Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Numerical studies from quantum to macroscopic scales of carbon nanoparticules in hydrogen plasma

NASA Astrophysics Data System (ADS)

Lombardi, Guillaume; Ngandjong, Alain; Mezei, Zsolt; Mougenot, Jonathan; Michau, Armelle; Hassouni, Khaled; Seydou, Mahamadou; Maurel, François

2016-09-01

Dusty plasmas take part in large scientific domains from Universe Science to nanomaterial synthesis processes. They are often generated by growth from molecular precursor. This growth leads to the formation of larger clusters which induce solid germs nucleation. Particle formed are described by an aerosol dynamic taking into account coagulation, molecular deposition and transport processes. These processes are controlled by the elementary particle. So there is a strong coupling between particle dynamics and plasma discharge equilibrium. This study is focused on the development of a multiscale physic and numeric model of hydrogen plasmas and carbon particles around three essential coupled axes to describe the various physical phenomena: (i) Macro/mesoscopic fluid modeling describing in an auto-coherent way, characteristics of the plasma, molecular clusters and aerosol behavior; (ii) the classic molecular dynamics offering a description to the scale molecular of the chains of chemical reactions and the phenomena of aggregation; (iii) the quantum chemistry to establish the activation barriers of the different processes driving the nanopoarticule formation.

Macro and micro analysis of small molecule diffusion in amorphous polymers

NASA Astrophysics Data System (ADS)

Putta, Santosh Krishna

In this study, both macroscopic and microscopic numerical techniques have been explored, to model and understand the diffusion behavior of small molecules in amorphous polymers, which very often do not follow the classical Fickian law. It was attempted to understand the influence of various aspects of the molecular structure of a polymer on its macroscopic diffusion behavior. At the macroscopic level, a hybrid finite-element/finite-difference model is developed to implement the coupled diffusion and deformation constitutive equations. A viscoelasticity theory, combined with time-freevolume superposition is used to model the deformation processes. A freevolume-based model is used to model the diffusion processes. The freevolume in the polymer is used as a coupling factor between the deformation and the diffusion processes. The model is shown to qualitatively describe some of the typical non-Fickian diffusion behavior in polymers. However, it does not directly involve the microstructure of a polymer. Further, some of the input parameters to the model are difficult to obtain experimentally. A numerical microscopic approach is therefore adopted to study the molecular structure of polymers. A molecular mechanics and dynamics technique combined with a modified Rotational Isomeric State (RIS) approach, is followed to generate the molecular structure for two types of polycarbonates, and, two types of polyacrylates, starting only with their chemical structures. A new efficient 3-D algorithm for Delaunay Tessellation is developed, and, then applied to discretize the molecular structure into Delaunay Tetrahedra. By using the dicretized molecular structure, size, shape, and, connectivity of free-spaces for small molecule diffusion in the above mentioned polymers, are then studied in relation to their diffusion properties. The influence of polymer and side chain flexibility, and diffusant-diffusant and diffusant-polymer molecular interactions, is also discussed with respect to the diffusion properties.

Rate Kinetics and Molecular Dynamics of the Structural Transitions in Amyloidogenic Proteins

NASA Astrophysics Data System (ADS)

Steckmann, Timothy M.

Amyloid fibril aggregation is associated with several horrific diseases such as Alzheimer's, Creutzfeld-Jacob, diabetes, Parkinson's and others. The process of amyloid aggregation involves forming myriad different metastable intermediate aggregates. Amyloid fibrils are composed of proteins that originate in an innocuous alpha-helix or random-coil structure. The alpha-helices convert their structure to beta-strands that aggregate into beta-sheets, and then into protofibrils, and ultimately into fully formed amyloid fibrils. On the basis of experimental data, I have developed a mathematical model for the kinetics of the reaction pathways and determined rate parameters for peptide secondary structural conversion and aggregation during the entire fibrillogenesis process from random coil to fibrils, including the molecular species that accelerate the conversions. The specific steps of the model and the rate constants that are determined by fitting to experimental data provide insight on the molecular species involved in the fibril formation process. To better understand the molecular basis of the protein structural transitions and aggregation, I report on molecular dynamics (MD) computational studies on the formation of amyloid protofibrillar structures in the small model protein ccbeta, which undergoes many of the structural transitions of the larger, naturally occurring amyloid forming proteins. Two different structural transition processes involving hydrogen bonds are observed for aggregation into fibrils: the breaking of intrachain hydrogen bonds to allow beta-hairpin proteins to straighten, and the subsequent formation of interchain hydrogen bonds during aggregation into amyloid fibrils. For my MD simulations, I found that the temperature dependence of these two different structural transition processes results in the existence of a temperature window that the ccbeta protein experiences during the process of forming protofibrillar structures. Both the mathematical modeling of the kinetics and the MD simulations show that molecular structural heterogeneity is a major factor in the process. The MD simulations also show that intrachain and interchain hydrogen bonds breaking and forming is strongly correlated to the process of amyloid formation.

Fine- and hyperfine-structure effects in molecular photoionization. II. Resonance-enhanced multiphoton ionization and hyperfine-selective generation of molecular cations

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

Germann, Matthias; Willitsch, Stefan, E-mail: stefan.willitsch@unibas.ch

2016-07-28

Resonance-enhanced multiphoton ionization (REMPI) is a widely used technique for studying molecular photoionization and producing molecular cations for spectroscopy and dynamics studies. Here, we present a model for describing hyperfine-structure effects in the REMPI process and for predicting hyperfine populations in molecular ions produced by this method. This model is a generalization of our model for fine- and hyperfine-structure effects in one-photon ionization of molecules presented in Paper I [M. Germann and S. Willitsch, J. Chem. Phys. 145, 044314 (2016)]. This generalization is achieved by covering two main aspects: (1) treatment of the neutral bound-bound transition including the hyperfine structuremore » that makes up the first step of the REMPI process and (2) modification of our ionization model to account for anisotropic populations resulting from this first excitation step. Our findings may be used for analyzing results from experiments with molecular ions produced by REMPI and may serve as a theoretical background for hyperfine-selective ionization experiments.« less

Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function.

PubMed

Perco, Paul; Heinzel, Andreas; Leierer, Johannes; Schneeberger, Stefan; Bösmüller, Claudia; Oberhuber, Rupert; Wagner, Silvia; Engler, Franziska; Mayer, Gert

2018-05-03

Donor organ quality affects long term outcome after renal transplantation. A variety of prognostic molecular markers is available, yet their validity often remains undetermined. A network-based molecular model reflecting donor kidney status based on transcriptomics data and molecular features reported in scientific literature to be associated with chronic allograft nephropathy was created. Significantly enriched biological processes were identified and representative markers were selected. An independent kidney pre-implantation transcriptomics dataset of 76 organs was used to predict estimated glomerular filtration rate (eGFR) values twelve months after transplantation using available clinical data and marker expression values. The best-performing regression model solely based on the clinical parameters donor age, donor gender, and recipient gender explained 17% of variance in post-transplant eGFR values. The five molecular markers EGF, CD2BP2, RALBP1, SF3B1, and DDX19B representing key molecular processes of the constructed renal donor organ status molecular model in addition to the clinical parameters significantly improved model performance (p-value = 0.0007) explaining around 33% of the variability of eGFR values twelve months after transplantation. Collectively, molecular markers reflecting donor organ status significantly add to prediction of post-transplant renal function when added to the clinical parameters donor age and gender.

Institute for Molecular Medicine Research Program

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

Phelps, Michael E

2012-12-14

The objectives of the project are the development of new Positron Emission Tomography (PET) imaging instrumentation, chemistry technology platforms and new molecular imaging probes to examine the transformations from normal cellular and biological processes to those of disease in pre-clinical animal models. These technology platforms and imaging probes provide the means to: 1. Study the biology of disease using pre-clinical mouse models and cells. 2. Develop molecular imaging probes for imaging assays of proteins in pre-clinical models. 3. Develop imaging assays in pre-clinical models to provide to other scientists the means to guide and improve the processes for discovering newmore » drugs. 4. Develop imaging assays in pre-clinical models for others to use in judging the impact of drugs on the biology of disease.« less

Challenge of representing entropy at different levels of resolution in molecular simulation.

PubMed

Huang, Wei; van Gunsteren, Wilfred F

2015-01-22

The role of entropic contributions in processes involving biomolecules is illustrated using the process of vaporization or condensation of the solvents water and methanol and the process of polypeptide folding in solution using molecular models at different levels of resolution: subatomic, atomic, supra-atomic, and supramolecular. For the folding process, a β-hexapeptide that adopts, as inferred from NMR experiments, both a right-handed 2.710/12-helical fold and a left-handed 314-helical fold in methanol, is used to illustrate the challenge of modeling thermodynamically driven processes at different levels of resolution.

Molecular processes in a high temperature shock layer

NASA Technical Reports Server (NTRS)

Guberman, S. L.

1984-01-01

Models of the shock layer encountered by an Aeroassisted Orbital Transfer Vehicle require as input accurate cross sections and rate constants for the atomic and molecular processes that characterize the shock radiation. From the estimated atomic and molecular densities in the shock layer and the expected residence time of 1 m/s, it can be expected that electron-ion collision processes will be important in the shock model. Electron capture by molecular ions followed by dissociation, e.g., O2(+) + e(-) yields 0 + 0, can be expected to be of major importance since these processes are known to have high rates (e.g., 10 to the -7th power cu/cm/sec) at room temperature. However, there have been no experimental measurements of dissociative recombination (DR) at temperatures ( 12000K) that are expected to characterize the shock layer. Indeed, even at room temperature, it is often difficult to perform experiments that determine the dependence of the translational energy and quantum yields of the product atoms on the electronic and vibrational state of the reactant molecular ions. Presented are ab initio quantum chemical studies of DR for molecular ions that are likely to be important in the atmospheric shock layer.

Multi-tissue DNA methylation age: Molecular relationships and perspectives for advancing biomarker utility.

PubMed

Nwanaji-Enwerem, Jamaji C; Weisskopf, Marc G; Baccarelli, Andrea A

2018-04-23

The multi-tissue DNA methylation estimator of chronological age (DNAm-age) has been associated with a wide range of exposures and health outcomes. Still, it is unclear how DNAm-age can have such broad relationships and how it can be best utilized as a biomarker. Understanding DNAm-age's molecular relationships is a promising approach to address this critical knowledge gap. In this review, we discuss the existing literature regarding DNAm-age's molecular relationships in six major categories: animal model systems, cancer processes, cellular aging processes, immune system processes, metabolic processes, and nucleic acid processes. We also present perspectives regarding the future of DNAm-age research, including the need to translate a greater number of ongoing research efforts to experimental and animal model systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE-/- Mouse.

PubMed

Szostak, Justyna; Martin, Florian; Talikka, Marja; Peitsch, Manuel C; Hoeng, Julia

2016-01-01

The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE -/- mouse aorta at 6 and 32 weeks. We concluded that network models combined with the network perturbation amplitude algorithm provide a sensitive, quantitative method to follow disease progression at the molecular level. This approach can be used to investigate and quantify molecular mechanisms during plaque progression.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

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…

Capillary Rise: Validity of the Dynamic Contact Angle Models.

PubMed

Wu, Pingkeng; Nikolov, Alex D; Wasan, Darsh T

2017-08-15

The classical Lucas-Washburn-Rideal (LWR) equation, using the equilibrium contact angle, predicts a faster capillary rise process than experiments in many cases. The major contributor to the faster prediction is believed to be the velocity dependent dynamic contact angle. In this work, we investigated the dynamic contact angle models for their ability to correct the dynamic contact angle effect in the capillary rise process. We conducted capillary rise experiments of various wetting liquids in borosilicate glass capillaries and compared the model predictions with our experimental data. The results show that the LWR equations modified by the molecular kinetic theory and hydrodynamic model provide good predictions on the capillary rise of all the testing liquids with fitting parameters, while the one modified by Joos' empirical equation works for specific liquids, such as silicone oils. The LWR equation modified by molecular self-layering model predicts well the capillary rise of carbon tetrachloride, octamethylcyclotetrasiloxane, and n-alkanes with the molecular diameter or measured solvation force data. The molecular self-layering model modified LWR equation also has good predictions on the capillary rise of silicone oils covering a wide range of bulk viscosities with the same key parameter W(0), which results from the molecular self-layering. The advantage of the molecular self-layering model over the other models reveals the importance of the layered molecularly thin wetting film ahead of the main meniscus in the energy dissipation associated with dynamic contact angle. The analysis of the capillary rise of silicone oils with a wide range of bulk viscosities provides new insights into the capillary dynamics of polymer melts.

Challenges in Materials Transformation Modeling for Polyolefins Industry

NASA Astrophysics Data System (ADS)

Lai, Shih-Yaw; Swogger, Kurt W.

2004-06-01

Unlike most published polymer processing and/or forming research, the transformation of polyolefins to fabricated articles often involves non-confined flow or so-called free surface flow (e.g. fiber spinning, blown films, and cast films) in which elongational flow takes place during a fabrication process. Obviously, the characterization and validation of extensional rheological parameters and their use to develop rheological constitutive models are the focus of polyolefins materials transformation research. Unfortunately, there are challenges that remain with limited validation for non-linear, non-isothermal constitutive models for polyolefins. Further complexity arises in the transformation of polyolefins in the elongational flow system as it involves stress-induced crystallization process. The complicated nature of elongational, non-linear rheology and non-isothermal crystallization kinetics make the development of numerical methods very challenging for the polyolefins materials forming modeling. From the product based company standpoint, the challenges of materials transformation research go beyond elongational rheology, crystallization kinetics and its numerical modeling. In order to make models useful for the polyolefin industry, it is critical to develop links between molecular parameters to both equipment and materials forming parameters. The recent advances in the constrained geometry catalysis and materials sciences understanding (INSITE technology and molecular design capability) has made industrial polyolefinic materials forming modeling more viable due to the fact that the molecular structure of the polymer can be well predicted and controlled during the polymerization. In this paper, we will discuss inter-relationship (models) among molecular parameters such as polymer molecular weight (Mw), molecular weight distribution (MWD), long chain branching (LCB), short chain branching (SCB or comonomer types and distribution) and their affects on shear and elongational rheologies, on tie-molecules probabilities, on non-isothermal stress-induced crystallization, on crystalline/amorphous orientation vs. mechanical property relationship, etc. All of the above mentioned inter-relationships (models) are critical to the successful development of a knowledge based industrial model. Dow Polyolefins and Elastomers business is one of the world largest polyolefins resin producers with the most advanced INSITE technology and a "6-Day model" molecular design capability. Dow also offers one of the broadest polyolefinic product ranges and applications to the market.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

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

Bibby, Jaclyn; Keegan, Ronan M.; Mayans, Olga

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

Multi input single output model predictive control of non-linear bio-polymerization process

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

Arumugasamy, Senthil Kumar; Ahmad, Z.

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state spacemore » model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.« less

Evidence from mixed hydrate nucleation for a funnel model of crystallization.

PubMed

Hall, Kyle Wm; Carpendale, Sheelagh; Kusalik, Peter G

2016-10-25

The molecular-level details of crystallization remain unclear for many systems. Previous work has speculated on the phenomenological similarities between molecular crystallization and protein folding. Here we demonstrate that molecular crystallization can involve funnel-shaped potential energy landscapes through a detailed analysis of mixed gas hydrate nucleation, a prototypical multicomponent crystallization process. Through this, we contribute both: (i) a powerful conceptual framework for exploring and rationalizing molecular crystallization, and (ii) an explanation of phenomenological similarities between protein folding and crystallization. Such funnel-shaped potential energy landscapes may be typical of broad classes of molecular ordering processes, and can provide a new perspective for both studying and understanding these processes.

Evidence from mixed hydrate nucleation for a funnel model of crystallization

PubMed Central

Hall, Kyle Wm.; Carpendale, Sheelagh; Kusalik, Peter G.

2016-01-01

The molecular-level details of crystallization remain unclear for many systems. Previous work has speculated on the phenomenological similarities between molecular crystallization and protein folding. Here we demonstrate that molecular crystallization can involve funnel-shaped potential energy landscapes through a detailed analysis of mixed gas hydrate nucleation, a prototypical multicomponent crystallization process. Through this, we contribute both: (i) a powerful conceptual framework for exploring and rationalizing molecular crystallization, and (ii) an explanation of phenomenological similarities between protein folding and crystallization. Such funnel-shaped potential energy landscapes may be typical of broad classes of molecular ordering processes, and can provide a new perspective for both studying and understanding these processes. PMID:27790987

Simulating the flow of entangled polymers.

PubMed

Masubuchi, Yuichi

2014-01-01

To optimize automation for polymer processing, attempts have been made to simulate the flow of entangled polymers. In industry, fluid dynamics simulations with phenomenological constitutive equations have been practically established. However, to account for molecular characteristics, a method to obtain the constitutive relationship from the molecular structure is required. Molecular dynamics simulations with atomic description are not practical for this purpose; accordingly, coarse-grained models with reduced degrees of freedom have been developed. Although the modeling of entanglement is still a challenge, mesoscopic models with a priori settings to reproduce entangled polymer dynamics, such as tube models, have achieved remarkable success. To use the mesoscopic models as staging posts between atomistic and fluid dynamics simulations, studies have been undertaken to establish links from the coarse-grained model to the atomistic and macroscopic simulations. Consequently, integrated simulations from materials chemistry to predict the macroscopic flow in polymer processing are forthcoming.

Live Imaging of Centriole Dynamics by Fluorescently Tagged Proteins in Starfish Oocyte Meiosis.

PubMed

Borrego-Pinto, Joana; Somogyi, Kálmán; Lénárt, Péter

2016-01-01

High throughput DNA sequencing, the decreasing costs of DNA synthesis, and universal techniques for genetic manipulation have made it much easier and quicker to establish molecular tools for any organism than it has been 5 years ago. This opens a great opportunity for reviving "nonconventional" model organisms, which are particularly suited to study a specific biological process and many of which have already been established before the era of molecular biology. By taking advantage of transcriptomics, in particular, these systems can now be easily turned into full fetched models for molecular cell biology.As an example, here we describe how we established molecular tools in the starfish Patiria miniata, which has been a popular model for cell and developmental biology due to the synchronous and rapid development, transparency, and easy handling of oocytes, eggs, and embryos. Here, we detail how we used a de novo assembled transcriptome to produce molecular markers and established conditions for live imaging to investigate the molecular mechanisms underlying centriole elimination-a poorly understood process essential for sexual reproduction of animal species.

Belowground Carbon Cycling Processes at the Molecular Scale: An EMSL Science Theme Advisory Panel Workshop

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

Hess, Nancy J.; Brown, Gordon E.; Plata, Charity

2014-02-21

As part of the Belowground Carbon Cycling Processes at the Molecular Scale workshop, an EMSL Science Theme Advisory Panel meeting held in February 2013, attendees discussed critical biogeochemical processes that regulate carbon cycling in soil. The meeting attendees determined that as a national scientific user facility, EMSL can provide the tools and expertise needed to elucidate the molecular foundation that underlies mechanistic descriptions of biogeochemical processes that control carbon allocation and fluxes at the terrestrial/atmospheric interface in landscape and regional climate models. Consequently, the workshop's goal was to identify the science gaps that hinder either development of mechanistic description ofmore » critical processes or their accurate representation in climate models. In part, this report offers recommendations for future EMSL activities in this research area. The workshop was co-chaired by Dr. Nancy Hess (EMSL) and Dr. Gordon Brown (Stanford University).« less

Towards better modelling of drug-loading in solid lipid nanoparticles: Molecular dynamics, docking experiments and Gaussian Processes machine learning.

PubMed

Hathout, Rania M; Metwally, Abdelkader A

2016-11-01

This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.

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 makes the system act like a band-stop filter over an infinite frequency range.

State of the Art Assessment of Simulation in Advanced Materials Development

NASA Technical Reports Server (NTRS)

Wise, Kristopher E.

2008-01-01

Advances in both the underlying theory and in the practical implementation of molecular modeling techniques have increased their value in the advanced materials development process. The objective is to accelerate the maturation of emerging materials by tightly integrating modeling with the other critical processes: synthesis, processing, and characterization. The aims of this report are to summarize the state of the art of existing modeling tools and to highlight a number of areas in which additional development is required. In an effort to maintain focus and limit length, this survey is restricted to classical simulation techniques including molecular dynamics and Monte Carlo simulations.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

PubMed Central

Chen, Yang; Shen, Kuang

2017-01-01

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process. PMID:28943680

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.

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.

Results from the Biology Concept Inventory (BCI), and what they mean for biogeoscience literacy.

NASA Astrophysics Data System (ADS)

Garvin-Doxas, K.; Klymkowsky, M.

2008-12-01

While researching the Biology Concept Inventory (BCI) we found that a wide class of student difficulties in genetics and molecular biology can be traced to deep-seated misconceptions about random processes and molecular interactions. Students believe that random processes are inefficient, while biological systems are very efficient, and are therefore quick to propose their own rational explanations for various processes (from diffusion to evolution). These rational explanations almost always make recourse to a driver (natural selection in genetics, or density gradients in molecular biology) with the process only taking place when the driver is present. The concept of underlying random processes that are taking place all the time giving rise to emergent behaviour is almost totally absent. Even students who have advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes. Furthermore, their understanding of molecular interactions is purely geometric, with a lock-and-key model (rather than an energy minimization model) that does not allow for the survival of slight variations of the "correct" molecule. Together with the dominant misconception about random processes, this results in a strong conceptual barrier in understanding evolutionary processes, and can frustrate the success of education programs.

The Treasure of the Humble: Lessons from Baker's Yeast

ERIC Educational Resources Information Center

Sitaraman, Ramakrishnan

2011-01-01

The study of model organisms is a powerful and proven experimental strategy for understanding biological processes. This paper describes an attempt to utilize advances in yeast molecular biology to enhance student understanding by presenting a more comprehensive view of several interconnected molecular processes in the overall functioning of an…

Mitochondrial genetics in Bakers' yeast: a molecular mechanism for recombinational polarity and suppressiveness.

PubMed

Perlman, P S; Birky, C W

1974-11-01

Recombinational polarity and suppressiveness are two well-known but puzzling cytoplasmic genetic phenomena in bakers' yeast, Saccharomyces cerevisiae. Little progress has been made in characterizing the underlying molecular mechanisms of these phenomena. In this paper we describe a molecular model for recombinational polarity that is compatible with the available genetic evidence. The model stresses the role of small deletions and excision/repair processes in otherwise canonical recombinational events. According to the model, both phenomena require recombination and may share mechanistic elements.

The physics of interstellar shock waves

NASA Technical Reports Server (NTRS)

Shull, J. Michael; Draine, Bruce T.

1987-01-01

This review discusses the observations and theoretical models of interstellar shock waves, in both diffuse cloud and molecular cloud environments. It summarizes the relevant gas dynamics, atomic, molecular and grain processes, radiative transfer, and physics of radiative and magnetic precursors in shock models. It then describes the importance of shocks for observations, diagnostics, and global interstellar dynamics. It concludes with current research problems and data needs for atomic, molecular and grain physics.

Virtual Model Validation of Complex Multiscale Systems: Applications to Nonlinear Elastostatics

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

Oden, John Tinsley; Prudencio, Ernest E.; Bauman, Paul T.

We propose a virtual statistical validation process as an aid to the design of experiments for the validation of phenomenological models of the behavior of material bodies, with focus on those cases in which knowledge of the fabrication process used to manufacture the body can provide information on the micro-molecular-scale properties underlying macroscale behavior. One example is given by models of elastomeric solids fabricated using polymerization processes. We describe a framework for model validation that involves Bayesian updates of parameters in statistical calibration and validation phases. The process enables the quanti cation of uncertainty in quantities of interest (QoIs) andmore » the determination of model consistency using tools of statistical information theory. We assert that microscale information drawn from molecular models of the fabrication of the body provides a valuable source of prior information on parameters as well as a means for estimating model bias and designing virtual validation experiments to provide information gain over calibration posteriors.« less

Comparing the Atmospheric Losses at Io and Europa

NASA Astrophysics Data System (ADS)

Dols, V. J.; Bagenal, F.; Crary, F. J.; Cassidy, T.

2017-12-01

At Io and Europa, the interaction of the Jovian plasma with the moon atmosphere leads to a significant loss of atomic/molecular neutrals and ions to space. The processes that lead to atmospheric escape are diverse: atmospheric sputtering, molecular dissociation, molecular ion recombination, Jeans escape etc. Each process leads to neutrals escaping at different velocities (i.e. electron impact dissociation leads to very slow atomic neutrals, sputtering might eject faster molecular neutrals). Some neutrals will be ejected out of the Jovian system; others will form extended neutral clouds along the orbit of the moons. These atomic/molecular extended neutral clouds are probably the main source of plasma for the Jovian magnetosphere. They are difficult to observe directly thus their composition and density are still poorly constrained. A future modeling of the formation of these extended clouds requires an estimate of their atmospheric sources. We estimate the atmospheric losses at Io and Europa for each loss process with a multi-species chemistry model, using a prescribed atmospheric distribution consistent with the observations. We compare the neutral losses at Io and Europa.

A systematic petri net approach for multiple-scale modeling and simulation of biochemical processes.

PubMed

Chen, Ming; Hu, Minjie; Hofestädt, Ralf

2011-06-01

A method to exploit hybrid Petri nets for modeling and simulating biochemical processes in a systematic way was introduced. Both molecular biology and biochemical engineering aspects are manipulated. With discrete and continuous elements, the hybrid Petri nets can easily handle biochemical factors such as metabolites concentration and kinetic behaviors. It is possible to translate both molecular biological behavior and biochemical processes workflow into hybrid Petri nets in a natural manner. As an example, penicillin production bioprocess is modeled to illustrate the concepts of the methodology. Results of the dynamic of production parameters in the bioprocess were simulated and observed diagrammatically. Current problems and post-genomic perspectives were also discussed.

Molecular structure of dextran sulphate sodium in aqueous environment

NASA Astrophysics Data System (ADS)

Yu, Miao; Every, Hayley A.; Jiskoot, Wim; Witkamp, Geert-Jan; Buijs, Wim

2018-03-01

Here we propose a 3D-molecular structural model for dextran sulphate sodium (DSS) in a neutral aqueous environment based on the results of a molecular modelling study. The DSS structure is dominated by the stereochemistry of the 1,6-linked α-glucose units and the presence of two sulphate groups on each α-glucose unit. The structure of DSS can be best described as a helix with various patterns of di-sulphate substitution on the glucose rings. The presence of a side chain does not alter the 3D-structure of the linear main chain much, but affects the overall spatial dimension of the polymer. The simulated polymers have a diameter similar to or in some cases even larger than model α-hemolysin nano-pores for macromolecule transport in many biological processes, indicating a size-limited translocation through such pores. All results of the molecular modelling study are in line with previously reported experimental data. This study establishes the three-dimensional structure of DSS and summarizes the spatial dimension of the polymer, serving as the basis for a better understanding on the molecular level of DSS-involved electrostatic interaction processes with biological components like proteins and cell pores.

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

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.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Model for diffuse interstellar clouds: improvements to the theory of molecular hydrogen photodestruction and to the gas phase chemistry of carbon monoxide

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

Federman, S.R.

1979-01-01

A theoretical model has been developed to determine physical processes in conjunction with astrophysical observation. The calculations are based on isobaric, steady-state, plane-parallel conditions. In the model, the cloud is illuminated by ultraviolet radiation from one side. The density and temperature of the gas are derived by invoking energy conservation in terms of thermal balance. The derived values for density and temperature then are used to determine the abundances of approximately fifty atomic and molecular species, including important ionic species and simple carbon and oxygen bearing molecules. Except for molecular hydrogen formation on dust grains, binary gas phase reactions aremore » used to develop the chemistry of the model cloud. The theoretical model has been found to be appropriate for a particular range of physical parameters. The results of the steady-state calculations have been compared to ultraviolet observations, predominantly those made with the Copernicus satellite. The theory of molecular hydrogen photodestruction has been reexamined so that improvements to the model can be made. By analyzing the region where the atomic to molecuar hydrogen transition occurs, several processes have been found to contribute to dissociation.« less

Of truth and pathways: chasing bits of information through myriads of articles.

PubMed

Krauthammer, Michael; Kra, Pauline; Iossifov, Ivan; Gomez, Shawn M; Hripcsak, George; Hatzivassiloglou, Vasileios; Friedman, Carol; Rzhetsky, Andrey

2002-01-01

Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct molecular interactions are known or can be identified by reading a few research articles. However, this assumption does not necessarily hold, as truth is rather an emerging property based on many potentially conflicting facts. This paper explores the processes of knowledge generation and publishing in the molecular biology literature using modelling and analysis of real molecular interaction data. The data analysed in this article were automatically extracted from 50000 research articles in molecular biology using a computer system called GeneWays containing a natural language processing module. The paper indicates that truthfulness of statements is associated in the minds of scientists with the relative importance (connectedness) of substances under study, revealing a potential selection bias in the reporting of research results. Aiming at understanding the statistical properties of the life cycle of biological facts reported in research articles, we formulate a stochastic model describing generation and propagation of knowledge about molecular interactions through scientific publications. We hope that in the future such a model can be useful for automatically producing consensus views of molecular interaction data.

Star formation in evolving molecular clouds

NASA Astrophysics Data System (ADS)

Völschow, M.; Banerjee, R.; Körtgen, B.

2017-09-01

Molecular clouds are the principle stellar nurseries of our universe; they thus remain a focus of both observational and theoretical studies. From observations, some of the key properties of molecular clouds are well known but many questions regarding their evolution and star formation activity remain open. While numerical simulations feature a large number and complexity of involved physical processes, this plethora of effects may hide the fundamentals that determine the evolution of molecular clouds and enable the formation of stars. Purely analytical models, on the other hand, tend to suffer from rough approximations or a lack of completeness, limiting their predictive power. In this paper, we present a model that incorporates central concepts of astrophysics as well as reliable results from recent simulations of molecular clouds and their evolutionary paths. Based on that, we construct a self-consistent semi-analytical framework that describes the formation, evolution, and star formation activity of molecular clouds, including a number of feedback effects to account for the complex processes inside those objects. The final equation system is solved numerically but at much lower computational expense than, for example, hydrodynamical descriptions of comparable systems. The model presented in this paper agrees well with a broad range of observational results, showing that molecular cloud evolution can be understood as an interplay between accretion, global collapse, star formation, and stellar feedback.

DEVELOPMENT OF A MODEL THAT CONTAINS BOTH MULTIPOLE MOMENTS AND GAUSSIANS FOR THE CALCULATION OF MOLECULAR ELECTROSTATIC POTENTIALS

EPA Science Inventory

The electrostatic interaction is a critical component of intermolecular interactions in biological processes. Rapid methods for the computation and characterization of the molecular electrostatic potential (MEP) that segment the molecular charge distribution and replace this cont...

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Processing-microstructure relationships in thermotropic liquid crystalline polymers: Experimental and numerical modeling studies

NASA Astrophysics Data System (ADS)

Fang, Jun

Thermotropic liquid crystalline polymers (TLCPs) are a class of promising engineering materials for high-demanding structural applications. Their excellent mechanical properties are highly correlated to the underlying molecular orientation states, which may be affected by complex flow fields during melt processing. Thus, understanding and eventually predicting how processing flows impact molecular orientation is a critical step towards rational design work in order to achieve favorable, balanced physical properties in finished products. This thesis aims to develop deeper understanding of orientation development in commercial TLCPs during processing by coordinating extensive experimental measurements with numerical computations. In situ measurements of orientation development of LCPs during processing are a focal point of this thesis. An x-ray capable injection molding apparatus is enhanced and utilized for time-resolved measurements of orientation development in multiple commercial TLCPs during injection molding. Ex situ wide angle x-ray scattering is also employed for more thorough characterization of molecular orientation distributions in molded plaques. Incompletely injection molded plaques ("short shots") are studied to gain further insights into the intermediate orientation states during mold filling. Finally, two surface orientation characterization techniques, near edge x-ray absorption fine structure (NEXAFS) and infrared attenuated total reflectance (FTIR-ATR) are combined to investigate the surface orientation distribution of injection molded plaques. Surface orientation states are found to be vastly different from their bulk counterparts due to different kinematics involved in mold filling. In general, complex distributions of orientation in molded plaques reflect the spatially varying competition between shear and extension during mold filling. To complement these experimental measurements, numerical calculations based on the Larson-Doi polydomain model are performed. The implementation of the Larson-Doi in complex processing flows is performed using a commercial process modeling software suite (MOLDFLOWRTM), exploiting a nearly exact analogy between the Larson-Doi model and a fiber orientation model that has been widely used in composites processing simulations. The modeling scheme is first verified by predicting many qualitative and quantitative features of molecular orientation distributions in isothermal extrusion-fed channel flows. In coordination with experiments, the model predictions are found to capture many qualitative features observed in injection molded plaques (including short shots). The final, stringent test of Larson-Doi model performance is prediction of in situ transient orientation data collected during mold filling. The model yields satisfactory results, though certain numerical approximations limit performance near the mold front.

A statistic-thermodynamic model for the DOM degradation in the estuary

NASA Astrophysics Data System (ADS)

Zheng, Quanan; Chen, Qin; Zhao, Haihong; Shi, Jiuxin; Cao, Yong; Wang, Dan

2008-03-01

This study aims to clarify the role of dissolved salts playing in the degradation process of terrestrial dissolved organic matter (DOM) at a scale of molecular movement. The molecular thermal movement is perpetual motion. In a multi-molecular system, this random motion also causes collision between the molecules. Seawater is a multi-molecular system consisting from water, salt, and terrestrial DOM molecules. This study attributes the DOM degradation in the estuary to the inelastic collision of DOM molecule with charged salt ions. From statistic-thermodynamic theories of molecular collision, the DOM degradation model and the DOM distribution model are derived. The models are validated by the field observations and satellite data. Thus, we conclude that the inelastic collision between the terrestrial DOM molecules and dissolved salt ions in seawater is a decisive dynamic mechanism for rapid loss of terrestrial DOM.

Molecular Modeling of Environmentally Important Processes: Reduction Potentials

ERIC Educational Resources Information Center

Lewis, Anne; Bumpus, John A.; Truhlar, Donald G.; Cramer, Christopher J.

2004-01-01

The increasing use of computational quantum chemistry in the modeling of environmentally important processes is described. The employment of computational quantum mechanics for the prediction of oxidation-reduction potential for solutes in an aqueous medium is discussed.

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

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes andmore » fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.« less

Weighted Watson-Crick automata

NASA Astrophysics Data System (ADS)

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

2014-07-01

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

Protonation free energy levels in complex molecular systems.

PubMed

Antosiewicz, Jan M

2008-04-01

All proteins, nucleic acids, and other biomolecules contain residues capable of exchanging protons with their environment. These proton transfer phenomena lead to pH sensitivity of many molecular processes underlying biological phenomena. In the course of biological evolution, Nature has invented some mechanisms to use pH gradients to regulate biomolecular processes inside cells or in interstitial fluids. Therefore, an ability to model protonation equilibria in molecular systems accurately would be of enormous value for our understanding of biological processes and for possible rational influence on them, like in developing pH dependent drugs to treat particular diseases. This work presents a derivation, by thermodynamic and statistical mechanical methods, of an expression for the free energy of a complex molecular system at arbitrary ionization state of its titratable residues. This constitutes one of the elements of modeling protonation equilibria. Starting from a consideration of a simple acid-base equilibrium of a model compound with a single tritratable group, we arrive at an expression which is of general validity for complex systems. The only approximation used in this derivation is the postulating that the interaction energy between any pair of titratable sites does not depend on the protonation states of all the remaining ionizable groups.

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.

Kinetic Theory and Simulation of Single-Channel Water Transport

NASA Astrophysics Data System (ADS)

Tajkhorshid, Emad; Zhu, Fangqiang; Schulten, Klaus

Water translocation between various compartments of a system is a fundamental process in biology of all living cells and in a wide variety of technological problems. The process is of interest in different fields of physiology, physical chemistry, and physics, and many scientists have tried to describe the process through physical models. Owing to advances in computer simulation of molecular processes at an atomic level, water transport has been studied in a variety of molecular systems ranging from biological water channels to artificial nanotubes. While simulations have successfully described various kinetic aspects of water transport, offering a simple, unified model to describe trans-channel translocation of water turned out to be a nontrivial task.

Understanding the kinetics of ligand binding to globins with molecular dynamics simulations: the necessity of multiple state models.

PubMed

Estarellas Martin, Carolina; Seira Castan, Constantí; Luque Garriga, F Javier; Bidon-Chanal Badia, Axel

2015-10-01

Residue conformational changes and internal cavity migration processes play a key role in regulating the kinetics of ligand migration and binding events in globins. Molecular dynamics simulations have demonstrated their value in the study of these processes in different haemoglobins, but derivation of kinetic data demands the use of more complex techniques like enhanced sampling molecular dynamics methods. This review discusses the different methodologies that are currently applied to study the ligand migration process in globins and highlight those specially developed to derive kinetic data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Atomic and molecular supernovae

NASA Technical Reports Server (NTRS)

Liu, Weihong

1997-01-01

Atomic and molecular physics of supernovae is discussed with an emphasis on the importance of detailed treatments of the critical atomic and molecular processes with the best available atomic and molecular data. The observations of molecules in SN 1987A are interpreted through a combination of spectral and chemical modelings, leading to strong constraints on the mixing and nucleosynthesis of the supernova. The non-equilibrium chemistry is used to argue that carbon dust can form in the oxygen-rich clumps where the efficient molecular cooling makes the nucleation of dust grains possible. For Type Ia supernovae, the analyses of their nebular spectra lead to strong constraints on the supernova explosion models.

Heterogeneously Catalyzed Endothermic Fuel Cracking

DTIC Science & Technology

2016-08-28

Much of this literature is in the context of gas -to- liquids technology and industrial dehydrogenation processes. Based on the published measurements...certain zeolites. Comparisons of conversion, major product distributions and molecular weight growth processes in the gas -phase pyrolysis of model...thereby maximizing the extent of cooling, (b) increase catalyst activity for fuel decomposition, but inhibit gas -phase molecular weight growth

Multiscale Molecular Simulation of Solution Processing of SMDPPEH: PCBM Small-Molecule Organic Solar Cells.

PubMed

Lee, Cheng-Kuang; Pao, Chun-Wei

2016-08-17

Solution-processed small-molecule organic solar cells are a promising renewable energy source because of their low production cost, mechanical flexibility, and light weight relative to their pure inorganic counterparts. In this work, we developed a coarse-grained (CG) Gay-Berne ellipsoid molecular simulation model based on atomistic trajectories from all-atom molecular dynamics simulations of smaller system sizes to systematically study the nanomorphology of the SMDPPEH/PCBM/solvent ternary blend during solution processing, including the blade-coating process by applying external shear to the solution. With the significantly reduced overall system degrees of freedom and computational acceleration from GPU, we were able to go well beyond the limitation of conventional all-atom molecular simulations with a system size on the order of hundreds of nanometers with mesoscale molecular detail. Our simulations indicate that, similar to polymer solar cells, the optimal blending ratio in small-molecule organic solar cells must provide the highest specific interfacial area for efficient exciton dissociation, while retaining balanced hole/electron transport pathway percolation. We also reveal that blade-coating processes have a significant impact on nanomorphology. For given donor/acceptor blending ratios, applying an external shear force can effectively promote donor/acceptor phase segregation and stacking in the SMDPPEH domains. The present study demonstrated the capability of an ellipsoid-based coarse-grained model for studying the nanomorphology evolution of small-molecule organic solar cells during solution processing/blade-coating and provided links between fabrication protocols and device nanomorphologies.

Features of Extrusion Processing of Ultrahigh Molecular Weight Polyethylene. Experiment and Theory

NASA Astrophysics Data System (ADS)

Skul‧skii, O. I.; Slavnov, E. V.

2018-05-01

Experimental studies have been made of the permissible regimes of processing ultrahigh molecular weight polyethylene GUR 2122 with molecular mass of 4.5 million g/moles in a laboratory extruder with an auger diameter 32 mm and a ratio L/D = 20 at temperatures of 155-165oC. On the basis of rotational viscometry, the rheological properties of the melt are described. A mathematical model and a numerical method for calculating the motion of ultrahigh molecular weight polyethylene melt in the auger and in the moulding rigging are proposed. The velocity and stress fields have been determined.

Markov-modulated Markov chains and the covarion process of molecular evolution.

PubMed

Galtier, N; Jean-Marie, A

2004-01-01

The covarion (or site specific rate variation, SSRV) process of biological sequence evolution is a process by which the evolutionary rate of a nucleotide/amino acid/codon position can change in time. In this paper, we introduce time-continuous, space-discrete, Markov-modulated Markov chains as a model for representing SSRV processes, generalizing existing theory to any model of rate change. We propose a fast algorithm for diagonalizing the generator matrix of relevant Markov-modulated Markov processes. This algorithm makes phylogeny likelihood calculation tractable even for a large number of rate classes and a large number of states, so that SSRV models become applicable to amino acid or codon sequence datasets. Using this algorithm, we investigate the accuracy of the discrete approximation to the Gamma distribution of evolutionary rates, widely used in molecular phylogeny. We show that a relatively large number of classes is required to achieve accurate approximation of the exact likelihood when the number of analyzed sequences exceeds 20, both under the SSRV and among site rate variation (ASRV) models.

Modelling morphology evolution during solidification of IPP in processing conditions

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

Pantani, R., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; De Santis, F., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; Speranza, V., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it

During polymer processing, crystallization takes place during or soon after flow. In most of cases, the flow field dramatically influences both the crystallization kinetics and the crystal morphology. On their turn, crystallinity and morphology affect product properties. Consequently, in the last decade, researchers tried to identify the main parameters determining crystallinity and morphology evolution during solidification In processing conditions. In this work, we present an approach to model flow-induced crystallization with the aim of predicting the morphology after processing. The approach is based on: interpretation of the FIC as the effect of molecular stretch on the thermodynamic crystallization temperature; modelingmore » the molecular stretch evolution by means of a model simple and easy to be implemented in polymer processing simulation codes; identification of the effect of flow on nucleation density and spherulites growth rate by means of simple experiments; determination of the condition under which fibers form instead of spherulites. Model predictions reproduce most of the features of final morphology observed in the samples after solidification.« less

Modeling Quantum Dynamics in Multidimensional Systems

NASA Astrophysics Data System (ADS)

Liss, Kyle; Weinacht, Thomas; Pearson, Brett

2017-04-01

Coupling between different degrees-of-freedom is an inherent aspect of dynamics in multidimensional quantum systems. As experiments and theory begin to tackle larger molecular structures and environments, models that account for vibrational and/or electronic couplings are essential for interpretation. Relevant processes include intramolecular vibrational relaxation, conical intersections, and system-bath coupling. We describe a set of simulations designed to model coupling processes in multidimensional molecular systems, focusing on models that provide insight and allow visualization of the dynamics. Undergraduates carried out much of the work as part of a senior research project. In addition to the pedagogical value, the simulations allow for comparison between both explicit and implicit treatments of a system's many degrees-of-freedom.

Interaction of a sodium ion with the water liquid-vapor interface

NASA Technical Reports Server (NTRS)

Wilson, M. A.; Pohorille, A.; Pratt, L. R.; MacElroy, R. D. (Principal Investigator)

1989-01-01

Molecular dynamics results are presented for the density profile of a sodium ion near the water liquid-vapor interface at 320 K. These results are compared with the predictions of a simple dielectric model for the interaction of a monovalent ion with this interface. The interfacial region described by the model profile is too narrow and the profile decreases too abruptly near the solution interface. Thus, the simple model does not provide a satisfactory description of the molecular dynamics results for ion positions within two molecular diameters from the solution interface where appreciable ion concentrations are observed. These results suggest that surfaces associated with dielectric models of ionic processes at aqueous solution interfaces should be located at least two molecular diameters inside the liquid phase. A free energy expense of about 2 kcal/mol is required to move the ion within two molecular layers of the free water liquid-vapor interface.

Comparing Classical Water Models Using Molecular Dynamics to Find Bulk Properties

ERIC Educational Resources Information Center

Kinnaman, Laura J.; Roller, Rachel M.; Miller, Carrie S.

2018-01-01

A computational chemistry exercise for the undergraduate physical chemistry laboratory is described. In this exercise, students use the molecular dynamics package Amber to generate trajectories of bulk liquid water for 4 different water models (TIP3P, OPC, SPC/E, and TIP4Pew). Students then process the trajectory to calculate structural (radial…

Computational Nanotechnology of Molecular Materials, Electronics and Machines

NASA Technical Reports Server (NTRS)

Srivastava, D.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

This viewgraph presentation covers carbon nanotubes, their characteristics, and their potential future applications. The presentation include predictions on the development of nanostructures and their applications, the thermal characteristics of carbon nanotubes, mechano-chemical effects upon carbon nanotubes, molecular electronics, and models for possible future nanostructure devices. The presentation also proposes a neural model for signal processing.

Examination of Bond Properties through Infrared Spectroscopy and Molecular Modeling in the General Chemistry Laboratory

ERIC Educational Resources Information Center

Csizmar, Clifford M.; Force, Dee Ann; Warner, Don L.

2012-01-01

A concerted effort has been made to increase the opportunities for undergraduate students to address scientific problems employing the processes used by practicing chemists. As part of this effort, an infrared (IR) spectroscopy and molecular modeling experiment was developed for the first-year general chemistry laboratory course. In the…

The Physics of Molecular Shocks in Star-Forming Regions

NASA Technical Reports Server (NTRS)

Hollenbach, David; Cuzzi, Jeffrey (Technical Monitor)

1996-01-01

Molecular shocks are produced by the impact of the supersonic infall of gas and dust onto protostars and by the interaction of the supersonic outflow from the protostar with the circumstellar material. Infalling gas creates an accretion shock around the circumstellar disk which emits a unique infrared spectrum and which processes the interstellar dust as it enters the disk. The winds and jets from protostars also impact the disk, the infalling material, and the ambient molecular cloud core creating shocks whose spectrum and morphology diagnose the mass loss processes of the protostar and the orientation and structure of the star forming system. We discuss the physics of these shocks, the model spectra derived from theoretical models, and comparisons with observations of H2O masers, H2 emission, as well as other shocks tracers. We show the strong effect of magnetic fields on molecular shock structure, and elucidate the chemical changes induced by the shock heating and compression.

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.

An End-to-End Model of Plant Pheromone Channel for Long Range Molecular Communication.

PubMed

Unluturk, Bige D; Akyildiz, Ian F

2017-01-01

A new track in molecular communication is using pheromones which can scale up the range of diffusion-based communication from μm meters to meters and enable new applications requiring long range. Pheromone communication is the emission of molecules in the air which trigger behavioral or physiological responses in receiving organisms. The objective of this paper is to introduce a new end-to-end model which incorporates pheromone behavior with communication theory for plants. The proposed model includes both the transmission and reception processes as well as the propagation channel. The transmission process is the emission of pheromones from the leaves of plants. The dispersion of pheromones by the flow of wind constitutes the propagation process. The reception process is the sensing of pheromones by the pheromone receptors of plants. The major difference of pheromone communication from other molecular communication techniques is the dispersion channel acting under the laws of turbulent diffusion. In this paper, the pheromone channel is modeled as a Gaussian puff, i.e., a cloud of pheromone released instantaneously from the source whose dispersion follows a Gaussian distribution. Numerical results on the performance of the overall end-to-end pheromone channel in terms of normalized gain and delay are provided.

Molecular C dynamics downstream: the biochemical decomposition sequence and its impact on soil organic matter structure and function.

PubMed

Grandy, A Stuart; Neff, Jason C

2008-10-15

Advances in spectroscopic and other chemical methods have greatly enhanced our ability to characterize soil organic matter chemistry. As a result, the molecular characteristics of soil C are now known for a range of ecosystems, soil types, and management intensities. Placing this knowledge into a broader ecological and management context is difficult, however, and remains one of the fundamental challenges of soil organic matter research. Here we present a conceptual model of molecular soil C dynamics to stimulate inter-disciplinary research into the ecological implications of molecular C turnover and its management- and process-level controls. Our model describes three properties of soil C dynamics: 1) soil size fractions have unique molecular patterns that reflect varying degrees of biological and physical control over decomposition; 2) there is a common decomposition sequence independent of plant inputs or other ecosystem properties; and 3) molecular decomposition sequences, although consistent, are not uniform and can be altered by processes that accelerate or slow the microbial transformation of specific molecules. The consequences of this model include several key points. First, lignin presents a constraint to decomposition of plant litter and particulate C (>53 microm) but exerts little influence on more stable mineral-associated soil fractions <53 microm. Second, carbon stabilized onto mineral fractions has a distinct composition related more to microbially processed organic matter than to plant-related compounds. Third, disturbances, such as N fertilization and tillage, which alter decomposition rates, can have "downstream effects"; that is, a disturbance that directly alters the molecular dynamics of particulate C may have a series of indirect effects on C stabilization in silt and clay fractions.

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, E; Kowalski, Karol

The NorthWest chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers [1-3]. It contains an umbrella of modules that today includes self-consistent eld (SCF), second order Møller-Plesset perturbation theory (MP2), coupled cluster (CC), multiconguration self-consistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real-time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics (AIMD), Car-Parrinello molecular dynamics (MD), classical MD, hybrid quantum mechanicsmore » molecular mechanics (QM/MM), hybrid ab initio molecular dynamics molecular mechanics (AIMD/MM), gauge independent atomic orbital nuclear magnetic resonance (GIAO NMR), conductor like screening solvation model (COSMO), conductor-like screening solvation model based on density (COSMO-SMD), and reference interaction site model (RISM) solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities [4]. Moreover, new capabilities continue to be added with each new release.« less

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 desorbed from grain surfaces, we find that the sulphur chemistry independently experiences an ``accretion catastrophe''. The S-bearing molecular abundances cease to lie within the observed range after about 3 x 106 years and this indicates that there may be at least two efficient surface desorption mechanisms operating in dark clouds - one quasi-continous and the other operating more sporadically on this time-scale. We suggest that mantle removal on short time-scales is mediated by clump dynamics, and by the effects of star formation on longer time-scales. The applicability of this type of dynamical-chemical model for molecular cloud evolution is discussed and comparison is made with other models of dark cloud chemistry.

