be an improved version of the present engine or an entirely new engine motif, thanks to the flexible design principle. The model is readily adaptable to aid these experimental developments towards high-performance molecular walkers.

Molecular Modeling as a Self-Taught Component of a Conventional Undergraduate Chemical Reaction Engineering Course

ERIC Educational Resources Information Center

Rothe, Erhard W.; Zygmunt, William E.

2016-01-01

We inserted a self-taught molecular modeling project into an otherwise conventional undergraduate chemical-reaction-engineering course. Our objectives were that students should (a) learn with minimal instructor intervention, (b) gain an appreciation for the relationship between molecular structure and, first, macroscopic state functions in…

Gesture Interaction Browser-Based 3D Molecular Viewer.

PubMed

Virag, Ioan; Stoicu-Tivadar, Lăcrămioara; Crişan-Vida, Mihaela

2016-01-01

The paper presents an open source system that allows the user to interact with a 3D molecular viewer using associated hand gestures for rotating, scaling and panning the rendered model. The novelty of this approach is that the entire application is browser-based and doesn't require installation of third party plug-ins or additional software components in order to visualize the supported chemical file formats. This kind of solution is suitable for instruction of users in less IT oriented environments, like medicine or chemistry. For rendering various molecular geometries our team used GLmol (a molecular viewer written in JavaScript). The interaction with the 3D models is made with Leap Motion controller that allows real-time tracking of the user's hand gestures. The first results confirmed that the resulting application leads to a better way of understanding various types of translational bioinformatics related problems in both biomedical research and education.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in amore » stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

The Molecular Modeling Workbook for Organic Chemistry (by Warren J. Hehre, Alan J. Shusterman, and Janet E. Nelson)

NASA Astrophysics Data System (ADS)

Crouch, R. David

1999-09-01

LUMOs, it adds an increased presence of physical organic chemistry in the introductory course. And, although the exercises are not really molecular modeling, this workbook also provides a low-cost introduction to the field without the considerable cost of modeling software. If Spartan or MacSpartan is already available in the department, the possible tie-in with the workbook and the capability to project the results should make this an attractive addition to any instructor's repertoire of visualization tools for lecture. The Molecular Modeling Workbook for Organic Chemistry is definitely worthy of consideration by anyone interested in adding molecular modeling to the organic course.

Additive Genetic Variability and the Bayesian Alphabet

PubMed Central

Gianola, Daniel; de los Campos, Gustavo; Hill, William G.; Manfredi, Eduardo; Fernando, Rohan

2009-01-01

The use of all available molecular markers in statistical models for prediction of quantitative traits has led to what could be termed a genomic-assisted selection paradigm in animal and plant breeding. This article provides a critical review of some theoretical and statistical concepts in the context of genomic-assisted genetic evaluation of animals and crops. First, relationships between the (Bayesian) variance of marker effects in some regression models and additive genetic variance are examined under standard assumptions. Second, the connection between marker genotypes and resemblance between relatives is explored, and linkages between a marker-based model and the infinitesimal model are reviewed. Third, issues associated with the use of Bayesian models for marker-assisted selection, with a focus on the role of the priors, are examined from a theoretical angle. The sensitivity of a Bayesian specification that has been proposed (called “Bayes A”) with respect to priors is illustrated with a simulation. Methods that can solve potential shortcomings of some of these Bayesian regression procedures are discussed briefly. PMID:19620397

A molecular dynamics study of polymer/graphene interfacial systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rissanou, Anastassia N.; Harmandaris, Vagelis

2014-05-15

Graphene based polymer nanocomposites are hybrid materials with a very broad range of technological applications. In this work, we study three hybrid polymer/graphene interfacial systems (polystyrene/graphene, poly(methyl methacrylate)/graphene and polyethylene/graphene) through detailed atomistic molecular dynamics (MD) simulations. Density profiles, structural characteristics and mobility aspects are being examined at the molecular level for all model systems. In addition, we compare the properties of the hybrid systems to the properties of the corresponding bulk ones, as well as to theoretical predictions.

Formation and reduction of carcinogenic furan in various model systems containing food additives.

PubMed

Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

2015-12-15

The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Finite-Rate-Catalytic Model For Hypersonic Flows Informed By Molecular Dynamics

NASA Astrophysics Data System (ADS)

Schwartzentruber, T. E.; Valentini, P.; Norman, P.; Sorensen, C.

2011-05-01

The implementation of a finite-rate catalytic (FRC) wall boundary condition within a general 3D unstructured CFD solver is described. A set of one-step gas-surface chemical equations and atomistic parameters that deter- mine the reaction rates must be prescribed as input to the model. The chemical rate equations are solved at each wall face in the CFD simulation and result in a net production of species at the wall. In order for a finite- rate gas-surface reaction model to be consistent at equilibrium, it is determined that not all forward and back- ward rates can be specified arbitrarily. Provided that the forward rates for each surface recombination are as- signed, the backward rates must be determined using equilibrium constants that are consistent with the gas- phase chemistry model and thermodynamics. Reactive molecular dynamics (MD) simulations are performed us- ing the ReaxFFSiO potential to investigate oxygen-silica interactions. β-quartz and amorphous SiO2 surfaces are accommodated to a high temperature gas via MD simulation and reach a steady-state surface coverage. In addition to stable surface reconstructions a number of active sites are observed on which recombination occurs. Single collision MD simulations are performed where gas-phase oxygen atoms interact with the most dominant active site. Probabilities of recombination are found to have an exponential trend with gas-surface system temperature. The MD simulations are used to determine the activation energy for Eley-Rideal recombination of oxygen on a specific silica active site which is an important input parameter for the FRC model.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors.

PubMed

Hansson, Mari; Pemberton, John; Engkvist, Ola; Feierberg, Isabella; Brive, Lars; Jarvis, Philip; Zander-Balderud, Linda; Chen, Hongming

2014-06-01

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp(3)-hybridized carbons (Fsp3), and fraction of molecular framework (f(MF)). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. f(MF) has only a minor influence besides its correlation with the other molecular descriptors. © 2013 Society for Laboratory Automation and Screening.

Molecular Characterization of Thiols in Fossil Fuels by Michael Addition Reaction Derivatization and Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry.

PubMed

Wang, Meng; Zhao, Suoqi; Liu, Xuxia; Shi, Quan

2016-10-04

Thiols widely occur in sediments and fossil fuels. However, the molecular composition of these compounds is unclear due to the lack of appropriate analytical methods. In this work, a characterization method for thiols in fossil fuels was developed on the basis of Michael addition reaction derivatization followed by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). Model thiol compound studies showed that thiols were selectively reacted with phenylvinylsulfone and transformed to sulfones with greater than 98% conversions. This method was applied to a coker naphtha, light and heavy gas oils, and crude oils from various geological sources. The results showed that long alkyl chain thiols are readily present in petroleum, which have up to 30 carbon atoms. Large DBE dispersity of thiols indicates that naphthenic and aromatic thiols are also present in the petroleum. This method is capable of detecting thiol compounds in the part per million range by weight. This method allows characterization of thiols in a complex hydrocarbon matrix, which is complementary to the comprehensive analysis of sulfur compounds in fossil fuels.

Modeling Carbon and Hydrocarbon Molecular Structures in EZTB

NASA Technical Reports Server (NTRS)

Lee, Seungwon; vonAllmen, Paul

2007-01-01

A software module that models the electronic and mechanical aspects of hydrocarbon molecules and carbon molecular structures on the basis of first principles has been written for incorporation into, and execution within, the Easy (Modular) Tight-Binding (EZTB) software infrastructure, which is summarized briefly in the immediately preceding article. Of particular interest, this module can model carbon crystals and nanotubes characterized by various coordinates and containing defects, without need to adjust parameters of the physical model. The module has been used to study the changes in electronic properties of carbon nanotubes, caused by bending of the nanotubes, for potential utility as the basis of a nonvolatile, electriccharge- free memory devices. For example, in one application of the module, it was found that an initially 50-nmlong carbon, (10,10)-chirality nanotube, which is a metallic conductor when straight, becomes a semiconductor with an energy gap of .3 meV when bent to a lateral displacement of 4 nm at the middle.

Kinetic Analysis of a Molecular Model of the Budding Yeast Cell Cycle