Water condensation: a multiscale phenomenon.

PubMed

Jensen, Kasper Risgaard; Fojan, Peter; Jensen, Rasmus Lund; Gurevich, Leonid

2014-02-01

The condensation of water is a phenomenon occurring in multiple situations in everyday life, e.g., when fog is formed or when dew forms on the grass or on windows. This means that this phenomenon plays an important role within the different fields of science including meteorology, building physics, and chemistry. In this review we address condensation models and simulations with the main focus on heterogeneous condensation of water. The condensation process is, at first, described from a thermodynamic viewpoint where the nucleation step is described by the classical nucleation theory. Further, we address the shortcomings of the thermodynamic theory in describing the nucleation and emphasize the importance of nanoscale effects. This leads to the description of condensation from a molecular viewpoint. Also presented is how the nucleation can be simulated by use of molecular models, and how the condensation process is simulated on the macroscale using computational fluid dynamics. Finally, examples of hybrid models combining molecular and macroscale models for the simulation of condensation on a surface are presented.

Effect of Bead and Illustrations Models on High School Students' Achievement in Molecular Genetics

ERIC Educational Resources Information Center

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

2006-01-01

Our main goal in this study was to explore whether the use of models in molecular genetics instruction in high school can contribute to students' understanding of concepts and processes in genetics. Three comparable groups of 11th and 12th graders participated: The control group (116 students) was taught in the traditional lecture format, while…

Tethered bilayer lipid membranes (tBLMs): interest and applications for biological membrane investigations.

PubMed

Rebaud, Samuel; Maniti, Ofelia; Girard-Egrot, Agnès P

2014-12-01

Biological membranes play a central role in the biology of the cell. They are not only the hydrophobic barrier allowing separation between two water soluble compartments but also a supra-molecular entity that has vital structural functions. Notably, they are involved in many exchange processes between the outside and inside cellular spaces. Accounting for the complexity of cell membranes, reliable models are needed to acquire current knowledge of the molecular processes occurring in membranes. To simplify the investigation of lipid/protein interactions, the use of biomimetic membranes is an approach that allows manipulation of the lipid composition of specific domains and/or the protein composition, and the evaluation of the reciprocal effects. Since the middle of the 80's, lipid bilayer membranes have been constantly developed as models of biological membranes with the ultimate goal to reincorporate membrane proteins for their functional investigation. In this review, after a brief description of the planar lipid bilayers as biomimetic membrane models, we will focus on the construction of the tethered Bilayer Lipid Membranes, the most promising model for efficient membrane protein reconstitution and investigation of molecular processes occurring in cell membranes. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Molecular simulations of self-assembly processes of amphiphiles in dilute solutions: the challenge for quantitative modelling

NASA Astrophysics Data System (ADS)

Jusufi, Arben

2013-11-01

We report on two recent developments in molecular simulations of self-assembly processes of amphiphilic solutions. We focus on the determination of micelle formation of ionic surfactants which exhibit the archetype of self-assembling compounds in solution. The first approach is centred on the challenge in predicting micellisation properties through explicit solvent molecular dynamics simulations. Even with a coarse-grained (CG) approach and the use of highly optimised software packages run on graphics processing unit hardware, it remains in many cases computationally infeasible to directly extract the critical micelle concentration (cmc). However, combined with a recently presented theoretical mean-field model this task becomes resolved. An alternative approach to study self-assembly is through implicit solvent modelling of the surfactants. Here we review some latest results and present new ones regarding capabilities of such a modelling approach in determining the cmc, and the aggregate structures in the dilute regime, that is currently not accessible through explicit solvent simulations, neither through atomistic nor through CG approaches. A special focus is put on surfactant concentration effects and surfactant correlations quantified by scattering intensities that are compared to recently published small-angle X-ray scattering data.

Challenges in modelling homogeneous catalysis: new answers from ab initio molecular dynamics to the controversy over the Wacker process.

PubMed

Stirling, András; Nair, Nisanth N; Lledós, Agustí; Ujaque, Gregori

2014-07-21

We present here a review of the mechanistic studies of the Wacker process stressing the long controversy about the key reaction steps. We give an overview of the previous experimental and theoretical studies on the topic. Then we describe the importance of the most recent Ab Initio Molecular Dynamics (AIMD) calculations in modelling organometallic reactivity in water. As a prototypical example of homogeneous catalytic reactions, the Wacker process poses serious challenges to modelling. The adequate description of the multiple role of the water solvent is very difficult by using static quantum chemical approaches including cluster and continuum solvent models. In contrast, such reaction systems are suitable for AIMD, and by combining with rare event sampling techniques, the method provides reaction mechanisms and the corresponding free energy profiles. The review also highlights how AIMD has helped to obtain a novel understanding of the mechanism and kinetics of the Wacker process.

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

Smart Sensing Based on DNA-Metal Interaction Enables a Label-Free and Resettable Security Model of Electrochemical Molecular Keypad Lock.

PubMed

Du, Yan; Han, Xu; Wang, Chenxu; Li, Yunhui; Li, Bingling; Duan, Hongwei

2018-01-26

Recently, molecular keypad locks have received increasing attention. As a new subgroup of smart biosensors, they show great potential for protecting information as a molecular security data processor, rather than merely molecular recognition and quantitation. Herein, label-free electrochemically transduced Ag + and cysteine (Cys) sensors were developed. A molecular keypad lock model with reset function was successfully realized based on the balanced interaction of metal ion with its nucleic acid and chemical ligands. The correct input of "1-2-3" (i.e., "Ag + -Cys-cDNA") is the only password of such molecular keypad lock. Moreover, the resetting process of either correct or wrong input order could be easily made by Cys, buffer, and DI water treatment. Therefore, our system provides an even smarter system of molecular keypad lock, which could inhibit illegal access of unauthorized users, holding great promise in information protection at the molecular level.

Roles of Diffusion Dynamics in Stem Cell Signaling and Three-Dimensional Tissue Development.

PubMed

McMurtrey, Richard J

2017-09-15

Recent advancements in the ability to construct three-dimensional (3D) tissues and organoids from stem cells and biomaterials have not only opened abundant new research avenues in disease modeling and regenerative medicine but also have ignited investigation into important aspects of molecular diffusion in 3D cellular architectures. This article describes fundamental mechanics of diffusion with equations for modeling these dynamic processes under a variety of scenarios in 3D cellular tissue constructs. The effects of these diffusion processes and resultant concentration gradients are described in the context of the major molecular signaling pathways in stem cells that both mediate and are influenced by gas and nutrient concentrations, including how diffusion phenomena can affect stem cell state, cell differentiation, and metabolic states of the cell. The application of these diffusion models and pathways is of vital importance for future studies of developmental processes, disease modeling, and tissue regeneration.

Simulation of meso-damage of refractory based on cohesion model and molecular dynamics method

NASA Astrophysics Data System (ADS)

Zhao, Jiuling; Shang, Hehao; Zhu, Zhaojun; Zhang, Guoxing; Duan, Leiguang; Sun, Xinya

2018-06-01

In order to describe the meso-damage of the refractories more accurately, and to study of the relationship between the mesostructured of the refractories and the macro-mechanics, this paper takes the magnesia-carbon refractories as the research object and uses the molecular dynamics method to instead the traditional sequential algorithm to establish the meso-particles filling model including small and large particles. Finally, the finite element software-ABAQUS is used to conducts numerical simulation on the meso-damage evolution process of refractory materials. From the results, the process of initiation and propagation of microscopic interface cracks can be observed intuitively, and the macroscopic stress-strain curve of the refractory material is obtained. The results show that the combination of molecular dynamics modeling and the use of Python in the interface to insert the cohesive element numerical simulation, obtaining of more accurate interface parameters through parameter inversion, can be more accurate to observe the interface of the meso-damage evolution process and effective to consider the effect of the mesostructured of the refractory material on its macroscopic mechanical properties.

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

de Miguel, E.; Rull, L.F.; Gubbins, K.E.

Using molecular-dynamics computer simulation, we study the dynamical behavior of the isotropic and nematic phases of highly anisotropic molecular fluids. The interactions are modeled by means of the Gay-Berne potential with anisotropy parameters {kappa}=3 and {kappa}{prime}=5. The linear-velocity autocorrelation function shows no evidence of a negative region in the isotropic phase, even at the higher densities considered. The self-diffusion coefficient parallel to the molecular axis shows an anomalous increase with density as the system enters the nematic region. This enhancement in parallel diffusion is also observed in the isotropic side of the transition as a precursor effect. The molecular reorientationmore » is discussed in the light of different theoretical models. The Debye diffusion model appears to explain the reorientational mechanism in the nematic phase. None of the models gives a satisfactory account of the reorientation process in the isotropic phase.« less

Transition from direct to inverted charge transport Marcus regions in molecular junctions via molecular orbital gating

NASA Astrophysics Data System (ADS)

Yuan, Li; Wang, Lejia; Garrigues, Alvar R.; Jiang, Li; Annadata, Harshini Venkata; Anguera Antonana, Marta; Barco, Enrique; Nijhuis, Christian A.

2018-04-01

Solid-state molecular tunnel junctions are often assumed to operate in the Landauer regime, which describes essentially activationless coherent tunnelling processes. In solution, on the other hand, charge transfer is described by Marcus theory, which accounts for thermally activated processes. In practice, however, thermally activated transport phenomena are frequently observed also in solid-state molecular junctions but remain poorly understood. Here, we show experimentally the transition from the Marcus to the inverted Marcus region in a solid-state molecular tunnel junction by means of intra-molecular orbital gating that can be tuned via the chemical structure of the molecule and applied bias. In the inverted Marcus region, charge transport is incoherent, yet virtually independent of temperature. Our experimental results fit well to a theoretical model that combines Landauer and Marcus theories and may have implications for the interpretation of temperature-dependent charge transport measurements in molecular junctions.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

PubMed

Russo, Michael F; Garrison, Barbara J

2006-10-15

Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

Electron Driven Processes in Atmospheric Behaviour

NASA Astrophysics Data System (ADS)

Campbell, L.; Brunger, M. J.; Teubner, P. J. O.

2006-11-01

Electron impact plays an important role in many atmospheric processes. Calculation of these is important for basic understanding, atmospheric modeling and remote sensing. Accurate atomic and molecular data, including electron impact cross sections, are required for such calculations. Five electron-driven processes are considered: auroral and dayglow emissions, the reduction of atmospheric electron density by vibrationally excited N2, NO production and infrared emission from NO. In most cases the predictions are compared with measurements. The dependence on experimental atomic and molecular data is also investigated.

Self-consistent Non-LTE Model of Infrared Molecular Emissions and Oxygen Dayglows in the Mesosphere and Lower Thermosphere

NASA Technical Reports Server (NTRS)

Feofilov, Artem G.; Yankovsky, Valentine A.; Pesnell, William D.; Kutepov, Alexander A.; Goldberg, Richard A.; Mauilova, Rada O.

2007-01-01

We present the new version of the ALI-ARMS (for Accelerated Lambda Iterations for Atmospheric Radiation and Molecular Spectra) model. The model allows simultaneous self-consistent calculating the non-LTE populations of the electronic-vibrational levels of the O3 and O2 photolysis products and vibrational level populations of CO2, N2,O2, O3, H2O, CO and other molecules with detailed accounting for the variety of the electronic-vibrational, vibrational-vibrational and vibrational-translational energy exchange processes. The model was used as the reference one for modeling the O2 dayglows and infrared molecular emissions for self-consistent diagnostics of the multi-channel space observations of MLT in the SABER experiment It also allows reevaluating the thermalization efficiency of the absorbed solar ultraviolet energy and infrared radiative cooling/heating of MLT by detailed accounting of the electronic-vibrational relaxation of excited photolysis products via the complex chain of collisional energy conversion processes down to the vibrational energy of optically active trace gas molecules.

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.

Targeted Cancer Therapy: Vital Oncogenes and a New Molecular Genetic Paradigm for Cancer Initiation Progression and Treatment.

PubMed

Willis, Rudolph E

2016-09-14

It has been declared repeatedly that cancer is a result of molecular genetic abnormalities. However, there has been no working model describing the specific functional consequences of the deranged genomic processes that result in the initiation and propagation of the cancer process during carcinogenesis. We no longer need to question whether or not cancer arises as a result of a molecular genetic defect within the cancer cell. The legitimate questions are: how and why? This article reviews the preeminent data on cancer molecular genetics and subsequently proposes that the sentinel event in cancer initiation is the aberrant production of fused transcription activators with new molecular properties within normal tissue stem cells. This results in the production of vital oncogenes with dysfunctional gene activation transcription properties, which leads to dysfunctional gene regulation, the aberrant activation of transduction pathways, chromosomal breakage, activation of driver oncogenes, reactivation of stem cell transduction pathways and the activation of genes that result in the hallmarks of cancer. Furthermore, a novel holistic molecular genetic model of cancer initiation and progression is presented along with a new paradigm for the approach to personalized targeted cancer therapy, clinical monitoring and cancer diagnosis.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained.

PubMed

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

2016-06-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. Copyright © 2016 The American Physiological Society.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained

PubMed Central

Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. PMID:27231262

Protein Molecular Structures, Protein SubFractions, and Protein Availability Affected by Heat Processing: A Review

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

Yu,P.

2007-01-01

The utilization and availability of protein depended on the types of protein and their specific susceptibility to enzymatic hydrolysis (inhibitory activities) in the gastrointestine and was highly associated with protein molecular structures. Studying internal protein structure and protein subfraction profiles leaded to an understanding of the components that make up a whole protein. An understanding of the molecular structure of the whole protein was often vital to understanding its digestive behavior and nutritive value in animals. In this review, recently obtained information on protein molecular structural effects of heat processing was reviewed, in relation to protein characteristics affecting digestive behaviormore » and nutrient utilization and availability. The emphasis of this review was on (1) using the newly advanced synchrotron technology (S-FTIR) as a novel approach to reveal protein molecular chemistry affected by heat processing within intact plant tissues; (2) revealing the effects of heat processing on the profile changes of protein subfractions associated with digestive behaviors and kinetics manipulated by heat processing; (3) prediction of the changes of protein availability and supply after heat processing, using the advanced DVE/OEB and NRC-2001 models, and (4) obtaining information on optimal processing conditions of protein as intestinal protein source to achieve target values for potential high net absorbable protein in the small intestine. The information described in this article may give better insight in the mechanisms involved and the intrinsic protein molecular structural changes occurring upon processing.« less

From molecules to mating: Rapid evolution and biochemical studies of reproductive proteins

PubMed Central

Wilburn, Damien B.; Swanson, Willie J.

2015-01-01

Sexual reproduction and the exchange of genetic information are essential biological processes for species across all branches of the tree of life. Over the last four decades, biochemists have continued to identify many of the factors that facilitate reproduction, but the molecular mechanisms that mediate this process continue to elude us. However, a recurring observation in this research has been the rapid evolution of reproductive proteins. In animals, the competing interests of males and females often result in arms race dynamics between pairs of interacting proteins. This phenomenon has been observed in all stages of reproduction, including pheromones, seminal fluid components, and gamete recognition proteins. In this article, we review how the integration of evolutionary theory with biochemical experiments can be used to study interacting reproductive proteins. Examples are included from both model and non-model organisms, and recent studies are highlighted for their use of state-of-the-art genomic and proteomic techniques. Significance Despite decades of research, our understanding of the molecular mechanisms that mediate fertilization remain poorly characterized. To date, molecular evolutionary studies on both model and non-model organisms have provided some of the best inferences to elucidating the molecular underpinnings of animal reproduction. This review article details how biochemical and evolutionary experiments have jointly enhanced the field for 40 years, and how recent work using high-throughput genomic and proteomic techniques have shed additional insights into this crucial biological process. PMID:26074353

Computer-aided design of polymers and composites

NASA Technical Reports Server (NTRS)

Kaelble, D. H.

1985-01-01

This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.

Accelerating the use of molecular modeling in the high school classroom with VMD Lite.

PubMed

Lundquist, Karl; Herndon, Conner; Harty, Tyson H; Gumbart, James C

2016-01-01

It is often difficult for students to develop an intuition about molecular processes, which occur in a realm far different from day-to-day life. For example, thermal fluctuations take on hurricane-like proportions at the molecular scale. Students need a way to visualize realistic depictions of molecular processes to appreciate them. To this end, we have developed a simplified graphical interface to the widely used molecular visualization and analysis tool Visual Molecular Dynamics (VMD) called VMD lite. We demonstrate the use of VMD lite through a module on diffusion and the hydrophobic effect as they relate to membrane formation. Trajectories from molecular dynamics simulations, which students can interact with freely, illustrate the dynamical behavior of lipid molecules and water. VMD lite was tested by ∼70 students with overall positive reception. Remaining deficiencies in conceptual understanding were noted, however, and the module has been revised in response. © 2016 The International Union of Biochemistry and Molecular Biology.

New analytic results for speciation times in neutral models.

PubMed

Gernhard, Tanja

2008-05-01

In this paper, we investigate the standard Yule model, and a recently studied model of speciation and extinction, the "critical branching process." We develop an analytic way-as opposed to the common simulation approach-for calculating the speciation times in a reconstructed phylogenetic tree. Simple expressions for the density and the moments of the speciation times are obtained. Methods for dating a speciation event become valuable, if for the reconstructed phylogenetic trees, no time scale is available. A missing time scale could be due to supertree methods, morphological data, or molecular data which violates the molecular clock. Our analytic approach is, in particular, useful for the model with extinction, since simulations of birth-death processes which are conditioned on obtaining n extant species today are quite delicate. Further, simulations are very time consuming for big n under both models.

Development of Continuum-Atomistic Approach for Modeling Metal Irradiation by Heavy Ions

NASA Astrophysics Data System (ADS)

Batgerel, Balt; Dimova, Stefka; Puzynin, Igor; Puzynina, Taisia; Hristov, Ivan; Hristova, Radoslava; Tukhliev, Zafar; Sharipov, Zarif

2018-02-01

Over the last several decades active research in the field of materials irradiation by high-energy heavy ions has been worked out. The experiments in this area are labor-consuming and expensive. Therefore the improvement of the existing mathematical models and the development of new ones based on the experimental data of interaction of high-energy heavy ions with materials are of interest. Presently, two approaches are used for studying these processes: a thermal spike model and molecular dynamics methods. The combination of these two approaches - the continuous-atomistic model - will give the opportunity to investigate more thoroughly the processes of irradiation of materials by high-energy heavy ions. To solve the equations of the continuous-atomistic model, a software package was developed and the block of molecular dynamics software was tested on the heterogeneous cluster HybriLIT.

Resistance of Bacillus Endospores to Extreme Terrestrial and Extraterrestrial Environments

PubMed Central

Nicholson, Wayne L.; Munakata, Nobuo; Horneck, Gerda; Melosh, Henry J.; Setlow, Peter

2000-01-01

Endospores of Bacillus spp., especially Bacillus subtilis, have served as experimental models for exploring the molecular mechanisms underlying the incredible longevity of spores and their resistance to environmental insults. In this review we summarize the molecular laboratory model of spore resistance mechanisms and attempt to use the model as a basis for exploration of the resistance of spores to environmental extremes both on Earth and during postulated interplanetary transfer through space as a result of natural impact processes. PMID:10974126

Investigation of flavonoid influence on peroxidation processes intensity in the blood

NASA Astrophysics Data System (ADS)

Navolokin, N. A.; Mudrak, D. A.; Plastun, I. L.; Bucharskaya, A. B.; Agandeeva, K. E.; Ivlichev, A. V.; Tychina, S. A.; Afanasyeva, G. A.; Polukonova, N. V.; Maslyakova, G. N.

2017-03-01

Influence of flavonoids on the intensity of peroxidation processes in the blood is investigated by numerical modeling and by experiment in vivo. As an example we consider the effects of flavonoid-containing extract of Helichrysum arenarium L. with antitumor activity on serum of rats with transplanted liver cancer PC-1. It was found that the content of malondialdehyde, lipid hydroperoxides and average mass molecules were decreased in animals with transplanted liver cancer after intramuscular and oral administration of Helichrysum arenarium L extract in a dose of 1000 mg/mL. The extract reduces the intensity of lipid peroxidation processes in animals. The compound formation possibility of flavonoids and products of lipid peroxidation is investigated by numerical simulations. Using the density functional theory method of molecular modeling, 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 products of lipid peroxidation processes on example of naringine and malondialdehyde. We have found that naringine can form a steady molecular complex with malondialdehyde by hydrogen bonds formation. Thus, the application of Helichrysum arenarium L. extract for suppression processes of lipid peroxidation and activation of enzymatic and non-enzymatic antioxidant systems is promising.

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.

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.

Mapping biological process relationships and disease perturbations within a pathway network.

PubMed

Stoney, Ruth; Robertson, David L; Nenadic, Goran; Schwartz, Jean-Marc

2018-01-01

Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network. Pathways represent spatial and temporal sets of context-dependent interactions, generating a high-level network when linked together, which incorporates contextual information without the need for molecular interaction data. Analysis of the pathway network revealed linked communities representing functional relationships, comparable to those found in molecular networks, including metabolism, signaling, immunity, and the cell cycle. We mapped a range of diseases onto this network and find that pathways associated with diseases tend to be functionally connected, highlighting the perturbed functions that result in disease phenotypes. We demonstrated that disease pathways cluster within the network. We then examined the distribution of cancer pathways and showed that cancer pathways tend to localize within the signaling, DNA processes and immune modules, although some cancer-associated nodes are found in other network regions. Altogether, we generated a high-confidence functional network, which avoids some of the shortcomings faced by conventional molecular models. Our representation provides an intuitive functional interpretation of cellular organization, which relies only on high-quality pathway and Gene Ontology data. The network is available at https://data.mendeley.com/datasets/3pbwkxjxg9/1.

Integration and scaling of UV-B radiation effects on plants: from molecular interactions to whole plant responses.

PubMed

Suchar, Vasile Alexandru; Robberecht, Ronald

2016-07-01

A process based model integrating the effects of UV-B radiation to molecular level processes and their consequences to whole plant growth and development was developed from key parameters in the published literature. Model simulations showed that UV-B radiation induced changes in plant metabolic and/or photosynthesis rates can result in plant growth inhibitions. The costs of effective epidermal UV-B radiation absorptive compounds did not result in any significant changes in plant growth, but any associated metabolic costs effectively reduced the potential plant biomass. The model showed significant interactions between UV-B radiation effects and temperature and any factor leading to inhibition of photosynthetic production or plant growth during the midday, but the effects were not cumulative for all factors. Vegetative growth were significantly delayed in species that do not exhibit reproductive cycles during a growing season, but vegetative growth and reproductive yield in species completing their life cycle in one growing season did not appear to be delayed more than 2-5 days, probably within the natural variability of the life cycles for many species. This is the first model to integrate the effects of increased UV-B radiation through molecular level processes and their consequences to whole plant growth and development.

Assessing the Impact of Electrostatic Drag on Processive Molecular Motor Transport.

PubMed

Smith, J Darby; McKinley, Scott A

2018-06-04

The bidirectional movement of intracellular cargo is usually described as a tug-of-war among opposite-directed families of molecular motors. While tug-of-war models have enjoyed some success, recent evidence suggests underlying motor interactions are more complex than previously understood. For example, these tug-of-war models fail to predict the counterintuitive phenomenon that inhibiting one family of motors can decrease the functionality of opposite-directed transport. In this paper, we use a stochastic differential equations modeling framework to explore one proposed physical mechanism, called microtubule tethering, that could play a role in this "co-dependence" among antagonistic motors. This hypothesis includes the possibility of a trade-off: weakly bound trailing molecular motors can serve as tethers for cargoes and processing motors, thereby enhancing motor-cargo run lengths along microtubules; however, this introduces a cost of processing at a lower mean velocity. By computing the small- and large-time mean-squared displacement of our theoretical model and comparing our results to experimental observations of dynein and its "helper protein" dynactin, we find some supporting evidence for microtubule tethering interactions. We extrapolate these findings to predict how dynein-dynactin might interact with the opposite-directed kinesin motors and introduce a criterion for when the trade-off is beneficial in simple systems.

Computing by physical interaction in neurons.

PubMed

Aur, Dorian; Jog, Mandar; Poznanski, Roman R

2011-12-01

The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.

Efficient implementation of constant pH molecular dynamics on modern graphics processors.

PubMed

Arthur, Evan J; Brooks, Charles L

2016-09-15

The treatment of pH sensitive ionization states for titratable residues in proteins is often omitted from molecular dynamics (MD) simulations. While static charge models can answer many questions regarding protein conformational equilibrium and protein-ligand interactions, pH-sensitive phenomena such as acid-activated chaperones and amyloidogenic protein aggregation are inaccessible to such models. Constant pH molecular dynamics (CPHMD) coupled with the Generalized Born with a Simple sWitching function (GBSW) implicit solvent model provide an accurate framework for simulating pH sensitive processes in biological systems. Although this combination has demonstrated success in predicting pKa values of protein structures, and in exploring dynamics of ionizable side-chains, its speed has been an impediment to routine application. The recent availability of low-cost graphics processing unit (GPU) chipsets with thousands of processing cores, together with the implementation of the accurate GBSW implicit solvent model on those chipsets (Arthur and Brooks, J. Comput. Chem. 2016, 37, 927), provide an opportunity to improve the speed of CPHMD and ionization modeling greatly. Here, we present a first implementation of GPU-enabled CPHMD within the CHARMM-OpenMM simulation package interface. Depending on the system size and nonbonded force cutoff parameters, we find speed increases of between one and three orders of magnitude. Additionally, the algorithm scales better with system size than the CPU-based algorithm, thus allowing for larger systems to be modeled in a cost effective manner. We anticipate that the improved performance of this methodology will open the door for broad-spread application of CPHMD in its modeling pH-mediated biological processes. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Biotechnology and genetic engineering in the new drug development. Part III. Biocatalysis, metabolic engineering and molecular modelling.

PubMed

Stryjewska, Agnieszka; Kiepura, Katarzyna; Librowski, Tadeusz; Lochyński, Stanisław

2013-01-01

Industrial biotechnology has been defined as the use and application of biotechnology for the sustainable processing and production of chemicals, materials and fuels. It makes use of biocatalysts such as microbial communities, whole-cell microorganisms or purified enzymes. In the review these processes are described. Drug design is an iterative process which begins when a chemist identifies a compound that displays an interesting biological profile and ends when both the activity profile and the chemical synthesis of the new chemical entity are optimized. Traditional approaches to drug discovery rely on a stepwise synthesis and screening program for large numbers of compounds to optimize activity profiles. Over the past ten to twenty years, scientists have used computer models of new chemical entities to help define activity profiles, geometries and relativities. This article introduces inter alia the concepts of molecular modelling and contains references for further reading.

Enhanced mechanical properties of graphene/copper nanocomposites using a molecular-level mixing process.

PubMed

Hwang, Jaewon; Yoon, Taeshik; Jin, Sung Hwan; Lee, Jinsup; Kim, Taek-Soo; Hong, Soon Hyung; Jeon, Seokwoo

2013-12-10

RGO flakes are homogeneously dispersed in a Cu matrix through a molecular-level mixing process. This novel fabrication process prevents the agglomeration of the RGO and enhances adhesion between the RGO and the Cu. The yield strength of the 2.5 vol% RGO/Cu nanocomposite is 1.8 times higher than that of pure Cu. The strengthening mechanism of the RGO is investigated by a double cantilever beam test using the graphene/Cu model structure. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Orientation distribution and process modeling of thermotropic liquid crystalline copolyester (TLCP) injection-moldings

NASA Astrophysics Data System (ADS)

Bubeck, Robert; Fang, Jun; Burghardt, Wesley; Burgard, Susan; Fischer, Daniel

2009-03-01

The influence of melt processing conditions upon mechanical properties and degrees of compound molecular orientation have been thoroughly studied for a series of well-defined injection molded samples fabricated from VECTRA (TM) A950 and 4,4'-dihydroxy-a-methylstilbene TLCPs. Fracture and tensile data were correlated with processing conditions, orientation, and molecular weight. Mechanical properties for both TLCPs were found to follow a ``universal'' Anisotropy Factor (AF) associated with the bimodal orientation states in the plaques determined from 2-D WAXS. Surface orientations were globally surveyed using Attenuated Total Reflectance -- Fourier Transform Infrared (ATR-FTIR) spectroscopy and C K edge Near-Edge X-ray Absorption Fine Structure (NEXAFS). The results derived from the two spectroscopy techniques confirmed each other well. These results along with those from 2-D WAXS in transmission were compared with the results of process modeling using a commercial program, MOLDFLOW(TM). The agreement between model predictions and the measured orientation states was gratifyingly good.

Semiclassical theory of electronically nonadiabatic transitions in molecular collision processes

NASA Technical Reports Server (NTRS)

Lam, K. S.; George, T. F.

1979-01-01

An introductory account of the semiclassical theory of the S-matrix for molecular collision processes is presented, with special emphasis on electronically nonadiabatic transitions. This theory is based on the incorporation of classical mechanics with quantum superposition, and in practice makes use of the analytic continuation of classical mechanics into the complex space of time domain. The relevant concepts of molecular scattering theory and related dynamical models are described and the formalism is developed and illustrated with simple examples - collinear collision of the A+BC type. The theory is then extended to include the effects of laser-induced nonadiabatic transitions. Two bound continuum processes collisional ionization and collision-induced emission also amenable to the same general semiclassical treatment are discussed.

Structure-Activity Relationship Studies and Molecular Modeling of Naphthalene-Based Sphingosine Kinase 2 Inhibitors.

PubMed

Congdon, Molly D; Kharel, Yugesh; Brown, Anne M; Lewis, Stephanie N; Bevan, David R; Lynch, Kevin R; Santos, Webster L

2016-03-10

The two isoforms of sphingosine kinase (SphK1 and SphK2) are the only enzymes that phosphorylate sphingosine to sphingosine-1-phosphate (S1P), which is a pleiotropic lipid mediator involved in a broad range of cellular processes including migration, proliferation, and inflammation. SphKs are targets for various diseases such as cancer, fibrosis, and Alzheimer's and sickle cell disease. Herein, we disclose the structure-activity profile of naphthalene-containing SphK inhibitors and molecular modeling studies that reveal a key molecular switch that controls SphK selectivity.

Testing the role of molecular physics in dissipative divertor operations through helium plasmas at DIII-D

DOE PAGES

Canik, John M.; Briesemeister, Alexis R.; McLean, Adam G.; ...

2017-05-10

Recent experiments in DIII-D helium plasmas are examined to resolve the role of atomic and molecular physics in major discrepancies between experiment and modeling of dissipative divertor operation. Helium operation removes the complicated molecular processes of deuterium plasmas that are a prime candidate for the inability of standard fluid models to reproduce dissipative divertor operation, primarily the consistent under-prediction of radiated power. Modeling of these experiments shows that the full divertor radiation can be accounted for, but only if measures are taken to ensure that the model reproduces the measured divertor density. Relying on upstream measurements instead results in amore » lower divertor density and radiation than is measured, indicating a need for improved modeling of the connection between the diverter and the upstream scrape-off layer. Furthermore, these results show that fluid models are able to quantitatively describe the divertor-region plasma, including radiative losses, and indicate that efforts to improve the fidelity of the molecular deuterium models are likely to help resolve the discrepancy in radiation for deuterium plasmas.« less

Carbon Isotope Chemistry in Molecular Clouds

NASA Technical Reports Server (NTRS)

Robertson, Amy N.; Willacy, Karen

2012-01-01

Few details of carbon isotope chemistry are known, especially the chemical processes that occur in astronomical environments like molecular clouds. Observational evidence shows that the C-12/C-13 abundance ratios vary due to the location of the C-13 atom within the molecular structure. The different abundances are a result of the diverse formation pathways that can occur. Modeling can be used to explore the production pathways of carbon molecules in an effort to understand and explain the chemical evolution of molecular clouds.

Spectroscopic properties of the molecular ions BeX+ (X=Na, K, Rb): forming cold molecular ions from an ion-atom mixture by stimulated Raman adiabatic process

NASA Astrophysics Data System (ADS)

Ladjimi, Hela; Sardar, Dibyendu; Farjallah, Mohamed; Alharzali, Nisrin; Naskar, Somnath; Mlika, Rym; Berriche, Hamid; Deb, Bimalendu

2018-07-01

In this theoretical work, we calculate potential energy curves, spectroscopic parameters and transition dipole moments of molecular ions BeX+ (X=Na, K, Rb) composed of alkaline ion Be and alkali atom X with a quantum chemistry approach based on the pseudopotential model, Gaussian basis sets, effective core polarisation potentials and full configuration interaction. We study in detail collisions of the alkaline ion and alkali atom in quantum regime. Besides, we study the possibility of the formation of molecular ions from the ion-atom colliding systems by stimulated Raman adiabatic process and discuss the parameters regime under which the population transfer is feasible. Our results are important for ion-atom cold collisions and experimental realisation of cold molecular ion formation.

Computing molecular fluctuations in biochemical reaction systems based on a mechanistic, statistical theory of irreversible processes.

PubMed

Kulasiri, Don

2011-01-01

We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions. © 2011 Elsevier Inc. All rights reserved.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum.

PubMed

Brunger, Axel T; Das, Debanu; Deacon, Ashley M; Grant, Joanna; Terwilliger, Thomas C; Read, Randy J; Adams, Paul D; Levitt, Michael; Schröder, Gunnar F

2012-04-01

Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 Å resolution is described using a combination of homology modeling with MODELLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence.

Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum

PubMed Central

Brunger, Axel T.; Das, Debanu; Deacon, Ashley M.; Grant, Joanna; Terwilliger, Thomas C.; Read, Randy J.; Adams, Paul D.; Levitt, Michael; Schröder, Gunnar F.

2012-01-01

Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 Å resolution is described using a combination of homology modeling with MODELLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence. PMID:22505259

The graph neural network model.

PubMed

Scarselli, Franco; Gori, Marco; Tsoi, Ah Chung; Hagenbuchner, Markus; Monfardini, Gabriele

2009-01-01

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) is an element of IR(m) that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.

The Jukes-Cantor Model of Molecular Evolution

ERIC Educational Resources Information Center

Erickson, Keith

2010-01-01

The material in this module introduces students to some of the mathematical tools used to examine molecular evolution. This topic is standard fare in many mathematical biology or bioinformatics classes, but could also be suitable for classes in linear algebra or probability. While coursework in matrix algebra, Markov processes, Monte Carlo…

The Development of Students' Mental Models of Chemical Substances and Processes at the Molecular Level

NASA Astrophysics Data System (ADS)

Dalton, Rebecca Marie

The development of student's mental models of chemical substances and processes at the molecular level was studied in a three-phase project. Animations produced in the VisChem project were used as an integral part of the chemistry instruction to help students develop their mental models. Phase one of the project involved examining the effectiveness of using animations to help first-year university chemistry students develop useful mental models of chemical phenomena. Phase two explored factors affecting the development of student's mental models, analysing results in terms of a proposed model of the perceptual processes involved in interpreting an animation. Phase three involved four case studies that served to confirm and elaborate on the effects of prior knowledge and disembedding ability on student's mental model development, and support the influence of study style on learning outcomes. Recommendations for use of the VisChem animations, based on the above findings, include: considering the prior knowledge of students; focusing attention on relevant features; encouraging a deep approach to learning; using animation to teach visual concepts; presenting ideas visually, verbally and conceptually; establishing 'animation literacy'; minimising cognitive load; using animation as feedback; using student drawings; repeating animations; and discussing 'scientific modelling'.

Multiscale Modeling of Mesoscale and Interfacial Phenomena

NASA Astrophysics Data System (ADS)

Petsev, Nikolai Dimitrov

With rapidly emerging technologies that feature interfaces modified at the nanoscale, traditional macroscopic models are pushed to their limits to explain phenomena where molecular processes can play a key role. Often, such problems appear to defy explanation when treated with coarse-grained continuum models alone, yet remain prohibitively expensive from a molecular simulation perspective. A prominent example is surface nanobubbles: nanoscopic gaseous domains typically found on hydrophobic surfaces that have puzzled researchers for over two decades due to their unusually long lifetimes. We show how an entirely macroscopic, non-equilibrium model explains many of their anomalous properties, including their stability and abnormally small gas-side contact angles. From this purely transport perspective, we investigate how factors such as temperature and saturation affect nanobubbles, providing numerous experimentally testable predictions. However, recent work also emphasizes the relevance of molecular-scale phenomena that cannot be described in terms of bulk phases or pristine interfaces. This is true for nanobubbles as well, whose nanoscale heights may require molecular detail to capture the relevant physics, in particular near the bubble three-phase contact line. Therefore, there is a clear need for general ways to link molecular granularity and behavior with large-scale continuum models in the treatment of many interfacial problems. In light of this, we have developed a general set of simulation strategies that couple mesoscale particle-based continuum models to molecular regions simulated through conventional molecular dynamics (MD). In addition, we derived a transport model for binary mixtures that opens the possibility for a wide range of applications in biological and drug delivery problems, and is readily reconciled with our hybrid MD-continuum techniques. Approaches that couple multiple length scales for fluid mixtures are largely absent in the literature, and we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.

Studies on Manfred Eigen's model for the self-organization of information processing.

PubMed

Ebeling, W; Feistel, R

2018-05-01

In 1971, Manfred Eigen extended the principles of Darwinian evolution to chemical processes, from catalytic networks to the emergence of information processing at the molecular level, leading to the emergence of life. In this paper, we investigate some very general characteristics of this scenario, such as the valuation process of phenotypic traits in a high-dimensional fitness landscape, the effect of spatial compartmentation on the valuation, and the self-organized transition from structural to symbolic genetic information of replicating chain molecules. In the first part, we perform an analysis of typical dynamical properties of continuous dynamical models of evolutionary processes. In particular, we study the mapping of genotype to continuous phenotype spaces following the ideas of Wright and Conrad. We investigate typical features of a Schrödinger-like dynamics, the consequences of the high dimensionality, the leading role of saddle points, and Conrad's extra-dimensional bypass. In the last part, we discuss in brief the valuation of compartment models and the self-organized emergence of molecular symbols at the beginning of life.

The Virtual Liver: Modeling Chemical-Induced Liver Toxicity

EPA Science Inventory

The US EPA Virtual Liver (v-Liver) project is aimed at modeling chemical-induced processes in hepatotoxicity and simulating their dose-dependent perturbations. The v-Liver embodies an emerging field of research in computational tissue modeling that integrates molecular and cellul...

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.

Coarse gaining of molecular crystals: limitations imposed by molecular flexibility

NASA Astrophysics Data System (ADS)

Picu, Catalin; Pal, Anirban

Molecular crystals include molecular electronics, energetic materials, pharmaceuticals and some food components. In many of these applications the small scale mechanical behavior of the crystal is important such as for example in energetic materials where detonation is induced by the formation of hot spots which are induced thermomechanically, and in pharmaceuticals where phase stability is critical for the biochemical activity of the drug. Accurate modeling of these processes requires resolving the atomistic scale details of the material. However, the cost of these models is very large due to the complexity of the molecules forming the crystal, and some form of coarse graning is necessary. In this study we identify the limitations imposed by the need to accurately capture molecular flexibility on the development of coarse grained models for the energetic molecular crystal RDX. We define guidelines for the definition of coarse grained models that target elastic and plastic crystal scale properties such as elastic constants, thermal expansion, compressibility, the critical stress for the motion of dislocations (Peierls stress) and the stacking fault energy This work was supported by the ARO through Grant W911NF-09-1-0330 and AFRL through Grant FA8651-16-1-0004.

Ordinary differential equations with applications in molecular biology.

PubMed

Ilea, M; Turnea, M; Rotariu, M

2012-01-01

Differential equations are of basic importance in molecular biology mathematics because many biological laws and relations appear mathematically in the form of a differential equation. In this article we presented some applications of mathematical models represented by ordinary differential equations in molecular biology. The vast majority of quantitative models in cell and molecular biology are formulated in terms of ordinary differential equations for the time evolution of concentrations of molecular species. Assuming that the diffusion in the cell is high enough to make the spatial distribution of molecules homogenous, these equations describe systems with many participating molecules of each kind. We propose an original mathematical model with small parameter for biological phospholipid pathway. All the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. If we reduce the size of the solution region the same small epsilon will result in a different condition number. It is clear that the solution for a smaller region is less difficult. We introduce the mathematical technique known as boundary function method for singular perturbation system. In this system, the small parameter is an asymptotic variable, different from the independent variable. In general, the solutions of such equations exhibit multiscale phenomena. Singularly perturbed problems form a special class of problems containing a small parameter which may tend to zero. Many molecular biology processes can be quantitatively characterized by ordinary differential equations. Mathematical cell biology is a very active and fast growing interdisciplinary area in which mathematical concepts, techniques, and models are applied to a variety of problems in developmental medicine and bioengineering. Among the different modeling approaches, ordinary differential equations (ODE) are particularly important and have led to significant advances. Ordinary differential equations are used to model biological processes on various levels ranging from DNA molecules or biosynthesis phospholipids on the cellular level.

Modeling and Deorphanization of Orphan GPCRs.

PubMed

Diaz, Constantino; Angelloz-Nicoud, Patricia; Pihan, Emilie

2018-01-01

Despite tremendous efforts, approximately 120 GPCRs remain orphan. Their physiological functions and their potential roles in diseases are poorly understood. Orphan GPCRs are extremely important because they may provide novel therapeutic targets for unmet medical needs. As a complement to experimental approaches, molecular modeling and virtual screening are efficient techniques to discover synthetic surrogate ligands which can help to elucidate the role of oGPCRs. Constitutively activated mutants and recently published active structures of GPCRs provide stimulating opportunities for building active molecular models for oGPCRs and identifying activators using virtual screening of compound libraries. We describe the molecular modeling and virtual screening process we have applied in the discovery of surrogate ligands, and provide examples for CCKA, a simulated oGPCR, and for two oGPCRs, GPR52 and GPR34.

Isotherms for Water Adsorption on Molecular Sieve 3A: Influence of Cation Composition

DOE PAGES

Lin, Ronghong; Ladshaw, Austin; Nan, Yue; ...

2015-06-16

This study is part of our continuing efforts to address engineering issues related to the removal of tritiated water from off-gases produced in used nuclear fuel reprocessing facilities. In the current study, adsorption equilibrium of water on molecular sieve 3A beads was investigated. Adsorption isotherms for water on the UOP molecular sieve 3A were measured by a continuous-flow adsorption system at 298, 313, 333, and 353 K. Experimental data collected were analyzed by the Generalized Statistical Thermodynamic Adsorption (GSTA) isotherm model. The K +/Na + molar ratio of this particular type of molecular sieve 3A was ~4:6. Our results showedmore » that the GSTA isotherm model worked very well to describe the equilibrium behavior of water adsorption on molecular sieve 3A. The optimum number of parameters for the current experimental data was determined to be a set of four equilibrium parameters. This result suggests that the adsorbent crystals contain four energetically distinct adsorption sites. In addition, it was found that water adsorption on molecular sieve 3A follows a three-stage adsorption process. This three-stage adsorption process confirmed different water adsorption sites in molecular sieve crystals. In addition, the second adsorption stage is significantly affected by the K +/Na + molar ratio. In this stage, the equilibrium adsorption capacity at a given water vapor pressure increases as the K +/Na + molar ratio increases.« less

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

The circadian clock controls toll-like receptor 9-mediated innate and adaptive immunity

PubMed Central

Silver, Adam C.; Arjona, Alvaro; Walker, Wendy E.; Fikrig, Erol

2012-01-01

Circadian rhythms refer to biologic processes that oscillate with a period of approximately 24 hours. These rhythms are sustained by a molecular clock and provide a temporal matrix that ensures the coordination of homeostatic processes with the periodicity of environmental challenges. We demonstrate the circadian molecular clock controls the expression and function of toll like receptor 9 (TLR9). In a vaccination model using TLR9 ligand as adjuvant, mice immunized at the time of enhanced TLR9 responsiveness presented weeks later with an improved adaptive immune response. In a TLR9-dependent mouse model of sepsis, we found that disease severity was dependent on the timing of sepsis induction, coinciding with the daily changes in TLR9 expression and function. These findings unveil a direct molecular link between the circadian and innate immune systems with important implications for immunoprophylaxis and immunotherapy. PMID:22342842

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations.

PubMed

Gao, Xiaodong; Han, Liping; Ren, Yujie

2016-05-05

Checkpoint kinase 1 (Chk1) is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q² values (0.531, 0.726), fitted correlation r² coefficients (higher than 0.90), and standard error of prediction (less than 0.250). These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity.

Atomic and Molecular Data and their Applications★

NASA Astrophysics Data System (ADS)

Drake, Gordon W. F.; Yoon, Jung-Sik; Kato, Daiji; Karwasz, Grzegorz

2018-03-01

This topical issue on Atomic and molecular data and their applications was motivated by the 10th International Conference on Atomic and Molecular Data (ICAMDATA 2016), which was held from September 26 to 29, 2016 in Gunsan, Republic of Korea. The topics of this issue reflect those of the conference program. The scientific papers in the topical issue cover the fields of atomic and molecular structure, radiative transitions, scattering processes, data base development, and the applications of atomic and molecular data to plasma modeling. Contribution to the Topical Issue "Atomic and Molecular Data and their Applications", edited by Gordon W.F. Drake, Jung-Sik Yoon, Daiji Kato, and Grzegorz Karwasz.

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

Deng, Mingsen; Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Institute of Applied Physics, Guizhou Normal College, Guiyang, 550018; Ye, Gui

The probe of flexible molecular conformation is crucial for the electric application of molecular systems. We have developed a theoretical procedure to analyze the couplings of molecular local vibrations with the electron transportation process, which enables us to evaluate the structural fingerprints of some vibrational modes in the inelastic electron tunneling spectroscopy (IETS). Based on a model molecule of Bis-(4-mercaptophenyl)-ether with a flexible center angle, we have revealed and validated a simple mathematical relationship between IETS signals and molecular angles. Our results might open a route to quantitatively measure key geometrical parameters of molecular junctions, which helps to achieve precisemore » control of molecular devices.« less

Multifunctional receptor model for dioxin and related compound toxic action: possible thyroid hormone-responsive effector-linked site.

PubMed Central

McKinney, J D

1989-01-01

Molecular/theoretical modeling studies have revealed that thyroid hormones and toxic chlorinated aromatic hydrocarbons of environmental significance (for which dioxin or TCDD is the prototype) have similar structural properties that could be important in molecular recognition in biochemical systems. These molecular properties include a somewhat rigid, sterically accessible and polarizable aromatic ring and size-limited, hydrophobic lateral substituents, usually contained in opposite adjoining rings of a diphenyl compound. These molecular properties define the primary binding groups thought to be important in molecular recognition of both types of structures in biochemical systems. Similar molecular reactivities are supported by the demonstration of effective specific binding of thyroid hormones and chlorinated aromatic hydrocarbons with four different proteins, enzymes, or receptor preparations that are known or suspected to be involved in the expression of thyroid hormone activity. These binding interactions represent both aromatic-aromatic (stacking) and molecular cleft-type recognition processes. A multiple protein or multifunctional receptor-ligand binding mechanism model is proposed as a way of visualizing the details and possible role of both the stacking and cleft type molecular recognition factors in the expression of biological activity. The model suggests a means by which hormone-responsive effector-linked sites (possible protein-protein-DNA complexes) can maintain highly structurally specific control of hormone action. Finally, the model also provides a theoretical basis for the design and conduct of further biological experimentation on the molecular mechanism(s) of action of toxic chlorinated aromatic hydrocarbons and thyroid hormones. Images FIGURE 3. A FIGURE 3. B FIGURE 3. C FIGURE 3. D PMID:2551666

Application potential of ATR-FT/IR molecular spectroscopy in animal nutrition: revelation of protein molecular structures of canola meal and presscake, as affected by heat-processing methods, in relationship with their protein digestive behavior and utilization for dairy cattle.

PubMed

Theodoridou, Katerina; Yu, Peiqiang

2013-06-12

Protein quality relies not only on total protein but also on protein inherent structures. The most commonly occurring protein secondary structures (α-helix and β-sheet) may influence protein quality, nutrient utilization, and digestive behavior. The objectives of this study were to reveal the protein molecular structures of canola meal (yellow and brown) and presscake as affected by the heat-processing methods and to investigate the relationship between structure changes and protein rumen degradations kinetics, estimated protein intestinal digestibility, degraded protein balance, and metabolizable protein. Heat-processing conditions resulted in a higher value for α-helix and β-sheet for brown canola presscake compared to brown canola meal. The multivariate molecular spectral analyses (PCA, CLA) showed that there were significant molecular structural differences in the protein amide I and II fingerprint region (ca. 1700-1480 cm(-1)) between the brown canola meal and presscake. The in situ degradation parameters, amide I and II, and α-helix to β-sheet ratio (R_a_β) were positively correlated with the degradable fraction and the degradation rate. Modeling results showed that α-helix was positively correlated with the truly absorbed rumen synthesized microbial protein in the small intestine when using both the Dutch DVE/OEB system and the NRC-2001 model. Concerning the protein profiles, R_a_β was a better predictor for crude protein (79%) and for neutral detergent insoluble crude protein (68%). In conclusion, ATR-FT/IR molecular spectroscopy may be used to rapidly characterize feed structures at the molecular level and also as a potential predictor of feed functionality, digestive behavior, and nutrient utilization of canola feed.

Advances of Molecular Imaging for Monitoring the Anatomical and Functional Architecture of the Olfactory System.

PubMed

Zhang, Xintong; Bi, Anyao; Gao, Quansheng; Zhang, Shuai; Huang, Kunzhu; Liu, Zhiguo; Gao, Tang; Zeng, Wenbin

2016-01-20

The olfactory system of organisms serves as a genetically and anatomically model for studying how sensory input can be translated into behavior output. Some neurologic diseases are considered to be related to olfactory disturbance, especially Alzheimer's disease, Parkinson's disease, multiple sclerosis, and so forth. However, it is still unclear how the olfactory system affects disease generation processes and olfaction delivery processes. Molecular imaging, a modern multidisciplinary technology, can provide valid tools for the early detection and characterization of diseases, evaluation of treatment, and study of biological processes in living subjects, since molecular imaging applies specific molecular probes as a novel approach to produce special data to study biological processes in cellular and subcellular levels. Recently, molecular imaging plays a key role in studying the activation of olfactory system, thus it could help to prevent or delay some diseases. Herein, we present a comprehensive review on the research progress of the imaging probes for visualizing olfactory system, which is classified on different imaging modalities, including PET, MRI, and optical imaging. Additionally, the probes' design, sensing mechanism, and biological application are discussed. Finally, we provide an outlook for future studies in this field.

Molecular imaging with bioconjugates in mouse models of cancer.

PubMed

Mather, Stephen

2009-04-01

The definition of molecular imaging provided by the Society of Nuclear Medicine is "the visualization, characterization and measurement of biological processes at the molecular and cellular levels in humans and other living systems". This review gives an overview of the technologies available for and the potential benefits from molecular imaging at the preclinical stage. It focuses on the use of imaging probes based on bioconjugates and for reasons of brevity confines itself to discussion of applications in the field of oncology, although molecular imaging can be equally useful in many fields including cardiovascular medicine, neurosciences, infection, and others.

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.

Disentangling the Role of Entanglement Density and Molecular Alignment in the Mechanical Response of Glassy Polymers

NASA Astrophysics Data System (ADS)

O'Connor, Thomas; Robbins, Mark

Glassy polymers are a ubiquitous part of modern life, but much about their mechanical properties remains poorly understood. Since chains in glassy states are hindered from exploring their conformational entropy, they can't be understood with common entropic network models. Additionally, glassy states are highly sensitive to material history and nonequilibrium distributions of chain alignment and entanglement can be produced during material processing. Understanding how these far-from equilibrium states impact mechanical properties is analytically challenging but essential to optimizing processing methods. We use molecular dynamics simulations to study the yield and strain hardening of glassy polymers as separate functions of the degree of molecular alignment and inter-chain entanglement. We vary chain alignment and entanglement with three different preparation protocols that mimic common processing conditions in and out of solution. We compare our results to common mechanical models of amorphous polymers and assess their applicability to different experimental processing conditions. This research was performed within the Center for Materials in Extreme Dynamic Environments (CMEDE) under the Hopkins Extreme Materials Institute at Johns Hopkins University. Financial support was provided by Grant W911NF-12-2-0022.

Predictive Finite Rate Model for Oxygen-Carbon Interactions at High Temperature

NASA Astrophysics Data System (ADS)

Poovathingal, Savio

An oxidation model for carbon surfaces is developed to predict ablation rates for carbon heat shields used in hypersonic vehicles. Unlike existing empirical models, the approach used here was to probe gas-surface interactions individually and then based on an understanding of the relevant fundamental processes, build a predictive model that would be accurate over a wide range of pressures and temperatures, and even microstructures. Initially, molecular dynamics was used to understand the oxidation processes on the surface. The molecular dynamics simulations were compared to molecular beam experiments and good qualitative agreement was observed. The simulations reproduced cylindrical pitting observed in the experiments where oxidation was rapid and primarily occurred around a defect. However, the studies were limited to small systems at low temperatures and could simulate time scales only of the order of nanoseconds. Molecular beam experiments at high surface temperature indicated that a majority of surface reaction products were produced through thermal mechanisms. Since the reactions were thermal, they occurred over long time scales which were computationally prohibitive for molecular dynamics to simulate. The experiments provided detailed dynamical data on the scattering of O, O2, CO, and CO2 and it was found that the data from molecular beam experiments could be used directly to build a model. The data was initially used to deduce surface reaction probabilities at 800 K. The reaction probabilities were then incorporated into the direct simulation Monte Carlo (DSMC) method. Simulations were performed where the microstructure was resolved and dissociated oxygen convected and diffused towards it. For a gas-surface temperature of 800 K, it was found that despite CO being the dominant surface reaction product, a gas-phase reaction forms significant CO2 within the microstructure region. It was also found that surface area did not play any role in concentration of reaction products because the reaction probabilities were in the diffusion dominant regime. The molecular beam data at different surface temperatures was then used to build a finite rate model. Each reaction mechanism and all rate parameters of the new model were determined individually based on the molecular beam data. Despite the experiments being performed at near vacuum conditions, the finite rate model developed using the data could be used at pressures and temperatures relevant to hypersonic conditions. The new model was implemented in a computational fluid dynamics (CFD) solver and flow over a hypersonic vehicle was simulated. The new model predicted similar overall mass loss rates compared to existing models, however, the individual species production rates were completely different. The most notable difference was that the new model (based on molecular beam data) predicts CO as the oxidation reaction product with virtually no CO2 production, whereas existing models predict the exact opposite trend. CO being the dominant oxidation product is consistent with recent high enthalpy wind tunnel experiments. The discovery that measurements taken in molecular beam facilities are able to determine individual reaction mechanisms, including dependence on surface coverage, opens up an entirely new way of constructing ablation models.

A computer model for one-dimensional mass and energy transport in and around chemically reacting particles, including complex gas-phase chemistry, multicomponent molecular diffusion, surface evaporation, and heterogeneous reaction

NASA Technical Reports Server (NTRS)

Cho, S. Y.; Yetter, R. A.; Dryer, F. L.

1992-01-01

Various chemically reacting flow problems highlighting chemical and physical fundamentals rather than flow geometry are presently investigated by means of a comprehensive mathematical model that incorporates multicomponent molecular diffusion, complex chemistry, and heterogeneous processes, in the interest of obtaining sensitivity-related information. The sensitivity equations were decoupled from those of the model, and then integrated one time-step behind the integration of the model equations, and analytical Jacobian matrices were applied to improve the accuracy of sensitivity coefficients that are calculated together with model solutions.

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.

First-Principles Molecular Dynamics Studies of Organometallic Complexes and Homogeneous Catalytic Processes.

PubMed

Vidossich, Pietro; Lledós, Agustí; Ujaque, Gregori

2016-06-21

Computational chemistry is a valuable aid to complement experimental studies of organometallic systems and their reactivity. It allows probing mechanistic hypotheses and investigating molecular structures, shedding light on the behavior and properties of molecular assemblies at the atomic scale. When approaching a chemical problem, the computational chemist has to decide on the theoretical approach needed to describe electron/nuclear interactions and the composition of the model used to approximate the actual system. Both factors determine the reliability of the modeling study. The community dedicated much effort to developing and improving the performance and accuracy of theoretical approaches for electronic structure calculations, on which the description of (inter)atomic interactions rely. Here, the importance of the model system used in computational studies is highlighted through examples from our recent research focused on organometallic systems and homogeneous catalytic processes. We show how the inclusion of explicit solvent allows the characterization of molecular events that would otherwise not be accessible in reduced model systems (clusters). These include the stabilization of nascent charged fragments via microscopic solvation (notably, hydrogen bonding), transfer of charge (protons) between distant fragments mediated by solvent molecules, and solvent coordination to unsaturated metal centers. Furthermore, when weak interactions are involved, we show how conformational and solvation properties of organometallic complexes are also affected by the explicit inclusion of solvent molecules. Such extended model systems may be treated under periodic boundary conditions, thus removing the cluster/continuum (or vacuum) boundary, and require a statistical mechanics simulation technique to sample the accessible configurational space. First-principles molecular dynamics, in which atomic forces are computed from electronic structure calculations (namely, density functional theory), is certainly the technique of choice to investigate chemical events in solution. This methodology is well established and thanks to advances in both algorithms and computational resources simulation times required for the modeling of chemical events are nowadays accessible, though the computational requirements use to be high. Specific applications reviewed here include mechanistic studies of the Shilov and Wacker processes, speciation in Pd chemistry, hydrogen bonding to metal centers, and the dynamics of agostic interactions.

Analysis of the Molecular Mechanisms of Reepithelialization in Drosophila Embryos

PubMed Central

Matsubayashi, Yutaka; Millard, Tom H.

2016-01-01

Significance: The epidermis provides the main barrier function of skin, and therefore its repair following wounding is an essential component of wound healing. Repair of the epidermis, also known as reepithelialization, occurs by collective migration of epithelial cells from around the wound edge across the wound until the advancing edges meet and fuse. Therapeutic manipulation of this process could potentially be used to accelerate wound healing. Recent Advances: It is difficult to analyze the cellular and molecular mechanisms of reepithelialization in human tissue, so a variety of model organisms have been used to improve our understanding of the process. One model system that has been especially useful is the embryo of the fruit fly Drosophila, which provides a simple, accessible model of the epidermis and can be manipulated genetically, allowing detailed analysis of reepithelialization at the molecular level. This review will highlight the key insights that have been gained from studying reepithelialization in Drosophila embryos. Critical Issues: Slow reepithelialization increases the risk of wounds becoming infected and ulcerous; therefore, the development of therapies to accelerate or enhance the process would be a great clinical advance. Improving our understanding of the molecular mechanisms that underlie reepithelialization will help in the development of such therapies. Future Directions: Research in Drosophila embryos has identified a variety of genes and proteins involved in triggering and driving reepithelialization, many of which are conserved in humans. These novel reepithelialization proteins are potential therapeutic targets and therefore findings obtained in Drosophila may ultimately lead to significant clinical advances. PMID:27274434

Antibody-controlled actuation of DNA-based molecular circuits.

PubMed

Engelen, Wouter; Meijer, Lenny H H; Somers, Bram; de Greef, Tom F A; Merkx, Maarten

2017-02-17

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Antibody-controlled actuation of DNA-based molecular circuits

NASA Astrophysics Data System (ADS)

Engelen, Wouter; Meijer, Lenny H. H.; Somers, Bram; de Greef, Tom F. A.; Merkx, Maarten

2017-02-01

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

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

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation.

PubMed

Al Sharif, Merilin; Tsakovska, Ivanka; Pajeva, Ilza; Alov, Petko; Fioravanzo, Elena; Bassan, Arianna; Kovarich, Simona; Yang, Chihae; Mostrag-Szlichtyng, Aleksandra; Vitcheva, Vessela; Worth, Andrew P; Richarz, Andrea-N; Cronin, Mark T D

2017-12-01

The aim of this paper was to provide a proof of concept demonstrating that molecular modelling methodologies can be employed as a part of an integrated strategy to support toxicity prediction consistent with the mode of action/adverse outcome pathway (MoA/AOP) framework. To illustrate the role of molecular modelling in predictive toxicology, a case study was undertaken in which molecular modelling methodologies were employed to predict the activation of the peroxisome proliferator-activated nuclear receptor γ (PPARγ) as a potential molecular initiating event (MIE) for liver steatosis. A stepwise procedure combining different in silico approaches (virtual screening based on docking and pharmacophore filtering, and molecular field analysis) was developed to screen for PPARγ full agonists and to predict their transactivation activity (EC 50 ). The performance metrics of the classification model to predict PPARγ full agonists were balanced accuracy=81%, sensitivity=85% and specificity=76%. The 3D QSAR model developed to predict EC 50 of PPARγ full agonists had the following statistical parameters: q 2 cv =0.610, N opt =7, SEP cv =0.505, r 2 pr =0.552. To support the linkage of PPARγ agonism predictions to prosteatotic potential, molecular modelling was combined with independently performed mechanistic mining of available in vivo toxicity data followed by ToxPrint chemotypes analysis. The approaches investigated demonstrated a potential to predict the MIE, to facilitate the process of MoA/AOP elaboration, to increase the scientific confidence in AOP, and to become a basis for 3D chemotype development. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Molecular scale modeling of polymer imprint nanolithography.

PubMed

Chandross, Michael; Grest, Gary S

2012-01-10

We present the results of large-scale molecular dynamics simulations of two different nanolithographic processes, step-flash imprint lithography (SFIL), and hot embossing. We insert rigid stamps into an entangled bead-spring polymer melt above the glass transition temperature. After equilibration, the polymer is then hardened in one of two ways, depending on the specific process to be modeled. For SFIL, we cross-link the polymer chains by introducing bonds between neighboring beads. To model hot embossing, we instead cool the melt to below the glass transition temperature. We then study the ability of these methods to retain features by removing the stamps, both with a zero-stress removal process in which stamp atoms are instantaneously deleted from the system as well as a more physical process in which the stamp is pulled from the hardened polymer at fixed velocity. We find that it is necessary to coat the stamp with an antifriction coating to achieve clean removal of the stamp. We further find that a high density of cross-links is necessary for good feature retention in the SFIL process. The hot embossing process results in good feature retention at all length scales studied as long as coated, low surface energy stamps are used.

Predicting Biological Information Flow in a Model Oxygen Minimum Zone

NASA Astrophysics Data System (ADS)

Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

2016-02-01

Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

Application of computational methods to the design and characterisation of porous molecular materials.

PubMed

Evans, Jack D; Jelfs, Kim E; Day, Graeme M; Doonan, Christian J

2017-06-06

Composed from discrete units, porous molecular materials (PMMs) possess unique properties not observed for conventional, extended, solids, such as solution processibility and permanent porosity in the liquid phase. However, identifying the origin of porosity is not a trivial process, especially for amorphous or liquid phases. Furthermore, the assembly of molecular components is typically governed by a subtle balance of weak intermolecular forces that makes structure prediction challenging. Accordingly, in this review we canvass the crucial role of molecular simulations in the characterisation and design of PMMs. We will outline strategies for modelling porosity in crystalline, amorphous and liquid phases and also describe the state-of-the-art methods used for high-throughput screening of large datasets to identify materials that exhibit novel performance characteristics.

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.

Using Osteoclast Differentiation as a Model for Gene Discovery in an Undergraduate Cell Biology Laboratory

ERIC Educational Resources Information Center

Birnbaum, Mark J.; Picco, Jenna; Clements, Meghan; Witwicka, Hanna; Yang, Meiheng; Hoey, Margaret T.; Odgren, Paul R.

2010-01-01

A key goal of molecular/cell biology/biotechnology is to identify essential genes in virtually every physiological process to uncover basic mechanisms of cell function and to establish potential targets of drug therapy combating human disease. This article describes a semester-long, project-oriented molecular/cellular/biotechnology laboratory…

On the Overdispersed Molecular Clock

PubMed Central

Takahata, Naoyuki

1987-01-01

Rates of molecular evolution at some loci are more irregular than described by simple Poisson processes. Three situations under which molecular evolution would not follow simple Poisson processes are reevaluated from the viewpoint of the neutrality hypothesis: (i) concomitant or multiple substitutions in a gene, (ii) fluctuating substitution rates in time caused by coupled effects of deleterious mutations and bottlenecks, and (iii) changes in the degree of selective constraints against a gene (neutral space) caused by successive substitutions. The common underlying assumption that these causes are lineage nonspecific excludes the case where mutation rates themselves change systematically among lineages or taxonomic groups, and severely limits the extent of variation in the number of substitutions among lineages. Even under this stringent condition, however, the third hypothesis, the fluctuating neutral space model, can generate fairly large variation. This is described by a time-dependent renewal process, which does not exhibit any episodic nature of molecular evolution. It is argued that the observed elevated variances in the number of nucleotide or amino acid substitutions do not immediately call for positive Darwinian selection in molecular evolution. PMID:3596230

Cryptic diversity in a fig wasp community-morphologically differentiated species are sympatric but cryptic species are parapatric.

PubMed

Darwell, C T; Cook, J M

2017-02-01

A key debate in ecology centres on the relative importance of niche and neutral processes in determining patterns of community assembly with particular focus on whether ecologically similar species with similar functional traits are able to coexist. Meanwhile, molecular studies are increasingly revealing morphologically indistinguishable cryptic species with presumably similar ecological roles. Determining the geographic distribution of such cryptic species provides opportunities to contrast predictions of niche vs. neutral models. Discovery of sympatric cryptic species increases alpha diversity and supports neutral models, while documentation of allopatric/parapatric cryptic species increases beta diversity and supports niche models. We tested these predictions using morphological and molecular data, coupled with environmental niche modelling analyses, of a fig wasp community along its 2700-km latitudinal range. Molecular methods increased previous species diversity estimates from eight to eleven species, revealing morphologically cryptic species in each of the four wasp genera studied. Congeneric species pairs that were differentiated by a key morphological functional trait (ovipositor length) coexisted sympatrically over large areas. In contrast, morphologically similar species, with similar ovipositor lengths, typically showed parapatric ranges with very little overlap. Despite parapatric ranges, environmental niche models of cryptic congeneric pairs indicate large regions of potential sympatry, suggesting that competitive processes are important in determining the distributions of ecologically similar species. Niche processes appear to structure this insect community, and cryptic diversity may typically contribute mostly to beta rather than alpha diversity. © 2016 John Wiley & Sons Ltd.

Complete protein-protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling

NASA Astrophysics Data System (ADS)

Plattner, Nuria; Doerr, Stefan; de Fabritiis, Gianni; Noé, Frank

2017-10-01

Protein-protein association is fundamental to many life processes. However, a microscopic model describing the structures and kinetics during association and dissociation is lacking on account of the long lifetimes of associated states, which have prevented efficient sampling by direct molecular dynamics (MD) simulations. Here we demonstrate protein-protein association and dissociation in atomistic resolution for the ribonuclease barnase and its inhibitor barstar by combining adaptive high-throughput MD simulations and hidden Markov modelling. The model reveals experimentally consistent intermediate structures, energetics and kinetics on timescales from microseconds to hours. A variety of flexibly attached intermediates and misbound states funnel down to a transition state and a native basin consisting of the loosely bound near-native state and the tightly bound crystallographic state. These results offer a deeper level of insight into macromolecular recognition and our approach opens the door for understanding and manipulating a wide range of macromolecular association processes.

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 of Supercritical Fluids through Single-Layer Nanoporous Solids: Theory and Molecular Simulations.

PubMed

Oulebsir, Fouad; Vermorel, Romain; Galliero, Guillaume

2018-01-16

With the advent of graphene material, membranes based on single-layer nanoporous solids appear as promising devices for fluid separation, be it liquid or gaseous mixtures. The design of such architectured porous materials would greatly benefit from accurate models that can predict their transport and separation properties. More specifically, there is no universal understanding of how parameters such as temperature, fluid loading conditions, or the ratio of the pore size to the fluid molecular diameter influence the permeation process. In this study, we address the problem of pure supercritical fluids diffusing through simplified models of single-layer porous materials. Basically, we investigate a toy model that consists of a single-layer lattice of Lennard-Jones interaction sites with a slit gap of controllable width. We performed extensive equilibrium and biased molecular dynamics simulations to document the physical mechanisms involved at the molecular scale. We propose a general constitutive equation for the diffusional transport coefficient derived from classical statistical mechanics and kinetic theory, which can be further simplified in the ideal gas limit. This transport coefficient relates the molecular flux to the fluid density jump across the single-layer membrane. It is found to be proportional to the accessible surface porosity of the single-layer porous solid and to a thermodynamic factor accounting for the inhomogeneity of the fluid close to the pore entrance. Both quantities directly depend on the potential of mean force that results from molecular interactions between solid and fluid atoms. Comparisons with the simulations data show that the kinetic model captures how narrowing the pore size below the fluid molecular diameter lowers dramatically the value of the transport coefficient. Furthermore, we demonstrate that our general constitutive equation allows for a consistent interpretation of the intricate effects of temperature and fluid loading conditions on the permeation process.

Phosphodiester models for cleavage of nucleic acids

PubMed Central

2018-01-01

Nucleic acids that store and transfer biological information are polymeric diesters of phosphoric acid. Cleavage of the phosphodiester linkages by protein enzymes, nucleases, is one of the underlying biological processes. The remarkable catalytic efficiency of nucleases, together with the ability of ribonucleic acids to serve sometimes as nucleases, has made the cleavage of phosphodiesters a subject of intensive mechanistic studies. In addition to studies of nucleases by pH-rate dependency, X-ray crystallography, amino acid/nucleotide substitution and computational approaches, experimental and theoretical studies with small molecular model compounds still play a role. With small molecules, the importance of various elementary processes, such as proton transfer and metal ion binding, for stabilization of transition states may be elucidated and systematic variation of the basicity of the entering or departing nucleophile enables determination of the position of the transition state on the reaction coordinate. Such data is important on analyzing enzyme mechanisms based on synergistic participation of several catalytic entities. Many nucleases are metalloenzymes and small molecular models offer an excellent tool to construct models for their catalytic centers. The present review tends to be an up to date summary of what has been achieved by mechanistic studies with small molecular phosphodiesters. PMID:29719577

Evaluating the solution from MrBUMP and BALBES

PubMed Central

Keegan, Ronan M.; Long, Fei; Fazio, Vincent J.; Winn, Martyn D.; Murshudov, Garib N.; Vagin, Alexei A.

2011-01-01

Molecular replacement is one of the key methods used to solve the problem of determining the phases of structure factors in protein structure solution from X-ray image diffraction data. Its success rate has been steadily improving with the development of improved software methods and the increasing number of structures available in the PDB for use as search models. Despite this, in cases where there is low sequence identity between the target-structure sequence and that of its set of possible homologues it can be a difficult and time-consuming chore to isolate and prepare the best search model for molecular replacement. MrBUMP and BALBES are two recent developments from CCP4 that have been designed to automate and speed up the process of determining and preparing the best search models and putting them through molecular replacement. Their intention is to provide the user with a broad set of results using many search models and to highlight the best of these for further processing. An overview of both programs is presented along with a description of how best to use them, citing case studies and the results of large-scale testing of the software. PMID:21460449

Influence of macromolecular architecture on necking in polymer extrusion film casting process

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

Pol, Harshawardhan; Banik, Sourya; Azad, Lal Busher

2015-05-22

Extrusion film casting (EFC) is an important polymer processing technique that is used to produce several thousand tons of polymer films/coatings on an industrial scale. In this research, we are interested in understanding quantitatively how macromolecular chain architecture (for example long chain branching (LCB) or molecular weight distribution (MWD or PDI)) influences the necking and thickness distribution of extrusion cast films. We have used different polymer resins of linear and branched molecular architecture to produce extrusion cast films under controlled experimental conditions. The necking profiles of the films were imaged and the velocity profiles during EFC were monitored using particlemore » tracking velocimetry (PTV) technique. Additionally, the temperature profiles were captured using an IR thermography and thickness profiles were calculated. The experimental results are compared with predictions of one-dimensional flow model of Silagy et al{sup 1} wherein the polymer resin rheology is modeled using molecular constitutive equations such as the Rolie-Poly (RP) and extended Pom Pom (XPP). We demonstrate that the 1-D flow model containing the molecular constitutive equations provides new insights into the role of macromolecular chain architecture on film necking.{sup 1}D. Silagy, Y. Demay, and J-F. Agassant, Polym. Eng. Sci., 36, 2614 (1996)« less

Simulations of molecular self-assembled monolayers on surfaces: packing structures, formation processes and functions tuned by intermolecular and interfacial interactions.

PubMed

Wen, Jin; Li, Wei; Chen, Shuang; Ma, Jing

2016-08-17

Surfaces modified with a functional molecular monolayer are essential for the fabrication of nano-scale electronics or machines with novel physical, chemical, and/or biological properties. Theoretical simulation based on advanced quantum chemical and classical models is at present a necessary tool in the development, design, and understanding of the interfacial nanostructure. The nanoscale surface morphology, growth processes, and functions are controlled by not only the electronic structures (molecular energy levels, dipole moments, polarizabilities, and optical properties) of building units but also the subtle balance between intermolecular and interfacial interactions. The switchable surfaces are also constructed by introducing stimuli-responsive units like azobenzene derivatives. To bridge the gap between experiments and theoretical models, opportunities and challenges for future development of modelling of ferroelectricity, entropy, and chemical reactions of surface-supported monolayers are also addressed. Theoretical simulations will allow us to obtain important and detailed information about the structure and dynamics of monolayer modified interfaces, which will guide the rational design and optimization of dynamic interfaces to meet challenges of controlling optical, electrical, and biological functions.

Protein folding simulations: from coarse-grained model to all-atom model.

PubMed

Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL, the development of discrete MD and its application in studying the alpha-beta conformational conversion and oligomer assembling process, and the modeling of metal ion involved protein folding. (c) 2009 IUBMB.

The effect of processing on the surface physical stability of amorphous solid dispersions.

PubMed

Yang, Ziyi; Nollenberger, Kathrin; Albers, Jessica; Moffat, Jonathan; Craig, Duncan; Qi, Sheng

2014-11-01

The focus of this study was to investigate the effect of processing on the surface crystallization of amorphous molecular dispersions and gain insight into the mechanisms underpinning this effect. The model systems, amorphous molecular dispersions of felodipine-EUDRAGIT® E PO, were processed both using spin coating (an ultra-fast solvent evaporation based method) and hot melt extrusion (HME) (a melting based method). Amorphous solid dispersions with drug loadings of 10-90% (w/w) were obtained by both processing methods. Samples were stored under 75% RH/room temperatures for up to 10months. Surface crystallization was observed shortly after preparation for the HME samples with high drug loadings (50-90%). Surface crystallization was characterized by powder X-ray diffraction (PXRD), ATR-FTIR spectroscopy and imaging techniques (SEM, AFM and localized thermal analysis). Spin coated molecular dispersions showed significantly higher surface physical stability than hot melt extruded samples. For both systems, the progress of the surface crystal growth followed zero order kinetics on aging. Drug enrichment at the surfaces of HME samples on aging was observed, which may contribute to surface crystallization of amorphous molecular dispersions. In conclusion it was found the amorphous molecular dispersions prepared by spin coating had a significantly higher surface physical stability than the corresponding HME samples, which may be attributed to the increased process-related apparent drug-polymer solubility and reduced molecular mobility due to the quenching effect caused by the rapid solvent evaporation in spin coating. Copyright © 2014 Elsevier B.V. All rights reserved.

Proprotein convertases in high-density lipoprotein metabolism.

PubMed

Choi, Seungbum; Korstanje, Ron

2013-09-18

The proprotein convertase subtilisin/kexins (PCSKs) are a serine endopeptidase family. PCSK members cleave amino acid residues and modulate the activity of precursor proteins. Evidence from patients and animal models carrying genetic alterations in PCSK members show that PCSK members are involved in various metabolic processes. These studies further revealed the molecular mechanism by which genetic alteration of some PCSK members impairs normal molecular and physiological functions, which in turn lead to cardiovascular disease. High-density lipoprotein (HDL) is anti-atherogenic as it removes excessive amount of cholesterol from blood and peripheral tissues. Several PCSK members are involved in HDL metabolism. PCSK3, PCSK5, and PCSK6 process two triglyceride lipase family members, endothelial lipase and lipoprotein lipase, which are important for HDL remodeling. Recent studies in our lab found evidence that PCSK1 and PCSK9 are also involved in HDL metabolism. A mouse model carrying an amino acid substitution in PCSK1 showed an increase in serum apolipoprotein A1 (APOA1) level. Another mouse model lacking PCSK9 showed a decrease in APOE-containing HDL. In this review, we summarize the role of the five PCSK members in lipid, glucose, and bile acid (BA) metabolism, each of which can influence HDL metabolism. We propose an integrative model in which PCSK members regulate HDL metabolism through various molecular mechanisms and metabolic processes and genetic variation in some PCSK members may affect the efficiency of reverse cholesterol transport. PCSK members are considered as attractive therapeutic targets. A greater understanding of the molecular and physiological functions of PCSK members will improve therapeutic strategies and drug efficacy for cardiovascular disease where PCSK members play critical role, with fewer adverse effects.

Proprotein convertases in high-density lipoprotein metabolism

PubMed Central

2013-01-01

The proprotein convertase subtilisin/kexins (PCSKs) are a serine endopeptidase family. PCSK members cleave amino acid residues and modulate the activity of precursor proteins. Evidence from patients and animal models carrying genetic alterations in PCSK members show that PCSK members are involved in various metabolic processes. These studies further revealed the molecular mechanism by which genetic alteration of some PCSK members impairs normal molecular and physiological functions, which in turn lead to cardiovascular disease. High-density lipoprotein (HDL) is anti-atherogenic as it removes excessive amount of cholesterol from blood and peripheral tissues. Several PCSK members are involved in HDL metabolism. PCSK3, PCSK5, and PCSK6 process two triglyceride lipase family members, endothelial lipase and lipoprotein lipase, which are important for HDL remodeling. Recent studies in our lab found evidence that PCSK1 and PCSK9 are also involved in HDL metabolism. A mouse model carrying an amino acid substitution in PCSK1 showed an increase in serum apolipoprotein A1 (APOA1) level. Another mouse model lacking PCSK9 showed a decrease in APOE-containing HDL. In this review, we summarize the role of the five PCSK members in lipid, glucose, and bile acid (BA) metabolism, each of which can influence HDL metabolism. We propose an integrative model in which PCSK members regulate HDL metabolism through various molecular mechanisms and metabolic processes and genetic variation in some PCSK members may affect the efficiency of reverse cholesterol transport. PCSK members are considered as attractive therapeutic targets. A greater understanding of the molecular and physiological functions of PCSK members will improve therapeutic strategies and drug efficacy for cardiovascular disease where PCSK members play critical role, with fewer adverse effects. PMID:24252756

Lighting the dark molecular gas and a Bok globule

NASA Astrophysics Data System (ADS)

Togi, Aditya G.

Stars are the building blocks of galaxies. The gas present in galaxies is the primary fuel for star formation. Galaxy evolution depends on the amount of gas present in the interstellar medium (ISM). Stars are born mainly from molecular gas in the GMCs. Robust knowledge of the molecular hydrogen H2 gas distribution is necessary to understand star formation in galaxies. Since H2 is not readily observable in the cold interstellar medium (ISM), the molecular gas content has traditionally been inferred using indirect tracers like carbon-monoxide (CO), dust emission, gamma ray interactions, and star formation efficiency. Physical processes resulting in enhancement and reduction of these indirect tracers can result in misleading estimates of molecular gas masses. My dissertation work is based on devising a new temperature power law distribution model for H2, a direct tracer, to calculate the total molecular gas mass in galaxies. The model parameters are estimated using mid infrared (MIR) H2 rotational line fluxes obtained from IRS-Spitzer (Infrared Spectrograph-Spitzer) instrument and the model is extrapolated to a suitable lower temperature to recover the total molecular gas mass. The power law model is able to recover the dark molecular gas, undetected by CO, in galaxies at metallicity as low as one-tenth of our Milky Way value. I have applied the power law model in U/LIRGs and shocks of Stephan's Quintet to understand molecular gas properties, where shocks play an important role in exciting H2. Comparing the molecular gas content derived through our power law model can be useful in studying the application of our model in mergers. The parameters derived by our model is useful in understanding variation in molecular gas properties in shock regions of Stephan's Quintet. Low mass stars are formed in small isolated dense cores known as Bok globules. Multiple star formation events are seen in a Bok globule. In my thesis I also studied a Bok globule, B207, and determined the physical properties and future evolutionary stage of the cloud. My thesis spans studying ISM properties in galaxies from kpc to sub-pc scales. Using the power law model in the coming era of James Webb Space Telescope (JWST) with the high sensitivity MIR Instrument (MIRI) spectrograph we will be able to understand the properties of molecular gas at low and high redshifts.

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.

Kinetic modeling of microscopic processes during electron cyclotron resonance microwave plasma-assisted molecular beam epitaxial growth of GaN/GaAs-based heterostructures

NASA Astrophysics Data System (ADS)

Bandić, Z. Z.; Hauenstein, R. J.; O'Steen, M. L.; McGill, T. C.

1996-03-01

Microscopic growth processes associated with GaN/GaAs molecular beam epitaxy (MBE) are examined through the introduction of a first-order kinetic model. The model is applied to the electron cyclotron resonance microwave plasma-assisted MBE (ECR-MBE) growth of a set of δ-GaNyAs1-y/GaAs strained-layer superlattices that consist of nitrided GaAs monolayers separated by GaAs spacers, and that exhibit a strong decrease of y with increasing T over the range 540-580 °C. This y(T) dependence is quantitatively explained in terms of microscopic anion exchange, and thermally activated N surface-desorption and surface-segregation processes. N surface segregation is found to be significant during GaAs overgrowth of GaNyAs1-y layers at typical GaN ECR-MBE growth temperatures, with an estimated activation energy Es˜0.9 eV. The observed y(T) dependence is shown to result from a combination of N surface segregation/desorption processes.

The affects on Titan atmospheric modeling by variable molecular reaction rates

NASA Astrophysics Data System (ADS)

Hamel, Mark D.

The main effort of this thesis is to study the production and loss of molecular ions in the ionosphere of Saturn's largest moon Titan. Titan's atmosphere is subject to complex photochemical processes that can lead to the production of higher order hydrocarbons and nitriles. Ion-molecule chemistry plays an important role in this process but remains poorly understood. In particular, current models that simulate the photochemistry of Titan's atmosphere overpredict the abundance of the ionosphere's main ions suggesting a flaw in the modeling process. The objective of this thesis is to determine which reactions are most important for production and loss of the two primary ions, C2H5+ and HCNH+, and what is the impact of uncertainty in the reaction rates on the production and loss of these ions. In reviewing the literature, there is a contention about what reactions are really necessary to illuminate what is occurring in the atmosphere. Approximately seven hundred reactions are included in the model used in this discussion (INT16). This paper studies what reactions are fundamental to the atmospheric processes in Titan's upper atmosphere, and also to the reactions that occur in the lower bounds of the ionosphere which are used to set a baseline molecular density for all species, and reflects what is expected at those altitudes on Titan. This research was conducted through evaluating reaction rates and cross sections available in the scientific literature and through conducting model simulations of the photochemistry in Titan's atmosphere under a range of conditions constrained by the literature source. The objective of this study is to determine the dependence of ion densities of C2H5+ and HCNH+ on the uncertainty in the reaction rates that involve these two ions in Titan's atmosphere.

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic 'two component system' protein network.

PubMed

Di Paola, Vieri; Marijuán, Pedro C; Lahoz-Beltra, Rafael

2004-01-01

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

Probing amyloid protein aggregation with optical superresolution methods: from the test tube to models of disease

PubMed Central

Kaminski, Clemens F.; Kaminski Schierle, Gabriele S.

2016-01-01

Abstract. The misfolding and self-assembly of intrinsically disordered proteins into insoluble amyloid structures are central to many neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Optical imaging of this self-assembly process in vitro and in cells is revolutionizing our understanding of the molecular mechanisms behind these devastating conditions. In contrast to conventional biophysical methods, optical imaging and, in particular, optical superresolution imaging, permits the dynamic investigation of the molecular self-assembly process in vitro and in cells, at molecular-level resolution. In this article, current state-of-the-art imaging methods are reviewed and discussed in the context of research into neurodegeneration. PMID:27413767

Conversion of laser energy to gas kinetic energy

NASA Technical Reports Server (NTRS)

Caledonia, G. E.

1975-01-01

Techniques for the gas phase absorption of laser radiation for conversion to gas kinetic energy are discussed. Absorption by inverse Bremsstrahlung, in which laser energy is converted at a gas kinetic rate in a spectrally continuous process, is briefly described, and absorption by molecular vibrational rotation bands is discussed at length. High pressure absorption is proposed as a means of minimizing gas bleaching and dissociation, the major disadvantages of the molecular absorption process. A band model is presented for predicting the molecular absorption spectra in the high pressure absorption region and is applied to the CO molecule. Use of a rare gas seeded with Fe(CO)5 for converting vibrational modes to translation modes is described.

Life-Game, with Glass Beads and Molecules, on the Principles of the Origin of Life

ERIC Educational Resources Information Center

Eigen, Manfred; Haglund, Herman

1976-01-01

Discusses a theoretical model that uses a game as a base for studying processes of a stochastic nature, which involve chemical reactions, molecular systems, biological processes, cells, or people in a population. (MLH)

Theoretical study of (e, 2e) process of atomic and molecular targets*

NASA Astrophysics Data System (ADS)

Houamer, Salim; Chinoune, Mehdi; Cappello, Claude Dal

2017-01-01

Triple differential ionization cross sections (TDCSs) by electron impact are calculated for some atomic and molecular targets by using several models where Post Collisional Interaction (PCI) is taken in account. We also investigate the effect of the short range potential and describe the ejected electron either by a Coulomb wave or by a distorted wave. Significant differences are observed between these models. A better agreement with experimental data is achieved when the short range potential and distortion effects are included.

The Fruit Fly Drosophila melanogaster as a Model for Aging Research.

PubMed

Brandt, Annely; Vilcinskas, Andreas

2013-01-01

: Average human life expectancy is increasing and so is the impact on society of aging and age-related diseases. Here we highlight recent advances in the diverse and multidisciplinary field of aging research, focusing on the fruit fly Drosophila melanogaster, an excellent model system in which to dissect the genetic and molecular basis of the aging processes. The conservation of human disease genes in D. melanogaster allows the functional analysis of orthologues implicated in human aging and age-related diseases. D. melanogaster models have been developed for a variety of age-related processes and disorders, including stem cell decline, Alzheimer's disease, and cardiovascular deterioration. Understanding the detailed molecular events involved in normal aging and age-related diseases could facilitate the development of strategies and treatments that reduce their impact, thus improving human health and increasing longevity.

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

Assembly/Disassembly of DNA-Au Nanoparticles: A Strategy of Intervention

DOE PAGES

Lim, I-Im S.; Wang, Lingyan; Chandrachud, Uma; ...

2008-01-01

This report describes the viability of a strategy for manipulating the assembly/disassembly processes of DNA-Au nanoparticles by molecular intervention. Using the temperature-induced assembly and disassembly processes of DNAs and gold nanoparticles as a model system, the introduction of a molecular recognition probe is demonstrated to lead to the intervention of the assembly/disassembly processes depending on its specific biorecognition. This process can be detected by monitoring the change in the optical properties of gold nanoparticles and their DNA assemblies. Implications of the preliminary results to exploration of the resulting nanostructures for fine-tuning of the interfacial reactivities in DNA-based bioassays and biomaterialmore » engineering are also discussed.« less

Growth of beta-MnO2 Films on TiO2(110) by Oxygen-Plasma-Assisted Molecular Beam Epitaxy

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

Chambers, Scott A.; Liang, Yong

Discusses the essential need to understand the heterogeneous chemistry of mineral surfaces at a molecular level for accurate modeling of surface complexion processes in natural environments. Describes the first MBE growth and characterization of ultrathin films of B-MnO2 on TiO2 (110).

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

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

A Synergistic Approach to Interpreting Planetary Atmospheres

NASA Astrophysics Data System (ADS)

Batalha, Natasha E.

We will soon have the technological capability to measure the atmospheric composition of temperate Earth-sized planets orbiting nearby stars. Interpreting these atmospheric signals poses a new challenge to planetary science. In contrast to jovian-like atmospheres, whose bulk compositions consist of hydrogen and helium, terrestrial planet atmospheres are likely comprised of high mean molecular weight secondary atmospheres, which have gone through a high degree of evolution. For example, present-day Mars has a frozen surface with a thin tenuous atmosphere, but 4 billion years ago it may have been warmed by a thick greenhouse atmosphere. Several processes contribute to a planet's atmospheric evolution: stellar evolution, geological processes, atmospheric escape, biology, etc. Each of these individual processes affects the planetary system as a whole and therefore they all must be considered in the modeling of terrestrial planets. In order to demonstrate the intricacies in modeling terrestrial planets, I use early Mars as a case study. I leverage a combination of one-dimensional climate, photochemical and energy balance models in order to create one self-consistent model that closely matches currently available climate data. One-dimensional models can address several processes: the influence of greenhouse gases on heating, the effect of the planet's geological processes (i.e. volcanoes and the carbonatesilicate cycle) on the atmosphere, the effect of rainfall on atmospheric composition and the stellar irradiance. After demonstrating the number of assumptions required to build a model, I look towards what exactly we can learn from remote observations of temperate Earths and Super Earths. However, unlike in-situ observations from our own solar system, remote sensing techniques need to be developed and understood in order to accurately characterize exo-atmospheres. I describe the models used to create synthetic transit transmission observations, which includes models of transit spectroscopy and instrumental noise. Using these, I lay the framework for an information content-based approach to optimize our observations and maximize the retrievable information from exoatmospheres. First I test the method on observing strategies of the well-studied, low-mean-molecular weight atmospheres of warm-Neptunes and hot Jupiters. Upon verifying the methodology, I finally address optimal observing strategies for temperate, high-mean-molecular weight atmospheres (Earths/super-Earths). iv.

2D- and 3D-quantitative structure-activity relationship studies for a series of phenazine N,N'-dioxide as antitumour agents.

PubMed

Cunha, Jonathan Da; Lavaggi, María Laura; Abasolo, María Inés; Cerecetto, Hugo; González, Mercedes

2011-12-01

Hypoxic regions of tumours are associated with increased resistance to radiation and chemotherapy. Nevertheless, hypoxia has been used as a tool for specific activation of some antitumour prodrugs, named bioreductive agents. Phenazine dioxides are an example of such bioreductive prodrugs. Our 2D-quantitative structure activity relationship studies established that phenazine dioxides electronic and lipophilic descriptors are related to survival fraction in oxia or in hypoxia. Additionally, statistically significant models, derived by partial least squares, were obtained between survival fraction in oxia and comparative molecular field analysis standard model (r² = 0.755, q² = 0.505 and F = 26.70) or comparative molecular similarity indices analysis-combined steric and electrostatic fields (r² = 0.757, q² = 0.527 and F = 14.93), and survival fraction in hypoxia and comparative molecular field analysis standard model (r² = 0.736, q² = 0.521 and F = 18.63) or comparative molecular similarity indices analysis-hydrogen bond acceptor field (r² = 0.858, q² = 0.737 and F = 27.19). Categorical classification was used for the biological parameter selective cytotoxicity emerging also good models, derived by soft independent modelling of class analogy, with both comparative molecular field analysis standard model (96% of overall classification accuracy) and comparative molecular similarity indices analysis-steric field (92% of overall classification accuracy). 2D- and 3D-quantitative structure-activity relationships models provided important insights into the chemical and structural basis involved in the molecular recognition process of these phenazines as bioreductive agents and should be useful for the design of new structurally related analogues with improved potency. © 2011 John Wiley & Sons A/S.

A visual metaphor describing neural dynamics in schizophrenia.

PubMed

van Beveren, Nico J M; de Haan, Lieuwe

2008-07-09

In many scientific disciplines the use of a metaphor as an heuristic aid is not uncommon. A well known example in somatic medicine is the 'defense army metaphor' used to characterize the immune system. In fact, probably a large part of the everyday work of doctors consists of 'translating' scientific and clinical information (i.e. causes of disease, percentage of success versus risk of side-effects) into information tailored to the needs and capacities of the individual patient. The ability to do so in an effective way is at least partly what makes a clinician a good communicator. Schizophrenia is a severe psychiatric disorder which affects approximately 1% of the population. Over the last two decades a large amount of molecular-biological, imaging and genetic data have been accumulated regarding the biological underpinnings of schizophrenia. However, it remains difficult to understand how the characteristic symptoms of schizophrenia such as hallucinations and delusions are related to disturbances on the molecular-biological level. In general, psychiatry seems to lack a conceptual framework with sufficient explanatory power to link the mental- and molecular-biological domains. Here, we present an essay-like study in which we propose to use visualized concepts stemming from the theory on dynamical complex systems as a 'visual metaphor' to bridge the mental- and molecular-biological domains in schizophrenia. We first describe a computer model of neural information processing; we show how the information processing in this model can be visualized, using concepts from the theory on complex systems. We then describe two computer models which have been used to investigate the primary theory on schizophrenia, the neurodevelopmental model, and show how disturbed information processing in these two computer models can be presented in terms of the visual metaphor previously described. Finally, we describe the effects of dopamine neuromodulation, of which disturbances have been frequently described in schizophrenia, in terms of the same visualized metaphor. The conceptual framework and metaphor described offers a heuristic tool to understand the relationship between the mental- and molecular-biological domains in an intuitive way. The concepts we present may serve to facilitate communication between researchers, clinicians and patients.

Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models.

PubMed

Le Muzic, M; Mindek, P; Sorger, J; Autin, L; Goodsell, D; Viola, I

2016-06-01

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine-tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer-based approach for visibility specification was valuable and effective for both, scientific and educational purposes.

Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models

PubMed Central

Le Muzic, M.; Mindek, P.; Sorger, J.; Autin, L.; Goodsell, D.; Viola, I.

2017-01-01

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine-tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer-based approach for visibility specification was valuable and effective for both, scientific and educational purposes. PMID:28344374

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

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: Multi-center molecular Ornstein-Zernike self-consistent field approach

NASA Astrophysics Data System (ADS)

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-01

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl- + CH3Cl → ClCH3 + Cl-) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: multi-center molecular Ornstein-Zernike self-consistent field approach.

PubMed

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-07

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl(-) + CH3Cl → ClCH3 + Cl(-)) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

Star formation in a hierarchical model for Cloud Complexes

NASA Astrophysics Data System (ADS)

Sanchez, N.; Parravano, A.

The effects of the external and initial conditions on the star formation processes in Molecular Cloud Complexes are examined in the context of a schematic model. The model considers a hierarchical system with five predefined phases: warm gas, neutral gas, low density molecular gas, high density molecular gas and protostars. The model follows the mass evolution of each substructure by computing its mass exchange with their parent and children. The parent-child mass exchange depends on the radiation density at the interphase, which is produced by the radiation coming from the stars that form at the end of the hierarchical structure, and by the external radiation field. The system is chaotic in the sense that its temporal evolution is very sensitive to small changes in the initial or external conditions. However, global features such as the star formation efficience and the Initial Mass Function are less affected by those variations.

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.

Bioethanol production optimization: a thermodynamic analysis.

PubMed

Alvarez, Víctor H; Rivera, Elmer Ccopa; Costa, Aline C; Filho, Rubens Maciel; Wolf Maciel, Maria Regina; Aznar, Martín

2008-03-01

In this work, the phase equilibrium of binary mixtures for bioethanol production by continuous extractive process was studied. The process is composed of four interlinked units: fermentor, centrifuge, cell treatment unit, and flash vessel (ethanol-congener separation unit). A proposal for modeling the vapor-liquid equilibrium in binary mixtures found in the flash vessel has been considered. This approach uses the Predictive Soave-Redlich-Kwong equation of state, with original and modified molecular parameters. The congeners considered were acetic acid, acetaldehyde, furfural, methanol, and 1-pentanol. The results show that the introduction of new molecular parameters r and q in the UNIFAC model gives more accurate predictions for the concentration of the congener in the gas phase for binary and ternary systems.

Isotope Fractionation in the Interstellar Medium

NASA Technical Reports Server (NTRS)

Charnley, Steven

2011-01-01

Anomalously fractionated isotopic material is found in many primitive Solar System objects, such as meteorites and comets. It is thought, in some cases, to trace interstellar matter that was incorporated into the Solar Nebula without undergoing significant processing. We will present the results of models of the nitrogen, oxygen, and carbon fractionation chemistry in dense molecular clouds, particularly in cores where substantial freeze-out of molecules on to dust has occurred. The range of fractionation ratios expected in different interstellar molecules will be discussed and compared to the ratios measured in molecular clouds, comets and meteoritic material. These models make several predictions that can be tested in the near future by molecular line observations, particularly with ALMA.

Classical molecular dynamics simulation of electronically non-adiabatic processes.

PubMed

Miller, William H; Cotton, Stephen J

2016-12-22

Both classical and quantum mechanics (as well as hybrids thereof, i.e., semiclassical approaches) find widespread use in simulating dynamical processes in molecular systems. For large chemical systems, however, which involve potential energy surfaces (PES) of general/arbitrary form, it is usually the case that only classical molecular dynamics (MD) approaches are feasible, and their use is thus ubiquitous nowadays, at least for chemical processes involving dynamics on a single PES (i.e., within a single Born-Oppenheimer electronic state). This paper reviews recent developments in an approach which extends standard classical MD methods to the treatment of electronically non-adiabatic processes, i.e., those that involve transitions between different electronic states. The approach treats nuclear and electronic degrees of freedom (DOF) equivalently (i.e., by classical mechanics, thereby retaining the simplicity of standard MD), and provides "quantization" of the electronic states through a symmetrical quasi-classical (SQC) windowing model. The approach is seen to be capable of treating extreme regimes of strong and weak coupling between the electronic states, as well as accurately describing coherence effects in the electronic DOF (including the de-coherence of such effects caused by coupling to the nuclear DOF). A survey of recent applications is presented to illustrate the performance of the approach. Also described is a newly developed variation on the original SQC model (found universally superior to the original) and a general extension of the SQC model to obtain the full electronic density matrix (at no additional cost/complexity).

Designing an educative curriculum unit for teaching molecular geometry in high school chemistry

NASA Astrophysics Data System (ADS)

Makarious, Nader N.

Chemistry is a highly abstract discipline that is taught and learned with the aid of various models. Among the most challenging, yet a fundamental topic in general chemistry at the high school level, is molecular geometry. This study focused on developing exemplary educative curriculum materials pertaining to the topic of molecular geometry. The methodology used in this study consisted of several steps. First, a diverse set of models were analyzed to determine to what extent each model serves its purpose in teaching molecular geometry. Second, a number of high school teachers and college chemistry professors were asked to share their experiences on using models in teaching molecular geometry through an online questionnaire. Third, findings from the comparative analysis of models, teachers’ experiences, literature review on models and students’ misconceptions, the curriculum expectations of the Next Generation Science Standards and their emphasis on three-dimensional learning and nature of science (NOS) contributed to the development of the molecular geometry unit. Fourth, the developed unit was reviewed by fellow teachers and doctoral-level science education experts and was revised to further improve its coherence and clarity in support of teaching and learning of the molecular geometry concepts. The produced educative curriculum materials focus on the scientific practice of developing and using models as promoted in the Next Generations Science Standards (NGSS) while also addressing nature of science (NOS) goals. The educative features of the newly developed unit support teachers’ pedagogical knowledge (PK) and pedagogical content knowledge (PCK). The unit includes an overview, teacher’s guide, and eight detailed lesson plans with inquiry oriented modeling activities replete with models and suggestions for teachers, as well as formative and summative assessment tasks. The unit design process serves as a model for redesigning other instructional units in science disciplines in general and chemistry courses in particular.

Ligand diffusion in proteins via enhanced sampling in molecular dynamics.

PubMed

Rydzewski, J; Nowak, W

2017-12-01

Computational simulations in biophysics describe the dynamics and functions of biological macromolecules at the atomic level. Among motions particularly important for life are the transport processes in heterogeneous media. The process of ligand diffusion inside proteins is an example of a complex rare event that can be modeled using molecular dynamics simulations. The study of physical interactions between a ligand and its biological target is of paramount importance for the design of novel drugs and enzymes. Unfortunately, the process of ligand diffusion is difficult to study experimentally. The need for identifying the ligand egress pathways and understanding how ligands migrate through protein tunnels has spurred the development of several methodological approaches to this problem. The complex topology of protein channels and the transient nature of the ligand passage pose difficulties in the modeling of the ligand entry/escape pathways by canonical molecular dynamics simulations. In this review, we report a methodology involving a reconstruction of the ligand diffusion reaction coordinates and the free-energy profiles along these reaction coordinates using enhanced sampling of conformational space. We illustrate the above methods on several ligand-protein systems, including cytochromes and G-protein-coupled receptors. The methods are general and may be adopted to other transport processes in living matter. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular dynamics study of dual-phase microstructure of Titanium and Zirconium metals during the quenching process

NASA Astrophysics Data System (ADS)

Miyazaki, Narumasa; Sato, Kazunori; Shibutani, Yoji

Dual-phase (DP) transformation, which is composed of felite- and/or martensite- multicomponent microstructural phases, is one of the most effective tools to product functional alloys. To obtain this DP structure such as DP steels and other materials, we usually apply thermal processes such as quenching, tempering and annealing. As the transformation dynamics of DP microstructure depends on conditions of temperature, annealing time, and quenching rate, physical properties of materials are able to be tuned by controlling microstructure type, size, their interfaces and so on. In this study, to understand the behavior of DP transformation and to control physical properties of materials by tuning DP microstructures, we analyze the atomistic dynamics of DP transformation during the quenching process and the detail of DP microstructures by using the molecular dynamics simulations. As target metals of DP transformation, we focus on group 4 transition metals, such as Ti and Zr described by EAM interatomic potentials. For Ti and Zr models we perform molecular dynamics simulations by assuming melt-quenching process from 3000 K to 0 K under the isothermal-isobaric ensemble. During the process for each material, we observe liquid to HCP like transition around the melting temperature, and continuously HCP-BCC like transition around martensitic transformation temperature. Furthermore, we clearly distinguish DP microstructure for each quenched model.

Molecular collision processes in the presence of picosecond laser pulses

NASA Technical Reports Server (NTRS)

Lee, H. W.; George, T. F.

1979-01-01

Radiative transitions in molecular collision processes taking place in the presence of picosecond pulses are studied within a semiclassical formalism. An expression for adiabatic potential surfaces in the electronic-field representation is obtained, which directly leads to the evaluation of transition probabilities. Calculations with a Landau-Zener-type model indicate that picosecond pulses can be much more effective in inducing transitions than a single long pulse of the same intensity and the same total energy, if the intensity is sufficiently high that the perturbation treatment is not valid.

Primitive bodies - Molecular abundances in Comet Halley as probes of cometary formation environments

NASA Technical Reports Server (NTRS)

Lunine, Jonathan I.

1989-01-01

The most recent results on abundances of molecules in Halley's comet are examined in the context of various models for the environment in which comets formed. These environments include molecular clouds associated with star-forming regions, the solar nebula, gaseous disks around proto-planets, and combinations of these. Of all constituents in a cometary nucleus, the highly volatile molecules such as methane, ammonia, molecular nitrogen, and carbon monoxide are most sensitive to the final episode of cometary grain formation and incorporation in the comet's nucleus; hence they likely reflect at least some chemical processing in the solar nebula. Proper interpretation requires modeling of a number of physical processes including gas phase chemistry, chemistry on grain surfaces, and fractionation effects resulting from preferential incorporation of certain gases in proto-cometary grains. The abundance of methane in Halley's comet could be a key indicator of where that comet formed, provided the methane abundance on grains in star-forming regions can be observationally constrained.

Diffusion Coefficients from Molecular Dynamics Simulations in Binary and Ternary Mixtures

NASA Astrophysics Data System (ADS)

Liu, Xin; Schnell, Sondre K.; Simon, Jean-Marc; Krüger, Peter; Bedeaux, Dick; Kjelstrup, Signe; Bardow, André; Vlugt, Thijs J. H.

2013-07-01

Multicomponent diffusion in liquids is ubiquitous in (bio)chemical processes. It has gained considerable and increasing interest as it is often the rate limiting step in a process. In this paper, we review methods for calculating diffusion coefficients from molecular simulation and predictive engineering models. The main achievements of our research during the past years can be summarized as follows: (1) we introduced a consistent method for computing Fick diffusion coefficients using equilibrium molecular dynamics simulations; (2) we developed a multicomponent Darken equation for the description of the concentration dependence of Maxwell-Stefan diffusivities. In the case of infinite dilution, the multicomponent Darken equation provides an expression for [InlineEquation not available: see fulltext.] which can be used to parametrize the generalized Vignes equation; and (3) a predictive model for self-diffusivities was proposed for the parametrization of the multicomponent Darken equation. This equation accurately describes the concentration dependence of self-diffusivities in weakly associating systems. With these methods, a sound framework for the prediction of mutual diffusion in liquids is achieved.

Electronic excitations in molecular solids: bridging theory and experiment.

PubMed

Skelton, Jonathan M; da Silva, E Lora; Crespo-Otero, Rachel; Hatcher, Lauren E; Raithby, Paul R; Parker, Stephen C; Walsh, Aron

2015-01-01

As the spatial and temporal resolution accessible to experiment and theory converge, computational chemistry is an increasingly powerful tool for modelling and interpreting spectroscopic data. However, the study of molecular processes, in particular those related to electronic excitations (e.g. photochemistry), frequently pushes quantum-chemical techniques to their limit. The disparity in the level of theory accessible to periodic and molecular calculations presents a significant challenge when modelling molecular crystals, since accurate calculations require a high level of theory to describe the molecular species, but must also take into account the influence of the crystalline environment on their properties. In this article, we briefly review the different classes of quantum-chemical techniques, and present an overview of methods that account for environmental influences with varying levels of approximation. Using a combination of solid-state and molecular calculations, we quantitatively evaluate the performance of implicit-solvent models for the [Ni(Et4dien)(η2-O,ON)(η1-NO2)] linkage-isomer system as a test case. We focus particularly on the accurate reproduction of the energetics of the isomerisation, and on predicting spectroscopic properties to compare with experimental results. This work illustrates how the synergy between periodic and molecular calculations can be exploited for the study of molecular crystals, and forms a basis for the investigation of more challenging phenomena, such as excited-state dynamics, and for further methodological developments.

Adsorptive Water Removal from Dichloromethane and Vapor-Phase Regeneration of a Molecular Sieve 3A Packed Bed

PubMed Central

2017-01-01

The drying of dichloromethane with a molecular sieve 3A packed bed process is modeled and experimentally verified. In the process, the dichloromethane is dried in the liquid phase and the adsorbent is regenerated by water desorption with dried dichloromethane product in the vapor phase. Adsorption equilibrium experiments show that dichloromethane does not compete with water adsorption, because of size exclusion; the pure water vapor isotherm from literature provides an accurate representation of the experiments. The breakthrough curves are adequately described by a mathematical model that includes external mass transfer, pore diffusion, and surface diffusion. During the desorption step, the main heat transfer mechanism is the condensation of the superheated dichloromethane vapor. The regeneration time is shortened significantly by external bed heating. Cyclic steady-state experiments demonstrate the feasibility of this novel, zero-emission drying process. PMID:28539701

Stochastic mechano-chemical kinetics of molecular motors: A multidisciplinary enterprise from a physicist’s perspective

NASA Astrophysics Data System (ADS)

Chowdhury, Debashish

2013-08-01

A molecular motor is made of either a single macromolecule or a macromolecular complex. Just like their macroscopic counterparts, molecular motors “transduce” input energy into mechanical work. All the nano-motors considered here operate under isothermal conditions far from equilibrium. Moreover, one of the possible mechanisms of energy transduction, called Brownian ratchet, does not even have any macroscopic counterpart. But, molecular motor is not synonymous with Brownian ratchet; a large number of molecular motors execute a noisy power stroke, rather than operating as Brownian ratchet. We review not only the structural design and stochastic kinetics of individual single motors, but also their coordination, cooperation and competition as well as the assembly of multi-module motors in various intracellular kinetic processes. Although all the motors considered here execute mechanical movements, efficiency and power output are not necessarily good measures of performance of some motors. Among the intracellular nano-motors, we consider the porters, sliders and rowers, pistons and hooks, exporters, importers, packers and movers as well as those that also synthesize, manipulate and degrade “macromolecules of life”. We review mostly the quantitative models for the kinetics of these motors. We also describe several of those motor-driven intracellular stochastic processes for which quantitative models are yet to be developed. In part I, we discuss mainly the methodology and the generic models of various important classes of molecular motors. In part II, we review many specific examples emphasizing the unity of the basic mechanisms as well as diversity of operations arising from the differences in their detailed structure and kinetics. Multi-disciplinary research is presented here from the perspective of physicists.

Molecular dynamic approach to the study of the intense heat and mass transfer processes on the vapor-liquid interface

NASA Astrophysics Data System (ADS)

Levashov, V. Yu; Kamenov, P. K.

2017-10-01

The paper is devoted to research of the heat and mass transfer processes on the vapor-liquid interface. These processes can be realized for example at metal tempering, accidents at nuclear power stations, followed by the release of the corium into the heat carrier, getting hot magma into the water during volcanic eruptions and other. In all these examples the vapor film can arise on the heated body surface. In this paper the vapor film formation process will be considered with help of molecular dynamics simulation methods. The main attention during this process modeling will be focused on the subject of the fluid and vapor interactions with the heater surface. Another direction of this work is to study of the processes inside the droplet that may take place as result of impact of the high-power laser radiation. Such impact can lead to intensive evaporation and explosive destruction of the droplet. At that the duration of heat and mass transfer processes in droplet substance is tens of femtoseconds. Thus, the methods of molecular dynamics simulation can give the possibilities describe the heat and mass transfer processes in the droplet and the vapor phase formation.

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

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation.

PubMed

Paluch, Andrew S; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L

2015-01-28

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

NASA Astrophysics Data System (ADS)

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Theoretical aspects and modelling of cellular decision making, cell killing and information-processing in photodynamic therapy of cancer.

PubMed

Gkigkitzis, Ioannis

2013-01-01

The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.

BioMOL: a computer-assisted biological modeling tool for complex chemical mixtures and biological processes at the molecular level.

PubMed Central

Klein, Michael T; Hou, Gang; Quann, Richard J; Wei, Wei; Liao, Kai H; Yang, Raymond S H; Campain, Julie A; Mazurek, Monica A; Broadbelt, Linda J

2002-01-01

A chemical engineering approach for the rigorous construction, solution, and optimization of detailed kinetic models for biological processes is described. This modeling capability addresses the required technical components of detailed kinetic modeling, namely, the modeling of reactant structure and composition, the building of the reaction network, the organization of model parameters, the solution of the kinetic model, and the optimization of the model. Even though this modeling approach has enjoyed successful application in the petroleum industry, its application to biomedical research has just begun. We propose to expand the horizons on classic pharmacokinetics and physiologically based pharmacokinetics (PBPK), where human or animal bodies were often described by a few compartments, by integrating PBPK with reaction network modeling described in this article. If one draws a parallel between an oil refinery, where the application of this modeling approach has been very successful, and a human body, the individual processing units in the oil refinery may be considered equivalent to the vital organs of the human body. Even though the cell or organ may be much more complicated, the complex biochemical reaction networks in each organ may be similarly modeled and linked in much the same way as the modeling of the entire oil refinery through linkage of the individual processing units. The integrated chemical engineering software package described in this article, BioMOL, denotes the biological application of molecular-oriented lumping. BioMOL can build a detailed model in 1-1,000 CPU sec using standard desktop hardware. The models solve and optimize using standard and widely available hardware and software and can be presented in the context of a user-friendly interface. We believe this is an engineering tool with great promise in its application to complex biological reaction networks. PMID:12634134

Theoretical and Experimental Study of Inclusion Complexes of β-Cyclodextrins with Chalcone and 2',4'-Dihydroxychalcone.

PubMed

Sancho, Matias I; Andujar, Sebastian; Porasso, Rodolfo D; Enriz, Ricardo D

2016-03-31

The inclusion complexes formed by chalcone and 2',4'-dihydroxychalcone with β-cyclodextrin have been studied combining experimental (phase solubility diagrams, Fourier transform infrared spectroscopy) and molecular modeling (molecular dynamics, quantum mechanics/molecular mechanics calculations) techniques. The formation constants of the complexes were determined at different temperatures, and the thermodynamic parameters of the process were obtained. The inclusion of chalcone in β-cyclodextrin is an exothermic process, while the inclusion of 2',4'-dihydroxychalcone is endothermic. Free energy profiles, derived from umbrella sampling using molecular dynamics simulations, were constructed to analyze the binding affinity and the complexation reaction at a molecular level. Hybrid QM/MM calculations were also employed to obtain a better description of the energetic and structural aspects of the complexes. The intermolecular interactions that stabilize both inclusion complexes were characterized by means of quantum atoms in molecules theory and reduce density gradient method. The calculated interactions were experimentally observed using FTIR.

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

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

Tim Schulze

2012-11-01

The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

H2-based star formation laws in hierarchical models of galaxy formation

NASA Astrophysics Data System (ADS)

Xie, Lizhi; De Lucia, Gabriella; Hirschmann, Michaela; Fontanot, Fabio; Zoldan, Anna

2017-07-01

We update our recently published model for GAlaxy Evolution and Assembly (GAEA), to include a self-consistent treatment of the partition of cold gas in atomic and molecular hydrogen. Our model provides significant improvements with respect to previous ones used for similar studies. In particular, GAEA (I) includes a sophisticated chemical enrichment scheme accounting for non-instantaneous recycling of gas, metals and energy; (II) reproduces the measured evolution of the galaxy stellar mass function; (III) reasonably reproduces the observed correlation between galaxy stellar mass and gas metallicity at different redshifts. These are important prerequisites for models considering a metallicity-dependent efficiency of molecular gas formation. We also update our model for disc sizes and show that model predictions are in nice agreement with observational estimates for the gas, stellar and star-forming discs at different cosmic epochs. We analyse the influence of different star formation laws including empirical relations based on the hydrostatic pressure of the disc, analytic models and prescriptions derived from detailed hydrodynamical simulations. We find that modifying the star formation law does not affect significantly the global properties of model galaxies, neither their distributions. The only quantity showing significant deviations in different models is the cosmic molecular-to-atomic hydrogen ratio, particularly at high redshift. Unfortunately, however, this quantity also depends strongly on the modelling adopted for additional physical processes. Useful constraints on the physical processes regulating star formation can be obtained focusing on low-mass galaxies and/or at higher redshift. In this case, self-regulation has not yet washed out differences imprinted at early time.

Enthalpy measurement of coal-derived liquids. Technical progress report, November 1982-January 1983

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

Kidnay, A.J.; Yesavage, V.F.

The objective of this research is to measure the enthalpy for representative coal-derived liquids and model compounds over the pressure and temperature regions most likely to be encountered in both liquefaction and processing systems, and to prepare from the data an enthalpy correlation suitable for process design calculations. The correlational effort this past quarter on the enthalpy of coal-derived syncrudes and model compounds has emphasized the experimental determination of a correlating factor for association in coal liquids. As in previous work, the degree of association is to be related to cryoscopic molecular weight determinations on the coal liquids. To thismore » end, work on and an evaluationof a cryoscopic molecular weight apparatus was completed this quarter. Molecular weights of coal liquids determined by the standard Beckman freezing point depression apparatus were consistently low (5 to 10%). After modifications of the apparatus, it was tested with the following compounds: hexane, dodecane, m-xylene and naphthalene. Benzene was the solvent used. However, the molecular weight measurements were again consistently lower than the true values, and in many cases the experimental error was greater than that of the Beckman apparatus.« less

Exploring Autophagy in Drosophila

PubMed Central

Juhász, Gábor

2017-01-01

Autophagy is a catabolic process in eukaryotic cells promoting bulk or selective degradation of cellular components within lysosomes. In recent decades, several model systems were utilized to dissect the molecular machinery of autophagy and to identify the impact of this cellular “self-eating” process on various physiological and pathological processes. Here we briefly discuss the advantages and limitations of using the fruit fly Drosophila melanogaster, a popular model in cell and developmental biology, to apprehend the main pathway of autophagy in a complete animal. PMID:28704946

Control mechanisms for stochastic biochemical systems via computation of reachable sets.

PubMed

Lakatos, Eszter; Stumpf, Michael P H

2017-08-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.

Control mechanisms for stochastic biochemical systems via computation of reachable sets

PubMed Central

Lakatos, Eszter

2017-01-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters. PMID:28878957

Linear Response Path Following: A Molecular Dynamics Method To Simulate Global Conformational Changes of Protein upon Ligand Binding.

PubMed

Tamura, Koichi; Hayashi, Shigehiko

2015-07-14

Molecular functions of proteins are often fulfilled by global conformational changes that couple with local events such as the binding of ligand molecules. High molecular complexity of proteins has, however, been an obstacle to obtain an atomistic view of the global conformational transitions, imposing a limitation on the mechanistic understanding of the functional processes. In this study, we developed a new method of molecular dynamics (MD) simulation called the linear response path following (LRPF) to simulate a protein's global conformational changes upon ligand binding. The method introduces a biasing force based on a linear response theory, which determines a local reaction coordinate in the configuration space that represents linear coupling between local events of ligand binding and global conformational changes and thus provides one with fully atomistic models undergoing large conformational changes without knowledge of a target structure. The overall transition process involving nonlinear conformational changes is simulated through iterative cycles consisting of a biased MD simulation with an updated linear response force and a following unbiased MD simulation for relaxation. We applied the method to the simulation of global conformational changes of the yeast calmodulin N-terminal domain and successfully searched out the end conformation. The atomistically detailed trajectories revealed a sequence of molecular events that properly lead to the global conformational changes and identified key steps of local-global coupling that induce the conformational transitions. The LRPF method provides one with a powerful means to model conformational changes of proteins such as motors and transporters where local-global coupling plays a pivotal role in their functional processes.

Modeling Molecular and Cellular Aspects of Human Disease using the Nematode Caenorhabditis elegans

PubMed Central

Silverman, Gary A.; Luke, Cliff J.; Bhatia, Sangeeta R.; Long, Olivia S.; Vetica, Anne C.; Perlmutter, David H.; Pak, Stephen C.

2009-01-01

As an experimental system, Caenorhabditis elegans, offers a unique opportunity to interrogate in vivo the genetic and molecular functions of human disease-related genes. For example, C. elegans has provided crucial insights into fundamental biological processes such as cell death and cell fate determinations, as well as pathological processes such as neurodegeneration and microbial susceptibility. The C. elegans model has several distinct advantages including a completely sequenced genome that shares extensive homology with that of mammals, ease of cultivation and storage, a relatively short lifespan and techniques for generating null and transgenic animals. However, the ability to conduct unbiased forward and reverse genetic screens in C. elegans remains one of the most powerful experimental paradigms for discovering the biochemical pathways underlying human disease phenotypes. The identification of these pathways leads to a better understanding of the molecular interactions that perturb cellular physiology, and forms the foundation for designing mechanism-based therapies. To this end, the ability to process large numbers of isogenic animals through automated work stations suggests that C. elegans, manifesting different aspects of human disease phenotypes, will become the platform of choice for in vivo drug discovery and target validation using high-throughput/content screening technologies. PMID:18852689

Uncertainties in Atomic Data and Their Propagation Through Spectral Models. I.

NASA Technical Reports Server (NTRS)

Bautista, M. A.; Fivet, V.; Quinet, P.; Dunn, J.; Gull, T. R.; Kallman, T. R.; Mendoza, C.

2013-01-01

We present a method for computing uncertainties in spectral models, i.e., level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data.We provide analytic expressions, in the form of linear sets of algebraic equations, for the coupled uncertainties among all levels. These equations can be solved efficiently for any set of physical conditions and uncertainties in the atomic data. We illustrate our method applied to spectral models of Oiii and Fe ii and discuss the impact of the uncertainties on atomic systems under different physical conditions. As to intrinsic uncertainties in theoretical atomic data, we propose that these uncertainties can be estimated from the dispersion in the results from various independent calculations. This technique provides excellent results for the uncertainties in A-values of forbidden transitions in [Fe ii]. Key words: atomic data - atomic processes - line: formation - methods: data analysis - molecular data - molecular processes - techniques: spectroscopic

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales

NASA Astrophysics Data System (ADS)

Mukherjee, Biswaroop; Peter, Christine; Kremer, Kurt

2017-09-01

Understanding the connections between the characteristic dynamical time scales associated with a coarse-grained (CG) and a detailed representation is central to the applicability of the coarse-graining methods to understand molecular processes. The process of coarse graining leads to an accelerated dynamics, owing to the smoothening of the underlying free-energy landscapes. Often a single time-mapping factor is used to relate the time scales associated with the two representations. We critically examine this idea using a model system ideally suited for this purpose. Single molecular transport properties are studied via molecular dynamics simulations of the CG and atomistic representations of a liquid crystalline, azobenzene containing mesogen, simulated in the smectic and the isotropic phases. The out-of-plane dynamics in the smectic phase occurs via molecular hops from one smectic layer to the next. Hopping can occur via two mechanisms, with and without significant reorientation. The out-of-plane transport can be understood as a superposition of two (one associated with each mode of transport) independent continuous time random walks for which a single time-mapping factor would be rather inadequate. A comparison of the free-energy surfaces, relevant to the out-of-plane transport, qualitatively supports the above observations. Thus, this work underlines the need for building CG models that exhibit both structural and dynamical consistency to the underlying atomistic model.

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.

Current challenges in organic photovoltaic solar energy conversion.

PubMed

Schlenker, Cody W; Thompson, Mark E

2012-01-01

Over the last 10 years, significant interest in utilizing conjugated organic molecules for solid-state solar to electric conversion has produced rapid improvement in device efficiencies. Organic photovoltaic (OPV) devices are attractive for their compatibility with low-cost processing techniques and thin-film applicability to flexible and conformal applications. However, many of the processes that lead to power losses in these systems still remain poorly understood, posing a significant challenge for the future efficiency improvements required to make these devices an attractive solar technology. While semiconductor band models have been employed to describe OPV operation, a more appropriate molecular picture of the pertinent processes is beginning to emerge. This chapter presents mechanisms of OPV device operation, based on the bound molecular nature of the involved transient species. With the intention to underscore the importance of considering both thermodynamic and kinetic factors, recent progress in elucidating molecular characteristics that dictate photovoltage losses in heterojunction organic photovoltaics is also discussed.

Review: Animal model and the current understanding of molecule dynamics of adipogenesis.

PubMed

Campos, C F; Duarte, M S; Guimarães, S E F; Verardo, L L; Wei, S; Du, M; Jiang, Z; Bergen, W G; Hausman, G J; Fernyhough-Culver, M; Albrecht, E; Dodson, M V

2016-06-01

Among several potential animal models that can be used for adipogenic studies, Wagyu cattle is the one that presents unique molecular mechanisms underlying the deposit of substantial amounts of intramuscular fat. As such, this review is focused on current knowledge of such mechanisms related to adipose tissue deposition using Wagyu cattle as model. So abundant is the lipid accumulation in the skeletal muscles of these animals that in many cases, the muscle cross-sectional area appears more white (adipose tissue) than red (muscle fibers). This enhanced marbling accumulation is morphologically similar to that seen in numerous skeletal muscle dysfunctions, disease states and myopathies; this might indicate cross-similar mechanisms between such dysfunctions and fat deposition in Wagyu breed. Animal models can be used not only for a better understanding of fat deposition in livestock, but also as models to an increased comprehension on molecular mechanisms behind human conditions. This revision underlies some of the complex molecular processes of fat deposition in animals.

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.

SMOG 2: A Versatile Software Package for Generating Structure-Based Models.

PubMed

Noel, Jeffrey K; Levi, Mariana; Raghunathan, Mohit; Lammert, Heiko; Hayes, Ryan L; Onuchic, José N; Whitford, Paul C

2016-03-01

Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

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

McLaughlin, E.; Gupta, S.

This project mainly involves a molecular dynamics and Monte Carlo study of the effect of molecular shape on thermophysical properties of bulk fluids with an emphasis on the aromatic hydrocarbon liquids. In this regard we have studied the modeling, simulation methodologies, and predictive and correlating methods for thermodynamic properties of fluids of nonspherical molecules. In connection with modeling we have studied the use of anisotropic site-site potentials, through a modification of the Gay-Berne Gaussian overlap potential, to successfully model the aromatic rings after adding the necessary electrostatic moments. We have also shown these interaction sites should be located at themore » geometric centers of the chemical groups. In connection with predictive methods, we have shown two perturbation type theories to work well for fluids modeled using one-center anisotropic potentials and the possibility exists for extending these to anisotropic site-site models. In connection with correlation methods, we have studied, through simulations, the effect of molecular shape on the attraction term in the generalized van der Waals equation of state for fluids of nonspherical molecules and proposed a possible form which is to be studied further. We have successfully studied the vector and parallel processing aspects of molecular simulations for fluids of nonspherical molecules.« less

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

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.

Toward the reconstitution of synthetic cell motility

PubMed Central

Siton-Mendelson, Orit; Bernheim-Groswasser, Anne

2016-01-01

ABSTRACT Cellular motility is a fundamental process essential for embryonic development, wound healing, immune responses, and tissues development. Cells are mostly moving by crawling on external, or inside, substrates which can differ in their surface composition, geometry, and dimensionality. Cells can adopt different migration phenotypes, e.g., bleb-based and protrusion-based, depending on myosin contractility, surface adhesion, and cell confinement. In the few past decades, research on cell motility has focused on uncovering the major molecular players and their order of events. Despite major progresses, our ability to infer on the collective behavior from the molecular properties remains a major challenge, especially because cell migration integrates numerous chemical and mechanical processes that are coupled via feedbacks that span over large range of time and length scales. For this reason, reconstituted model systems were developed. These systems allow for full control of the molecular constituents and various system parameters, thereby providing insight into their individual roles and functions. In this review we describe the various reconstituted model systems that were developed in the past decades. Because of the multiple steps involved in cell motility and the complexity of the overall process, most of the model systems focus on very specific aspects of the individual steps of cell motility. Here we describe the main advancement in cell motility reconstitution and discuss the main challenges toward the realization of a synthetic motile cell. PMID:27019160

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

Molecular diagnostics of FUV and accretion-related heating in protoplanetary disks

NASA Astrophysics Data System (ADS)

Adamkovics, Mate; Najita, Joan R.

2017-10-01

Emission lines from the terrestrial planet forming regions of disks are diagnostic of both the physical processes that heat the gas and the chemistry that determines the inventory of nebular material available during the epoch of planet formation. Interpreting emission spectra is informed by models of radiative, thermal, physical, and chemical processes, such as: (i) the radiation transfer of X-rays and FUV --- both continuum and Ly-alpha, (ii) direct and indirect heating processes such as the photoelectric effect and photochemical heating, (iii) heating related to turbulent processes and viscous dissipation, and (iv) gas phase chemical reaction kinetics. Many of these processes depend on a the spatial distribution of dust grains and their properties, which temporally evolve during the lifetime of the disk and the formation of planets. Studies of disks atmospheres often predict a layered structure of hot (a few thousand K) atomic gas overlying warm (a few hundred K) molecular gas, which is generally consistent with the isothermal slab emission models that are used to interpret emission spectra. However, detailed comparison between observed spectra and models (e.g., comparing the total columns and the radial extent of warm emitting species) is rare.We present results including the implementation of Ly-alpha scattering, which is an important part of the photochemical heating and FUV heating radiation budget. By including these processes we find a new component of the disk atmosphere; hot molecular gas at ~2000K within radial distances of ~0.5AU, which is consistent with observations of UV-fluorescent H2 emission (Ádámkovics, Najita & Glassgold, 2016). Constraining the most optimistic contribution of radiative heating mechanisms via X-rays and FUV together with a favorable comparison to observations, allows us to explore and evaluate additional heating mechanisms. We find that the total columns of warm (90-400K) emitting molecules such as CO, arising directly below the irradiated molecular layer, are diagnostic of the role of turbulent (viscous) mechanical heating. We discuss how the total columns of warm molecules in this layer may be diagnostic of the magnetorotational instability (Najita & Ádámkovics, 2017).

Social molecular pathways and the evolution of bee societies

PubMed Central

Bloch, Guy; Grozinger, Christina M.

2011-01-01

Bees provide an excellent model with which to study the neuronal and molecular modifications associated with the evolution of sociality because relatively closely related species differ profoundly in social behaviour, from solitary to highly social. The recent development of powerful genomic tools and resources has set the stage for studying the social behaviour of bees in molecular terms. We review ‘ground plan’ and ‘genetic toolkit’ models which hypothesize that discrete pathways or sets of genes that regulate fundamental behavioural and physiological processes in solitary species have been co-opted to regulate complex social behaviours in social species. We further develop these models and propose that these conserved pathways and genes may be incorporated into ‘social pathways’, which consist of relatively independent modules involved in social signal detection, integration and processing within the nervous and endocrine systems, and subsequent behavioural outputs. Modifications within modules or in their connections result in the evolution of novel behavioural patterns. We describe how the evolution of pheromonal regulation of social pathways may lead to the expression of behaviour under new social contexts, and review plasticity in circadian rhythms as an example for a social pathway with a modular structure. PMID:21690132

Molecular environmental geochemistry

NASA Astrophysics Data System (ADS)

O'Day, Peggy A.

1999-05-01

The chemistry, mobility, and bioavailability of contaminant species in the natural environment are controlled by reactions that occur in and among solid, aqueous, and gas phases. These reactions are varied and complex, involving changes in chemical form and mass transfer among inorganic, organic, and biochemical species. The field of molecular environmental geochemistry seeks to apply spectroscopic and microscopic probes to the mechanistic understanding of environmentally relevant chemical processes, particularly those involving contaminants and Earth materials. In general, empirical geochemical models have been shown to lack uniqueness and adequate predictive capability, even in relatively simple systems. Molecular geochemical tools, when coupled with macroscopic measurements, can provide the level of chemical detail required for the credible extrapolation of contaminant reactivity and bioavailability over ranges of temperature, pressure, and composition. This review focuses on recent advances in the understanding of molecular chemistry and reaction mechanisms at mineral surfaces and mineral-fluid interfaces spurred by the application of new spectroscopies and microscopies. These methods, such as synchrotron X-ray absorption and scattering techniques, vibrational and resonance spectroscopies, and scanning probe microscopies, provide direct chemical information that can elucidate molecular mechanisms, including element speciation, ligand coordination and oxidation state, structural arrangement and crystallinity on different scales, and physical morphology and topography of surfaces. Nonvacuum techniques that allow examination of reactions in situ (i.e., with water or fluids present) and in real time provide direct links between molecular structure and reactivity and measurements of kinetic rates or thermodynamic properties. Applications of these diverse probes to laboratory model systems have provided fundamental insight into inorganic and organic reactions at mineral surfaces and mineral-water interfaces. A review of recent studies employing molecular characterizations of soils, sediments, and biological samples from contaminated sites exemplifies the utility and benefits, as well as the challenge, of applying molecular probes to complicated natural materials. New techniques, technological advances, and the crossover of methods from other disciplines such as biochemistry and materials science promise better examination of environmental chemical processes in real time and at higher resolution, and will further the integration of molecular information into field-scale chemical and hydrologic models.

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

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

PubMed

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-07-21

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma

PubMed Central

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-01-01

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene’s expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment. PMID:27468205

Molecular Dynamics Simulations of the Oil-Detachment from the Hydroxylated Silica Surface: Effects of Surfactants, Electrostatic Interactions, and Water Flows on the Water Molecular Channel Formation.

PubMed

Tang, Jian; Qu, Zhou; Luo, Jianhui; He, Lanyan; Wang, Pingmei; Zhang, Ping; Tang, Xianqiong; Pei, Yong; Ding, Bin; Peng, Baoliang; Huang, Yunqing

2018-02-15

The detachment process of an oil molecular layer situated above a horizontal substrate was often described by a three-stage process. In this mechanism, the penetration and diffusion of water molecules between the oil phase and the substrate was proposed to be a crucial step to aid in removal of oil layer/drops from substrate. In this work, the detachment process of a two-dimensional alkane molecule layer from a silica surface in aqueous surfactant solutions is studied by means of molecular dynamics (MD) simulations. By tuning the polarity of model silica surfaces, as well as considering the different types of surfactant molecules and the water flow effects, more details about the formation of water molecular channel and the expansion processes are elucidated. It is found that for both ionic and nonionic type surfactant solutions, the perturbation of surfactant molecules on the two-dimensional oil molecule layer facilitates the injection and diffusion of water molecules between the oil layer and silica substrate. However, the water channel formation and expansion speed is strongly affected by the substrate polarity and properties of surfactant molecules. First, only for the silica surface with relative stronger polarity, the formation of water molecular channel is observed. Second, the expansion speed of the water molecular channel upon the ionic surfactant (dodecyl trimethylammonium bromide, DTAB and sodium dodecyl benzenesulfonate, SDBS) flooding is more rapidly than the nonionic surfactant system (octylphenol polyoxyethylene(10) ether, OP-10). Third, the water flow speed may also affect the injection and diffusion of water molecules. These simulation results indicate that the water molecular channel formation process is affected by multiple factors. The synergistic effects of perturbation of surfactant molecules and the electrostatic interactions between silica substrate and water molecules are two key factors aiding in the injection and diffusion of water molecules and helpful for the oil detachment from silica substrate.

First principle chemical kinetics in zeolites: the methanol-to-olefin process as a case study.

PubMed

Van Speybroeck, Veronique; De Wispelaere, Kristof; Van der Mynsbrugge, Jeroen; Vandichel, Matthias; Hemelsoet, Karen; Waroquier, Michel

2014-11-07

To optimally design next generation catalysts a thorough understanding of the chemical phenomena at the molecular scale is a prerequisite. Apart from qualitative knowledge on the reaction mechanism, it is also essential to be able to predict accurate rate constants. Molecular modeling has become a ubiquitous tool within the field of heterogeneous catalysis. Herein, we review current computational procedures to determine chemical kinetics from first principles, thus by using no experimental input and by modeling the catalyst and reacting species at the molecular level. Therefore, we use the methanol-to-olefin (MTO) process as a case study to illustrate the various theoretical concepts. This process is a showcase example where rational design of the catalyst was for a long time performed on the basis of trial and error, due to insufficient knowledge of the mechanism. For theoreticians the MTO process is particularly challenging as the catalyst has an inherent supramolecular nature, for which not only the Brønsted acidic site is important but also organic species, trapped in the zeolite pores, must be essentially present during active catalyst operation. All these aspects give rise to specific challenges for theoretical modeling. It is shown that present computational techniques have matured to a level where accurate enthalpy barriers and rate constants can be predicted for reactions occurring at a single active site. The comparison with experimental data such as apparent kinetic data for well-defined elementary reactions has become feasible as current computational techniques also allow predicting adsorption enthalpies with reasonable accuracy. Real catalysts are truly heterogeneous in a space- and time-like manner. Future theory developments should focus on extending our view towards phenomena occurring at longer length and time scales and integrating information from various scales towards a unified understanding of the catalyst. Within this respect molecular dynamics methods complemented with additional techniques to simulate rare events are now gradually making their entrance within zeolite catalysis. Recent applications have already given a flavor of the benefit of such techniques to simulate chemical reactions in complex molecular environments.

Molecular Mechanisms and Modeling of Skin Irritation from JP-8

DTIC Science & Technology

2006-03-01

levels of performance than shallow levels of processing ( Craik & Lockhart , 1972). Deeper levels of processing focus on the meaning of...of group processes for decision- making. New York: John Wiley & Sons. Craik , F.I.M., & Lockhart , R.S. (1972). Levels of processing : A framework for...has been demonstrated to result in differential levels of memory performance ( Craik & Lockhart , 1972). If the objective is to store

The Structure and Evolution of Self-Gravitating Molecular Clouds

NASA Astrophysics Data System (ADS)

Holliman, John Herbert, II

1995-01-01

We present a theoretical formalism to evaluate the structure of molecular clouds and to determine precollapse conditions in star-forming regions. Models consist of pressure-bounded, self-gravitating spheres of a single -fluid ideal gas. We treat the case without rotation. The analysis is generalized to consider states in hydrostatic equilibrium maintained by multiple pressure components. Individual pressures vary with density as P_i(r) ~ rho^{gamma {rm p},i}(r), where gamma_{rm p},i is the polytropic index. Evolution depends additionally on whether conduction occurs on a dynamical time scale and on the adiabatic index gammai of each component, which is modified to account for the effects of any thermal coupling to the environment of the cloud. Special attention is given to properly representing the major contributors to dynamical support in molecular clouds: the pressures due to static magnetic fields, Alfven waves, and thermal motions. Straightforward adjustments to the model allow us to treat the intrinsically anisotropic support provided by the static fields. We derive structure equations, as well as perturbation equations for performing a linear stability analysis. The analysis provides insight on the nature of dynamical motions due to collapse from an equilibrium state and estimates the mass of condensed objects that form in such a process. After presenting a set of general results, we describe models of star-forming regions that include the major pressure components. We parameterize the extent of ambipolar diffusion. The analysis contributes to the physical understanding of several key results from observations of these regions. Commonly observed quantities are explicitly cross-referenced with model results. We theoretically determine density and linewidth profiles on scales ranging from that of molecular cloud cores to that of giant molecular clouds (GMCs). The model offers an explanation of the mean pressures in GMCs, which are observed to be high relative to that in the intercloud medium. We estimate what fraction of a cloud on the verge of gravitational collapse will ultimately form a condensed object, and we predict the qualitative appearance of the collapse. Finally, we simulate fragmentation--a key step in the star-forming process whereby molecular clouds or clumps within more massive clouds break up into substantially less massive cores that can in turn condense into stars. Fragmentation occurs in the context of dynamical collapse--a highly nonlinear process--so it has been difficult to reach a consensus on its specific appearance or on the influence of initial conditions. Increases in density by several orders of magnitude and the unknown, time-dependent positions of the rapidly evolving fragments present difficulties for the simulation of fragmentation. In order to increase the efficiency and effective resolution with which we can model this process, we have assembled can adaptive mesh refinement (AMR) hydrodynamics algorithm and an adaptive elliptical solver for self-gravity. The code is adaptive in the sense that it can dynamically and automatically alter the configuration of a recursively finer mesh in the computational domain. A test suite helps confirm the proper operation of the algorithm. Using initial conditions adopted in previous fragmentation studies, we simulate the collapse of a molecular cloud core. (Abstract shortened by UMI.).

Vibronic coupling effect on the electron transport through molecules

NASA Astrophysics Data System (ADS)

Tsukada, Masaru; Mitsutake, Kunihiro

2007-03-01

Electron transport through molecular bridges or molecular layers connected to nano-electrodes is determined by the combination of coherent and dissipative processes, controlled by the electron-vibron coupling, transfer integrals between the molecular orbitals, applied electric field and temperature. We propose a novel theoretical approach, which combines ab initio molecular orbital method with analytical many-boson model. As a case study, the long chain model of the thiophene oligomer is solved by a variation approach. Mixed states of moderately extended molecular orbital states mediated and localised by dress of vibron cloud are found as eigen-states. All the excited states accompanied by multiple quanta of vibration can be solved, and the overall carrier transport properties including the conductance, mobility, dissipation spectra are analyzed by solving the master equation with the transition rates estimated by the golden rule. We clarify obtained in a uniform systematic way, how the transport mode changes from a dominantly coherent transport to the dissipative hopping transport.

Structure and atomic correlations in molecular systems probed by XAS reverse Monte Carlo refinement

NASA Astrophysics Data System (ADS)

Di Cicco, Andrea; Iesari, Fabio; Trapananti, Angela; D'Angelo, Paola; Filipponi, Adriano

2018-03-01

The Reverse Monte Carlo (RMC) algorithm for structure refinement has been applied to x-ray absorption spectroscopy (XAS) multiple-edge data sets for six gas phase molecular systems (SnI2, CdI2, BBr3, GaI3, GeBr4, GeI4). Sets of thousands of molecular replicas were involved in the refinement process, driven by the XAS data and constrained by available electron diffraction results. The equilibrated configurations were analysed to determine the average tridimensional structure and obtain reliable bond and bond-angle distributions. Detectable deviations from Gaussian models were found in some cases. This work shows that a RMC refinement of XAS data is able to provide geometrical models for molecular structures compatible with present experimental evidence. The validation of this approach on simple molecular systems is particularly important in view of its possible simple extension to more complex and extended systems including metal-organic complexes, biomolecules, or nanocrystalline systems.

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

Probing the effects of surface hydrophobicity and tether orientation on antibody-antigen binding

NASA Astrophysics Data System (ADS)

Bush, Derek B.; Knotts, Thomas A.

2017-04-01

Antibody microarrays have the potential to revolutionize molecular detection for many applications, but their current use is limited by poor reliability, and efforts to change this have not yielded fruitful results. One difficulty which limits the rational engineering of next-generation devices is that little is known, at the molecular level, about the antibody-antigen binding process near solid surfaces. Atomic-level structural information is scant because typical experimental techniques (X-ray crystallography and NMR) cannot be used to image proteins bound to surfaces. To overcome this limitation, this study uses molecular simulation and an advanced, experimentally validated, coarse-grain, protein-surface model to compare fab-lysozyme binding in bulk solution and when the fab is tethered to hydrophobic and hydrophilic surfaces. The results show that the tether site in the fab, as well as the surface hydrophobicity, significantly impacts the binding process and suggests that the optimal design involves tethering fabs upright on a hydrophilic surface. The results offer an unprecedented, molecular-level picture of the binding process and give hope that the rational design of protein-microarrays is possible.

Spectral studies related to dissociation of HBr, HCl and BrO

NASA Technical Reports Server (NTRS)

Ginter, M. L.

1986-01-01

Concern over halogen catalyzed decomposition of O3 in the upper atmosphere has generated need for data on the atomic and molecular species X, HX and XO (where X is Cl and Br). Of special importance are Cl produced from freon decomposition and Cl and Br produced from natural processes and from other industrial and agricultural chemicals. Basic spectral data is provided on HCl, HBr, and BrO necessary to detect specific states and energy levels, to enable detailed modeling of the processes involving molecular dissociation, ionization, etc., and to help evaluate field experiments to check the validity of model calculations for these species in the upper atmosphere. Results contained in four published papers and two major spectral compilations are summarized together with other results obtained.

Isotopic Fractionation in Primitive Material: Quantifying the Contribution of Interstellar Chemistry

NASA Technical Reports Server (NTRS)

Charnley, Steven

2010-01-01

Anomalously fractionated isotopic material is found in many primitive Solar System objects, such as meteorites and comets. It is thought, in some cases, to trace interstellar matter that was incorporated into the Solar Nebula without undergoing significant processing. We will present the results of models of the nitrogen, oxygen, and carbon fractionation chemistry in dense molecular clouds, particularly in cores where substantial freeze-out of molecules on to dust has occurred. The range of fractionation ratios expected in different interstellar molecules will be discussed and compared to the ratios measured in molecular clouds, comets and meteoritic material. These models make several predictions that can be tested in the near future by molecular line observations, particularly with ALMA.

Control of Mechanotransduction by Molecular Clutch Dynamics.

PubMed

Elosegui-Artola, Alberto; Trepat, Xavier; Roca-Cusachs, Pere

2018-05-01

The linkage of cells to their microenvironment is mediated by a series of bonds that dynamically engage and disengage, in what has been conceptualized as the molecular clutch model. Whereas this model has long been employed to describe actin cytoskeleton and cell migration dynamics, it has recently been proposed to also explain mechanotransduction (i.e., the process by which cells convert mechanical signals from their environment into biochemical signals). Here we review the current understanding on how cell dynamics and mechanotransduction are driven by molecular clutch dynamics and its master regulator, the force loading rate. Throughout this Review, we place a specific emphasis on the quantitative prediction of cell response enabled by combined experimental and theoretical approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of Coarse Grained Models for Long Chain Alkanes

NASA Astrophysics Data System (ADS)

Gyawali, Gaurav; Sternfield, Samuel; Hwang, In Chul; Rick, Steven; Kumar, Revati; Rick Group Team; Kumar Group Team

Modeling aggregation in aqueous solution is a challenge for molecular simulations as it involves long time scales, a range of length scales, and the correct balance of hydrophobic and hydrophilic interactions. We have developed a coarse-grained model fast enough for the rapid testing of molecular structures for their aggregation properties. This model, using the Stillinger-Weber potential, achieves efficiency through a reduction in the number of interaction sites and the use of short-ranged interactions. The model can be two to three orders of magnitude more efficient than conventional all atom simulations, yet through a careful parameterization process and the use of many-body interactions can be remarkably accurate. We have developed models for long chain alkanes in water that reproduce the thermodynamics and structure of water-alkane and liquid alkane systems.

Molecular simulations and experimental studies of zeolites

NASA Astrophysics Data System (ADS)

Moloy, Eric C.

Zeolites are microporous aluminosilicate tetrahedral framework materials that have symmetric cages and channels with open-diameters between 0.2 and 2.0 nm. Zeolites are used extensively in the petrochemical industries for both their microporosity and their catalytic properties. The role of water is paramount to the formation, structure, and stability of these materials. Zeolites frequently have extra-framework cations, and as a result, are important ion-exchange materials. Zeolites also play important roles as molecular sieves and catalysts. For all that is known about zeolites, much remains a mystery. How, for example, can the well established metastability of these structures be explained? What is the role of water with respect to the formation, stabilization, and dynamical properties? This dissertation addresses these questions mainly from a modeling perspective, but also with some experimental work as well. The first discussion addresses a special class of zeolites: pure-silica zeolites. Experimental enthalpy of formation data are combined with molecular modeling to address zeolitic metastability. Molecular modeling is used to calculate internal surface areas, and a linear relationship between formation enthalpy and internal surface areas is clearly established, producing an internal surface energy of approximately 93 mJ/m2. Nitrate bearing sodalite and cancrinite have formed under the caustic chemical conditions of some nuclear waste processing centers in the United States. These phases have fouled expensive process equipment, and are the primary constituents of the resilient heels in the bottom of storage tanks. Molecular modeling, including molecular mechanics, molecular dynamics, and density functional theory, is used to simulate these materials with respect to structure and dynamical properties. Some new, very interesting results are extracted from the simulation of anhydrous Na6[Si6Al 6O24] sodalite---most importantly, the identification of two distinct oxygen sites (rather than one), and formation of a new supercell. New calorimetric measurements of enthalpy are used to examine the energetics of the hydrosodalite family of zeolites---specifically, formation enthalpies and hydration energies. Finally, force-field computational methods begin the examination of water in terms of energetics, structure, and radionuclide containment and diffusion.

Understanding phylogenetic incongruence: lessons from phyllostomid bats

PubMed Central

Dávalos, Liliana M; Cirranello, Andrea L; Geisler, Jonathan H; Simmons, Nancy B

2012-01-01

All characters and trait systems in an organism share a common evolutionary history that can be estimated using phylogenetic methods. However, differential rates of change and the evolutionary mechanisms driving those rates result in pervasive phylogenetic conflict. These drivers need to be uncovered because mismatches between evolutionary processes and phylogenetic models can lead to high confidence in incorrect hypotheses. Incongruence between phylogenies derived from morphological versus molecular analyses, and between trees based on different subsets of molecular sequences has become pervasive as datasets have expanded rapidly in both characters and species. For more than a decade, evolutionary relationships among members of the New World bat family Phyllostomidae inferred from morphological and molecular data have been in conflict. Here, we develop and apply methods to minimize systematic biases, uncover the biological mechanisms underlying phylogenetic conflict, and outline data requirements for future phylogenomic and morphological data collection. We introduce new morphological data for phyllostomids and outgroups and expand previous molecular analyses to eliminate methodological sources of phylogenetic conflict such as taxonomic sampling, sparse character sampling, or use of different algorithms to estimate the phylogeny. We also evaluate the impact of biological sources of conflict: saturation in morphological changes and molecular substitutions, and other processes that result in incongruent trees, including convergent morphological and molecular evolution. Methodological sources of incongruence play some role in generating phylogenetic conflict, and are relatively easy to eliminate by matching taxa, collecting more characters, and applying the same algorithms to optimize phylogeny. The evolutionary patterns uncovered are consistent with multiple biological sources of conflict, including saturation in morphological and molecular changes, adaptive morphological convergence among nectar-feeding lineages, and incongruent gene trees. Applying methods to account for nucleotide sequence saturation reduces, but does not completely eliminate, phylogenetic conflict. We ruled out paralogy, lateral gene transfer, and poor taxon sampling and outgroup choices among the processes leading to incongruent gene trees in phyllostomid bats. Uncovering and countering the possible effects of introgression and lineage sorting of ancestral polymorphism on gene trees will require great leaps in genomic and allelic sequencing in this species-rich mammalian family. We also found evidence for adaptive molecular evolution leading to convergence in mitochondrial proteins among nectar-feeding lineages. In conclusion, the biological processes that generate phylogenetic conflict are ubiquitous, and overcoming incongruence requires better models and more data than have been collected even in well-studied organisms such as phyllostomid bats. PMID:22891620

Carbon chemistry in dense molecular clouds: Theory and observational constraints

NASA Technical Reports Server (NTRS)

Blake, Geoffrey A.

1990-01-01

For the most part, gas phase models of the chemistry of dense molecular clouds predict the abundances of simple species rather well. However, for larger molecules and even for small systems rich in carbon these models often fail spectacularly. Researchers present a brief review of the basic assumptions and results of large scale modeling of the carbon chemistry in dense molecular clouds. Particular attention is to the influence of the gas phase C/O ratio in molecular clouds, and the likely role grains play in maintaining this ratio as clouds evolve from initially diffuse objects to denser cores with associated stellar and planetary formation. Recent spectral line surveys at centimeter and millimeter wavelengths along with selected observations in the submillimeter have now produced an accurate inventory of the gas phase carbon budget in several different types of molecular clouds, though gaps in our knowledge clearly remain. The constraints these observations place on theoretical models of interstellar chemistry can be used to gain insights into why the models fail, and show also which neglected processes must be included in more complete analyses. Looking toward the future, larger molecules are especially difficult to study both experimentally and theoretically in such dense, cold regions, and some new methods are therefore outlined which may ultimately push the detectability of small carbon chains and rings to much heavier species.

Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

PubMed

Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

2017-05-01

The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

Atomic and molecular physics in the gas phase

NASA Astrophysics Data System (ADS)

Toburen, L. H.

1990-09-01

The spatial and temporal distributions of energy deposition by high-linear-energy-transfer radiation play an important role in the subsequent chemical and biological processes leading to radiation damage. Because the spatial structures of energy deposition events are of the same dimensions as molecular structures in the mammalian cell, direct measurements of energy deposition distributions appropriate to radiation biology are infeasible. This has led to the development of models of energy transport based on a knowledge of atomic and molecular interactions process that enable one to simulate energy transfer on an atomic scale. Such models require a detailed understanding of the interactions of ions and electrons with biologically relevant material. During the past 20 years there has been a great deal of progress in our understanding of these interactions; much of it coming from studies in the gas phase. These studies provide information on the systematics of interaction cross sections leading to a knowledge of the regions of energy deposition where molecular and phase effects are important and that guide developments in appropriate theory. In this report studies of the doubly differential cross sections, crucial to the development of stochastic energy deposition calculations and track structure simulation, will be reviewed. Areas of understanding are discussed and directions for future work addressed. Particular attention is given to experimental and theoretical findings that have changed the traditional view of secondary electron production for charged particle interactions with atomic and molecular targets.

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

A mathematical approach to molecular organization and proteolytic disintegration of bacterial inclusion bodies.

PubMed

Cubarsi, R; Carrió, M M; Villaverde, A

2005-09-01

The in vivo proteolytic digestion of bacterial inclusion bodies (IBs) and the kinetic analysis of the resulting protein fragments is an interesting approach to investigate the molecular organization of these unconventional protein aggregates. In this work, we describe a set of mathematical instruments useful for such analysis and interpretation of observed data. These methods combine numerical estimation of digestion rate and approximation of its high-order derivatives, modelling of fragmentation events from a mixture of Poisson processes associated with differentiated protein species, differential equations techniques in order to estimate the mixture parameters, an iterative predictor-corrector algorithm for describing the flow diagram along the cascade process, as well as least squares procedures with minimum variance estimates. The models are formulated and compared with data, and successively refined to better match experimental observations. By applying such procedures as well as newer improved algorithms of formerly developed equations, it has been possible to model, for two kinds of bacterially produced aggregation prone recombinant proteins, their cascade digestion process that has revealed intriguing features of the IB-forming polypeptides.

Germline Transgenic Methods for Tracking Cells and Testing Gene Function during Regeneration in the Axolotl

PubMed Central

Khattak, Shahryar; Schuez, Maritta; Richter, Tobias; Knapp, Dunja; Haigo, Saori L.; Sandoval-Guzmán, Tatiana; Hradlikova, Kristyna; Duemmler, Annett; Kerney, Ryan; Tanaka, Elly M.

2013-01-01

The salamander is the only tetrapod that regenerates complex body structures throughout life. Deciphering the underlying molecular processes of regeneration is fundamental for regenerative medicine and developmental biology, but the model organism had limited tools for molecular analysis. We describe a comprehensive set of germline transgenic strains in the laboratory-bred salamander Ambystoma mexicanum (axolotl) that open up the cellular and molecular genetic dissection of regeneration. We demonstrate tissue-dependent control of gene expression in nerve, Schwann cells, oligodendrocytes, muscle, epidermis, and cartilage. Furthermore, we demonstrate the use of tamoxifen-induced Cre/loxP-mediated recombination to indelibly mark different cell types. Finally, we inducibly overexpress the cell-cycle inhibitor p16INK4a, which negatively regulates spinal cord regeneration. These tissue-specific germline axolotl lines and tightly inducible Cre drivers and LoxP reporter lines render this classical regeneration model molecularly accessible. PMID:24052945

Molecular vibrational energy flow

NASA Astrophysics Data System (ADS)

Gruebele, M.; Bigwood, R.

This article reviews some recent work in molecular vibrational energy flow (IVR), with emphasis on our own computational and experimental studies. We consider the problem in various representations, and use these to develop a family of simple models which combine specific molecular properties (e.g. size, vibrational frequencies) with statistical properties of the potential energy surface and wavefunctions. This marriage of molecular detail and statistical simplification captures trends of IVR mechanisms and survival probabilities beyond the abilities of purely statistical models or the computational limitations of full ab initio approaches. Of particular interest is IVR in the intermediate time regime, where heavy-atom skeletal modes take over the IVR process from hydrogenic motions even upon X H bond excitation. Experiments and calculations on prototype heavy-atom systems show that intermediate time IVR differs in many aspects from the early stages of hydrogenic mode IVR. As a result, IVR can be coherently frozen, with potential applications to selective chemistry.

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, Edoardo; Kowalski, Karol

The NorthWest Chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers[6, 28, 49]. It contains an umbrella of modules that today includes Self Consistent Field (SCF), second order Mller-Plesset perturbation theory (MP2), Coupled Cluster, multi-conguration selfconsistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics, Car-Parrinello molecular dynamics, classical molecular dynamics (MD), QM/MM,more » AIMD/MM, GIAO NMR, COSMO, COSMO-SMD, and RISM solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities[ 22]. Moreover new capabilities continue to be added with each new release.« less

Inferring phenomenological models of Markov processes from data

NASA Astrophysics Data System (ADS)

Rivera, Catalina; Nemenman, Ilya

Microscopically accurate modeling of stochastic dynamics of biochemical networks is hard due to the extremely high dimensionality of the state space of such networks. Here we propose an algorithm for inference of phenomenological, coarse-grained models of Markov processes describing the network dynamics directly from data, without the intermediate step of microscopically accurate modeling. The approach relies on the linear nature of the Chemical Master Equation and uses Bayesian Model Selection for identification of parsimonious models that fit the data. When applied to synthetic data from the Kinetic Proofreading process (KPR), a common mechanism used by cells for increasing specificity of molecular assembly, the algorithm successfully uncovers the known coarse-grained description of the process. This phenomenological description has been notice previously, but this time it is derived in an automated manner by the algorithm. James S. McDonnell Foundation Grant No. 220020321.

On simulation of local fluxes in molecular junctions

NASA Astrophysics Data System (ADS)

Cabra, Gabriel; Jensen, Anders; Galperin, Michael

2018-05-01

We present a pedagogical review of the current density simulation in molecular junction models indicating its advantages and deficiencies in analysis of local junction transport characteristics. In particular, we argue that current density is a universal tool which provides more information than traditionally simulated bond currents, especially when discussing inelastic processes. However, current density simulations are sensitive to the choice of basis and electronic structure method. We note that while discussing the local current conservation in junctions, one has to account for the source term caused by the open character of the system and intra-molecular interactions. Our considerations are illustrated with numerical simulations of a benzenedithiol molecular junction.

Photoelectron angular distributions for states of any mixed character: An experiment-friendly model for atomic, molecular, and cluster anions

NASA Astrophysics Data System (ADS)

Khuseynov, Dmitry; Blackstone, Christopher C.; Culberson, Lori M.; Sanov, Andrei

2014-09-01

We present a model for laboratory-frame photoelectron angular distributions in direct photodetachment from (in principle) any molecular orbital using linearly polarized light. A transparent mathematical approach is used to generalize the Cooper-Zare central-potential model to anionic states of any mixed character. In the limit of atomic-anion photodetachment, the model reproduces the Cooper-Zare formula. In the case of an initial orbital described as a superposition of s and p-type functions, the model yields the previously obtained s-p mixing formula. The formalism is further advanced using the Hanstorp approximation, whereas the relative scaling of the partial-wave cross-sections is assumed to follow the Wigner threshold law. The resulting model describes the energy dependence of photoelectron anisotropy for any atomic, molecular, or cluster anions, usually without requiring a direct calculation of the transition dipole matrix elements. As a benchmark case, we apply the p-d variant of the model to the experimental results for NO- photodetachment and show that the observed anisotropy trend is described well using physically meaningful values of the model parameters. Overall, the presented formalism delivers insight into the photodetachment process and affords a new quantitative strategy for analyzing the photoelectron angular distributions and characterizing mixed-character molecular orbitals using photoelectron imaging spectroscopy of negative ions.

Photoelectron angular distributions for states of any mixed character: an experiment-friendly model for atomic, molecular, and cluster anions.

PubMed

Khuseynov, Dmitry; Blackstone, Christopher C; Culberson, Lori M; Sanov, Andrei

2014-09-28

We present a model for laboratory-frame photoelectron angular distributions in direct photodetachment from (in principle) any molecular orbital using linearly polarized light. A transparent mathematical approach is used to generalize the Cooper-Zare central-potential model to anionic states of any mixed character. In the limit of atomic-anion photodetachment, the model reproduces the Cooper-Zare formula. In the case of an initial orbital described as a superposition of s and p-type functions, the model yields the previously obtained s-p mixing formula. The formalism is further advanced using the Hanstorp approximation, whereas the relative scaling of the partial-wave cross-sections is assumed to follow the Wigner threshold law. The resulting model describes the energy dependence of photoelectron anisotropy for any atomic, molecular, or cluster anions, usually without requiring a direct calculation of the transition dipole matrix elements. As a benchmark case, we apply the p-d variant of the model to the experimental results for NO(-) photodetachment and show that the observed anisotropy trend is described well using physically meaningful values of the model parameters. Overall, the presented formalism delivers insight into the photodetachment process and affords a new quantitative strategy for analyzing the photoelectron angular distributions and characterizing mixed-character molecular orbitals using photoelectron imaging spectroscopy of negative ions.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

PubMed Central

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes. PMID:25637996

Electrospray-assisted encapsulation of caffeine in alginate microhydrogels.

PubMed

Nikoo, Alireza Mehregan; Kadkhodaee, Rassoul; Ghorani, Behrouz; Razzaq, Hussam; Tucker, Nick

2018-05-02

One of the major challenges with microencapsulation and delivery of low molecular weight bioactive compounds is their diffusional loss during storage and process conditions as well as under gastric conditions. In an attempt to slow down the release rate of core material, electrospray fabricated calcium alginate microhydrogels were coated with low molecular weight and high molecular weight chitosans. Caffeine as a hydrophilic model compound was used due to its several advantages on human behavior especially increasing consciousness. Mathematical modeling of the caffeine release by fitting the data with Korsmeyer-Peppas model showed that Fick's diffusion law could be the prevalent mechanism of the release. Electrostatic interaction between alginate and chitosan (particularly in the presence of 1% low molecular weight chitosan) provided an effective barrier against caffeine release and significantly reduced swelling of particles compared to control samples. The results of this study demonstrated that calcium alginate microhydrogels coated by chitosan could be used for encapsulation of low molecular compounds. However, more complementary research must be done in this field. In addition, electrospray, by producing monodisperse particles, would be as an alternative method for fabrication of microparticles based on natural polymers. Copyright © 2018. Published by Elsevier B.V.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

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

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang

2012-12-15

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less

Uncovering a Predictive Molecular Signature for the Onset of NASH-Related Fibrosis in a Translational NASH Mouse Model.

PubMed

van Koppen, Arianne; Verschuren, Lars; van den Hoek, Anita M; Verheij, Joanne; Morrison, Martine C; Li, Kelvin; Nagabukuro, Hiroshi; Costessi, Adalberto; Caspers, Martien P M; van den Broek, Tim J; Sagartz, John; Kluft, Cornelis; Beysen, Carine; Emson, Claire; van Gool, Alain J; Goldschmeding, Roel; Stoop, Reinout; Bobeldijk-Pastorova, Ivana; Turner, Scott M; Hanauer, Guido; Hanemaaijer, Roeland

2018-01-01

The incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis. A time-course study in low-density lipoprotein-receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets. High-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis. An early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames.

From Reactor to Rheology in LDPE Modeling

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

Read, Daniel J.; Das, Chinmay; Auhl, Dietmar

2008-07-07

In recent years the association between molecular structure and linear rheology has been established and well-understood through the tube concept and its extensions for well-characterized materials (e.g. McLeish, Adv. Phys. 2002). However, for industrial branched polymeric material at processing conditions this piece of information is missing. A large number of phenomenological models have been developed to describe the nonlinear response of polymers. But none of these models takes into account the underlying molecular structure, leading to a fitting procedure with arbitrary fitting parameters. The goal of applied molecular rheology is a predictive scheme that runs in its entirety from themore » molecular structure from the reactor to the non-linear rheology of the resin. In our approach, we use a model for the industrial reactor to explicitly generate the molecular structure ensemble of LDPE's, (Tobita, J. Polym. Sci. B 2001), which are consistent with the analytical information. We calculate the linear rheology of the LDPE ensemble with the use of a tube model for branched polymers (Das et al., J. Rheol. 2006). We then, separate the contribution of the stress decay to a large number of pompom modes (McLeish et al., J. Rheol. 1998 and Inkson et al., J. Rheol. 1999) with the stretch time and the priority variables corresponding to the actual ensemble of molecules involved. This multimode pompom model allows us to predict the nonlinear properties without any fitting parameter. We present and analyze our results in comparison with experimental data on industrial materials.« less

Molecular recognition of the environment and mechanisms of the origin of species in quantum-like modeling of evolution.

PubMed

Melkikh, Alexey V; Khrennikov, Andrei

2017-11-01

A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown that these mechanisms, at the molecular level, cannot work steadily in terms of classical mechanics. Quantum mechanisms of changes in the genome, based on the long-range interaction potential between biologically important molecules, are proposed as one of possible explanation. Different variants of interactions of the organism and environment based on molecular recognition and leading to new species origins are considered. Experiments to verify the model are proposed. This bio-physical study is completed by the general operational model of based on quantum information theory. The latter is applied to model of epigenetic evolution. We briefly present the basics of the quantum-like approach to modeling of bio-informational processes. This approach is illustrated by the quantum-like model of epigenetic evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deconstructing (and reconstructing) cell migration.

PubMed

Maheshwari, G; Lauffenburger, D A

1998-12-01

An overriding objective in cell biology is to be able to relate properties of particular molecular components to cell behavioral functions and even physiology. In the "traditional" mode of molecular cell biology, this objective has been tackled on a molecule-by-molecule basis, and in the "future" mode sometimes termed "functional genomics," it might be attacked in a high-throughput, parallel manner. Regardless of the manner of approach, the relationship between molecular-level properties and cell-level function is exceedingly difficult to elucidate because of the large number of relevant components involved, their high degree of interconnectedness, and the inescapable fact that they operate as physico-chemical entities-according to the laws of kinetics and mechanics-in space and time within the cell. Cell migration is a prominent representative example of such a cell behavioral function that requires increased understanding for both scientific and technological advance. This article presents a framework, derived from an engineering perspective regarding complex systems, intended to aid in developing improved understanding of how properties of molecular components influence the function of cell migration. That is, cell population migration behavior can be deconstructed as follows: first in terms of a mathematical model comprising cell population parameters (random motility, chemotaxis/haptotaxis, and chemokinesis/haptokinesis coefficients), which in turn depend on characteristics of individual cell paths that can be analyzed in terms of a mathematical model comprising individual cell parameters (translocation speed, directional persistence time, chemotactic/haptotactic index), which in turn depend on cell-level physical processes underlying motility (membrane extension and retraction, cell/substratum adhesion, cell contractile force, front-vs.-rear asymmetry), which in turn depend on molecular-level properties of the plethora of components involved in governance and regulation of these processes. Hence, the influence of any molecular component on cell population migration can be understood by reconstructing these relationships from the molecular level to the physical process level to the individual cell path level to the cell population distribution level. This approach requires combining experimental, theoretical, and computational methodologies from molecular biology, biochemistry, biophysics, and bioengineering.

Molecular Structure and Sequence in Complex Coacervates

NASA Astrophysics Data System (ADS)

Sing, Charles; Lytle, Tyler; Madinya, Jason; Radhakrishna, Mithun

Oppositely-charged polyelectrolytes in aqueous solution can undergo associative phase separation, in a process known as complex coacervation. This results in a polyelectrolyte-dense phase (coacervate) and polyelectrolyte-dilute phase (supernatant). There remain challenges in understanding this process, despite a long history in polymer physics. We use Monte Carlo simulation to demonstrate that molecular features (charge spacing, size) play a crucial role in governing the equilibrium in coacervates. We show how these molecular features give rise to strong monomer sequence effects, due to a combination of counterion condensation and correlation effects. We distinguish between structural and sequence-based correlations, which can be designed to tune the phase diagram of coacervation. Sequence effects further inform the physical understanding of coacervation, and provide the basis for new coacervation models that take monomer-level features into account.

Animation Model to Conceptualize ATP Generation: A Mitochondrial Oxidative Phosphorylation

ERIC Educational Resources Information Center

Jena, Ananta Kumar

2015-01-01

Adenosine triphosphate (ATP) is the molecular unit of intracellular energy and it is the product of oxidative phosphorylation of cellular respiration uses in cellular processes. The study explores the growth of the misconception levels amongst the learners and evaluates the effectiveness of animation model over traditional methods. The data…

Laboratory and modeling studies of chemistry in dense molecular clouds

NASA Technical Reports Server (NTRS)

Huntress, W. T., Jr.; Prasad, S. S.; Mitchell, G. F.

1980-01-01

A chemical evolutionary model with a large number of species and a large chemical library is used to examine the principal chemical processes in interstellar clouds. Simple chemical equilibrium arguments show the potential for synthesis of very complex organic species by ion-molecule radiative association reactions.

Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

NASA Astrophysics Data System (ADS)

Kovalenko, Andriy

2014-08-01

Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology enables rational design of CNC-based bionanocomposite materials and systems. Furthermore, the 3D-RISM-KH based multiscale modeling addresses the effect of hemicellulose and lignin composition on nanoscale forces that control cell wall strength towards overcoming plant biomass recalcitrance. It reveals molecular forces maintaining the cell wall structure and provides directions for genetic modulation of plants and pretreatment design to render biomass more amenable to processing. We envision integrated biomass valorization based on extracting and decomposing the non-cellulosic components to low molecular weight chemicals and utilizing the cellulose microfibrils to make CNC. This is an important alternative to approaches of full conversion of lignocellulose to biofuels that face challenges arising from the deleterious impact of cellulose crystallinity on enzymatic processing.

QSAR and molecular modelling studies on B-DNA recognition of minor groove binders.

PubMed

de Oliveira, André Mauricio; Custódio, Flávia Beatriz; Donnici, Cláudio Luis; Montanari, Carlos Alberto

2003-02-01

Aromatic bisamidines have been proved to be efficient compounds against Leishmania spp. and Pneumocystis carinii. Although the mode of action is still not known, these molecules are supposed to be DNA minor groove binders (MGBs). This paper describes a molecular modelling study for a set of MGBs in order to rank them through their complementarity to the Dickerson Drew Dodecamer (DDD) according to their interaction energies with B-DNA. A comparative molecular field analysis (CoMFA) has shown the importance of relatively bulky positively charged groups attached to the MGB aromatic rings, and small and negatively charged substituents into the middle chain. Models were obtained for DNA denaturation related to H-bonding processes of binding modes. Validation of the model demonstrated the robustness of CoMFA in terms of independent test set of similar MGBs. GRID results allotted bioisosteric substitution of z.sbnd;Oz.sbnd; by z.sbnd;NHz.sbnd; in furan ring of furamidine and related compounds as being capable to enhance the binding to DDD.

Zebrafish models flex their muscles to shed light on muscular dystrophies.

PubMed

Berger, Joachim; Currie, Peter D

2012-11-01

Muscular dystrophies are a group of genetic disorders that specifically affect skeletal muscle and are characterized by progressive muscle degeneration and weakening. To develop therapies and treatments for these diseases, a better understanding of the molecular basis of muscular dystrophies is required. Thus, identification of causative genes mutated in specific disorders and the study of relevant animal models are imperative. Zebrafish genetic models of human muscle disorders often closely resemble disease pathogenesis, and the optical clarity of zebrafish embryos and larvae enables visualization of dynamic molecular processes in vivo. As an adjunct tool, morpholino studies provide insight into the molecular function of genes and allow rapid assessment of candidate genes for human muscular dystrophies. This unique set of attributes makes the zebrafish model system particularly valuable for the study of muscle diseases. This review discusses how recent research using zebrafish has shed light on the pathological basis of muscular dystrophies, with particular focus on the muscle cell membrane and the linkage between the myofibre cytoskeleton and the extracellular matrix.

Insights using the molecular model of Lipoxygenase from Finger millet (Eleusine coracana (L.)).

PubMed

Tiwari, Apoorv; Avashthi, Himanshu; Jha, Richa; Srivastava, Ambuj; Kumar Garg, Vijay; Wasudev Ramteke, Pramod; Kumar, Anil

2016-01-01

Lipoxygenase-1 (LOX-1) protein provides defense against pests and pathogens and its presence have been positively correlated with plant resistance against pathogens. Linoleate is a known substrate of lipoxygenase and it induces necrosis leading to the accumulation of isoflavonoid phytoalexins in plant leaves. Therefore, it is of interest to study the structural features of LOX-1 from Finger millet. However, the structure ofLOX-1 from Finger millet is not yet known. A homology model of LOX-1 from Finger millet is described. Domain architecture study suggested the presence of two domains namely PLAT (Phospho Lipid Acyl Transferase) and lipoxygenase. Molecular docking models of linoleate with lipoxygenase from finger millet, rice and sorghum are reported. The features of docked models showed that finger millet have higher pathogen resistance in comparison to other cereal crops. This data is useful for the molecular cloning of fulllength LOX-1 gene for validating its role in improving plant defense against pathogen infection and for various other biological processes.

Interwell Connectivity Evaluation Using Injection and Production Fluctuation Data

NASA Astrophysics Data System (ADS)

Shang, Barry Zhongqi

The development of multiscale methods for computational simulation of biophysical systems represents a significant challenge. Effective computational models that bridge physical insights obtained from atomistic simulations and experimental findings are lacking. An accurate passing of information between these scales would enable: (1) an improved physical understanding of structure-function relationships, and (2) enhanced rational strategies for molecular engineering and materials design. Two approaches are described in this dissertation to facilitate these multiscale goals. In Part I, we develop a lattice kinetic Monte Carlo model to simulate cellulose decomposition by cellulase enzymes and to understand the effects of spatial confinement on enzyme kinetics. An enhanced mechanistic understanding of this reaction system could enhance the design of cellulose bioconversion technologies for renewable and sustainable energy. Using our model, we simulate the reaction up to experimental conversion times of days, while simultaneously capturing the microscopic kinetic behaviors. Therefore, the influence of molecular-scale kinetics on the macroscopic conversion rate is made transparent. The inclusion of spatial constraints in the kinetic model represents a significant advance over classical mass-action models commonly used to describe this reaction system. We find that restrictions due to enzyme jamming and substrate heterogeneity at the molecular level play a dominate role in limiting cellulose conversion. We identify that the key rate limitations are the slow rates of enzyme complexation with glucan chains and the competition between enzyme processivity and jamming. We show that the kinetics of complexation, which involves extraction of a glucan chain end from the cellulose surface and threading through the enzyme active site, occurs slowly on the order of hours, while intrinsic hydrolytic bond cleavage occurs on the order of seconds. We also elucidate the subtle trade-off between processivity and jamming. Highly processive enzymes cleave a large fraction of a glucan chain during each processive run but are prone to jamming at obstacles. Less processive enzymes avoid jamming but cleave only a small fraction of a chain. Optimizing this trade-off maximizes the cellulose conversion rate. We also elucidate the molecular-scale kinetic origins for synergy among cellulases in enzyme mixtures. In contrast to the currently accepted theory, we show that the ability of an endoglucanase to increase the concentration of chain ends for exoglucanases is insufficient for synergy to occur. Rather, endoglucanases must enhance the rate of complexation between exoglucanases and the newly created chain ends. This enhancement occurs when the endoglucanase is able to partially decrystallize the cellulose surface. We show generally that the driving forces for complexation and jamming, which govern the kinetics of pure exoglucanases, also control the degree of synergy in endo-exo mixtures. In Part II, we focus our attention on a different multiscale problem. This challenge is the development of coarse-grained models from atomistic models to access larger length- and time-scales in a simulation. This problem is difficult because it requires a delicate balance between maintaining (1) physical simplicity in the coarse-grained model and (2) physical consistency with the atomistic model. To achieve these goals, we develop a scheme to coarse-grain an atomistic fluid model into a fluctuating hydrodynamics (FHD) model. The FHD model describes the solvent as a field of fluctuating mass, momentum, and energy densities. The dynamics of the fluid are governed by continuum balance equations and fluctuation-dissipation relations based on the constitutive transport laws. The incorporation of both macroscopic transport and microscopic fluctuation phenomena could provide richer physical insight into the behaviors of biophysical systems driven by hydrodynamic fluctuations, such as hydrophobic assembly and crystal nucleation. We further extend our coarse-graining method by developing an interfacial FHD model using information obtained from simulations of an atomistic liquid-vapor interface. We illustrate that a phenomenological Ginzburg-Landau free energy employed in the FHD model can effectively represent the attractive molecular interactions of the atomistic model, which give rise to phase separation. For argon and water, we show that the interfacial FHD model can reproduce the compressibility, surface tension, and capillary wave spectrum of the atomistic model. Via this approach, simulations that explore the coupling between hydrodynamic fluctuations and phase equilibria with molecular-scale consistency are now possible. In both Parts I and II, the emerging theme is that the combination of bottom-up coarse graining and top-down phenomenology is essential for enabling a multiscale approach to remain physically consistent with molecular-scale interactions while simultaneously capturing the collective macroscopic behaviors. This hybrid strategy enables the resulting computational models to be both physically insightful and practically meaningful. (Abstract shortened by UMI.).

On The Development of Biophysical Models for Space Radiation Risk Assessment

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Dicello, J. F.

1999-01-01

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression.

Thermodynamic properties for applications in chemical industry via classical force fields.

PubMed

Guevara-Carrion, Gabriela; Hasse, Hans; Vrabec, Jadran

2012-01-01

Thermodynamic properties of fluids are of key importance for the chemical industry. Presently, the fluid property models used in process design and optimization are mostly equations of state or G (E) models, which are parameterized using experimental data. Molecular modeling and simulation based on classical force fields is a promising alternative route, which in many cases reasonably complements the well established methods. This chapter gives an introduction to the state-of-the-art in this field regarding molecular models, simulation methods, and tools. Attention is given to the way modeling and simulation on the scale of molecular force fields interact with other scales, which is mainly by parameter inheritance. Parameters for molecular force fields are determined both bottom-up from quantum chemistry and top-down from experimental data. Commonly used functional forms for describing the intra- and intermolecular interactions are presented. Several approaches for ab initio to empirical force field parameterization are discussed. Some transferable force field families, which are frequently used in chemical engineering applications, are described. Furthermore, some examples of force fields that were parameterized for specific molecules are given. Molecular dynamics and Monte Carlo methods for the calculation of transport properties and vapor-liquid equilibria are introduced. Two case studies are presented. First, using liquid ammonia as an example, the capabilities of semi-empirical force fields, parameterized on the basis of quantum chemical information and experimental data, are discussed with respect to thermodynamic properties that are relevant for the chemical industry. Second, the ability of molecular simulation methods to describe accurately vapor-liquid equilibrium properties of binary mixtures containing CO(2) is shown.

Mechanistic Investigation on Grinding-Induced Subvisible Particle Formation during Mixing and Filling of Monoclonal Antibody Formulations.

PubMed

Gikanga, Benson; Hui, Ada; Maa, Yuh-Fun

2018-01-01

Processing equipment involving grinding of two solid surfaces has been demonstrated to induce subvisible particle formation in monoclonal antibody drug product manufacturing processes. This study elucidated potential stress types associated with grinding action to identify the stress mechanism responsible for subvisible particle formation. Several potential stress types can be associated with the grinding action, including interfacial stresses (air-liquid and liquid-solid), hydraulic/mechanical shear stress, cavitation, nucleation of stressed protein molecules, and localized thermal stress. More than one stress type can synergically affect monoclonal antibody product quality, making it challenging to determine the primary mode of stress. Our strategy was to assess and rule out some stress types through platform knowledge, rational judgments, or via small-scale models, for example, rheometer/rotator-stator homogenizer for hydraulic/mechanical shear stress, sonicator for cavitation, etc. These models may not provide direct evidence but can offer rational correlations. Cavitation, as demonstrated by sonication, proved to be quite detrimental to monoclonal antibody molecules in forming not just subvisible particles but also soluble high-molecular-weight species as well as low-molecular-weight species. This outcome was not consistent with that of grinding monoclonal antibodies between the impeller and the drive unit of a bottom-mounted mixer or between the piston and the housing of a rotary piston pump, both of which formed only subvisible particles without obvious high-molecular-weight species and low-molecular-weight species. In addition, a p -nitrophenol model suggested that cavitation in the bottom-mounted mixer is barely detectable. We attributed the grinding-induced, localized thermal effect to be the primary stress to subvisible particle formation based on a high-temperature, spray-drying model. The heat effect of spray drying also caused subvisible particles, in the absence of significant high-molecular-weight species and low-molecular-weight species, in spray-dried monoclonal antibody powders. This investigation provides a mechanistic understanding of the underlying stress mechanism leading to monoclonal antibody subvisible particle formation as the result of drug product processing involving grinding of solid surfaces. LAY ABSTRACT: Subvisible particles present in therapeutic protein formulations could adversely affect drug product safety and efficacy. We previously illustrated that grinding action of the solid surfaces in some bottom-mounted mixers and piston pump is responsible for subvisible particle formation of monoclonal antibody formulations. In this study, we delved into mechanistic understanding of the stress types associated with solid surface grinding. The approach was to employ several scale-down stress models with known stress types. Protein formulations stressed in these models were analytically characterized for subvisible particles and other degradants. Some commonly known stress types-such as air-liquid interface, mechanical stress, cavitation, nucleation, and thermal effect-were assessed in this study. The stress model yielding a degradation profile matching that of bottom-mounted mixers and piston pump warranted further assessment. Localized, thermal stress proved to be the most feasible mechanism. This study, along with previously published results, may further advance our understanding of these particular drug product manufacturing processes and benefit scientists and engineers in overcoming these development challenges. © PDA, Inc. 2018.

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.

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

PubMed Central

2011-01-01

Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis. PMID:21375730

An Interdisciplinary Approach for Designing Kinetic Models of the Ras/MAPK Signaling Pathway.

PubMed

Reis, Marcelo S; Noël, Vincent; Dias, Matheus H; Albuquerque, Layra L; Guimarães, Amanda S; Wu, Lulu; Barrera, Junior; Armelin, Hugo A

2017-01-01

We present in this article a methodology for designing kinetic models of molecular signaling networks, which was exemplarily applied for modeling one of the Ras/MAPK signaling pathways in the mouse Y1 adrenocortical cell line. The methodology is interdisciplinary, that is, it was developed in a way that both dry and wet lab teams worked together along the whole modeling process.

Direct molecular dynamics simulation of Ge deposition on amorphous SiO 2 at experimentally relevant conditions

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

Chuang, Claire Y.; Zepeda-Ruiz, Luis A.; Han, Sang M.

2015-06-01

Molecular dynamics simulations were used to study Ge island nucleation and growth on amorphous SiO 2 substrates. This process is relevant in selective epitaxial growth of Ge on Si, for which SiO 2 is often used as a template mask. The islanding process was studied over a wide range of temperatures and fluxes, using a recently proposed empirical potential model for the Si–SiO 2–Ge system. The simulations provide an excellent quantitative picture of the Ge islanding and compare well with detailed experimental measurements. These quantitative comparisons were enabled by an analytical rate model as a bridge between simulations and experimentsmore » despite the fact that deposition fluxes accessible in simulations and experiments are necessarily different by many orders of magnitude. In particular, the simulations led to accurate predictions of the critical island size and the scaling of island density as a function of temperature. Lastly, the overall approach used here should be useful not just for future studies in this particular system, but also for molecular simulations of deposition in other materials.« less

Molecular Modeling of a Probe in 2D IR Spectroscopy

NASA Astrophysics Data System (ADS)

Cooper, Anthony; Larini, Luca

Proteins must adopt a precise three dimensional structure in the folding process in order to perform its designated function. Although much has been learned about folding, there are still many details in structural dynamics that are difficult to characterize by existing experimental techniques. In order to overcome these challenges, novel infrared and fluorescent spectroscopic techniques have recently been employed to probe the molecular structure at the atomistic scale. These techniques rely on the spectroscopic properties of the nitrile group attached to a phenylalanine. In this study, we model this probe and we compute its properties in different solvents. This is done by performing Molecular Dynamics simulations with a PheCN solvated in water, urea and TMAO. We measure the decay rate of the vibrational stretching of the CN group in order to characterize the effects of different solvents on the local structure of the molecule. This data can be used to identify non-trivial conformational changes of the protein in the folding process. Preliminary results show agreement with current experimental data on 2D IR spectroscopy.

Development of reactive force fields using ab initio molecular dynamics simulation minimally biased to experimental data

NASA Astrophysics Data System (ADS)

Chen, Chen; Arntsen, Christopher; Voth, Gregory A.

2017-10-01

Incorporation of quantum mechanical electronic structure data is necessary to properly capture the physics of many chemical processes. Proton hopping in water, which involves rearrangement of chemical and hydrogen bonds, is one such example of an inherently quantum mechanical process. Standard ab initio molecular dynamics (AIMD) methods, however, do not yet accurately predict the structure of water and are therefore less than optimal for developing force fields. We have instead utilized a recently developed method which minimally biases AIMD simulations to match limited experimental data to develop novel multiscale reactive molecular dynamics (MS-RMD) force fields by using relative entropy minimization. In this paper, we present two new MS-RMD models using such a parameterization: one which employs water with harmonic internal vibrations and another which uses anharmonic water. We show that the newly developed MS-RMD models very closely reproduce the solvation structure of the hydrated excess proton in the target AIMD data. We also find that the use of anharmonic water increases proton hopping, thereby increasing the proton diffusion constant.

Overdispersion of the Molecular Clock: Temporal Variation of Gene-Specific Substitution Rates in Drosophila

PubMed Central

Hartl, Daniel L.

2008-01-01

Simple models of molecular evolution assume that sequences evolve by a Poisson process in which nucleotide or amino acid substitutions occur as rare independent events. In these models, the expected ratio of the variance to the mean of substitution counts equals 1, and substitution processes with a ratio greater than 1 are called overdispersed. Comparing the genomes of 10 closely related species of Drosophila, we extend earlier evidence for overdispersion in amino acid replacements as well as in four-fold synonymous substitutions. The observed deviation from the Poisson expectation can be described as a linear function of the rate at which substitutions occur on a phylogeny, which implies that deviations from the Poisson expectation arise from gene-specific temporal variation in substitution rates. Amino acid sequences show greater temporal variation in substitution rates than do four-fold synonymous sequences. Our findings provide a general phenomenological framework for understanding overdispersion in the molecular clock. Also, the presence of substantial variation in gene-specific substitution rates has broad implications for work in phylogeny reconstruction and evolutionary rate estimation. PMID:18480070

Using Carbon-14 Isotope Tracing to Investigate Molecular Structure Effects of the Oxygenate Dibutyl Maleate on Soot Emissions from a DI Diesel Engine

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

Buchholz, B A; Mueller, C J; Upatnieks, A

2004-01-07

The effect of oxygenate molecular structure on soot emissions from a DI diesel engine was examined using carbon-14 ({sup 14}C) isotope tracing. Carbon atoms in three distinct chemical structures within the diesel oxygenate dibutyl maleate (DBM) were labeled with {sup 14}C. The {sup 14}C from the labeled DBM was then detected in engine-out particulate matter (PM), in-cylinder deposits, and CO{sub 2} emissions using accelerator mass spectrometry (AMS). The results indicate that molecular structure plays an important role in determining whether a specific carbon atom either does or does not form soot. Chemical-kinetic modeling results indicate that structures that produce CO{submore » 2} directly from the fuel are less effective at reducing soot than structures that produce CO before producing CO{sub 2}. Because they can follow individual carbon atoms through a real combustion process, {sup 14}C isotope tracing studies help strengthen the connection between actual engine emissions and chemical-kinetic models of combustion and soot formation/oxidation processes.« less

Studying the Brain in a Dish: 3D Cell Culture Models of Human Brain Development and Disease.

PubMed

Brown, Juliana; Quadrato, Giorgia; Arlotta, Paola

2018-01-01

The study of the cellular and molecular processes of the developing human brain has been hindered by access to suitable models of living human brain tissue. Recently developed 3D cell culture models offer the promise of studying fundamental brain processes in the context of human genetic background and species-specific developmental mechanisms. Here, we review the current state of 3D human brain organoid models and consider their potential to enable investigation of complex aspects of human brain development and the underpinning of human neurological disease. © 2018 Elsevier Inc. All rights reserved.

An Examination of the Evolution of Radiation and Advection Fogs

DTIC Science & Technology

1993-01-01

and fog diagnostic and prediction models have developed in sophistication so that they can reproduce fairly accurate one- or two-dimensional...occurred only by molecular diffusion near the interface created between the species during the mixing process. The rate of homogenization is minimal until...of excess vapor by molecular diffusion at the interfaces of nearly saturated air mixing in eddies is faster than the relaxation time of droplet

A study of water uptake by selected superdisintegrants from the sub-molecular to the particulate level.

PubMed

Barmpalexis, P; Syllignaki, P; Kachrimanis, K

2018-06-01

Water diffusion through the matrix of three superdisintegrants, namely sodium starch glycolate (SSG), croscarmellose sodium (cCMC-Na) and crospovidone (cPVP), was studied at the sub-molecular level using Attenuated Total Reflectance (ATR)-FTIR spectroscopy and molecular dynamics simulations, and the results were correlated to water uptake studies conducted at the particulate level using Parallel Exponential Kinetics (PEK) modeling in dynamic moisture sorption studies and optical microscopy. ATR-FTIR studies indicated that water diffuses inside cPVP by a single fast acting process, while in SSG and cCMC-Na, a slow and a fast process acting simultaneously, were identified. The same pattern regarding the rate of water uptake for all superdisintegrants was found also at the particulate level by PEK modeling. Moreover, molecular dynamics simulation helped elucidate the hydrogen bonding patterns formed between water-SSG and water-cCMC-Na, mainly via their carboxylic oxygen atoms and secondarily via their hydroxyl groups, while cPVP formed hydrogen bonds only through carbonyl oxygen. Finally, cPVP chains showed significant flexibility during hydration, while cCMC-Na and SSG chains retain their conformation to some extent, explaining the extensive swelling observed also at the particulate level by optical microscopy hydration studies.

Crystallization kinetics and molecular mobility of an amorphous active pharmaceutical ingredient: A case study with Biclotymol.

PubMed

Schammé, Benjamin; Couvrat, Nicolas; Malpeli, Pascal; Delbreilh, Laurent; Dupray, Valérie; Dargent, Éric; Coquerel, Gérard

2015-07-25

The present case study focuses on the crystallization kinetics and molecular mobility of an amorphous mouth and throat drug namely Biclotymol, through differential scanning calorimetry (DSC), temperature resolved X-ray powder diffraction (TR-XRPD) and hot stage microscopy (HSM). Kinetics of crystallization above the glass transition through isothermal and non-isothermal cold crystallization were considered. Avrami model was used for isothermal crystallization process. Non-isothermal cold crystallization was investigated through Augis and Bennett model. Differences between crystallization processes have been ascribed to a site-saturated nucleation mechanism of the metastable form, confirmed by optical microscopy images. Regarding molecular mobility, a feature of molecular dynamics in glass-forming liquids as thermodynamic fragility index m was determined through calorimetric measurements. It turned out to be around m=100, describing Biclotymol as a fragile glass-former for Angell's classification. Relatively long-term stability of amorphous Biclotymol above Tg was analyzed indirectly by calorimetric monitoring to evaluate thermodynamic parameters and crystallization behavior of glassy Biclotymol. Within eight months of storage above Tg (T=Tg+2°C), amorphous Biclotymol does not show a strong inclination to crystallize and forms a relatively stable glass. This case study, involving a multidisciplinary approach, points out the importance of continuing looking for stability predictors. Copyright © 2015 Elsevier B.V. All rights reserved.

Two-dimensional ice mapping of molecular cores

NASA Astrophysics Data System (ADS)

Noble, J. A.; Fraser, H. J.; Pontoppidan, K. M.; Craigon, A. M.

2017-06-01

We present maps of the column densities of H2O, CO2 and CO ices towards the molecular cores B 35A, DC 274.2-00.4, BHR 59 and DC 300.7-01.0. These ice maps, probing spatial distances in molecular cores as low as 2200 au, challenge the traditional hypothesis that the denser the region observed, the more ice is present, providing evidence that the relationships between solid molecular species are more varied than the generic picture we often adopt to model gas-grain chemical processes and explain feedback between solid phase processes and gas phase abundances. We present the first combined solid-gas maps of a single molecular species, based upon observations of both CO ice and gas phase C18O towards B 35A, a star-forming dense core in Orion. We conclude that molecular species in the solid phase are powerful tracers of 'small-scale' chemical diversity, prior to the onset of star formation. With a component analysis approach, we can probe the solid phase chemistry of a region at a level of detail greater than that provided by statistical analyses or generic conclusions drawn from single pointing line-of-sight observations alone.

Fundamental data on the desorption of pure interstellar ices

NASA Astrophysics Data System (ADS)

Brown, Wendy A.; Bolina, Amandeep S.

2007-01-01

The desorption of molecular ices from grain surfaces is important in a number of astrophysical environments including dense molecular clouds, cometary nuclei and the surfaces and atmospheres of some planets. With this in mind, we have performed a detailed investigation of the desorption of pure water, pure methanol and pure ammonia ices from a model dust-grain surface. We have used these results to determine the desorption energy, order of desorption and the pre-exponential factor for the desorption of these molecular ices from our model surface. We find good agreement between our desorption energies and those determined previously; however, our values for the desorption orders, and hence also the pre-exponential factors, are different to those reported previously. The kinetic parameters derived from our data have been used to model desorption on time-scales relevant to astrophysical processes and to calculate molecular residence times, given in terms of population half-life as a function of temperature. These results show the importance of laboratory data for the understanding of astronomical situations whereby icy mantles are warmed by nearby stars and by other dynamical events.

Anti-inflammatory activity and molecular mechanism of delphinidin 3-sambubioside, a Hibiscus anthocyanin.

PubMed

Sogo, Takayuki; Terahara, Norihiko; Hisanaga, Ayami; Kumamoto, Takuma; Yamashiro, Takaaki; Wu, Shusong; Sakao, Kozue; Hou, De-Xing

2015-01-01

Delphinidin 3-sambubioside (Dp3-Sam), a Hibiscus anthocyanin, was isolated from the dried calices of Hibiscus sabdariffa L, which has been used for folk beverages and herbal medicine although the molecular mechanisms are poorly defined. Based on the properties of Dp3-Sam and the information of inflammatory processes, we investigated the anti-inflammatory activity and molecular mechanisms in both cell and animal models in the present study. In the cell model, Dp3-Sam and Delphinidin (Dp) reduced the levels of inflammatory mediators including iNOS, NO, IL-6, MCP-1, and TNF-α induced by LPS. Cellular signaling analysis revealed that Dp3-Sam and Dp downregulated NF-κB pathway and MEK1/2-ERK1/2 signaling. In animal model, Dp3-Sam and Dp reduced the production of IL-6, MCP-1 and TNF-α and attenuated mouse paw edema induced by LPS. Our in vitro and in vivo data demonstrated that Hibiscus Dp3-Sam possessed potential anti-inflammatory properties. © 2015 International Union of Biochemistry and Molecular Biology.

Engineering controllable bidirectional molecular motors based on myosin

PubMed Central

Chen, Lu; Nakamura, Muneaki; Schindler, Tony D.; Parker, David; Bryant, Zev

2012-01-01

Cytoskeletal motors drive the transport of organelles and molecular cargoes within cells1, and have potential applications in molecular detection and diagnostic devices2,3. Engineering molecular motors with dynamically controllable properties will allow selective perturbation of mechanical processes in living cells, and yield optimized device components for complex tasks such as molecular sorting and directed assembly3. Biological motors have previously been modified by introducing activation/deactivation switches that respond to metal ions4,5 and other signals6. Here we show that myosin motors can be engineered to reversibly change their direction of motion in response to a calcium signal. Building on previous protein engineering studies7–11 and guided by a structural model12 for the redirected power stroke of myosin VI, we constructed bidirectional myosins through the rigid recombination of structural modules. The performance of the motors was confirmed using gliding filament assays and single fluorophore tracking. Our general strategy, in which external signals trigger changes in the geometry and mechanics of myosin lever arms, should enable spatiotemporal control over a range of motor properties including processivity, stride size13, and branchpoint turning14. PMID:22343382

Engineering controllable bidirectional molecular motors based on myosin

NASA Astrophysics Data System (ADS)

Chen, Lu; Nakamura, Muneaki; Schindler, Tony D.; Parker, David; Bryant, Zev

2012-04-01

Cytoskeletal motors drive the transport of organelles and molecular cargoes within cells and have potential applications in molecular detection and diagnostic devices. Engineering molecular motors with controllable properties will allow selective perturbation of mechanical processes in living cells and provide optimized device components for tasks such as molecular sorting and directed assembly. Biological motors have previously been modified by introducing activation/deactivation switches that respond to metal ions and other signals. Here, we show that myosin motors can be engineered to reversibly change their direction of motion in response to a calcium signal. Building on previous protein engineering studies and guided by a structural model for the redirected power stroke of myosin VI, we have constructed bidirectional myosins through the rigid recombination of structural modules. The performance of the motors was confirmed using gliding filament assays and single fluorophore tracking. Our strategy, in which external signals trigger changes in the geometry and mechanics of myosin lever arms, should make it possible to achieve spatiotemporal control over a range of motor properties including processivity, stride size and branchpoint turning.

Molecular dynamics of reversible self-healing materials

NASA Astrophysics Data System (ADS)

Madden, Ian; Luijten, Erik

Hydrolyzable polymers have numerous industrial applications as degradable materials. Recent experimental work by Cheng and co-workers has introduced the concept of hindered urea bond (HUB) chemistry to design self-healing systems. Important control parameters are the steric hindrance of the HUB structures, which is used to tune the hydrolytic degradation kinetics, and their density. We employ molecular dynamics simulations of polymeric interfaces to systematically explore the role of these properties in a coarse-grained model, and make direct comparison to experimental data. Our model provides direct insight into the self-healing process, permitting optimization of the control parameters.

Modelling of Molecular Structures and Properties. Proceedings of the International Meeting of Physical Chemistry on Modeling of Molecular Structures and Properties in Physical Chemistry and Biophysics Organized by the Division de Chimie Physique of the Societe Francaise de Chimie Held in Nancy, France on 11-15 September 1989

DTIC Science & Technology

1990-01-01

expert systems, "intelligent" computer-aided instruction , symbolic learning . These aspects will be discussed, focusing on the specific problems the...VLSI chips) according to preliminary specifications. Finally ES are also used in computer-aided instruction (CAI) due to their ability of... instructions to process controllers), academic teaching (for mathematics , physics, foreign language, etc.). Domains of application The different

3D molecular models of whole HIV-1 virions generated with cellPACK

PubMed Central

Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection

PubMed Central

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung. PMID:28912729

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

PubMed

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

Homogenous Nucleation and Crystal Growth in a Model Liquid from Direct Energy Landscape Sampling Simulation

NASA Astrophysics Data System (ADS)

Walter, Nathan; Zhang, Yang

Nucleation and crystal growth are understood to be activated processes involving the crossing of free-energy barriers. Attempts to capture the entire crystallization process over long timescales with molecular dynamic simulations have met major obstacles because of molecular dynamics' temporal constraints. Herein, we circumvent this temporal limitation by using a brutal-force, metadynamics-like, adaptive basin-climbing algorithm and directly sample the free-energy landscape of a model liquid Argon. The algorithm biases the system to evolve from an amorphous liquid like structure towards an FCC crystal through inherent structure, and then traces back the energy barriers. Consequently, the sampled timescale is macroscopically long. We observe that the formation of a crystal involves two processes, each with a unique temperature-dependent energy barrier. One barrier corresponds to the crystal nucleus formation; the other barrier corresponds to the crystal growth. We find the two processes dominate in different temperature regimes. Compared to other computation techniques, our method requires no assumptions about the shape or chemical potential of the critical crystal nucleus. The success of this method is encouraging for studying the crystallization of more complex

Interstellar Isotopes: Prospects with ALMA

NASA Technical Reports Server (NTRS)

Charnley Steven B.

2010-01-01

Cold molecular clouds are natural environments for the enrichment of interstellar molecules in the heavy isotopes of H, C, N and O. Anomalously fractionated isotopic material is found in many primitive Solar System objects, such as meteorites and comets, that may trace interstellar matter that was incorporated into the Solar Nebula without undergoing significant processing. Models of the fractionation chemistry of H, C, N and O in dense molecular clouds, particularly in cores where substantial freeze-out of molecules on to dust has occurred, make several predictions that can be tested in the near future by molecular line observations. The range of fractionation ratios expected in different interstellar molecules will be discussed and the capabilities of ALMA for testing these models (e.g. in observing doubly-substituted isotopologues) will be outlined.

Coupled Phases and Combinatorial Selection in Fluctuating Hydrothermal Pools: A Scenario to Guide Experimental Approaches to the Origin of Cellular Life

PubMed Central

Damer, Bruce; Deamer, David

2015-01-01

Hydrothermal fields on the prebiotic Earth are candidate environments for biogenesis. We propose a model in which molecular systems driven by cycles of hydration and dehydration in such sites undergo chemical evolution in dehydrated films on mineral surfaces followed by encapsulation and combinatorial selection in a hydrated bulk phase. The dehydrated phase can consist of concentrated eutectic mixtures or multilamellar liquid crystalline matrices. Both conditions organize and concentrate potential monomers and thereby promote polymerization reactions that are driven by reduced water activity in the dehydrated phase. In the case of multilamellar lipid matrices, polymers that have been synthesized are captured in lipid vesicles upon rehydration to produce a variety of molecular systems. Each vesicle represents a protocell, an “experiment” in a natural version of combinatorial chemistry. Two kinds of selective processes can then occur. The first is a physical process in which relatively stable molecular systems will be preferentially selected. The second is a chemical process in which rare combinations of encapsulated polymers form systems capable of capturing energy and nutrients to undergo growth by catalyzed polymerization. Given continued cycling over extended time spans, such combinatorial processes will give rise to molecular systems having the fundamental properties of life. PMID:25780958

Muscle activation described with a differential equation model for large ensembles of locally coupled molecular motors.

PubMed

Walcott, Sam

2014-10-01

Molecular motors, by turning chemical energy into mechanical work, are responsible for active cellular processes. Often groups of these motors work together to perform their biological role. Motors in an ensemble are coupled and exhibit complex emergent behavior. Although large motor ensembles can be modeled with partial differential equations (PDEs) by assuming that molecules function independently of their neighbors, this assumption is violated when motors are coupled locally. It is therefore unclear how to describe the ensemble behavior of the locally coupled motors responsible for biological processes such as calcium-dependent skeletal muscle activation. Here we develop a theory to describe locally coupled motor ensembles and apply the theory to skeletal muscle activation. The central idea is that a muscle filament can be divided into two phases: an active and an inactive phase. Dynamic changes in the relative size of these phases are described by a set of linear ordinary differential equations (ODEs). As the dynamics of the active phase are described by PDEs, muscle activation is governed by a set of coupled ODEs and PDEs, building on previous PDE models. With comparison to Monte Carlo simulations, we demonstrate that the theory captures the behavior of locally coupled ensembles. The theory also plausibly describes and predicts muscle experiments from molecular to whole muscle scales, suggesting that a micro- to macroscale muscle model is within reach.

Atomic Precision Plasma Processing - Modeling Investigations

NASA Astrophysics Data System (ADS)

Rauf, Shahid

2016-09-01

Sub-nanometer precision is increasingly being required of many critical plasma processes in the semiconductor industry. Some of these critical processes include atomic layer etch and plasma enhanced atomic layer deposition. Accurate control over ion energy and ion / radical composition is needed during plasma processing to meet the demanding atomic-precision requirements. While improvements in mainstream inductively and capacitively coupled plasmas can help achieve some of these goals, newer plasma technologies can expand the breadth of problems addressable by plasma processing. Computational modeling is used to examine issues relevant to atomic precision plasma processing in this paper. First, a molecular dynamics model is used to investigate atomic layer etch of Si and SiO2 in Cl2 and fluorocarbon plasmas. Both planar surfaces and nanoscale structures are considered. It is shown that accurate control of ion energy in the sub-50 eV range is necessary for atomic scale precision. In particular, if the ion energy is greater than 10 eV during plasma processing, several atomic layers get damaged near the surface. Low electron temperature (Te) plasmas are particularly attractive for atomic precision plasma processing due to their low plasma potential. One of the most attractive options in this regard is energetic-electron beam generated plasma, where Te <0.5 eV has been achieved in plasmas of molecular gases. These low Te plasmas are computationally examined in this paper using a hybrid fluid-kinetic model. It is shown that such plasmas not only allow for sub-5 eV ion energies, but also enable wider range of ion / radical composition. Coauthors: Jun-Chieh Wang, Jason Kenney, Ankur Agarwal, Leonid Dorf, and Ken Collins.

Acoustic response of cemented granular sedimentary rocks: molecular dynamics modeling.

PubMed

García, Xavier; Medina, Ernesto

2007-06-01

The effect of cementation processes on the acoustical properties of sands is studied via molecular dynamics simulation methods. We propose numerical methods where the initial uncemented sand is built by simulating the settling process of sediments. Uncemented samples of different porosity are considered by emulating natural mechanical compaction of sediments due to overburden. Cementation is considered through a particle-based model that captures the underlying physics behind the process. In our simulations, we consider samples with different degrees of compaction and cementing materials with distinct elastic properties. The microstructure of cemented sands is taken into account while adding cement at specific locations within the pores, such as grain-to-grain contacts. Results show that the acoustical properties of cemented sands are strongly dependent on the amount of cement, its stiffness relative to the hosting medium, and its location within the pores. Simulation results are in good correspondence with available experimental data and compare favorably with some theoretical predictions for the sound velocity within a range of cement saturation, porosity, and confining pressure.

[Study on the dynamic model with supercritical CO2 fluid extracting the lipophilic components in Panax notoginseng].

PubMed

Duan, Xian-Chun; Wang, Yong-Zhong; Zhang, Jun-Ru; Luo, Huan; Zhang, Heng; Xia, Lun-Zhu

2011-08-01

To establish a dynamics model for extracting the lipophilic components in Panax notoginseng with supercritical carbon dioxide (CO2). Based on the theory of counter-flow mass transfer and the molecular mass transfer between the material and the supercritical CO2 fluid under differential mass-conservation equation, a dynamics model was established and computed to compare forecasting result with the experiment process. A dynamics model has been established for supercritical CO2 to extract the lipophilic components in Panax notoginseng, the computed result of this model was consistent with the experiment process basically. The supercritical fluid extract dynamics model established in this research can expound the mechanism in the extract process of which lipophilic components of Panax notoginseng dissolve the mass transfer and is tallied with the actual extract process. This provides certain instruction for the supercritical CO2 fluid extract' s industrialization enlargement.

VOLATILIZATION OF ALKYLBENZENES FROM WATER.

USGS Publications Warehouse

Rathbun, R.E.; Tai, D.Y.

1985-01-01

Volatilization is a physical process of importance in determining the fate of many organic compounds in streams and rivers. This process is frequently described by the conceptual-two-film model. The model assumes uniformly mixed water and air phases separated by thin films of water and air in which mass transfer is by molecular diffusion. Mass-transfer coefficients for the water and air films are related to an overall mass-transfer coefficient for volatilization through the Henry's law constant.

Combining experimental and simulation data of molecular processes via augmented Markov models.

PubMed

Olsson, Simon; Wu, Hao; Paul, Fabian; Clementi, Cecilia; Noé, Frank

2017-08-01

Accurate mechanistic description of structural changes in biomolecules is an increasingly important topic in structural and chemical biology. Markov models have emerged as a powerful way to approximate the molecular kinetics of large biomolecules while keeping full structural resolution in a divide-and-conquer fashion. However, the accuracy of these models is limited by that of the force fields used to generate the underlying molecular dynamics (MD) simulation data. Whereas the quality of classical MD force fields has improved significantly in recent years, remaining errors in the Boltzmann weights are still on the order of a few [Formula: see text], which may lead to significant discrepancies when comparing to experimentally measured rates or state populations. Here we take the view that simulations using a sufficiently good force-field sample conformations that are valid but have inaccurate weights, yet these weights may be made accurate by incorporating experimental data a posteriori. To do so, we propose augmented Markov models (AMMs), an approach that combines concepts from probability theory and information theory to consistently treat systematic force-field error and statistical errors in simulation and experiment. Our results demonstrate that AMMs can reconcile conflicting results for protein mechanisms obtained by different force fields and correct for a wide range of stationary and dynamical observables even when only equilibrium measurements are incorporated into the estimation process. This approach constitutes a unique avenue to combine experiment and computation into integrative models of biomolecular structure and dynamics.

Three Dimensional Projection Environment for Molecular Design and Surgical Simulation

DTIC Science & Technology

2011-08-01

bypasses the cumbersome meshing process . The deformation model is only comprised of mass nodes, which are generated by sampling the object volume before...force should minimize the penetration volume, the haptic feedback force is derived directly. Additionally, a post- processing technique is developed to...render distinct physi-cal tissue properties across different interaction areas. The proposed approach does not require any pre- processing and is

Molecular modeling of the AhR structure and interactions can shed light on ligand-dependent activation and transformation mechanisms.

PubMed

Bonati, Laura; Corrada, Dario; Tagliabue, Sara Giani; Motta, Stefano

2017-02-01

Molecular modeling has given important contributions to elucidation of the main stages in the AhR signal transduction pathway. Despite the lack of experimentally determined structures of the AhR functional domains, information derived from homologous systems has been exploited for modeling their structure and interactions. Homology models of the AhR PASB domain have provided information on the binding cavity and contributed to elucidate species-specific differences in ligand binding. Molecular Docking simulations of the ligand binding process have given insights into differences in binding of diverse agonists, antagonists, and selective AhR modulators, and their application to virtual screening of large databases of compounds have allowed identification of novel AhR ligands. Recently available structural information on protein-protein and protein-DNA complexes of other bHLH-PAS systems has opened the way for modeling the AhR:ARNT dimer structure and investigating the mechanisms of AhR transformation and DNA binding. Future research directions should include simulation of the protein dynamics to obtain a more reliable description of intermolecular interactions involved in signal transmission.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Calibration and validation of coarse-grained models of atomic systems: application to semiconductor manufacturing

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley

2014-07-01

Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and methods through applications to representative atomic structures and we discuss extensions to the validation process for molecular models of polymer structures encountered in certain semiconductor nanomanufacturing processes. The powerful method of model plausibility as a means for selecting interaction potentials for coarse-grained models is discussed in connection with a coarse-grained hexane molecule. Discussions of how all-atom information is used to construct priors are contained in an appendix.

Computational and Experimental Investigations of the Molecular Scale Structure and Dynamics of Gologically Important Fluids and Mineral-Fluid Interfaces

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

Bowers, Geoffrey

United States Department of Energy grant DE-FG02-10ER16128, “Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces” (Geoffrey M. Bowers, P.I.) focused on developing a molecular-scale understanding of processes that occur in fluids and at solid-fluid interfaces using the combination of spectroscopic, microscopic, and diffraction studies with molecular dynamics computer modeling. The work is intimately tied to the twin proposal at Michigan State University (DOE DE-FG02-08ER15929; same title: R. James Kirkpatrick, P.I. and A. Ozgur Yazaydin, co-P.I.).

A scaling law of radial gas distribution in disk galaxies

NASA Technical Reports Server (NTRS)

Wang, Zhong

1990-01-01

Based on the idea that local conditions within a galactic disk largely determine the region's evolution time scale, researchers built a theoretical model to take into account molecular cloud and star formations in the disk evolution process. Despite some variations that may be caused by spiral arms and central bulge masses, they found that many late-type galaxies show consistency with the model in their radial atomic and molecular gas profiles. In particular, researchers propose that a scaling law be used to generalize the gas distribution characteristics. This scaling law may be useful in helping to understand the observed gas contents in many galaxies. Their model assumes an exponential mass distribution with disk radius. Most of the mass are in atomic gas state at the beginning of the evolution. Molecular clouds form through a modified Schmidt Law which takes into account gravitational instabilities in a possible three-phase structure of diffuse interstellar medium (McKee and Ostriker, 1977; Balbus and Cowie, 1985); whereas star formation proceeds presumably unaffected by the environmental conditions outside of molecular clouds (Young, 1987). In such a model both atomic and molecular gas profiles in a typical galactic disk (as a result of the evolution) can be fitted simultaneously by adjusting the efficiency constants. Galaxies of different sizes and masses, on the other hand, can be compared with the model by simply scaling their characteristic length scales and shifting their radial ranges to match the assumed disk total mass profile sigma tot(r).

MOLECULAR MECHANISMS OF FEAR LEARNING AND MEMORY

PubMed Central

Johansen, Joshua P.; Cain, Christopher K.; Ostroff, Linnaea E.; LeDoux, Joseph E.

2011-01-01

Pavlovian fear conditioning is a useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Together, this research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals, and potentially for understanding fear related disorders, such as PTSD and phobias. PMID:22036561

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Nonadiabatic ab initio molecular dynamics with PME-ONIOM scheme of photoisomerization reaction between 1,3-cyclohexadiene and 1,3,5-cis-hexatriene in solution phase

NASA Astrophysics Data System (ADS)

Ohta, Ayumi; Kobayashi, Osamu; Danielache, Sebastian O.; Nanbu, Shinkoh

2017-03-01

The ultra-fast photoisomerization reactions between 1,3-cyclohexadiene (CHD) and 1,3,5-cis-hexatriene (HT) in both hexane and ethanol solvents were revealed by nonadiabatic ab initio molecular dynamics (AI-MD) with a particle-mesh Ewald summation method and our Own N-layered Integrated molecular Orbital and molecular Mechanics model (PME-ONIOM) scheme. Zhu-Nakamura version trajectory surface hopping method (ZN-TSH) was employed to treat the ultra-fast nonadiabatic decaying process. The results for hexane and ethanol simulations reasonably agree with experimental data. The high nonpolar-nonpolar affinity between CHD and the solvent was observed in hexane solvent, which definitely affected the excited state lifetimes, the product branching ratio of CHD:HT, and solute (CHD) dynamics. In ethanol solvent, however, the CHD solute was isomerized in the solvent cage caused by the first solvation shell. The photochemical dynamics in ethanol solvent results in the similar property to the process appeared in vacuo (isolated CHD dynamics).

Effect of Chemical and Physical Properties on the In Vitro Degradation of 3D Printed High Resolution Poly(propylene fumarate) Scaffolds.

PubMed

Walker, Jason M; Bodamer, Emily; Krebs, Olivia; Luo, Yuanyuan; Kleinfehn, Alex; Becker, Matthew L; Dean, David

2017-04-10

Two distinct molecular masses of poly(propylene fumarate) (PPF) are combined with an additive manufacturing process to fabricate highly complex scaffolds possessing controlled chemical properties and porous architecture. Scaffolds were manufactured with two polymer molecular masses and two architecture styles. Degradation was assessed in an accelerated in vitro environment. The purpose of the degradation study is not to model or mimic in vivo degradation, but to efficiently compare the effect of modulating scaffold properties. This is the first study addressing degradation of chain-growth synthesized PPF, a process that allows for considerably more control over molecular mass distribution. It demonstrates that, with greater process control, not only is scaffold fabrication reproducible, but the mechanical properties and degradation kinetics can be tailored by altering the physical properties of the scaffold. This is a clear step forward in using PPF to address unmet medical needs while meeting regulatory demands and ultimately obtaining clinical relevancy.

Dynamic NMR Study of Model CMP Slurry Containing Silica Particles as Abrasives

NASA Astrophysics Data System (ADS)

Odeh, F.; Al-Bawab, A.; Li, Y.

2018-02-01

Chemical mechanical planarization (CMP) should provide a good surface planarity with minimal surface defectivity. Since CMP slurries are multi-component systems, it is very important to understand the various processes and interactions taking place in such slurries. Several techniques have been employed for such task, however, most of them lack the molecular recognition to investigate molecular interactions without adding probes which in turn increase complexity and might alter the microenvironment of the slurry. Nuclear magnetic resonance (NMR) is a powerful technique that can be employed in such study. The longitudinal relaxation times (T1) of the different components of CMP slurries were measured using Spin Echo-NMR (SE-NMR) at a constant temperature. The fact that NMR is non-invasive and gives information on the molecular level gives more advantage to the technique. The model CMP slurry was prepared in D2O to enable monitoring of T1 for the various components' protons. SE-NMR provide a very powerful tool to study the various interactions and adsorption processes that take place in a model CMP silica based slurry which contains BTA and/or glycine and/or Cu+2 ions. It was found that BTA is very competitive towards complexation with Cu+2 ions and BTA-Cu complex adsorbs on silica surface.

Modeling human endothelial cell transformation in vascular neoplasias

PubMed Central

Wen, Victoria W.; MacKenzie, Karen L.

2013-01-01

Endothelial cell (EC)-derived neoplasias range from benign hemangioma to aggressive metastatic angiosarcoma, which responds poorly to current treatments and has a very high mortality rate. The development of treatments that are more effective for these disorders will be expedited by insight into the processes that promote abnormal proliferation and malignant transformation of human ECs. The study of primary endothelial malignancy has been limited by the rarity of the disease; however, there is potential for carefully characterized EC lines and animal models to play a central role in the discovery, development and testing of molecular targeted therapies for vascular neoplasias. This review describes molecular alterations that have been identified in EC-derived neoplasias, as well as the processes that underpin the immortalization and tumorigenic conversion of ECs. Human EC lines, established through the introduction of defined genetic elements or by culture of primary tumor tissue, are catalogued and discussed in relation to their relevance as models of vascular neoplasia. PMID:24046386

Investigating molecule-semiconductor interfaces with nonlinear spectroscopies

NASA Astrophysics Data System (ADS)

Giokas, Paul George

Knowledge of electronic structures and transport mechanisms at molecule-semiconductor interfaces is motivated by their ubiquity in photoelectrochemical cells. In this dissertation, optical spectroscopies are used uncover the influence of electronic coupling, coherent vibrational motion, and molecular geometry, and other factors on dynamics initiated by light absorption at such interfaces. These are explored for a family of ruthenium bipyridyl chromophores bound to titanium dioxide. Transient absorption measurements show molecular singlet state electron injection in 100 fs or less. Resonance Raman intensity analysis suggests the electronic excitations possess very little charge transfer character. The connections drawn in this work between molecular structure and photophysical behavior contribute to the general understanding of photoelectrochemical cells. Knowledge of binding geometry in nanocrystalline films is challenged by heterogeneity of semiconductor surfaces. Polarized resonance Raman spectroscopy is used to characterize the ruthenium chromophore family on single crystal titanium dioxide . Chromophores display a broad distribution of molecular geometries at the interface, with increased variation in binding angle due to the presence of a methylene bridge, as well as additional phosphonate anchors. This result implies multiple binding configurations for chromophores which incorporate multiple phosphonate ligands, and indicates the need for careful consideration when developing surface-assembled chromophore-catalyst cells. Electron transfer transitions occurring on the 100 fs time scale challenge conventional second-order approximations made when modeling these reactions. A fourth-order perturbative model which includes the relationship between coincident electron transfer and nuclear relaxation processes is presented. Insights provided by the model are illustrated for a two-level donor molecule. The presented fourth-order rate formula constitutes a rigorous and intuitive framework for understanding sub-picosecond photoinduced electron transfer dynamics. Charge transfer systems fit by this model include catechol-sensitized titanium dioxide nanoparticles and a closely-related molecular complex. These systems exhibit vibrational coherence coincident with back-electron transfer in the first picosecond after excitation, which suggests that intramolecular nuclear motion strongly influences the electronic transfer process and plays an important role in the dynamics of interfacial systems following light absorption.

Nanoscale Engineering of Designer Cellulosomes.

PubMed

Gunnoo, Melissabye; Cazade, Pierre-André; Galera-Prat, Albert; Nash, Michael A; Czjzek, Mirjam; Cieplak, Marek; Alvarez, Beatriz; Aguilar, Marina; Karpol, Alon; Gaub, Hermann; Carrión-Vázquez, Mariano; Bayer, Edward A; Thompson, Damien

2016-07-01

Biocatalysts showcase the upper limit obtainable for high-speed molecular processing and transformation. Efforts to engineer functionality in synthetic nanostructured materials are guided by the increasing knowledge of evolving architectures, which enable controlled molecular motion and precise molecular recognition. The cellulosome is a biological nanomachine, which, as a fundamental component of the plant-digestion machinery from bacterial cells, has a key potential role in the successful development of environmentally-friendly processes to produce biofuels and fine chemicals from the breakdown of biomass waste. Here, the progress toward so-called "designer cellulosomes", which provide an elegant alternative to enzyme cocktails for lignocellulose breakdown, is reviewed. Particular attention is paid to rational design via computational modeling coupled with nanoscale characterization and engineering tools. Remaining challenges and potential routes to industrial application are put forward. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.

PubMed

Inoue, Yasuhiro; Adachi, Taiji

2011-07-01

Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.

On-the-Fly Kinetic Monte Carlo Simulation of Aqueous Phase Advanced Oxidation Processes.

PubMed

Guo, Xin; Minakata, Daisuke; Crittenden, John

2015-08-04

We have developed an on-the-fly kinetic Monte Carlo (KMC) model to predict the degradation mechanisms and fates of intermediates and byproducts that are produced during aqueous-phase advanced oxidation processes (AOPs). The on-the-fly KMC model is composed of a reaction pathway generator, a reaction rate constant estimator, a mechanistic reduction module, and a KMC solver. The novelty of this work is that we develop the pathway as we march forward in time rather than developing the pathway before we use the KMC method to solve the equations. As a result, we have fewer reactions to consider, and we have greater computational efficiency. We have verified this on-the-fly KMC model for the degradation of polyacrylamide (PAM) using UV light and titanium dioxide (i.e., UV/TiO2). Using the on-the-fly KMC model, we were able to predict the time-dependent profiles of the average molecular weight for PAM. The model provided detailed and quantitative insights into the time evolution of the molecular weight distribution and reaction mechanism. We also verified our on-the-fly KMC model for the destruction of (1) acetone, (2) trichloroethylene (TCE), and (3) polyethylene glycol (PEG) for the ultraviolet light and hydrogen peroxide AOP. We demonstrated that the on-the-fly KMC model can achieve the same accuracy as the computer-based first-principles KMC (CF-KMC) model, which has already been validated in our earlier work. The on-the-fly KMC is particularly suitable for molecules with large molecular weights (e.g., polymers) because the degradation mechanisms for large molecules can result in hundreds of thousands to even millions of reactions. The ordinary differential equations (ODEs) that describe the degradation pathways cannot be solved using traditional numerical methods, but the KMC can solve these equations.

Probing the brain with molecular fMRI.

PubMed

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-06-01

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

A review on nanomechanical resonators and their applications in sensors and molecular transportation

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

Arash, Behrouz; Rabczuk, Timon, E-mail: timon.rabczuk@uni-weimar.de; Jiang, Jin-Wu

2015-06-15

Nanotechnology has opened a new area in science and engineering, leading to the development of novel nano-electromechanical systems such as nanoresonators with ultra-high resonant frequencies. The ultra-high-frequency resonators facilitate wide-ranging applications such as ultra-high sensitive sensing, molecular transportation, molecular separation, high-frequency signal processing, and biological imaging. This paper reviews recent studies on dynamic characteristics of nanoresonators. A variety of theoretical approaches, i.e., continuum modeling, molecular simulations, and multiscale methods, in modeling of nanoresonators are reviewed. The potential application of nanoresonators in design of sensor devices and molecular transportation systems is introduced. The essence of nanoresonator sensors for detection of atomsmore » and molecules with vibration and wave propagation analyses is outlined. The sensitivity of the resonator sensors and their feasibility in detecting different atoms and molecules are particularly discussed. Furthermore, the applicability of molecular transportation using the propagation of mechanical waves in nanoresonators is presented. An extended application of the transportation methods for building nanofiltering systems with ultra-high selectivity is surveyed. The article aims to provide an up-to-date review on the mechanical properties and applications of nanoresonators, and inspire additional potential of the resonators.« less

The simulation of molecular clouds formation in the Milky Way

NASA Astrophysics Data System (ADS)

Khoperskov, S. A.; Vasiliev, E. O.; Sobolev, A. M.; Khoperskov, A. V.

2013-01-01

Using 3D hydrodynamic calculations we simulate formation of molecular clouds in the Galaxy. The simulations take into account molecular hydrogen chemical kinetics, cooling and heating processes. Comprehensive gravitational potential accounts for contributions from the stellar bulge, two- and four-armed spiral structure, stellar disc, dark halo and takes into account self-gravitation of the gaseous component. Gas clouds in our model form in the spiral arms due to shear and wiggle instabilities and turn into molecular clouds after t ≳ 100 Myr. At the times t ˜ 100-300 Myr the clouds form hierarchical structures and agglomerations with the sizes of 100 pc and greater. We analyse physical properties of the simulated clouds and find that synthetic statistical distributions like mass spectrum, `mass-size' relation and velocity dispersion are close to those observed in the Galaxy. The synthetic l-v (galactic longitude-radial velocity) diagram of the simulated molecular gas distribution resembles observed one and displays a structure with appearance similar to molecular ring of the Galaxy. Existence of this structure in our modelling can be explained by superposition of emission from the galactic bar and the spiral arms at ˜3-4 kpc.

Proposal of a model of mammalian neural induction

PubMed Central

Levine, Ariel J.; Brivanlou, Ali H.

2009-01-01

How does the vertebrate embryo make a nervous system? This complex question has been at the center of developmental biology for many years. The earliest step in this process – the induction of neural tissue – is intimately linked to patterning of the entire early embryo, and the molecular and embryological basis these processes are beginning to emerge. Here, we analyze classic and cutting-edge findings on neural induction in the mouse. We find that data from genetics, tissue explants, tissue grafting, and molecular marker expression support a coherent framework for mammalian neural induction. In this model, the gastrula organizer of the mouse embryo inhibits BMP signaling to allow neural tissue to form as a default fate – in the absence of instructive signals. The first neural tissue induced is anterior and subsequent neural tissue is posteriorized to form the midbrain, hindbrain, and spinal cord. The anterior visceral endoderm protects the pre-specified anterior neural fate from similar posteriorization, allowing formation of forebrain. This model is very similar to the default model of neural induction in the frog, thus bridging the evolutionary gap between amphibians and mammals. PMID:17585896

Conversion of an atomic to a molecular argon ion and low pressure argon relaxation

NASA Astrophysics Data System (ADS)

M, N. Stankov; A, P. Jovanović; V, Lj Marković; S, N. Stamenković

2016-01-01

The dominant process in relaxation of DC glow discharge between two plane parallel electrodes in argon at pressure 200 Pa is analyzed by measuring the breakdown time delay and by analytical and numerical models. By using the approximate analytical model it is found that the relaxation in a range from 20 to 60 ms in afterglow is dominated by ions, produced by atomic-to-molecular conversion of Ar+ ions in the first several milliseconds after the cessation of the discharge. This conversion is confirmed by the presence of double-Gaussian distribution for the formative time delay, as well as conversion maxima in a set of memory curves measured in different conditions. Finally, the numerical one-dimensional (1D) model for determining the number densities of dominant particles in stationary DC glow discharge and two-dimensional (2D) model for the relaxation are used to confirm the previous assumptions and to determine the corresponding collision and transport coefficients of dominant species and processes. Project supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant No. ON171025).

An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

PubMed

Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

2017-01-27

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases. Copyright © 2016 Elsevier B.V. All rights reserved.

Modelling rate distributions using character compatibility: implications for morphological evolution among fossil invertebrates.

PubMed

Wagner, Peter J

2012-02-23

Rate distributions are important considerations when testing hypotheses about morphological evolution or phylogeny. They also have implications about general processes underlying character evolution. Molecular systematists often assume that rates are Poisson processes with gamma distributions. However, morphological change is the product of multiple probabilistic processes and should theoretically be affected by hierarchical integration of characters. Both factors predict lognormal rate distributions. Here, a simple inverse modelling approach assesses the best single-rate, gamma and lognormal models given observed character compatibility for 115 invertebrate groups. Tests reject the single-rate model for nearly all cases. Moreover, the lognormal outperforms the gamma for character change rates and (especially) state derivation rates. The latter in particular is consistent with integration affecting morphological character evolution.

Space Research Program on Planarian Schmidtea Mediterranea's Establishment of the Anterior-Posterior Axis in Altered Gravity Conditions

NASA Astrophysics Data System (ADS)

Auletta, G.; Adell, T.; Colagè, I.; D'Ambrosio, P.; Salò, E.

2012-12-01

Planarians of the species Schmidtea mediterranea are a well-established model for regeneration studies. In this paper, we first recall the morphological characters and the molecular mechanisms involved in the regeneration process, especially focussing on the Wnt pathway and the establishment of the antero-posterior axial polarity. Then, after an assessment of a space-experiment (run in 2006 on the Russian Segment of the International Space Station) on planarians of the species Girardia tigrina, we present our experimental program to ascertain the effects that altered-gravity conditions may have on regeneration processes in S. mediterrnea at the molecular and genetic level.

Molecular processors: from qubits to fuzzy logic.

PubMed

Gentili, Pier Luigi

2011-03-14

Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi-valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in sepsis research derived from animal models.

PubMed

Männel, Daniela N

2007-09-01

Inflammation is the basic process by which tissues of the body respond to infection. Activation of the immune system normally leads to removal of microbial pathogens, and after resolution of the inflammation immune homeostasis is restored. This controlled process, however, can be disturbed resulting in disease. Therefore, many studies using infection models have investigated the participating immune mechanisms aiming at possible therapeutic interventions. Defined model substances such as bacterial lipopolysaccharide (endotoxin) have been used to mimic bacterial infections and analyze their immune stimulating functions. A complex network of molecular mechanisms involved in the recognition and activation processes of bacterial infections and their regulation has developed from these studies. More complex infection models will now help to interpret earlier observations leading to the design of relevant new infection models.

North Carolina Biomolecular Engineering and Materials Applications Center (NC-BEMAC).

DTIC Science & Technology

1987-12-29

enzyme has been replaced with cobalt(II). A further objective was to investigate Co2 activation by low molecular weight transition metal complexes as...Characterization of Low Molecular Weight Metal Complexes as Potential Models for IBio-Catalytic Processes. A number of transit ion met~~il oom~pi cxe; hive...binding, the enzyme suffered loss of activity during radiation polymerization. When covalent binding was u:sed it was necessary to introduce suitably

Ames interactive molecular model building system - A 3-D computer modelling system applied to the study of the origin of life

NASA Technical Reports Server (NTRS)

Coeckelenbergh, Y.; Macelroy, R. D.; Rein, R.

1978-01-01

The investigation of specific interactions among biological molecules must take into consideration the stereochemistry of the structures. Thus, models of the molecules are essential for describing the spatial organization of potentially interacting groups, and estimations of conformation are required for a description of spatial organization. Both the function of visualizing molecules, and that of estimating conformation through calculations of energy, are part of the molecular modeling system described in the present paper. The potential uses of the system in investigating some aspects of the origin of life rest on the assumption that translation of conformation from genetic elements to catalytic elements would have been required for the development of the first replicating systems subject to the process of biological evolution.

Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

NASA Astrophysics Data System (ADS)

Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

2017-10-01

Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

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.

Dynamics and kinetics of reversible homo-molecular dimerization of polycyclic aromatic hydrocarbons

NASA Astrophysics Data System (ADS)

Mao, Qian; Ren, Yihua; Luo, K. H.; van Duin, Adri C. T.

2017-12-01

Physical dimerization of polycyclic aromatic hydrocarbons (PAHs) has been investigated via molecular dynamics (MD) simulation with the ReaxFF reactive force field that is developed to bridge the gap between the quantum mechanism and classical MD. Dynamics and kinetics of homo-molecular PAH collision under different temperatures, impact parameters, and orientations are studied at an atomic level, which is of great value to understand and model the PAH dimerization. In the collision process, the enhancement factors of homo-molecular dimerizations are quantified and found to be larger at lower temperatures or with smaller PAH instead of size independent. Within the capture radius, the lifetime of the formed PAH dimer decreases as the impact parameter increases. Temperature and PAH characteristic dependent forward and reverse rate constants of homo-molecular PAH dimerization are derived from MD simulations, on the basis of which a reversible model is developed. This model can predict the tendency of PAH dimerization as validated by pyrene dimerization experiments [H. Sabbah et al., J. Phys. Chem. Lett. 1(19), 2962 (2010)]. Results from this study indicate that the physical dimerization cannot be an important source under the typical flame temperatures and PAH concentrations, which implies a more significant role played by the chemical route.

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

A software platform for continuum modeling of ion channels based on unstructured mesh

NASA Astrophysics Data System (ADS)

Tu, B.; Bai, S. Y.; Chen, M. X.; Xie, Y.; Zhang, L. B.; Lu, B. Z.

2014-01-01

Most traditional continuum molecular modeling adopted finite difference or finite volume methods which were based on a structured mesh (grid). Unstructured meshes were only occasionally used, but an increased number of applications emerge in molecular simulations. To facilitate the continuum modeling of biomolecular systems based on unstructured meshes, we are developing a software platform with tools which are particularly beneficial to those approaches. This work describes the software system specifically for the simulation of a typical, complex molecular procedure: ion transport through a three-dimensional channel system that consists of a protein and a membrane. The platform contains three parts: a meshing tool chain for ion channel systems, a parallel finite element solver for the Poisson-Nernst-Planck equations describing the electrodiffusion process of ion transport, and a visualization program for continuum molecular modeling. The meshing tool chain in the platform, which consists of a set of mesh generation tools, is able to generate high-quality surface and volume meshes for ion channel systems. The parallel finite element solver in our platform is based on the parallel adaptive finite element package PHG which wass developed by one of the authors [1]. As a featured component of the platform, a new visualization program, VCMM, has specifically been developed for continuum molecular modeling with an emphasis on providing useful facilities for unstructured mesh-based methods and for their output analysis and visualization. VCMM provides a graphic user interface and consists of three modules: a molecular module, a meshing module and a numerical module. A demonstration of the platform is provided with a study of two real proteins, the connexin 26 and hemolysin ion channels.

Atomization and dense-fluid breakup regimes in liquid rocket engines

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

Oefelein, Joseph; Dahms, Rainer Norbert Uwe

Until recently, modern theory has lacked a fundamentally based model to predict the operating pressures where classical sprays transition to dense-fluid mixing with diminished surface tension. In this paper, such a model is presented to quantify this transition for liquid-oxygen–hydrogen and n-decane–gaseous-oxygen injection processes. The analysis reveals that respective molecular interfaces break down not necessarily because of vanishing surface tension forces but instead because of the combination of broadened interfaces and a reduction in mean free molecular path. When this occurs, the interfacial structure itself enters the continuum regime, where transport processes rather than intermolecular forces dominate. Using this model,more » regime diagrams for the respective systems are constructed that show the range of operating pressures and temperatures where this transition occurs. The analysis also reveals the conditions where classical spray dynamics persists even at high supercritical pressures. As a result, it demonstrates that, depending on the composition and temperature of the injected fluids, the injection process can exhibit either classical spray atomization, dense-fluid diffusion-dominated mixing, or supercritical mixing phenomena at chamber pressures encountered in state-of-the-art liquid rocket engines.« less

Atomization and dense-fluid breakup regimes in liquid rocket engines

DOE PAGES

Oefelein, Joseph; Dahms, Rainer Norbert Uwe

2015-04-20

Until recently, modern theory has lacked a fundamentally based model to predict the operating pressures where classical sprays transition to dense-fluid mixing with diminished surface tension. In this paper, such a model is presented to quantify this transition for liquid-oxygen–hydrogen and n-decane–gaseous-oxygen injection processes. The analysis reveals that respective molecular interfaces break down not necessarily because of vanishing surface tension forces but instead because of the combination of broadened interfaces and a reduction in mean free molecular path. When this occurs, the interfacial structure itself enters the continuum regime, where transport processes rather than intermolecular forces dominate. Using this model,more » regime diagrams for the respective systems are constructed that show the range of operating pressures and temperatures where this transition occurs. The analysis also reveals the conditions where classical spray dynamics persists even at high supercritical pressures. As a result, it demonstrates that, depending on the composition and temperature of the injected fluids, the injection process can exhibit either classical spray atomization, dense-fluid diffusion-dominated mixing, or supercritical mixing phenomena at chamber pressures encountered in state-of-the-art liquid rocket engines.« less

Thinking Processes Associated with Undergraduate Chemistry Students' Success at Applying a Molecular-Level Model in a New Context

ERIC Educational Resources Information Center

Teichert, Melonie A.; Tien, Lydia T.; Dysleski, Lisa; Rickey, Dawn

2017-01-01

This study investigated relationships between the thinking processes that 28 undergraduate chemistry students engaged in during guided discovery and their subsequent success at reasoning through a transfer problem during an end-of-semester interview. During a guided-discovery laboratory module, students were prompted to use words, pictures, and…

Light induced kickoff of magnetic domain walls in Ising chains

NASA Astrophysics Data System (ADS)

Bogani, Lapo

2012-02-01

Controlling the speed at which systems evolve is a challenge shared by all disciplines, and otherwise unrelated areas use common theoretical frameworks towards this goal. A particularly widespread model is Glauber dynamics, which describes the time evolution of the Ising model and can be applied to any binary system. Here we show, using molecular nanowires under irradiation, that Glauber dynamics can be controlled by a novel domain-wall kickoff mechanism. Contrary to known processes, the kickoff has unambiguous fingerprints, slowing down the spin-flip attempt rate by several orders of magnitude, and following a scaling law. The required irradiation power is very low, a substantial improvement over present methods of magnetooptical switching: in our experimental demonstration we switched molecular nanowires with light, using powers thousands of times lower than in previous optical switching methods. This manipulation of stochastic dynamic processes is extremely clean, leading to fingerprint signatures and scaling laws. These observations can be used, in material science, to better study domain-wall displacements and solitons in discrete lattices. These results provide a new way to control and study stochastic dynamic processes. Being general for Glauber dynamics, they can be extended to different kinds of magnetic nanowires and to a myriad of fields, ranging from social evolution to neural networks and chemical reactivity. For nanoelectronics and molecular spintronics the kickoff affords external control of molecular spin-valves and a magnetic fingerprint in single molecule measurements. It can also be applied to the dynamics of mechanical switches and the related study of phasons and order-disorder transitions.

Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.

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.

A discrete in continuous mathematical model of cardiac progenitor cells formation and growth as spheroid clusters (Cardiospheres).

PubMed

Di Costanzo, Ezio; Giacomello, Alessandro; Messina, Elisa; Natalini, Roberto; Pontrelli, Giuseppe; Rossi, Fabrizio; Smits, Robert; Twarogowska, Monika

2018-03-14

We propose a discrete in continuous mathematical model describing the in vitro growth process of biophsy-derived mammalian cardiac progenitor cells growing as clusters in the form of spheres (Cardiospheres). The approach is hybrid: discrete at cellular scale and continuous at molecular level. In the present model, cells are subject to the self-organizing collective dynamics mechanism and, additionally, they can proliferate and differentiate, also depending on stochastic processes. The two latter processes are triggered and regulated by chemical signals present in the environment. Numerical simulations show the structure and the development of the clustered progenitors and are in a good agreement with the results obtained from in vitro experiments.

Computational approach on PEB process in EUV resist: multi-scale simulation

NASA Astrophysics Data System (ADS)

Kim, Muyoung; Moon, Junghwan; Choi, Joonmyung; Lee, Byunghoon; Jeong, Changyoung; Kim, Heebom; Cho, Maenghyo

2017-03-01

For decades, downsizing has been a key issue for high performance and low cost of semiconductor, and extreme ultraviolet lithography is one of the promising candidates to achieve the goal. As a predominant process in extreme ultraviolet lithography on determining resolution and sensitivity, post exposure bake has been mainly studied by experimental groups, but development of its photoresist is at the breaking point because of the lack of unveiled mechanism during the process. Herein, we provide theoretical approach to investigate underlying mechanism on the post exposure bake process in chemically amplified resist, and it covers three important reactions during the process: acid generation by photo-acid generator dissociation, acid diffusion, and deprotection. Density functional theory calculation (quantum mechanical simulation) was conducted to quantitatively predict activation energy and probability of the chemical reactions, and they were applied to molecular dynamics simulation for constructing reliable computational model. Then, overall chemical reactions were simulated in the molecular dynamics unit cell, and final configuration of the photoresist was used to predict the line edge roughness. The presented multiscale model unifies the phenomena of both quantum and atomic scales during the post exposure bake process, and it will be helpful to understand critical factors affecting the performance of the resulting photoresist and design the next-generation material.

Thermo-Gas-Dynamic Model of Afterburning in Explosions

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

Kuhl, A L; Ferguson, R E; Bell, J B

2003-07-27

A theoretical model of afterburning in explosions created by turbulent mixing of the detonation products from fuel-rich charges with air is described. It contains three key elements: (i) a thermodynamic-equilibrium description of the fluids (fuel, air, and products), (ii) a multi-component gas-dynamic treatment of the flow field, and (iii) a sub-grid model of molecular processes of mixing, combustion and equilibration.

Fracture of Carbon Nanotube - Amorphous Carbon Composites: Molecular Modeling

NASA Technical Reports Server (NTRS)

Jensen, Benjamin D.; Wise, Kristopher E.; Odegard, Gregory M.

2015-01-01

Carbon nanotubes (CNTs) are promising candidates for use as reinforcements in next generation structural composite materials because of their extremely high specific stiffness and strength. They cannot, however, be viewed as simple replacements for carbon fibers because there are key differences between these materials in areas such as handling, processing, and matrix design. It is impossible to know for certain that CNT composites will represent a significant advance over carbon fiber composites before these various factors have been optimized, which is an extremely costly and time intensive process. This work attempts to place an upper bound on CNT composite mechanical properties by performing molecular dynamics simulations on idealized model systems with a reactive forcefield that permits modeling of both elastic deformations and fracture. Amorphous carbon (AC) was chosen for the matrix material in this work because of its structural simplicity and physical compatibility with the CNT fillers. It is also much stiffer and stronger than typical engineering polymer matrices. Three different arrangements of CNTs in the simulation cell have been investigated: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. The SWNT and MWNT array systems are clearly idealizations, but the SWNT bundle system is a step closer to real systems in which individual tubes aggregate into large assemblies. The effect of chemical crosslinking on composite properties is modeled by adding bonds between the CNTs and AC. The balance between weakening the CNTs and improving fiber-matrix load transfer is explored by systematically varying the extent of crosslinking. It is, of course, impossible to capture the full range of deformation and fracture processes that occur in real materials with even the largest atomistic molecular dynamics simulations. With this limitation in mind, the simulation results reported here provide a plausible upper limit on achievable CNT composite properties and yield some insight on the influence of processing conditions on the mechanical properties of CNT composites.

Polymorph selection: the role of nucleation, crystal growth and molecular modeling.

PubMed

Erdemir, Deniz; Lee, Alfred Y; Myerson, Allan S

2007-11-01

Solution crystallization is an important separation and purification process used in the chemical, pharmaceutical and food industries. The quality of a crystalline product is generally judged by four main criteria: purity, crystal habit, particle size and solid form. Consistent production of the desired polymorph is crucial as the unanticipated emergence of a different crystal form may have severe consequences. Thus, the selection of a solid-state form for a crystalline product is vital and is ultimately based on knowledge of the properties of the other polymorphs. This review discusses the role of nucleation, crystal growth and molecular modeling on polymorphism in molecular crystals. Examples are presented demonstrating how the first two factors can govern the appearance of a particular crystalline form, and how the latter factor can be used as a tool for understanding polymorphism.

Theoretical Modeling of Interstellar Chemistry

NASA Technical Reports Server (NTRS)

Charnley, Steven

2009-01-01

The chemistry of complex interstellar organic molecules will be described. Gas phase processes that may build large carbon-chain species in cold molecular clouds will be summarized. Catalytic reactions on grain surfaces can lead to a large variety of organic species, and models of molecule formation by atom additions to multiply-bonded molecules will be presented. The subsequent desorption of these mixed molecular ices can initiate a distinctive organic chemistry in hot molecular cores. The general ion-molecule pathways leading to even larger organics will be outlined. The predictions of this theory will be compared with observations to show how possible organic formation pathways in the interstellar medium may be constrained. In particular, the success of the theory in explaining trends in the known interstellar organics, in predicting recently-detected interstellar molecules, and, just as importantly, non-detections, will be discussed.

Drug-loaded electrospun mats of poly(vinyl alcohol) fibres and their release characteristics of four model drugs

NASA Astrophysics Data System (ADS)

Taepaiboon, Pattama; Rungsardthong, Uracha; Supaphol, Pitt

2006-05-01

Mats of PVA nanofibres were successfully prepared by the electrospinning process and were developed as carriers of drugs for a transdermal drug delivery system. Four types of non-steroidal anti-inflammatory drug with varying water solubility property, i.e. sodium salicylate (freely soluble in water), diclofenac sodium (sparingly soluble in water), naproxen (NAP), and indomethacin (IND) (both insoluble in water), were selected as model drugs. The morphological appearance of the drug-loaded electrospun PVA mats depended on the nature of the model drugs. The 1H-nuclear magnetic resonance results confirmed that the electrospinning process did not affect the chemical integrity of the drugs. Thermal properties of the drug-loaded electrospun PVA mats were analysed by differential scanning calorimetry and thermogravimetric analysis. The molecular weight of the model drugs played a major role on both the rate and the total amount of drugs released from the as-prepared drug-loaded electrospun PVA mats, with the rate and the total amount of the drugs released decreasing with increasing molecular weight of the drugs. Lastly, the drug-loaded electrospun PVA mats exhibited much better release characteristics of the model drugs than drug-loaded as-cast films.

Sketching the Invisible to Predict the Visible: From Drawing to Modeling in Chemistry.

PubMed

Cooper, Melanie M; Stieff, Mike; DeSutter, Dane

2017-10-01

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. Copyright © 2017 Cognitive Science Society, Inc.

Analysis of Circadian Leaf Movements.

PubMed

Müller, Niels A; Jiménez-Gómez, José M

2016-01-01

The circadian clock is a molecular timekeeper that controls a wide variety of biological processes. In plants, clock outputs range from the molecular level, with rhythmic gene expression and metabolite content, to physiological processes such as stomatal conductance or leaf movements. Any of these outputs can be used as markers to monitor the state of the circadian clock. In the model plant Arabidopsis thaliana, much of the current knowledge about the clock has been gained from time course experiments profiling expression of endogenous genes or reporter constructs regulated by the circadian clock. Since these methods require labor-intensive sample preparation or transformation, monitoring leaf movements is an interesting alternative, especially in non-model species and for natural variation studies. Technological improvements both in digital photography and image analysis allow cheap and easy monitoring of circadian leaf movements. In this chapter we present a protocol that uses an autonomous point and shoot camera and free software to monitor circadian leaf movements in tomato.

AIM for Allostery: Using the Ising Model to Understand Information Processing and Transmission in Allosteric Biomolecular Systems.

PubMed

LeVine, Michael V; Weinstein, Harel

2015-05-01

In performing their biological functions, molecular machines must process and transmit information with high fidelity. Information transmission requires dynamic coupling between the conformations of discrete structural components within the protein positioned far from one another on the molecular scale. This type of biomolecular "action at a distance" is termed allostery . Although allostery is ubiquitous in biological regulation and signal transduction, its treatment in theoretical models has mostly eschewed quantitative descriptions involving the system's underlying structural components and their interactions. Here, we show how Ising models can be used to formulate an approach to allostery in a structural context of interactions between the constitutive components by building simple allosteric constructs we termed Allosteric Ising Models (AIMs). We introduce the use of AIMs in analytical and numerical calculations that relate thermodynamic descriptions of allostery to the structural context, and then show that many fundamental properties of allostery, such as the multiplicative property of parallel allosteric channels, are revealed from the analysis of such models. The power of exploring mechanistic structural models of allosteric function in more complex systems by using AIMs is demonstrated by building a model of allosteric signaling for an experimentally well-characterized asymmetric homodimer of the dopamine D2 receptor.

Biology of Healthy Aging and Longevity.

PubMed

Carmona, Juan José; Michan, Shaday

2016-01-01

As human life expectancy is prolonged, age-related diseases are thriving. Aging is a complex multifactorial process of molecular and cellular decline that affects tissue function over time, rendering organisms frail and susceptible to disease and death. Over the last decades, a growing body of scientific literature across different biological models, ranging from yeast, worms, flies, and mice to primates, humans and other long-lived animals, has contributed greatly towards identifying conserved biological mechanisms that ward off structural and functional deterioration within living systems. Collectively, these data offer powerful insights into healthy aging and longevity. For example, molecular integrity of the genome, telomere length, epigenetic landscape stability, and protein homeostasis are all features linked to "youthful" states. These molecular hallmarks underlie cellular functions associated with aging like mitochondrial fitness, nutrient sensing, efficient intercellular communication, stem cell renewal, and regenerative capacity in tissues. At present, calorie restriction remains the most robust strategy for extending health and lifespan in most biological models tested. Thus, pathways that mediate the beneficial effects of calorie restriction by integrating metabolic signals to aging processes have received major attention, such as insulin/insulin growth factor-1, sirtuins, mammalian target of rapamycin, and 5' adenosine monophosphate-activated protein kinase. Consequently, small-molecule targets of these pathways have emerged in the impetuous search for calorie restriction mimetics, of which resveratrol, metformin, and rapamycin are the most extensively studied. A comprehensive understanding of the molecular and cellular mechanisms that underlie age-related deterioration and repair, and how these pathways interconnect, remains a major challenge for uncovering interventions to slow human aging while extending molecular and physiological youthfulness, vitality, and health. This review summarizes key molecular mechanisms underlying the biology of healthy aging and longevity.

Defect-induced solid state amorphization of molecular crystals

NASA Astrophysics Data System (ADS)

Lei, Lei; Carvajal, Teresa; Koslowski, Marisol

2012-04-01

We investigate the process of mechanically induced amorphization in small molecule organic crystals under extensive deformation. In this work, we develop a model that describes the amorphization of molecular crystals, in which the plastic response is calculated with a phase field dislocation dynamics theory in four materials: acetaminophen, sucrose, γ-indomethacin, and aspirin. The model is able to predict the fraction of amorphous material generated in single crystals for a given applied stress. Our results show that γ-indomethacin and sucrose demonstrate large volume fractions of amorphous material after sufficient plastic deformation, while smaller amorphous volume fractions are predicted in acetaminophen and aspirin, in agreement with experimental observation.

Root gravitropism: an experimental tool to investigate basic cellular and molecular processes underlying mechanosensing and signal transmission in plants

NASA Technical Reports Server (NTRS)

Boonsirichai, K.; Guan, C.; Chen, R.; Masson, P. H.

2002-01-01

The ability of plant organs to use gravity as a guide for growth, named gravitropism, has been recognized for over two centuries. This growth response to the environment contributes significantly to the upward growth of shoots and the downward growth of roots commonly observed throughout the plant kingdom. Root gravitropism has received a great deal of attention because there is a physical separation between the primary site for gravity sensing, located in the root cap, and the site of differential growth response, located in the elongation zones (EZs). Hence, this system allows identification and characterization of different phases of gravitropism, including gravity perception, signal transduction, signal transmission, and curvature response. Recent studies support some aspects of an old model for gravity sensing, which postulates that root-cap columellar amyloplasts constitute the susceptors for gravity perception. Such studies have also allowed the identification of several molecules that appear to function as second messengers in gravity signal transduction and of potential signal transducers. Auxin has been implicated as a probable component of the signal that carries the gravitropic information between the gravity-sensing cap and the gravity-responding EZs. This has allowed the identification and characterization of important molecular processes underlying auxin transport and response in plants. New molecular models can be elaborated to explain how the gravity signal transduction pathway might regulate the polarity of auxin transport in roots. Further studies are required to test these models, as well as to study the molecular mechanisms underlying a poorly characterized phase of gravitropism that is independent of an auxin gradient.

Theoretical study on interaction of cytochrome f and plastocyanin complex by a simple coarse-grained model with molecular crowding effect

NASA Astrophysics Data System (ADS)

Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Kawaguchi, Kazutomo; Nagao, Hidemi

2018-03-01

We present a simple coarse-grained model with the molecular crowding effect in solvent to investigate the structure and dynamics of protein complexes including association and/or dissociation processes and investigate some physical properties such as the structure and the reaction rate from the viewpoint of the hydrophobic intermolecular interactions of protein complex. In the present coarse-grained model, a function depending upon the density of hydrophobic amino acid residues in a binding area of the complex is introduced, and the function involves the molecular crowding effect for the intermolecular interactions of hydrophobic amino acid residues between proteins. We propose a hydrophobic intermolecular potential energy between proteins by using the density-dependent function. The present coarse-grained model is applied to the complex of cytochrome f and plastocyanin by using the Langevin dynamics simulation to investigate some physical properties such as the complex structure, the electron transfer reaction rate constant from plastocyanin to cytochrome f and so on. We find that for proceeding the electron transfer reaction, the distance between metals in their active sites is necessary within about 18 Å. We discuss some typical complex structures formed in the present simulation in relation to the molecular crowding effect on hydrophobic interactions.

A new model for biological effects of radiation and the driven force of molecular evolution

NASA Astrophysics Data System (ADS)

Wada, Takahiro; Manabe, Yuichiro; Nakajima, Hiroo; Tsunoyama, Yuichi; Bando, Masako

We proposed a new mathematical model to estimate biological effects of radiation, which we call Whack-A-Mole (WAM) model. A special feature of WAM model is that it involves the dose rate of radiation as a key ingredient. We succeeded to reproduce the experimental data of various species concerning the radiation induced mutation frequencies. From the analysis of the mega-mouse experiments, we obtained the mutation rate per base-pair per year for mice which is consistent with the so-called molecular clock in evolution genetics, 10-9 mutation/base-pair/year. Another important quantity is the equivalent dose rate for the whole spontaneous mutation, deff. The value of deff for mice is 1.1*10-3 Gy/hour which is much larger than the dose rate of natural radiation (10- (6 - 7) Gy/hour) by several orders of magnitude. We also analyzed Drosophila data and obtained essentially the same numbers. This clearly indicates that the natural radiation is not the dominant driving force of the molecular evolution, but we should look for other factors, such as miscopy of DNA in duplication process. We believe this is the first quantitative proof of the small contribution of the natural radiation in the molecular evolution.

Synapse alterations in autism: Review of animal model findings.

PubMed

Zatkova, Martina; Bakos, Jan; Hodosy, Julius; Ostatnikova, Daniela

2016-06-01

Recent research has produced an explosion of experimental data on the complex neurobiological mechanisms of developmental disorders including autism. Animal models are one approach to studying the phenotypic features and molecular basis of autism. In this review, we describe progress in understanding synaptogenesis and alterations to this process with special emphasis on the cell adhesion molecules and scaffolding proteins implicated in autism. Genetic mouse model experiments are discussed in relation to alterations to selected synaptic proteins and consequent behavioral deficits measured in animal experiments. Pubmed databases were used to search for original and review articles on animal and human clinical studies on autism. The cell adhesion molecules, neurexin, neurolignin and the Shank family of proteins are important molecular targets associated with autism. The heterogeneity of the autism spectrum of disorders limits interpretation of information acquired from any single animal model or animal test. We showed synapse-specific/ model-specific defects associated with a given genotype in these models. Characterization of mouse models with genetic variations may help study the mechanisms of autism in humans. However, it will be necessary to apply new analytic paradigms in using genetically modified mice for understanding autism etiology in humans. Further studies are needed to create animal models with mutations that match the molecular and neural bases of autism.

Computer simulation of surface and film processes

NASA Technical Reports Server (NTRS)

Tiller, W. A.; Halicioglu, M. T.

1984-01-01

All the investigations which were performed employed in one way or another a computer simulation technique based on atomistic level considerations. In general, three types of simulation methods were used for modeling systems with discrete particles that interact via well defined potential functions: molecular dynamics (a general method for solving the classical equations of motion of a model system); Monte Carlo (the use of Markov chain ensemble averaging technique to model equilibrium properties of a system); and molecular statics (provides properties of a system at T = 0 K). The effects of three-body forces on the vibrational frequencies of triatomic cluster were investigated. The multilayer relaxation phenomena for low index planes of an fcc crystal was analyzed also as a function of the three-body interactions. Various surface properties for Si and SiC system were calculated. Results obtained from static simulation calculations for slip formation were presented. The more elaborate molecular dynamics calculations on the propagation of cracks in two-dimensional systems were outlined.

Building up a QSAR model for toxicity toward Tetrahymena pyriformis by the Monte Carlo method: A case of benzene derivatives.

PubMed

Toropova, Alla P; Schultz, Terry W; Toropov, Andrey A

2016-03-01

Data on toxicity toward Tetrahymena pyriformis is indicator of applicability of a substance in ecologic and pharmaceutical aspects. Quantitative structure-activity relationships (QSARs) between the molecular structure of benzene derivatives and toxicity toward T. pyriformis (expressed as the negative logarithms of the population growth inhibition dose, mmol/L) are established. The available data were randomly distributed three times into the visible training and calibration sets, and invisible validation sets. The statistical characteristics for the validation set are the following: r(2)=0.8179 and s=0.338 (first distribution); r(2)=0.8682 and s=0.341 (second distribution); r(2)=0.8435 and s=0.323 (third distribution). These models are built up using only information on the molecular structure: no data on physicochemical parameters, 3D features of the molecular structure and quantum mechanics descriptors are involved in the modeling process. Copyright © 2016 Elsevier B.V. All rights reserved.

A novel approach to the investigation of passive molecular permeation through lipid bilayers from atomistic simulations.

PubMed

Ghaemi, Zhaleh; Minozzi, Manuela; Carloni, Paolo; Laio, Alessandro

2012-07-26

Predicting the permeability coefficient (P) of drugs permeating through the cell membrane is of paramount importance in drug discovery. We here propose an approach for calculating P based on bias-exchange metadynamics. The approach allows constructing from atomistic simulations a model of permeation taking explicitly into account not only the "trivial" reaction coordinate, the position of the drug along the direction normal to the lipid membrane plane, but also other degrees of freedom, for example, the torsional angles of the permeating molecule, or variables describing its solvation/desolvation. This allows deriving an accurate picture of the permeation process, and constructing a detailed molecular model of the transition state, making a rational control of permeation properties possible. We benchmarked this approach on the permeation of ethanol molecules through a POPC membrane, showing that the value of P calculated with our model agrees with the one calculated by a long unbiased molecular dynamics of the same system.

Nonholonomic Hamiltonian Method for Molecular Dynamics Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Bass, Joseph

2015-06-01

Conventional molecular dynamics simulations of reacting shocks employ a holonomic Hamiltonian formulation: the breaking and forming of covalent bonds is described by potential functions. In general these potential functions: (a) are algebraically complex, (b) must satisfy strict smoothness requirements, and (c) contain many fitted parameters. In recent research the authors have developed a new noholonomic formulation of reacting molecular dynamics. In this formulation bond orders are determined by rate equations and the bonding-debonding process need not be described by differentiable functions. This simplifies the representation of complex chemistry and reduces the number of fitted model parameters. Example applications of the method show molecular level shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

Predicting unfolding thermodynamics and stable intermediates for alanine-rich helical peptides with the aid of coarse-grained molecular simulation.

PubMed

Calero-Rubio, Cesar; Paik, Bradford; Jia, Xinqiao; Kiick, Kristi L; Roberts, Christopher J

2016-10-01

This report focuses on the molecular-level processes and thermodynamics of unfolding of a series of helical peptides using a coarse-grained (CG) molecular model. The CG model was refined to capture thermodynamics and structural changes as a function of temperature for a set of published peptide sequences. Circular dichroism spectroscopy (CD) was used to experimentally monitor the temperature-dependent conformational changes and stability of published peptides and new sequences introduced here. The model predictions were quantitatively or semi-quantitatively accurate in all cases. The simulations and CD results showed that, as expected, in most cases the unfolding of helical peptides is well described by a simply 2-state model, and conformational stability increased with increased length of the helices. A notable exception in a 19-residue helix was when two Ala residues were each replaced with Phe. This stabilized a partly unfolded intermediate state via hydrophobic contacts, and also promoted aggregates at higher peptide concentrations. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling of lipase catalyzed ring-opening polymerization of epsilon-caprolactone.

PubMed

Sivalingam, G; Madras, Giridhar

2004-01-01

Enzymatic ring-opening polymerization of epsilon-caprolactone by various lipases was investigated in toluene at various temperatures. The determination of molecular weight and structural identification was carried out with gel permeation chromatography and proton NMR, respectively. Among the various lipases employed, an immobilized lipase from Candida antartica B (Novozym 435) showed the highest catalytic activity. The polymerization of epsilon-caprolactone by Novozym 435 showed an optimal temperature of 65 degrees C and an optimum toluene content of 50/50 v/v of toluene and epsilon-caprolactone. As lipases can degrade polyesters, a maximum in the molecular weight with time was obtained due to the competition of ring opening polymerization and degradation by specific chain end scission. The optimum temperature, toluene content, and the variation of molecular weight with time are consistent with earlier observations. A comprehensive model based on continuous distribution kinetics was developed to model these phenomena. The model accounts for simultaneous polymerization, degradation and enzyme deactivation and provides a technique to determine the rate coefficients for these processes. The dependence of these rate coefficients with temperature and monomer concentration is also discussed.

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

Modeling of the U1 snRNP assembly pathway in alternative splicing in human cells using Petri nets.

PubMed

Kielbassa, J; Bortfeldt, R; Schuster, S; Koch, I

2009-02-01

The investigation of spliceosomal processes is currently a topic of intense research in molecular biology. In the molecular mechanism of alternative splicing, a multi-protein-RNA complex - the spliceosome - plays a crucial role. To understand the biological processes of alternative splicing, it is essential to comprehend the biogenesis of the spliceosome. In this paper, we propose the first abstract model of the regulatory assembly pathway of the human spliceosomal subunit U1. Using Petri nets, we describe its highly ordered assembly that takes place in a stepwise manner. Petri net theory represents a mathematical formalism to model and analyze systems with concurrent processes at different abstraction levels with the possibility to combine them into a uniform description language. There exist many approaches to determine static and dynamic properties of Petri nets, which can be applied to analyze biochemical systems. In addition, Petri net tools usually provide intuitively understandable graphical network representations, which facilitate the dialog between experimentalists and theoreticians. Our Petri net model covers binding, transport, signaling, and covalent modification processes. Through the computation of structural and behavioral Petri net properties and their interpretation in biological terms, we validate our model and use it to get a better understanding of the complex processes of the assembly pathway. We can explain the basic network behavior, using minimal T-invariants which represent special pathways through the network. We find linear as well as cyclic pathways. We determine the P-invariants that represent conserved moieties in a network. The simulation of the net demonstrates the importance of the stability of complexes during the maturation pathway. We can show that complexes that dissociate too fast, hinder the formation of the complete U1 snRNP.

Heat capacity changes in carbohydrates and protein-carbohydrate complexes.

PubMed

Chavelas, Eneas A; García-Hernández, Enrique

2009-05-13

Carbohydrates are crucial for living cells, playing myriads of functional roles that range from being structural or energy-storage devices to molecular labels that, through non-covalent interaction with proteins, impart exquisite selectivity in processes such as molecular trafficking and cellular recognition. The molecular bases that govern the recognition between carbohydrates and proteins have not been fully understood yet. In the present study, we have obtained a surface-area-based model for the formation heat capacity of protein-carbohydrate complexes, which includes separate terms for the contributions of the two molecular types. The carbohydrate model, which was calibrated using carbohydrate dissolution data, indicates that the heat capacity contribution of a given group surface depends on its position in the saccharide molecule, a picture that is consistent with previous experimental and theoretical studies showing that the high abundance of hydroxy groups in carbohydrates yields particular solvation properties. This model was used to estimate the carbohydrate's contribution in the formation of a protein-carbohydrate complex, which in turn was used to obtain the heat capacity change associated with the protein's binding site. The model is able to account for protein-carbohydrate complexes that cannot be explained using a previous model that only considered the overall contribution of polar and apolar groups, while allowing a more detailed dissection of the elementary contributions that give rise to the formation heat capacity effects of these adducts.

What Can Biochemistry Students Learn about Protein Translation? Using Variation Theory to Explore the Space of Learning Created by Some Common External Representations

ERIC Educational Resources Information Center

Bussey, Thomas J.

2013-01-01

Biochemistry education relies heavily on students' ability to visualize abstract cellular and molecular processes, mechanisms, and components. As such, biochemistry educators often turn to external representations to provide tangible, working models from which students' internal representations (mental models) can be constructed, evaluated, and…

[Influence of Three Low-Molecular-Weight Organic Acids on the Adsorption of Phenanthrene in Purple Soil].

PubMed

Xie, Li; Chen, Ben-shou; Zhang, Jin-zhong; Lu, Song; Jiang, Tao

2016-03-15

The effects of three low-molecular-weight organic acids (citric acid, malic acid and oxalic acid) on the adsorption of phenanthrene in purple soil were studied by static adsorption experiment. The results showed that the adsorption kinetic process of phenanthrene in purple soil could be described by the second-order kinetic model, and the adsorption rate constant would significantly decrease in the presence of the three low-molecular-weight organic acids ( LMWOAs). The adsorption thermodynamic process could be well described by linear adsorption model, which was dominated by distribution role. The three LMWOAs could promote the adsorption of phenantherene in purple soil when their concentrations were less than 5 mmol · L⁻¹, whereas inhibit the adsorption when their concentrations were more than 10 mmol · L⁻¹, and the inhibition would increase with increasing concentrations. Moreover, the inhibitory ability displayed a decreasing order of citric acid, oxalic acid, and malic acid when their concentrations were 20 mmol · L⁻¹, which is related to the molecular structure and acidity of the three LMWOAs. Compared with the control, the content of dissolved organic matter (DOM) released from purple soil showed a trend of first decrease and then increase with increasing LMWOAs concentration, and the adsorption capacity of phenanthrene in purple soil was negatively related to DOM content.

The Physics and Physical Chemistry of Molecular Machines.

PubMed

Astumian, R Dean; Mukherjee, Shayantani; Warshel, Arieh

2016-06-17

The concept of a "power stroke"-a free-energy releasing conformational change-appears in almost every textbook that deals with the molecular details of muscle, the flagellar rotor, and many other biomolecular machines. Here, it is shown by using the constraints of microscopic reversibility that the power stroke model is incorrect as an explanation of how chemical energy is used by a molecular machine to do mechanical work. Instead, chemically driven molecular machines operating under thermodynamic constraints imposed by the reactant and product concentrations in the bulk function as information ratchets in which the directionality and stopping torque or stopping force are controlled entirely by the gating of the chemical reaction that provides the fuel for the machine. The gating of the chemical free energy occurs through chemical state dependent conformational changes of the molecular machine that, in turn, are capable of generating directional mechanical motions. In strong contrast to this general conclusion for molecular machines driven by catalysis of a chemical reaction, a power stroke may be (and often is) an essential component for a molecular machine driven by external modulation of pH or redox potential or by light. This difference between optical and chemical driving properties arises from the fundamental symmetry difference between the physics of optical processes, governed by the Bose-Einstein relations, and the constraints of microscopic reversibility for thermally activated processes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability

PubMed Central

2014-01-01

Background Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Methods We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. Results Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. Conclusions We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability. PMID:24965703

Boundary conditions for the paleoenvironment: Chemical and Physical Processes in dense interstellar clouds

NASA Technical Reports Server (NTRS)

Irvine, W. M.; Schloerb, F. P.; Ziurys, L. M.

1986-01-01

The present research includes searches for important new interstellar constituents; observations relevant to differentiating between different models for the chemical processes that are important in the interstellar environment; and coordinated studies of the chemistry, physics, and dynamics of molecular clouds which are the sites or possible future sites of star formation. Recent research has included the detection and study of four new interstellar molecules; searches which have placed upper limits on the abundance of several other potential constituents of interstellar clouds; quantitative studies of comparative molecular abundances in different types of interstellar clouds; investigation of reaction pathways for astrochemistry from a comparison of theory and the observed abundance of related species such as isomers and isotopic variants; studies of possible tracers of energenic events related to star formation, including silicon and sulfur containing molecules; and mapping of physical, chemical, and dynamical properties over extended regions of nearby cold molecular clouds.

Mesoscale Polymer Dissolution Probed by Raman Spectroscopy and Molecular Simulations

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

Chang, Tsun-Mei; Xantheas, Sotiris S.; Vasdekis, Andreas E.

2016-10-13

The diffusion of various solvents into a polystyrene (PS) matrix was probed experimentally by monitoring the temporal profiles of the Raman spectra and theoretically from molecular dynamics (MD) simulations of the binary system. The simulation results assist in providing a fundamental, molecular level connection between the mixing/dissolution processes and the difference = solvent – PS in the values of the Hildebrand parameter () between the two components of the binary systems: solvents having similar values of with PS (small ) exhibit fast diffusion into the polymer matrix, whereas the diffusion slows down considerably when the ’s are different (large ).more » To this end, the Hildebrand parameter was identified as a useful descriptor that governs the process of mixing in polymer – solvent binary systems. The experiments also provide insight into further refinements of the models specific to non-Fickian diffusion phenomena that need to be used in the simulations.« less

Final Report: Molecular mechanisms and kinetics of microbial anaerobic nitrate-dependent U(IV) and Fe(II) oxidation

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

O'Day, Peggy A.; Asta, Maria P.; Kanematsu, Masakazu

2015-02-27

In this project, we combined molecular genetic, spectroscopic, and microscopic techniques with kinetic and reactive transport studies to describe and quantify biotic and abiotic mechanisms underlying anaerobic, nitrate-dependent U(IV) and Fe(II) oxidation, which influences the long-term efficacy of in situ reductive immobilization of uranium at DOE sites. In these studies, Thiobacillus denitrificans, an autotrophic bacterium that catalyzes anaerobic U(IV) and Fe(II) oxidation, was used to examine coupled oxidation-reduction processes under either biotic (enzymatic) or abiotic conditions in batch and column experiments with biogenically produced UIVO2(s). Synthesis and quantitative analysis of coupled chemical and transport processes were done with the reactivemore » transport modeling code Crunchflow. Research focused on identifying the primary redox proteins that catalyze metal oxidation, environmental factors that influence protein expression, and molecular-scale geochemical factors that control the rates of biotic and abiotic oxidation.« less

Materials-by-design: computation, synthesis, and characterization from atoms to structures

NASA Astrophysics Data System (ADS)

Yeo, Jingjie; Jung, Gang Seob; Martín-Martínez, Francisco J.; Ling, Shengjie; Gu, Grace X.; Qin, Zhao; Buehler, Markus J.

2018-05-01

In the 50 years that succeeded Richard Feynman’s exposition of the idea that there is ‘plenty of room at the bottom’ for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Molecular ion yield enhancement induced by gold deposition in static secondary ion mass spectrometry

NASA Astrophysics Data System (ADS)

Wehbe, Nimer; Delcorte, Arnaud; Heile, Andreas; Arlinghaus, Heinrich F.; Bertrand, Patrick

2008-12-01

Static ToF-SIMS was used to evaluate the effect of gold condensation as a sample treatment prior to analysis. The experiments were carried out with a model molecular layer (Triacontane M = 422.4 Da), upon atomic (In +) and polyatomic (Bi 3+) projectile bombardment. The results indicate that the effect of molecular ion yield improvement using gold metallization exists only under atomic projectile impact. While the quasi-molecular ion (M+Au) + signal can become two orders of magnitude larger than that of the deprotonated molecular ion from the pristine sample under In + bombardment, it barely reaches the initial intensity of (M-H) + when Bi 3+ projectiles are used. The differences observed for mono- and polyatomic primary ion bombardment might be explained by differences in near-surface energy deposition, which influences the sputtering and ionization processes.

Molecular mechanisms of temperature adaptation

PubMed Central

Bagriantsev, Sviatoslav N; Gracheva, Elena O

2015-01-01

Thermal perception is a fundamental physiological process pertaining to the vast majority of organisms. In vertebrates, environmental temperature is detected by the primary afferents of the somatosensory neurons in the skin, which express a ‘choir’ of ion channels tuned to detect particular temperatures. Nearly two decades of research have revealed a number of receptor ion channels that mediate the perception of several temperature ranges, but most still remain molecularly orphaned. Yet even within this well-researched realm, most of our knowledge largely pertains to two closely related species of rodents, mice and rats. While these are standard biomedical research models, mice and rats provide a limited perspective to elucidate the general principles that drive somatosensory evolution. In recent years, significant advances have been made in understanding the molecular mechanism of temperature adaptation in evolutionarily distant vertebrates and in organisms with acute thermal sensitivity. These studies have revealed the remarkable versatility of the somatosensory system and highlighted adaptations at the molecular level, which often include changes in biophysical properties of ion channels from the transient receptor potential family. Exploiting non-standard animal models has the potential to provide unexpected insights into general principles of thermosensation and thermoregulation, unachievable using the rodent model alone. PMID:25433072

Molecular perspective on diazonium adsorption for controllable functionalization of single-walled carbon nanotubes in aqueous surfactant solutions.

PubMed

Lin, Shangchao; Hilmer, Andrew J; Mendenhall, Jonathan D; Strano, Michael S; Blankschtein, Daniel

2012-05-16

Functionalization of single-walled carbon nanotubes (SWCNTs) using diazonium salts allows modification of their optical and electronic properties for a variety of applications, ranging from drug-delivery vehicles to molecular sensors. However, control of the functionalization process remains a challenge, requiring molecular-level understanding of the adsorption of diazonium ions onto heterogeneous, charge-mobile SWCNT surfaces, which are typically decorated with surfactants. In this paper, we combine molecular dynamics (MD) simulations, experiments, and equilibrium reaction modeling to understand and model the extent of diazonium functionalization of SWCNTs coated with various surfactants (sodium cholate, sodium dodecyl sulfate, and cetyl trimethylammonium bromide). We show that the free energy of diazonium adsorption, determined using simulations, can be used to rank surfactants in terms of the extent of functionalization attained following their adsorption on the nanotube surface. The difference in binding affinities between linear and rigid surfactants is attributed to the synergistic binding of the diazonium ion to the local "hot/cold spots" formed by the charged surfactant heads. A combined simulation-modeling framework is developed to provide guidance for controlling the various sensitive experimental conditions needed to achieve the desired extent of SWCNT functionalization.

Molecular-dynamics Simulation-based Cohesive Zone Representation of Intergranular Fracture Processes in Aluminum

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin I.; Saether, Erik; Phillips, Dawn R.; Glaessgen, Edward H.

2006-01-01

A traction-displacement relationship that may be embedded into a cohesive zone model for microscale problems of intergranular fracture is extracted from atomistic molecular-dynamics simulations. A molecular-dynamics model for crack propagation under steady-state conditions is developed to analyze intergranular fracture along a flat 99 [1 1 0] symmetric tilt grain boundary in aluminum. Under hydrostatic tensile load, the simulation reveals asymmetric crack propagation in the two opposite directions along the grain boundary. In one direction, the crack propagates in a brittle manner by cleavage with very little or no dislocation emission, and in the other direction, the propagation is ductile through the mechanism of deformation twinning. This behavior is consistent with the Rice criterion for cleavage vs. dislocation blunting transition at the crack tip. The preference for twinning to dislocation slip is in agreement with the predictions of the Tadmor and Hai criterion. A comparison with finite element calculations shows that while the stress field around the brittle crack tip follows the expected elastic solution for the given boundary conditions of the model, the stress field around the twinning crack tip has a strong plastic contribution. Through the definition of a Cohesive-Zone-Volume-Element an atomistic analog to a continuum cohesive zone model element - the results from the molecular-dynamics simulation are recast to obtain an average continuum traction-displacement relationship to represent cohesive zone interaction along a characteristic length of the grain boundary interface for the cases of ductile and brittle decohesion. Keywords: Crack-tip plasticity; Cohesive zone model; Grain boundary decohesion; Intergranular fracture; Molecular-dynamics simulation

Embryonic exposure to model naphthenic acids delays growth and hatching in the pond snail Lymnaea stagnalis.

PubMed

Johnston, Christina U; Clothier, Lindsay N; Quesnel, Dean M; Gieg, Lisa M; Chua, Gordon; Hermann, Petra M; Wildering, Willem C

2017-02-01

Naphthenic acids (NAs), a class of structurally diverse carboxylic acids with often complex ring structures and large aliphatic tail groups, are important by-products of many petrochemical processes including the oil sands mining activity of Northern Alberta. While it is evident that NAs have both acute and chronic harmful effects on many organisms, many aspects of their toxicity remain to be clarified. Particularly, while substantive data sets have been collected on NA toxicity in aquatic prokaryote and vertebrate model systems, to date, nothing is known about the toxic effects of these compounds on the embryonic development of aquatic invertebrate taxa, including freshwater mollusks. This study examines under laboratory conditions the toxicity of NAs extracted from oil sands process water (OSPW) and the low-molecular weight model NAs cyclohexylsuccinic acid (CHSA), cyclohexanebutyric acid (CHBA), and 4-tert-butylcyclohexane carboxylic acid (4-TBCA) on embryonic development of the snail Lymnaea stagnalis, a common freshwater gastropod with a broad Palearctic distribution. Evidence is provided for concentration-dependent teratogenic effects of both OSPW-derived and model NAs with remarkably similar nominal threshold concentrations between 15 and 20 mg/L and 28d EC 50 of 31 mg/L. In addition, the data provide evidence for substantial toxicokinetic differences between CHSA, CHBA and 4-TBCA. Together, our study introduces Lymnaea stagnalis embryonic development as an effective model to assay NA-toxicity and identifies molecular architecture as a potentially important toxicokinetic parameter in the toxicity of low-molecular weight NA in embryonic development of aquatic gastropods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dissociation and Internal Excitation of Molecular Nitrogen Due to N + N2 Collisions Using Direct Molecular Simulation

NASA Technical Reports Server (NTRS)

Grover, Maninder S.; Schwartzentruber, Thomas E.; Jaffe, Richard L.

2017-01-01

In this work we present a molecular level study of N2+N collisions, focusing on excitation of internal energy modes and non-equilibrium dissociation. The computation technique used here is the direct molecular simulation (DMS) method and the molecular interactions have been modeled using an ab-initio potential energy surface (PES) developed at NASA's Ames Research Center. We carried out vibrational excitation calculations between 5000K and 30000K and found that the characteristic vibrational excitation time for the N + N2 process was an order of magnitude lower than that predicted by the Millikan and White correlation. It is observed that during vibrational excitation the high energy tail of the vibrational energy distribution gets over populated first and the lower energy levels get populated as the system evolves. It is found that the non-equilibrium dissociation rate coefficients for the N + N2 process are larger than those for the N2 + N2 process. This is attributed to the non-equilibrium vibrational energy distributions for the N + N2 process being less depleted than that for the N2 +N2 process. For an isothermal simulation we find that the probability of dissociation goes as 1/T(sub tr) for molecules with internal energy (epsilon(sub int)) less than approximately 9.9eV, while for molecules with epsilon (sub int) greater than 9.9eV the dissociation probability was weakly dependent on translational temperature of the system. We compared non-equilibrium dissociation rate coefficients and characteristic vibrational excitation times obtained by using the ab-initio PES developed at NASA's Ames Research Center to those obtained by using an ab-initio PES developed at the University of Minnesota. Good agreement was found between the macroscopic properties and molecular level description of the system obtained by using the two PESs.

Combined 3D-QSAR, molecular docking, molecular dynamics simulation, and binding free energy calculation studies on the 5-hydroxy-2H-pyridazin-3-one derivatives as HCV NS5B polymerase inhibitors.

PubMed

Yu, Haijing; Fang, Yu; Lu, Xia; Liu, Yongjuan; Zhang, Huabei

2014-01-01

The NS5B RNA-dependent RNA polymerase (RdRP) is a promising therapeutic target for developing novel anti-hepatitis C virus (HCV) drugs. In this work, a combined molecular modeling study was performed on a series of 193 5-hydroxy-2H-pyridazin-3-one derivatives as inhibitors of HCV NS5B Polymerase. The best 3D-QSAR models, including CoMFA and CoMSIA, are based on receptor (or docking). Furthermore, a 40-ns molecular dynamics (MD) simulation and binding free energy calculations using docked structures of NS5B with ten compounds, which have diverse structures and pIC50 values, were employed to determine the detailed binding process and to compare the binding modes of the inhibitors with different activities. On one side, the stability and rationality of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM-PBSA method gave a good correlation with the experimental biological activity. On the other side, by analyzing some differences between the molecular docking and the MD simulation results, we can find that the MD simulation could also remedy the defects of molecular docking. The analyses of the combined molecular modeling results have identified that Tyr448, Ser556, and Asp318 are the key amino acid residues in the NS5B binding pocket. The results from this study can provide some insights into the development of novel potent NS5B inhibitors. © 2013 John Wiley & Sons A/S.

REVIEWS OF TOPICAL PROBLEMS: Physical aspects of cryobiology

NASA Astrophysics Data System (ADS)

Zhmakin, A. I.

2008-03-01

Physical phenomena during biological freezing and thawing processes at the molecular, cellular, tissue, and organ levels are examined. The basics of cryosurgery and cryopreservation of cells and tissues are presented. Existing cryobiological models, including numerical ones, are reviewed.

Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

PubMed

Ramírez, Carlos; Mendoza, Luis

2018-04-01

Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

S&MPO - An information system for ozone spectroscopy on the WEB

NASA Astrophysics Data System (ADS)

Babikov, Yurii L.; Mikhailenko, Semen N.; Barbe, Alain; Tyuterev, Vladimir G.

2014-09-01

Spectroscopy and Molecular Properties of Ozone ("S&MPO") is an Internet accessible information system devoted to high resolution spectroscopy of the ozone molecule, related properties and data sources. S&MPO contains information on original spectroscopic data (line positions, line intensities, energies, transition moments, spectroscopic parameters) recovered from comprehensive analyses and modeling of experimental spectra as well as associated software for data representation written in PHP Java Script, C++ and FORTRAN. The line-by-line list of vibration-rotation transitions and other information is organized as a relational database under control of MySQL database tools. The main S&MPO goal is to provide access to all available information on vibration-rotation molecular states and transitions under extended conditions based on extrapolations of laboratory measurements using validated theoretical models. Applications for the S&MPO may include: education/training in molecular physics, radiative processes, laser physics; spectroscopic applications (analysis, Fourier transform spectroscopy, atmospheric optics, optical standards, spectroscopic atlases); applications to environment studies and atmospheric physics (remote sensing); data supply for specific databases; and to photochemistry (laser excitation, multiphoton processes). The system is accessible via Internet on two sites: http://smpo.iao.ru and http://smpo.univ-reims.fr.

INVOLVEMENT OF MULTIPLE MOLECULAR PATHWAYS IN THE GENETICS OF OCULAR REFRACTION AND MYOPIA.

PubMed

Wojciechowski, Robert; Cheng, Ching-Yu

2018-01-01

The prevalence of myopia has increased dramatically worldwide within the last three decades. Recent studies have shown that refractive development is influenced by environmental, behavioral, and inherited factors. This review aims to analyze recent progress in the genetics of refractive error and myopia. A comprehensive literature search of PubMed and OMIM was conducted to identify relevant articles in the genetics of refractive error. Genome-wide association and sequencing studies have increased our understanding of the genetics involved in refractive error. These studies have identified interesting candidate genes. All genetic loci discovered to date indicate that refractive development is a heterogeneous process mediated by a number of overlapping biological processes. The exact mechanisms by which these biological networks regulate eye growth are poorly understood. Although several individual genes and/or molecular pathways have been investigated in animal models, a systematic network-based approach in modeling human refractive development is necessary to understand the complex interplay between genes and environment in refractive error. New biomedical technologies and better-designed studies will continue to refine our understanding of the genetics and molecular pathways of refractive error, and may lead to preventative and therapeutic measures to combat the myopia epidemic.

Multiscale computational modeling reveals a critical role for TNF-α receptor 1 dynamics in tuberculosis granuloma formation.

PubMed

Fallahi-Sichani, Mohammad; El-Kebir, Mohammed; Marino, Simeone; Kirschner, Denise E; Linderman, Jennifer J

2011-03-15

Multiple immune factors control host responses to Mycobacterium tuberculosis infection, including the formation of granulomas, which are aggregates of immune cells whose function may reflect success or failure of the host to contain infection. One such factor is TNF-α. TNF-α has been experimentally characterized to have the following activities in M. tuberculosis infection: macrophage activation, apoptosis, and chemokine and cytokine production. Availability of TNF-α within a granuloma has been proposed to play a critical role in immunity to M. tuberculosis. However, in vivo measurement of a TNF-α concentration gradient and activities within a granuloma are not experimentally feasible. Further, processes that control TNF-α concentration and activities in a granuloma remain unknown. We developed a multiscale computational model that includes molecular, cellular, and tissue scale events that occur during granuloma formation and maintenance in lung. We use our model to identify processes that regulate TNF-α concentration and cellular behaviors and thus influence the outcome of infection within a granuloma. Our model predicts that TNF-αR1 internalization kinetics play a critical role in infection control within a granuloma, controlling whether there is clearance of bacteria, excessive inflammation, containment of bacteria within a stable granuloma, or uncontrolled growth of bacteria. Our results suggest that there is an interplay between TNF-α and bacterial levels in a granuloma that is controlled by the combined effects of both molecular and cellular scale processes. Finally, our model elucidates processes involved in immunity to M. tuberculosis that may be new targets for therapy.

Extraction of gelatin from salmon (Salmo salar) fish skin using trypsin-aided process: optimization by Plackett-Burman and response surface methodological approaches.

PubMed

Fan, HuiYin; Dumont, Marie-Josée; Simpson, Benjamin K

2017-11-01

Gelatin from salmon ( Salmo salar ) skin with high molecular weight protein chains ( α -chains) was extracted using trypsin-aided process. Response surface methodology was used to optimise the extraction parameters. Yield, hydroxyproline content and protein electrophoretic profile via sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of gelatin were used as responses in the optimization study. The optimum conditions were determined as: trypsin concentration at 1.49 U/g; extraction temperature at 45 °C; and extraction time at 6 h 16 min. This response surface optimized model was significant and produced an experimental value (202.04 ± 8.64%) in good agreement with the predicted value (204.19%). Twofold higher yields of gelatin with high molecular weight protein chains were achieved in the optimized process with trypsin treatment when compared to the process without trypsin.

Modelling rate distributions using character compatibility: implications for morphological evolution among fossil invertebrates

PubMed Central

Wagner, Peter J.

2012-01-01

Rate distributions are important considerations when testing hypotheses about morphological evolution or phylogeny. They also have implications about general processes underlying character evolution. Molecular systematists often assume that rates are Poisson processes with gamma distributions. However, morphological change is the product of multiple probabilistic processes and should theoretically be affected by hierarchical integration of characters. Both factors predict lognormal rate distributions. Here, a simple inverse modelling approach assesses the best single-rate, gamma and lognormal models given observed character compatibility for 115 invertebrate groups. Tests reject the single-rate model for nearly all cases. Moreover, the lognormal outperforms the gamma for character change rates and (especially) state derivation rates. The latter in particular is consistent with integration affecting morphological character evolution. PMID:21795266

Agent based simulations in disease modeling Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Pappalardo, Francesco; Pennisi, Marzio

2016-07-01

Fibrosis represents a process where an excessive tissue formation in an organ follows the failure of a physiological reparative or reactive process. Mathematical and computational techniques may be used to improve the understanding of the mechanisms that lead to the disease and to test potential new treatments that may directly or indirectly have positive effects against fibrosis [1]. In this scenario, Ben Amar and Bianca [2] give us a broad picture of the existing mathematical and computational tools that have been used to model fibrotic processes at the molecular, cellular, and tissue levels. Among such techniques, agent based models (ABM) can give a valuable contribution in the understanding and better management of fibrotic diseases.

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

PubMed

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

Stochastic algorithm for simulating gas transport coefficients

NASA Astrophysics Data System (ADS)

Rudyak, V. Ya.; Lezhnev, E. V.

2018-02-01

The aim of this paper is to create a molecular algorithm for modeling the transport processes in gases that will be more efficient than molecular dynamics method. To this end, the dynamics of molecules are modeled stochastically. In a rarefied gas, it is sufficient to consider the evolution of molecules only in the velocity space, whereas for a dense gas it is necessary to model the dynamics of molecules also in the physical space. Adequate integral characteristics of the studied system are obtained by averaging over a sufficiently large number of independent phase trajectories. The efficiency of the proposed algorithm was demonstrated by modeling the coefficients of self-diffusion and the viscosity of several gases. It was shown that the accuracy comparable to the experimental one can be obtained on a relatively small number of molecules. The modeling accuracy increases with the growth of used number of molecules and phase trajectories.

Studies for the Loss of Atomic and Molecular Species from Io

NASA Technical Reports Server (NTRS)

Smyth, William H.

1998-01-01

Continued effort is reported to improve the emission rates of various emission lines for atomic oxygen and sulfur. Atomic hydrogen has been included as a new species in the neutral cloud model. The pertinent lifetime processes for hydrogen in the plasma torus and the relevant excitation processes for H Lyman-alpha emission in Io's atmosphere are discussed.

The molecular dynamic simulation on impact and friction characters of nanofluids with many nanoparticles system

PubMed Central

2011-01-01

Impact and friction model of nanofluid for molecular dynamics simulation was built which consists of two Cu plates and Cu-Ar nanofluid. The Cu-Ar nanofluid model consisted of eight spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard-Jones potential function was adopted to deal with the interactions between atoms. Thus motion states and interaction of nanoparticles at different time through impact and friction process could be obtained and friction mechanism of nanofluids could be analyzed. In the friction process, nanoparticles showed motions of rotation and translation, but effected by the interactions of nanoparticles, the rotation of nanoparticles was trapped during the compression process. In this process, agglomeration of nanoparticles was very apparent, with the pressure increasing, the phenomenon became more prominent. The reunited nanoparticles would provide supporting efforts for the whole channel, and in the meantime reduced the contact between two friction surfaces, therefore, strengthened lubrication and decreased friction. In the condition of overlarge positive pressure, the nanoparticles would be crashed and formed particles on atomic level and strayed in base liquid. PMID:21711753

Activation of Antitumorigenic Stat3beta in Breast Cancer by Splicing Redirection

DTIC Science & Technology

2013-07-01

4175) model system REPORTABLE OUTCOMES 1. Lee Spraggon and Luca Cartegni; Antisense Modulation of RNA Processing as a Therapeutic Approach in...modulation. Proc Natl Acad Sci U S A 108: 17779-17784. 26. Spraggon L, Cartegni L (2013) Antisense modulation of RNA processing as a therapeutic...pre-print copy 1 Antisense Modulation of RNA Processing as a Therapeutic Approach in Cancer Therapy Lee Spraggon and Luca Cartegni Molecular

Time scale of diffusion in molecular and cellular biology

NASA Astrophysics Data System (ADS)

Holcman, D.; Schuss, Z.

2014-05-01

Diffusion is the driver of critical biological processes in cellular and molecular biology. The diverse temporal scales of cellular function are determined by vastly diverse spatial scales in most biophysical processes. The latter are due, among others, to small binding sites inside or on the cell membrane or to narrow passages between large cellular compartments. The great disparity in scales is at the root of the difficulty in quantifying cell function from molecular dynamics and from simulations. The coarse-grained time scale of cellular function is determined from molecular diffusion by the mean first passage time of molecular Brownian motion to a small targets or through narrow passages. The narrow escape theory (NET) concerns this issue. The NET is ubiquitous in molecular and cellular biology and is manifested, among others, in chemical reactions, in the calculation of the effective diffusion coefficient of receptors diffusing on a neuronal cell membrane strewn with obstacles, in the quantification of the early steps of viral trafficking, in the regulation of diffusion between the mother and daughter cells during cell division, and many other cases. Brownian trajectories can represent the motion of a molecule, a protein, an ion in solution, a receptor in a cell or on its membrane, and many other biochemical processes. The small target can represent a binding site or an ionic channel, a hidden active site embedded in a complex protein structure, a receptor for a neurotransmitter on the membrane of a neuron, and so on. The mean time to attach to a receptor or activator determines diffusion fluxes that are key regulators of cell function. This review describes physical models of various subcellular microdomains, in which the NET coarse-grains the molecular scale to a higher cellular-level, thus clarifying the role of cell geometry in determining subcellular function.

Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

PubMed

Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

A computational model for telomere-dependent cell-replicative aging.

PubMed

Portugal, R D; Land, M G P; Svaiter, B F

2008-01-01

Telomere shortening provides a molecular basis for the Hayflick limit. Recent data suggest that telomere shortening also influence mitotic rate. We propose a stochastic growth model of this phenomena, assuming that cell division in each time interval is a random process which probability decreases linearly with telomere shortening. Computer simulations of the proposed stochastic telomere-regulated model provides good approximation of the qualitative growth of cultured human mesenchymal stem cells.

Molecular pathology of adamantinomatous craniopharyngioma: review and opportunities for practice.

PubMed

Apps, John Richard; Martinez-Barbera, Juan Pedro

2016-12-01

Since the first identification of CTNNB1 mutations in adamantinomatous craniopharyngioma (ACP), much has been learned about the molecular pathways and processes that are disrupted in ACP pathogenesis. To date this understanding has not translated into tangible patient benefit. The recent development of novel techniques and a range of preclinical models now provides an opportunity to begin to support treatment decisions and develop new therapeutics based on molecular pathology. In this review the authors summarize many of the key findings and pathways implicated in ACP pathogenesis and discuss the challenges that need to be tackled to translate these basic science findings for the benefit of patients.

Advances in the mechanical modeling of filamentous actin and its cross-linked networks on multiple scales.

PubMed

Unterberger, Michael J; Holzapfel, Gerhard A

2014-11-01

The protein actin is a part of the cytoskeleton and, therefore, responsible for the mechanical properties of the cells. Starting with the single molecule up to the final structure, actin creates a hierarchical structure of several levels exhibiting a remarkable behavior. The hierarchy spans several length scales and limitations in computational power; therefore, there is a call for different mechanical modeling approaches for the different scales. On the molecular level, we may consider each atom in molecular dynamics simulations. Actin forms filaments by combining the molecules into a double helix. In a model, we replace molecular subdomains using coarse-graining methods, allowing the investigation of larger systems of several atoms. These models on the nanoscale inform continuum mechanical models of large filaments, which are based on worm-like chain models for polymers. Assemblies of actin filaments are connected with cross-linker proteins. Models with discrete filaments, so-called Mikado models, allow us to investigate the dependence of the properties of networks on the parameters of the constituents. Microstructurally motivated continuum models of the networks provide insights into larger systems containing cross-linked actin networks. Modeling of such systems helps to gain insight into the processes on such small scales. On the other hand, they call for verification and hence trigger the improvement of established experiments and the development of new methods.

Model-based intensification of a fed-batch microbial process for the maximization of polyhydroxybutyrate (PHB) production rate.

PubMed

Penloglou, Giannis; Vasileiadou, Athina; Chatzidoukas, Christos; Kiparissides, Costas

2017-08-01

An integrated metabolic-polymerization-macroscopic model, describing the microbial production of polyhydroxybutyrate (PHB) in Azohydromonas lata bacteria, was developed and validated using a comprehensive series of experimental measurements. The model accounted for biomass growth, biopolymer accumulation, carbon and nitrogen sources utilization, oxygen mass transfer and uptake rates and average molecular weights of the accumulated PHB, produced under batch and fed-batch cultivation conditions. Model predictions were in excellent agreement with experimental measurements. The validated model was subsequently utilized to calculate optimal operating conditions and feeding policies for maximizing PHB productivity for desired PHB molecular properties. More specifically, two optimal fed-batch strategies were calculated and experimentally tested: (1) a nitrogen-limited fed-batch policy and (2) a nitrogen sufficient one. The calculated optimal operating policies resulted in a maximum PHB content (94% g/g) in the cultivated bacteria and a biopolymer productivity of 4.2 g/(l h), respectively. Moreover, it was demonstrated that different PHB grades with weight average molecular weights of up to 1513 kg/mol could be produced via the optimal selection of bioprocess operating 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 dynamics modeling of bonding two materials by atomic scale friction stir welding at different process parameters

NASA Astrophysics Data System (ADS)

Konovalenko S., Iv.; Psakhie, S. G.

2017-12-01

Using the molecular dynamics method, we simulated the atomic scale butt friction stir welding on two crystallites and varied the onset FSW tool plunge depth. The effects of the plunge depth value on the thermomechanical evolution of nanosized crystallites and mass transfer in the course of FSW have been studied. The increase of plunge depth values resulted in more intense heating and reducing the plasticized metal resistance to the tool movement. The mass transfer intensity was hardly dependent on the plunge depth value. The plunge depth was recommended to be used as a FSW process control parameter in addition to the commonly used ones.

[Vitamin K3-induced activation of molecular oxygen in glioma cells].

PubMed

Krylova, N G; Kulagova, T A; Semenkova, G N; Cherenkevich, S N

2009-01-01

It has been shown by the method of fluorescent analysis that the rate of hydrogen peroxide generation in human U251 glioma cells under the effect of lipophilic (menadione) or hydrophilic (vikasol) analogues of vitamin K3 was different. Analyzing experimental data we can conclude that menadione underwent one- and two-electron reduction by intracellular reductases in glioma cells. Reduced forms of menadione interact with molecular oxygen leading to reactive oxygen species (ROS) generation. The theoretical model of ROS generation including two competitive processes of one- and two-electron reduction of menadione has been proposed. Rate constants of ROS generation mediated by one-electron reduction process have been estimated.

A robust and reproducible human pluripotent stem cell derived model of neurite outgrowth in a three-dimensional culture system and its application to study neurite inhibition.

PubMed

Clarke, Kirsty E; Tams, Daniel M; Henderson, Andrew P; Roger, Mathilde F; Whiting, Andrew; Przyborski, Stefan A

2017-06-01

The inability of neurites to grow and restore neural connections is common to many neurological disorders, including trauma to the central nervous system and neurodegenerative diseases. Therefore, there is need for a robust and reproducible model of neurite outgrowth, to provide a tool to study the molecular mechanisms that underpin the process of neurite inhibition and to screen molecules that may be able to overcome such inhibition. In this study a novel in vitro pluripotent stem cell based model of human neuritogenesis was developed. This was achieved by incorporating additional technologies, notably a stable synthetic inducer of neural differentiation, and the application of three-dimensional (3D) cell culture techniques. We have evaluated the use of photostable, synthetic retinoid molecules to promote neural differentiation and found that 0.01 μM EC23 was the optimal concentration to promote differentiation and neurite outgrowth from human pluripotent stem cells within our model. We have also developed a methodology to enable quick and accurate quantification of neurite outgrowth derived from such a model. Furthermore, we have obtained significant neurite outgrowth within a 3D culture system enhancing the level of neuritogenesis observed and providing a more physiological microenvironment to investigate the molecular mechanisms that underpin neurite outgrowth and inhibition within the nervous system. We have demonstrated a potential application of our model in co-culture with glioma cells, to recapitulate aspects of the process of neurite inhibition that may also occur in the injured spinal cord. We propose that such a system that can be utilised to investigate the molecular mechanisms that underpin neurite inhibition mediated via glial and neuron interactions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Kinetics of CO2 diffusion in human carbonic anhydrase: a study using molecular dynamics simulations and the Markov-state model.

PubMed

Chen, Gong; Kong, Xian; Lu, Diannan; Wu, Jianzhong; Liu, Zheng

2017-05-10

Molecular dynamics (MD) simulations, in combination with the Markov-state model (MSM), were applied to probe CO 2 diffusion from an aqueous solution into the active site of human carbonic anhydrase II (hCA-II), an enzyme useful for enhanced CO 2 capture and utilization. The diffusion process in the hydrophobic pocket of hCA-II was illustrated in terms of a two-dimensional free-energy landscape. We found that CO 2 diffusion in hCA-II is a rate-limiting step in the CO 2 diffusion-binding-reaction process. The equilibrium distribution of CO 2 shows its preferential accumulation within a hydrophobic domain in the protein core region. An analysis of the committors and reactive fluxes indicates that the main pathway for CO 2 diffusion into the active site of hCA-II is through a binding pocket where residue Gln 136 contributes to the maximal flux. The simulation results offer a new perspective on the CO 2 hydration kinetics and useful insights toward the development of novel biochemical processes for more efficient CO 2 sequestration and utilization.

Process for attaching molecular wires and devices to carbon nanotubes and compositions thereof

NASA Technical Reports Server (NTRS)

Yang, Jiping (Inventor); Tour, James M. (Inventor); Bahr, Jeffrey L. (Inventor)

2008-01-01

The present invention is directed towards processes for covalently attaching molecular wires and molecular electronic devices to carbon nanotubes and compositions thereof. Such processes utilize diazonium chemistry to bring about this marriage of wire-like nanotubes with molecular wires and molecular electronic devices.

Template directed assembly of nanoelements in viscous polymer environments

NASA Astrophysics Data System (ADS)

Modi, Satyamkumar

Polymer melt-based manufacturing methods, such as injection molding, offer the potential of directly fabricating three-dimensional parts with nanostructured surfaces in a one-step, high-rate, and solventless process. Electrophoretic deposition has the potential to produce in-mold assembly of nanoparticles during injection molding. The process is fast, is cost effective and can be automated. This electrophoretic deposition, however, has been performed from low-viscosity media and polymer melts are far more viscous. This research provided a fundamental understanding of the electrophoretic deposition process in viscous media. Electrophoresis was performed using a model system of carbon black and polystyrene in tetrahydrofuran (THF). Examined were the effects of processing parameters, polystyrene molecular weight, and carbon black charge. The presence of polystyrene did not prevent deposition of carbon black, but deposition rates decreased at shorter deposition times; deposition was not linear with increasing applied voltage; and greater solution concentrations reduced the critical voltages. A comparison of experimental data with Hamaker's model showed that about 1.6% of the available polystyrene was initially deposited with the carbon black. At voltages above the critical voltage, the deposited mass indicated formation of electrically insulating layers on the electrodes. Increases in polystyrene molecular weight reduced the electrophoretic deposition of the carbon black particles due to increases in suspension viscosity and preferential adsorption of the longer polystyrene chains on the carbon black particles. At low deposition times (≤ 5 seconds), only carbon black deposited onto the electrodes. For longer deposition times, polystyrene co-deposited with the carbon black, with the amount of polystyrene increasing with molecular weight and decreasing with greater charge on the polystyrene molecules. The additional of function groups to the carbon black surface decoupled the carbon black and polystyrene, however, the deposition of the carbon black particles, followed by deposition of a thick layer of polystyrene was observed. This polystyrene deposition was present regardless of the applied voltage, the deposition time, the polystyrene molecular weight, polystyrene material (i.e., charge), and solvent polarity. This deposition behavior suggests that use of lower molecular polymers and unmodified carbon blacks, and control of electrical properties will permit electrophoretic deposition of nanoparticles from polymer melts.

The Effects of Polymer Carrier, Hot Melt Extrusion Process and Downstream Processing Parameters on the Moisture Sorption Properties of Amorphous Solid Dispersions

PubMed Central

Feng, Xin; Vo, Anh; Patil, Hemlata; Tiwari, Roshan V.; Alshetaili, Abdullah S.; Pimparade, Manjeet B.; Repka, Michael A.

2017-01-01

Objective The aim of this study was to evaluate the effect of polymer carrier, hot melt extrusion (HME) and downstream processing parameters on the water uptake properties of amorphous solid dispersions. Methods Three polymers and a model drug were used to prepare amorphous solid dispersions utilizing HME technology. The sorption-desorption isotherms of solid dispersions and their physical mixtures were measured by the Dynamic Vapor Sorption system, and the effect of polymer hydrophobicity, hygroscopicity, molecular weight and the HME process were investigated. FTIR imaging was performed to understand the phase separation driven by the moisture. Key findings Solid dispersions with polymeric carriers with lower hydrophilicity, hygroscopicity, and higher molecular weight could sorb less moisture under the high RH conditions. The water uptake ability of polymer-drug solid dispersion systems were decreased compared to the physical mixture after HME, which might be due to the decreased surface area and porosity. The FTIR imaging indicated the homogeneity of the drug molecularly dispersed within the polymer matrix was changed after exposure to high RH. Conclusion Understanding the effect of formulation and processing on the moisture sorption properties of solid dispersions is essential for the development of drug products with desired physical and chemical stability. PMID:26589107

What Is Moving in Hybrid Halide Perovskite Solar Cells?

PubMed Central

2016-01-01

Conspectus Organic–inorganic semiconductors, which adopt the perovskite crystal structure, have perturbed the landscape of contemporary photovoltaics research. High-efficiency solar cells can be produced with solution-processed active layers. The materials are earth abundant, and the simple processing required suggests that high-throughput and low-cost manufacture at scale should be possible. While these materials bear considerable similarity to traditional inorganic semiconductors, there are notable differences in their optoelectronic behavior. A key distinction of these materials is that they are physically soft, leading to considerable thermally activated motion. In this Account, we discuss the internal motion of methylammonium lead iodide (CH3NH3PbI3) and formamidinium lead iodide ([CH(NH2)2]PbI3), covering: (i) molecular rotation-libration in the cuboctahedral cavity; (ii) drift and diffusion of large electron and hole polarons; (iii) transport of charged ionic defects. These processes give rise to a range of properties that are unconventional for photovoltaic materials, including frequency-dependent permittivity, low electron–hole recombination rates, and current–voltage hysteresis. Multiscale simulations, drawing from electronic structure, ab initio molecular dynamic and Monte Carlo computational techniques, have been combined with neutron diffraction measurements, quasi-elastic neutron scattering, and ultrafast vibrational spectroscopy to qualify the nature and time scales of the motions. Electron and hole motion occurs on a femtosecond time scale. Molecular libration is a sub-picosecond process. Molecular rotations occur with a time constant of several picoseconds depending on the cation. Recent experimental evidence and theoretical models for simultaneous electron and ion transport in these materials has been presented, suggesting they are mixed-mode conductors with similarities to fast-ion conducting metal oxide perovskites developed for battery and fuel cell applications. We expound on the implications of these effects for the photovoltaic action. The temporal behavior displayed by hybrid perovskites introduces a sensitivity in materials characterization to the time and length scale of the measurement, as well as the history of each sample. It also poses significant challenges for accurate materials modeling and device simulations. There are large differences between the average and local crystal structures, and the nature of charge transport is too complex to be described by common one-dimensional drift-diffusion models. Herein, we critically discuss the atomistic origin of the dynamic processes and the associated chemical disorder intrinsic to crystalline hybrid perovskite semiconductors. PMID:26859250

Genomic Signal Processing: Predicting Basic Molecular Biological Principles

NASA Astrophysics Data System (ADS)

Alter, Orly

2005-03-01

Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of these two sets of states. Mapping genome-scale protein binding data using pseudoinverse projection onto patterns of RNA expression data that had been extracted by SVD and GSVD, a novel correlation between DNA replication initiation and RNA transcription during the cell cycle in yeast, that might be due to a previously unknown mechanism of regulation, is predicted. (1) Alter & Golub, Proc. Natl. Acad. Sci. USA 101, 16577 (2004). (2) Alter, Golub, Brown & Botstein, Miami Nat. Biotechnol. Winter Symp. 2004 (www.med.miami.edu/mnbws/alter-.pdf)

Molecular mechanisms of fear learning and memory.

PubMed

Johansen, Joshua P; Cain, Christopher K; Ostroff, Linnaea E; LeDoux, Joseph E

2011-10-28

Pavlovian fear conditioning is a particularly useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here, we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Collectively, this body of research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals and potentially for understanding fear-related disorders, such as PTSD and phobias. Copyright © 2011 Elsevier Inc. All rights reserved.

TRIGGERED STAR FORMATION SURROUNDING WOLF-RAYET STAR HD 211853

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

Liu Tie; Wu Yuefang; Zhang Huawei

The environment surrounding Wolf-Rayet (W-R) star HD 211853 is studied in molecular, infrared, as well as radio, and H I emission. The molecular ring consists of well-separated cores, which have a volume density of 10{sup 3} cm{sup -3} and kinematic temperature {approx}20 K. Most of the cores are under gravitational collapse due to external pressure from the surrounding ionized gas. From the spectral energy distribution modeling toward the young stellar objects, the sequential star formation is revealed on a large scale in space spreading from the W-R star to the molecular ring. A small-scale sequential star formation is revealed towardmore » core 'A', which harbors a very young star cluster. Triggered star formations are thus suggested. The presence of the photodissociation region, the fragmentation of the molecular ring, the collapse of the cores, and the large-scale sequential star formation indicate that the 'collect and collapse' process functions in this region. The star-forming activities in core 'A' seem to be affected by the 'radiation-driven implosion' process.« less

Carbohydrates.

PubMed

Cocinero, Emilio J; Çarçabal, Pierre

2015-01-01

Although carbohydrates represent one of the most important families of biomolecules, they remain under-studied in comparison to the other biomolecular families (peptides, nucleobases). Beyond their best-known function of energy source in living systems, they act as mediator of molecular recognition processes, carrying molecular information in the so-called "sugar code," just to name one of their countless functions. Owing to their high conformational flexibility, they encode extremely rich information conveyed via the non-covalent hydrogen bonds within the carbohydrate and with other biomolecular assemblies, such as peptide subunits of proteins. Over the last decade there has been tremendous progress in the study of the conformational preferences of neutral oligosaccharides, and of the interactions between carbohydrates and various molecular partners (water, aromatic models, and peptide models), using vibrational spectroscopy as a sensitive probe. In parallel, other spectroscopic techniques have recently become available to the study of carbohydrates in the gas phase (microwave spectroscopy, IRMPD on charged species).

Stabilization of Model Membrane Systems by Disaccharides. Quasielastic Neutron Scattering Experiments and Atomistic Simulations

NASA Astrophysics Data System (ADS)

Doxastakis, Emmanouil; Garcia Sakai, Victoria; Ohtake, Satoshi; Maranas, Janna K.; de Pablo, Juan J.

2006-03-01

Trehalose, a disaccharide of glucose, is often used for the stabilization of cell membranes in the absence of water. This work studies the effects of trehalose on model membrane systems as they undergo a melting transition using a combination of experimental methods and atomistic molecular simulations. Quasielastic neutron scattering experiments on selectively deuterated samples provide the incoherent dynamic structure over a wide time range. Elastic scans probing the lipid tail dynamics display clear evidence of a main melting transition that is significantly lowered in the presence of trehalose. Lipid headgroup mobility is considerably restricted at high temperatures and directly associated with the dynamics of the sugar in the mixture. Molecular simulations provide a detailed overview of the dynamics and their spatial and time dependence. The combined simulation and experimental methodology offers a unique, molecular view of the physics of systems commonly employed in cryopreservation and lyophilization processes.

A systems biology approach identifies molecular networks defining skeletal muscle abnormalities in chronic obstructive pulmonary disease.

PubMed

Turan, Nil; Kalko, Susana; Stincone, Anna; Clarke, Kim; Sabah, Ayesha; Howlett, Katherine; Curnow, S John; Rodriguez, Diego A; Cascante, Marta; O'Neill, Laura; Egginton, Stuart; Roca, Josep; Falciani, Francesco

2011-09-01

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co-ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients.

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory

NASA Astrophysics Data System (ADS)

Pontes, Arthur; de Sousa, Marcelo

2016-10-01

The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

Molecular modeling study of the induced-fit effect on kinase inhibition: the case of fibroblast growth factor receptor 3 (FGFR3)

NASA Astrophysics Data System (ADS)

Li, Yan; Delamar, Michel; Busca, Patricia; Prestat, Guillaume; Le Corre, Laurent; Legeai-Mallet, Laurence; Hu, RongJing; Zhang, Ruisheng; Barbault, Florent

2015-07-01

Tyrosine kinases are a wide family of targets with strong pharmacological relevance. These proteins undergo large-scale conformational motions able to inactivate them. By the end of one of these structural processes, a new cavity is opened allowing the access to a specific type of inhibitors, called type II. The kinase domain of fibroblast growth factor receptor 3 (FGFR3) falls into this family of kinases. We describe here, for the first time, its inactivation process through target molecular dynamics. The transient cavity, at the crossroad between the DFGout and Cα helix out inactivation is herein explored. Molecular docking calculations of known ligands demonstrated that type II inhibitors are able to interact with this metastable transient conformation of FGFR3 kinase. Besides, supplemental computations were conducted and clearly show that type II inhibitors drive the kinase inactivation process through specific stabilization with the DFG triad. This induced-fit effect of type II ligands toward FGFR3 might be extrapolated to other kinase systems and provides meaningful structural information for future drug developments.

Molecular dynamics studies on the interaction and encapsulation processes of the nucleotide and peptide chains inside of a carbon nanotube matrix with inclusion of gold nanoparticles

NASA Astrophysics Data System (ADS)

Kholmurodov, Kholmirzo; Dushanov, Eric; Khusenov, Mirzoaziz; Rahmonov, Khaiyom; Zelenyak, Tatyana; Doroshkevich, Alexander; Majumder, Subrata

2017-05-01

Studying of molecular systems as single nucleotides, nucleotide and peptide chains, RNA and DNA interacting with metallic nanoparticles within a carbon nanotube matrix represents a great interest in modern research. In this respect it is worth mentioning the development of the electronics diagnostic apparatus, the biochemical and biotechnological application tools (nanorobotic design, facilities of drug delivery in a living cell), so on. In the present work using molecular dynamics (MD) simulation method the interaction process of small nucleotide chains (NCs) and elongated peptide chains with different sets of metallic nanoparticles (NPs) on a matrix from carbon nanotube (CNT) were simulated to study their mechanisms of encapsulation and folding processes. We have performed a series of the MD calculations with different NC,peptides-NP-CNT models that were aimed on the investigation of the peculiarities of NC,peptide-NP interactions, the formation of bonds and structures in the system, as well as the dynamical behavior in an environment confined by the CNT matrix.

Modeling Amorphous Microporous Polymers for CO2 Capture and Separations.

PubMed

Kupgan, Grit; Abbott, Lauren J; Hart, Kyle E; Colina, Coray M

2018-06-13

This review concentrates on the advances of atomistic molecular simulations to design and evaluate amorphous microporous polymeric materials for CO 2 capture and separations. A description of atomistic molecular simulations is provided, including simulation techniques, structural generation approaches, relaxation and equilibration methodologies, and considerations needed for validation of simulated samples. The review provides general guidelines and a comprehensive update of the recent literature (since 2007) to promote the acceleration of the discovery and screening of amorphous microporous polymers for CO 2 capture and separation processes.

The Molecular Structure of a Phosphatidylserine Bilayer Determined by Scattering and Molecular Dynamics Simulations

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

Pan, Jianjun; Cheng, Xiaolin; Monticelli, Luca

2014-01-01

Phosphatidylserine (PS) lipids play essential roles in biological processes, including enzyme activation and apoptosis. We report on the molecular structure and atomic scale interactions of a fluid bilayer composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS). A scattering density profile model, aided by molecular dynamics (MD) simulations, was developed to jointly refine different contrast small-angle neutron and X-ray scattering data, which yielded a lipid area of 62.7 A2 at 25 C. MD simulations with POPS lipid area constrained at different values were also performed using all-atom and aliphatic united-atom models. The optimal simulated bilayer was obtained using a model-free comparison approach. Examination of themore » simulated bilayer, which agrees best with the experimental scattering data, reveals a preferential interaction between Na+ ions and the terminal serine and phosphate moieties. Long-range inter-lipid interactions were identified, primarily between the positively charged ammonium, and the negatively charged carboxylic and phosphate oxygens. The area compressibility modulus KA of the POPS bilayer was derived by quantifying lipid area as a function of surface tension from area-constrained MD simulations. It was found that POPS bilayers possess a much larger KA than that of neutral phosphatidylcholine lipid bilayers. We propose that the unique molecular features of POPS bilayers may play an important role in certain physiological functions.« less

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

Molecular and genetic insights into an infantile epileptic encephalopathy - CDKL5 disorder.

PubMed

Zhou, Ailing; Han, Song; Zhou, Zhaolan Joe

2017-02-01

The discovery that mutations in cyclin-dependent kinase-like 5 ( CDKL5 ) gene are associated with infantile epileptic encephalopathy has stimulated world-wide research effort to understand the molecular and genetic basis of CDKL5 disorder. Given the large number of literature published thus far, this review aims to summarize current genetic studies, draw a consensus on proposed molecular functions, and point to gaps of knowledge in CDKL5 research. A systematic review process was conducted using the PubMed search engine focusing on CDKL5 studies in the recent ten years. We analyzed these publications and summarized the findings into four sections: genetic studies, CDKL5 expression patterns, molecular functions, and animal models. We also discussed challenges and future directions in each section. On the clinical side, CDKL5 disorder is characterized by early onset epileptic seizures, intellectual disability, and stereotypical behaviors. On the research side, a series of molecular and genetic studies in human patients, cell cultures and animal models have established the causality of CDKL5 to the infantile epileptic encephalopathy, and pointed to a key role for CDKL5 in regulating neuronal function in the brain. Mouse models of CDKL5 disorder have also been developed, and notably, manifest behavioral phenotypes, mimicking numerous clinical symptoms of CDKL5 disorder and advancing CDKL5 research to the preclinical stage. Given what we have learned thus far, future identification of robust, quantitative, and sensitive outcome measures would be the key in animal model studies, particularly in heterozygous females. In the meantime, molecular and cellular studies of CDKL5 should focus on mechanism-based investigation and aim to uncover druggable targets that offer the potential to rescue or ameliorate CDKL5 disorder-related phenotypes.

Molecular and genetic insights into an infantile epileptic encephalopathy – CDKL5 disorder

PubMed Central

Zhou, Ailing; Han, Song

2017-01-01

Background The discovery that mutations in cyclin-dependent kinase-like 5 (CDKL5) gene are associated with infantile epileptic encephalopathy has stimulated world-wide research effort to understand the molecular and genetic basis of CDKL5 disorder. Given the large number of literature published thus far, this review aims to summarize current genetic studies, draw a consensus on proposed molecular functions, and point to gaps of knowledge in CDKL5 research. Methods A systematic review process was conducted using the PubMed search engine focusing on CDKL5 studies in the recent ten years. We analyzed these publications and summarized the findings into four sections: genetic studies, CDKL5 expression patterns, molecular functions, and animal models. We also discussed challenges and future directions in each section. Results On the clinical side, CDKL5 disorder is characterized by early onset epileptic seizures, intellectual disability, and stereotypical behaviors. On the research side, a series of molecular and genetic studies in human patients, cell cultures and animal models have established the causality of CDKL5 to the infantile epileptic encephalopathy, and pointed to a key role for CDKL5 in regulating neuronal function in the brain. Mouse models of CDKL5 disorder have also been developed, and notably, manifest behavioral phenotypes, mimicking numerous clinical symptoms of CDKL5 disorder and advancing CDKL5 research to the preclinical stage. Conclusions Given what we have learned thus far, future identification of robust, quantitative, and sensitive outcome measures would be the key in animal model studies, particularly in heterozygous females. In the meantime, molecular and cellular studies of CDKL5 should focus on mechanism-based investigation and aim to uncover druggable targets that offer the potential to rescue or ameliorate CDKL5 disorder-related phenotypes. PMID:28580010

Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

PubMed

Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

2011-06-09

Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

Ex vivo generation of a functional and regenerative wound epithelium from axolotl (Ambystoma mexicanum) skin.

PubMed

Ferris, Donald R; Satoh, Akira; Mandefro, Berhan; Cummings, Gillian M; Gardiner, David M; Rugg, Elizabeth L

2010-10-01

Urodele amphibians (salamanders) are unique among adult vertebrates in their ability to regenerate structurally complete and fully functional limbs. Regeneration is a stepwise process that requires interactions between keratinocytes, nerves and fibroblasts. The formation of a wound epithelium covering the amputation site is an early and necessary event in the process but the molecular mechanisms that underlie the role of the wound epithelium in regeneration remain unclear. We have developed an ex vivo model that recapitulates many features of in vivo wound healing. The model comprises a circular explant of axolotl (Ambystoma mexicanum) limb skin with a central circular, full thickness wound. Re-epithelialization of the wound area is rapid (typically <11 h) and is dependent on metalloproteinase activity. The ex vivo wound epithelium is viable, responds to neuronal signals and is able to participate in ectopic blastema formation and limb regeneration. This ex vivo model provides a reproducible and tractable system in which to study the cellular and molecular events that underlie wound healing and regeneration. © 2010 The Authors. Journal compilation © 2010 Japanese Society of Developmental Biologists.

Characterizing the multiexciton fission intermediate in pentacene through 2D spectral modeling

NASA Astrophysics Data System (ADS)

Tempelaar, Roel; Reichman, David

Singlet fission, the molecular process in which a singlet excitation splits into two triplet excitons, holds promise to enhance the photoconversion efficiency of solar cells. Despite advances in both experiments and theory, a detailed understanding of this process remains lacking. In particular, the nature of the correlated triplet pair state (TT), which acts as a fission intermediate, remains obscure. Recently, 2D spectroscopy was shown to allow for the direct detection of the extremely weak optical transition between TT and the ground state through coherently prepared vibrational wavepackets in the associated electronic potentials. Here, we present a microscopic model of singlet fission which includes an exact quantum treatment of such vibrational modes. Our model reproduces the reported 2D spectra of pentacene, while providing a detailed insight into the anatomy of TT. As such, our results form a stepping stone towards understanding singlet fission at a molecular level, while bridging the gap between the wealth of recent theoretical works on one side and experimental measurements on the other. R.T. acknowledges The Netherlands Organisation for Scientific Research NWO for support through a Rubicon Grant.

Patterning nanowire and micro-nanoparticle array on micropillar-structured surface: Experiment and modeling.

PubMed

Lin, Chung Hsun; Guan, Jingjiao; Chau, Shiu Wu; Chen, Shia Chung; Lee, L James

2010-08-04

DNA molecules in a solution can be immobilized and stretched into a highly ordered array on a solid surface containing micropillars by molecular combing technique. However, the mechanism of this process is not well understood. In this study, we demonstrated the generation of DNA nanostrand array with linear, zigzag, and fork-zigzag patterns and the microfluidic processes are modeled based on a deforming body-fitted grid approach. The simulation results provide insights for explaining the stretching, immobilizing, and patterning of DNA molecules observed in the experiments.

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.

The zebrafish as a novel animal model to study the molecular mechanisms of mechano-electrical feedback in the heart

PubMed Central

Werdich, Andreas A; Brzezinski, Anna; Jeyaraj, Darwin; Ficker, Eckhard; Wan, Xiaoping; McDermott, Brian M; Sabeh, M Khaled; MacRae, Calum A; Rosenbaum, David S

2013-01-01

Altered mechanical loading of the heart leads to hypertrophy, decompensated heart failure and fatal arrhythmias. However, the molecular mechanisms that link mechanical and electrical dysfunction remain poorly understood. Growing evidence suggest that ventricular electrical remodeling (VER) is a process that can be induced by altered mechanical stress, creating persistent electrophysiological changes that predispose the heart to life-threatening arrhythmias. While VER is clearly a physiological property of the human heart, as evidenced by “T wave memory”, it is also thought to occur in a variety of pathological states associated with altered ventricular activation such as bundle branch block, myocardial infarction, and cardiac pacing. Animal models that are currently being used for investigating stretch-induced VER have significant limitations. The zebrafish has recently emerged as an attractive animal model for studying cardiovascular disease and could overcome some of these limitations. Owing to its extensively sequenced genome, high conservation of gene function, and the comprehensive genetic resources that are available in this model, the zebrafish may provide new insights into the molecular mechanisms that drive detrimental electrical remodeling in response to stretch. Here, we have established a zebrafish model to study mechano-electrical feedback in the heart, which combines efficient genetic manipulation with high-precision stretch and high-resolution electrophysiology. In this model, only ninety minutes of ventricular stretch caused VER and recapitulated key features of VER found previously in the mammalian heart. Our data suggest that the zebrafish model is a powerful platform for investigating the molecular mechanisms underlying mechano-electrical feedback and VER in the heart. PMID:22835662

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device.

PubMed

Lambropoulos, Nicholas A; Reimers, Jeffrey R; Crossley, Maxwell J; Hush, Noel S; Silverbrook, Kia

2013-12-20

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device

NASA Astrophysics Data System (ADS)

Lambropoulos, Nicholas A.; Reimers, Jeffrey R.; Crossley, Maxwell J.; Hush, Noel S.; Silverbrook, Kia

2013-12-01

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer.

PubMed

Habermann, Nina; Mardin, Balca R; Yakneen, Sergei; Korbel, Jan O

2016-01-01

Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer. Copyright © 2016. Published by Elsevier SAS.

A global resource allocation strategy governs growth transition kinetics of Escherichia coli

PubMed Central

Erickson, David W; Schink, Severin J.; Patsalo, Vadim; Williamson, James R.; Gerland, Ulrich; Hwa, Terence

2018-01-01

A grand challenge of systems biology is to predict the kinetic responses of living systems to perturbations starting from the underlying molecular interactions. Changes in the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms1–3 and they remain a topic of active investigation4–11. Although much is known about the molecular interactions that govern the regulation of key metabolic processes in response to applied perturbations12–17, they are insufficiently quantified for predictive bottom-up modelling. Here we develop a top-down approach, expanding the recently established coarse-grained proteome allocation models15,18–20 from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions that is independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (for example, diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts owing to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach does not rely on kinetic parameters, and therefore points to a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions. PMID:29072300

Four decades of modeling methane cycling in terrestrial ecosystems: Where we are heading?

NASA Astrophysics Data System (ADS)

Xu, X.; Yuan, F.; Hanson, P. J.; Wullschleger, S. D.; Thornton, P. E.; Tian, H.; Riley, W. J.; Song, X.; Graham, D. E.; Song, C.

2015-12-01

A modeling approach to methane (CH4) is widely used to quantify the budget, investigate spatial and temporal variabilities, and understand the mechanistic processes and environmental controls on CH4 fluxes across spatial and temporal scales. Moreover, CH4 models are an important tool for integrating CH4 data from multiple sources, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. We reviewed 39 terrestrial CH4 models to characterize their strengths and weaknesses and to design a roadmap for future model improvement and application. We found that: (1) the focus of CH4 models have been shifted from theoretical to site- to regional-level application over the past four decades, expressed as dramatic increases in CH4 model development on regional budget quantification; (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls; (3) significant data-model and model-model mismatches are partially attributed to different representations of wetland characterization and inundation dynamics. Three efforts should be paid special attention for future improvements and applications of fully mechanistic CH4 models: (1) CH4 models should be improved to represent the mechanisms underlying land-atmosphere CH4 exchange, with emphasis on improving and validating individual CH4 processes over depth and horizontal space; (2) models should be developed that are capable of simulating CH4 fluxes across space and time (particularly hot moments and hot spots); (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. A newly developed microbial functional group-based CH4 model (CLM-Microbe) was further used to demonstrate the features of mechanistic representation and integration with multiple source of observational datasets.

Small interstellar molecules and what they tell us

NASA Astrophysics Data System (ADS)

Neufeld, David A.

2018-06-01

Observations at ultraviolet, visible, infrared and radio wavelengths provide a wealth of information about the molecular inventory of the interstellar medium (ISM). Because of the different chemical pathways responsible for their formation and destruction, different molecules probe specific aspects of the interstellar environment. Carefully interpreted with the use of astrochemical models, they provide unique information of general astrophysical importance, yielding estimates of the cosmic ray density, the molecular fraction, the ultraviolet radiation field, and the dissipation of energy within the turbulent ISM. Laboratory experiments and quantum-mechanical calculations are essential both in providing the spectroscopic data needed to identify interstellar molecules and for elucidating the fundamental physical and chemical processes that must be included in astrochemical models.

Preparation of Magnetic Molecularly Imprinted Polymer for Chlorpyrifos Adsorption and Enrichment

NASA Astrophysics Data System (ADS)

Chen, M.; Ma, X.; Sheng, J.

2017-11-01

Magnetic molecularly imprinted polymer (MMIP) for chlorpyrifos was prepared and characterized. The adsorption performance of MMIP for chlorpyrifos was evaluated under various conditions. The results showed that the adsorption equilibrium was achieved within 1 h, the adsorption capacity was 16.8 mg/g, and the adsorption process could be well described by Langmuir isotherm model and pseudo-second-order kinetic model. The MMIP was used as the selective sorbent for solid-phase extraction of chlorpyrifos from environmental water and vegetable samples. Combined with gas chromatography-mass spectrometry, a LOD of 30 ng/L, spiked recovery of 89.6%-107.3% and RSD of 1.9%-3.8% for chlorpyrifos were obtained.

Canadian Association of Neurosciences Review: learning at a snail's pace.

PubMed

Parvez, Kashif; Rosenegger, David; Martens, Kara; Orr, Michael; Lukowiak, Ken

2006-11-01

While learning and memory are related, they are distinct processes each with different forms of expression and underlying molecular mechanisms. An invertebrate model system, Lymnaea stagnalis, is used to study memory formation of a non-declarative memory. We have done so because: (1) We have discovered the neural circuit that mediates an interesting and tractable behaviour; (2) This behaviour can be operantly conditioned and intermediate-term and long-term memory can be demonstrated; and (3) It is possible to demonstrate that a single neuron in the model system is a necessary site of memory formation. This article reviews how Lymnaea has been used in the study of behavioural and molecular mechanisms underlying consolidation, reconsolidation, extinction and forgetting.

The Scientist as Illustrator.

PubMed

Iwasa, Janet H

2016-04-01

Proficiency in art and illustration was once considered an essential skill for biologists, because text alone often could not suffice to describe observations of biological systems. With modern imaging technology, it is no longer necessary to illustrate what we can see by eye. However, in molecular and cellular biology, our understanding of biological processes is dependent on our ability to synthesize diverse data to generate a hypothesis. Creating visual models of these hypotheses is important for generating new ideas and for communicating to our peers and to the public. Here, I discuss the benefits of creating visual models in molecular and cellular biology and consider steps to enable researchers to become more effective visual communicators. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reduced Order Models for Reactions of Energetic Materials

NASA Astrophysics Data System (ADS)

Kober, Edward

The formulation of reduced order models for the reaction chemistry of energetic materials under high pressures is needed for the development of mesoscale models in the areas of initiation, deflagration and detonation. Phenomenologically, 4-8 step models have been formulated from the analysis of cook-off data by analyzing the temperature rise of heated samples. Reactive molecular dynamics simulations have been used to simulate many of these processes, but reducing the results of those simulations to simple models has not been achieved. Typically, these efforts have focused on identifying molecular species and detailing specific chemical reactions. An alternative approach is presented here that is based on identifying the coordination geometries of each atom in the simulation and tracking classes of reactions by correlated changes in these geometries. Here, every atom and type of reaction is documented for every time step; no information is lost from unsuccessful molecular identification. Principal Component Analysis methods can then be used to map out the effective chemical reaction steps. For HMX and TATB decompositions simulated with ReaxFF, 90% of the data can be explained by 4-6 steps, generating models similar to those from the cook-off analysis. By performing these simulations at a variety of temperatures and pressures, both the activation and reaction energies and volumes can then be extracted.

Stochastic dynamics of coupled active particles in an overdamped limit

NASA Astrophysics Data System (ADS)

Ann, Minjung; Lee, Kong-Ju-Bock; Park, Pyeong Jun

2015-10-01

We introduce a model for Brownian dynamics of coupled active particles in an overdamped limit. Our system consists of several identical active particles and one passive particle. Each active particle is elastically coupled to the passive particle and there is no direct coupling among the active particles. We investigate the dynamics of the system with respect to the number of active particles, viscous friction, and coupling between the active and passive particles. For this purpose, we consider an intracellular transport process as an application of our model and perform a Brownian dynamics simulation using realistic parameters for processive molecular motors such as kinesin-1. We determine an adequate energy conversion function for molecular motors and study the dynamics of intracellular transport by multiple motors. The results show that the average velocity of the coupled system is not affected by the number of active motors and that the stall force increases linearly as the number of motors increases. Our results are consistent with well-known experimental observations. We also examine the effects of coupling between the motors and the cargo, as well as of the spatial distribution of the motors around the cargo. Our model might provide a physical explanation of the cooperation among active motors in the cellular transport processes.

Final Report, University of California Merced: Uranium and strontium fate in waste-weathered sediments: Scaling of molecular processes to predict reactive transport

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

Chorover, Jon; Mueller, Karl; O'Day, Peggy Anne

2016-06-30

Objectives of the Project: 1. Determine the process coupling that occurs between mineral transformation and contaminant (U and Sr) speciation in acid-uranium waste weathered Hanford sediments. 2. Establish linkages between molecular-scale contaminant speciation and meso-scale contaminant lability, release and reactive transport. 3. Make conjunctive use of molecular- to bench-scale data to constrain the development of a mechanistic, reactive transport model that includes coupling of contaminant sorption-desorption and mineral transformation reactions. Hypotheses Tested: Uranium and strontium speciation in legacy sediments from the U-8 and U-12 Crib sites can be reproduced in bench-scale weathering experiments conducted on unimpacted Hanford sediments from themore » same formations; Reactive transport modeling of future uranium and strontium releases from the vadose zone of acid-waste weathered sediments can be effectively constrained by combining molecular-scale information on contaminant bonding environment with grain-scale information on contaminant phase partitioning, and meso-scale kinetic data on contaminant release from the waste-weathered porous media; Although field contamination and laboratory experiments differ in their diagenetic time scales (decades for field vs. months to years for lab), sediment dissolution, neophase nucleation, and crystal growth reactions that occur during the initial disequilibrium induced by waste-sediment interaction leave a strong imprint that persists over subsequent longer-term equilibration time scales and, therefore, give rise to long-term memory effects. Enabling Capabilities Developed: Our team developed an iterative measure-model approach that is broadly applicable to elucidate the mechanistic underpinnings of reactive contaminant transport in geomedia subject to active weathering.« less

A novel network analysis approach reveals DNA damage, oxidative stress and calcium/cAMP homeostasis-associated biomarkers in frontotemporal dementia

PubMed Central

Ferrari, Raffaele; Graziano, Francesca; Novelli, Valeria; Rossi, Giacomina; Galimberti, Daniela; Rainero, Innocenzo; Benussi, Luisa; Nacmias, Benedetta; Bruni, Amalia C.; Cusi, Daniele; Salvi, Erika; Borroni, Barbara; Grassi, Mario

2017-01-01

Frontotemporal Dementia (FTD) is the form of neurodegenerative dementia with the highest prevalence after Alzheimer’s disease, equally distributed in men and women. It includes several variants, generally characterized by behavioural instability and language impairments. Although few mendelian genes (MAPT, GRN, and C9orf72) have been associated to the FTD phenotype, in most cases there is only evidence of multiple risk loci with relatively small effect size. To date, there are no comprehensive studies describing FTD at molecular level, highlighting possible genetic interactions and signalling pathways at the origin FTD-associated neurodegeneration. In this study, we designed a broad FTD genetic interaction map of the Italian population, through a novel network-based approach modelled on the concepts of disease-relevance and interaction perturbation, combining Steiner tree search and Structural Equation Model (SEM) analysis. Our results show a strong connection between Calcium/cAMP metabolism, oxidative stress-induced Serine/Threonine kinases activation, and postsynaptic membrane potentiation, suggesting a possible combination of neuronal damage and loss of neuroprotection, leading to cell death. In our model, Calcium/cAMP homeostasis and energetic metabolism impairments are primary causes of loss of neuroprotection and neural cell damage, respectively. Secondly, the altered postsynaptic membrane potentiation, due to the activation of stress-induced Serine/Threonine kinases, leads to neurodegeneration. Our study investigates the molecular underpinnings of these processes, evidencing key genes and gene interactions that may account for a significant fraction of unexplained FTD aetiology. We emphasized the key molecular actors in these processes, proposing them as novel FTD biomarkers that could be crucial for further epidemiological and molecular studies. PMID:29020091

Molecular classification of benign prostatic hyperplasia: A gene expression profiling study in a rat model.

PubMed

Hata, Junya; Satoh, Yuichi; Akaihata, Hidenori; Hiraki, Hiroyuki; Ogawa, Soichiro; Haga, Nobuhiro; Ishibashi, Kei; Aikawa, Ken; Kojima, Yoshiyuki

2016-07-01

To characterize the molecular features of benign prostatic hyperplasia by carrying out a gene expression profiling analysis in a rat model. Fetal urogenital sinus isolated from 20-day-old male rat embryo was implanted into a pubertal male rat ventral prostate. The implanted urogenital sinus grew time-dependently, and the pathological findings at 3 weeks after implantation showed epithelial hyperplasia as well as stromal hyperplasia. Whole-genome oligonucleotide microarray analysis utilizing approximately 30 000 oligonucleotide probes was carried out using prostate specimens during the prostate growth process (3 weeks after implantation). Microarray analyses showed 926 upregulated (>2-fold change, P < 0.01) and 3217 downregulated genes (<0.5-fold change, P < 0.01) in benign prostatic hyperplasia specimens compared with normal prostate. Gene ontology analyses of upregulated genes showed predominant genetic themes of involvement in development (162 genes, P = 2.01 × 10(-4) ), response to stimulus (163 genes, P = 7.37 × 10(-13) ) and growth (32 genes, P = 1.93 × 10(-5) ). When we used both normal prostate and non-transplanted urogenital sinuses as controls to identify benign prostatic hyperplasia-specific genes, 507 and 406 genes were upregulated and downregulated, respectively. Functional network and pathway analyses showed that genes associated with apoptosis modulation by heat shock protein 70, interleukin-1, interleukin-2 and interleukin-5 signaling pathways, KIT signaling pathway, and secretin-like G-protein-coupled receptors, class B, were relatively activated during the growth process in the benign prostatic hyperplasia specimens. In contrast, genes associated with cholesterol biosynthesis were relatively inactivated. Our microarray analyses of the benign prostatic hyperplasia model rat might aid in clarifying the molecular mechanism of benign prostatic hyperplasia progression, and identifying molecular targets for benign prostatic hyperplasia treatment. © 2016 The Japanese Urological Association.

Random intermittent search and the tug-of-war model of motor-driven transport

NASA Astrophysics Data System (ADS)

Newby, Jay; Bressloff, Paul C.

2010-04-01

We formulate the 'tug-of-war' model of microtubule cargo transport by multiple molecular motors as an intermittent random search for a hidden target. A motor complex consisting of multiple molecular motors with opposing directional preference is modeled using a discrete Markov process. The motors randomly pull each other off of the microtubule so that the state of the motor complex is determined by the number of bound motors. The tug-of-war model prescribes the state transition rates and corresponding cargo velocities in terms of experimentally measured physical parameters. We add space to the resulting Chapman-Kolmogorov (CK) equation so that we can consider delivery of the cargo to a hidden target at an unknown location along the microtubule track. The target represents some subcellular compartment such as a synapse in a neuron's dendrites, and target delivery is modeled as a simple absorption process. Using a quasi-steady-state (QSS) reduction technique we calculate analytical approximations of the mean first passage time (MFPT) to find the target. We show that there exists an optimal adenosine triphosphate (ATP) concentration that minimizes the MFPT for two different cases: (i) the motor complex is composed of equal numbers of kinesin motors bound to two different microtubules (symmetric tug-of-war model) and (ii) the motor complex is composed of different numbers of kinesin and dynein motors bound to a single microtubule (asymmetric tug-of-war model).

High-throughput screening, predictive modeling and computational embryology - Abstract

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

Epileptogenesis in experimental models.

PubMed

Pitkänen, Asla; Kharatishvili, Irina; Karhunen, Heli; Lukasiuk, Katarzyna; Immonen, Riikka; Nairismägi, Jaak; Gröhn, Olli; Nissinen, Jari

2007-01-01

Epileptogenesis refers to a phenomenon in which the brain undergoes molecular and cellular alterations after a brain-damaging insult, which increase its excitability and eventually lead to the occurrence of recurrent spontaneous seizures. Common epileptogenic factors include traumatic brain injury (TBI), stroke, and cerebral infections. Only a subpopulation of patients with any of these brain insults, however, will develop epilepsy. Thus, there are two great challenges: (1) identifying patients at risk, and (2) preventing and/or modifying the epileptogenic process. Target identification for antiepileptogenic treatments is difficult in humans because patients undergoing epileptogenesis cannot currently be identified. Animal models of epileptogenesis are therefore necessary for scientific progress. Recent advances in the development of experimental models of epileptogenesis have provided tools to investigate the molecular and cellular alterations and their temporal appearance, as well as the epilepsy phenotype after various clinically relevant epileptogenic etiologies, including TBI and stroke. Studying these models will lead to answers to critical questions such as: Do the molecular mechanisms of epileptogenesis depend on the etiology? Is the spectrum of network alterations during epileptogenesis the same after various clinically relevant etiologies? Is the temporal progression of epileptogenesis similar? Work is ongoing, and answers to these questions will facilitate the identification of molecular targets for antiepileptogenic treatments, the design of treatment paradigms, and the determination of whether data from one etiology can be extrapolated to another.

Sialyldisaccharide conformations: a molecular dynamics perspective

NASA Astrophysics Data System (ADS)

Selvin, Jeyasigamani F. A.; Priyadarzini, Thanu R. K.; Veluraja, Kasinadar

2012-04-01

Sialyldisaccharides are significant terminal components of glycoconjugates and their negative charge and conformation are extensively utilized in molecular recognition processes. The conformation and flexibility of four biologically important sialyldisaccharides [Neu5Acα(2-3)Gal, Neu5Acα(2-6)Gal, Neu5Acα(2-8)Neu5Ac and Neu5Acα(2-9)Neu5Ac] are studied using Molecular Dynamics simulations of 20 ns duration to deduce the conformational preferences of the sialyldisaccharides and the interactions which stabilize the conformations. This study clearly describes the possible conformational models of sialyldisaccharides deduced from 20 ns Molecular Dynamics simulations and our results confirm the role of water in the structural stabilization of sialyldisaccharides. An extensive analysis on the sialyldisaccharide structures available in PDB also confirms the conformational regions found by experiments are detected in MD simulations of 20 ns duration. The three dimensional structural coordinates for all the MD derived sialyldisaccharide conformations are deposited in the 3DSDSCAR database and these conformational models will be useful for glycobiologists and biotechnologists to understand the biological functions of sialic acid containing glycoconjugates.

Computational studies of Ras and PI3K

NASA Technical Reports Server (NTRS)

Ren, Lei; Cucinotta, Francis A.

2004-01-01

Until recently, experimental techniques in molecular cell biology have been the primary means to investigate biological risk upon space radiation. However, computational modeling provides an alternative theoretical approach, which utilizes various computational tools to simulate proteins, nucleotides, and their interactions. In this study, we are focused on using molecular mechanics (MM) and molecular dynamics (MD) to study the mechanism of protein-protein binding and to estimate the binding free energy between proteins. Ras is a key element in a variety of cell processes, and its activation of phosphoinositide 3-kinase (PI3K) is important for survival of transformed cells. Different computational approaches for this particular study are presented to calculate the solvation energies and binding free energies of H-Ras and PI3K. The goal of this study is to establish computational methods to investigate the roles of different proteins played in the cellular responses to space radiation, including modification of protein function through gene mutation, and to support the studies in molecular cell biology and theoretical kinetics models for our risk assessment project.

Neurobiological Mechanisms for the Regulation of Mammalian Sleep-Wake Behavior: Reinterpretation of Historical Evidence and Inclusion of Contemporary Cellular and Molecular Evidence

PubMed Central

Datta, Subimal; MacLean, Robert Ross

2007-01-01

At its most basic level, the function of mammalian sleep can be described as a restorative process of the brain and body; recently, however, progressive research has revealed a host of vital functions to which sleep is essential. Although many excellent reviews on sleep behavior have been published, none have incorporated contemporary studies examining the molecular mechanisms that govern the various stages of sleep. Utilizing a holistic approach, this review is focused on the basic mechanisms involved in the transition from wakefulness, initiation of sleep and the subsequent generation of slow-wave sleep and rapid eye movement (REM) sleep. Additionally, using recent molecular studies and experimental evidence that provides a direct link to sleep as a behavior, we have developed a new model, the Cellular-Molecular-Network model, explaining the mechanisms responsible for regulating REM sleep. By analyzing the fundamental neurobiological mechanisms responsible for the generation and maintenance of sleep-wake behavior in mammals, we intend to provide a broader understanding of our present knowledge in the field of sleep research. PMID:17445891

Efficient approach to include molecular polarizations using charge and atom dipole response kernels to calculate free energy gradients in the QM/MM scheme.

PubMed

Asada, Toshio; Ando, Kanta; Sakurai, Koji; Koseki, Shiro; Nagaoka, Masataka

2015-10-28

An efficient approach to evaluate free energy gradients (FEGs) within the quantum mechanical/molecular mechanical (QM/MM) framework has been proposed to clarify reaction processes on the free energy surface (FES) in molecular assemblies. The method is based on response kernel approximations denoted as the charge and the atom dipole response kernel (CDRK) model that include explicitly induced atom dipoles. The CDRK model was able to reproduce polarization effects for both electrostatic interactions between QM and MM regions and internal energies in the QM region obtained by conventional QM/MM methods. In contrast to charge response kernel (CRK) models, CDRK models could be applied to various kinds of molecules, even linear or planer molecules, without using imaginary interaction sites. Use of the CDRK model enabled us to obtain FEGs on QM atoms in significantly reduced computational time. It was also clearly demonstrated that the time development of QM forces of the solvated propylene carbonate radical cation (PC˙(+)) provided reliable results for 1 ns molecular dynamics (MD) simulation, which were quantitatively in good agreement with expensive QM/MM results. Using FEG and nudged elastic band (NEB) methods, we found two optimized reaction paths on the FES for decomposition reactions to generate CO2 molecules from PC˙(+), whose reaction is known as one of the degradation mechanisms in the lithium-ion battery. Two of these reactions proceed through an identical intermediate structure whose molecular dipole moment is larger than that of the reactant to be stabilized in the solvent, which has a high relative dielectric constant. Thus, in order to prevent decomposition reactions, PC˙(+) should be modified to have a smaller dipole moment along two reaction paths.

Phylogenetic mixtures and linear invariants for equal input models.

PubMed

Casanellas, Marta; Steel, Mike

2017-04-01

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).

System Design for Nano-Network Communications

NASA Astrophysics Data System (ADS)

ShahMohammadian, Hoda

The potential applications of nanotechnology in a wide range of areas necessities nano-networking research. Nano-networking is a new type of networking which has emerged by applying nanotechnology to communication theory. Therefore, this dissertation presents a framework for physical layer communications in a nano-network and addresses some of the pressing unsolved challenges in designing a molecular communication system. The contribution of this dissertation is proposing well-justified models for signal propagation, noise sources, optimum receiver design and synchronization in molecular communication channels. The design of any communication system is primarily based on the signal propagation channel and noise models. Using the Brownian motion and advection molecular statistics, separate signal propagation and noise models are presented for diffusion-based and flow-based molecular communication channels. It is shown that the corrupting noise of molecular channels is uncorrelated and non-stationary with a signal dependent magnitude. The next key component of any communication system is the reception and detection process. This dissertation provides a detailed analysis of the effect of the ligand-receptor binding mechanism on the received signal, and develops the first optimal receiver design for molecular communications. The bit error rate performance of the proposed receiver is evaluated and the impact of medium motion on the receiver performance is investigated. Another important feature of any communication system is synchronization. In this dissertation, the first blind synchronization algorithm is presented for the molecular communication channels. The proposed algorithm uses a non-decision directed maximum likelihood criterion for estimating the channel delay. The Cramer-Rao lower bound is also derived and the performance of the proposed synchronization algorithm is evaluated by investigating its mean square error.

Unfolding and melting of DNA (RNA) hairpins: the concept of structure-specific 2D dynamic landscapes.

PubMed

Lin, Milo M; Meinhold, Lars; Shorokhov, Dmitry; Zewail, Ahmed H

2008-08-07

A 2D free-energy landscape model is presented to describe the (un)folding transition of DNA/RNA hairpins, together with molecular dynamics simulations and experimental findings. The dependence of the (un)folding transition on the stem sequence and the loop length is shown in the enthalpic and entropic contributions to the free energy. Intermediate structures are well defined by the two coordinates of the landscape during (un)zipping. Both the free-energy landscape model and the extensive molecular dynamics simulations totaling over 10 mus predict the existence of temperature-dependent kinetic intermediate states during hairpin (un)zipping and provide the theoretical description of recent ultrafast temperature-jump studies which indicate that hairpin (un)zipping is, in general, not a two-state process. The model allows for lucid prediction of the collapsed state(s) in simple 2D space and we term it the kinetic intermediate structure (KIS) model.

In situ sensing and modeling of molecular events at the cellular level

NASA Astrophysics Data System (ADS)

Yang, Ruiguo

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior. To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the pathway map was delineated in detail while others were condensed into a single reaction. The model parameters were obtained by extracting the mechanical response from the experiment. The model refinements were conducted by testing a series of inhibition mechanisms and comparing the simulation data with the experimental data. The model was then used to predict the existences of certain reactions that are qualitatively reported in the literature.

Making lineage decisions with biological noise: Lessons from the early mouse embryo.

PubMed

Simon, Claire S; Hadjantonakis, Anna-Katerina; Schröter, Christian

2018-04-30

Understanding how individual cells make fate decisions that lead to the faithful formation and homeostatic maintenance of tissues is a fundamental goal of contemporary developmental and stem cell biology. Seemingly uniform populations of stem cells and multipotent progenitors display a surprising degree of heterogeneity, primarily originating from the inherent stochastic nature of molecular processes underlying gene expression. Despite this heterogeneity, lineage decisions result in tissues of a defined size and with consistent proportions of differentiated cell types. Using the early mouse embryo as a model we review recent developments that have allowed the quantification of molecular intercellular heterogeneity during cell differentiation. We first discuss the relationship between these heterogeneities and developmental cellular potential. We then review recent theoretical approaches that formalize the mechanisms underlying fate decisions in the inner cell mass of the blastocyst stage embryo. These models build on our extensive knowledge of the genetic control of fate decisions in this system and will become essential tools for a rigorous understanding of the connection between noisy molecular processes and reproducible outcomes at the multicellular level. We conclude by suggesting that cell-to-cell communication provides a mechanism to exploit and buffer intercellular variability in a self-organized process that culminates in the reproducible formation of the mature mammalian blastocyst stage embryo that is ready for implantation into the maternal uterus. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Cellular Differentiation Establishment of Spatial and Temporal Patterns > Regulation of Size, Proportion, and Timing Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics Gene Expression and Transcriptional Hierarchies > Quantitative Methods and Models. © 2018 Wiley Periodicals, Inc.

Experimental anti-GBM disease as a tool for studying spontaneous lupus nephritis.

PubMed

Fu, Yuyang; Du, Yong; Mohan, Chandra

2007-08-01

Lupus nephritis is an immune-mediated disease, where antibodies and T cells both play pathogenic roles. Since spontaneous lupus nephritis in mouse models takes 6-12 months to manifest, there is an urgent need for a mouse model that can be used to delineate the pathogenic processes that lead to immune nephritis, over a quicker time frame. We propose that the experimental anti-glomerular basement membrane (GBM) disease model might be a suitable tool for uncovering some of the molecular steps underlying lupus nephritis. This article reviews the current evidence that supports the use of the experimental anti-GBM nephritis model for studying spontaneous lupus nephritis. Importantly, out of about 25 different molecules that have been specifically examined in the experimental anti-GBM model and also spontaneous lupus nephritis, all influence both diseases concordantly, suggesting that the experimental model might be a useful tool for unraveling the molecular basis of spontaneous lupus nephritis. This has important clinical implications, both from the perspective of genetic susceptibility as well as clinical therapeutics.

Mesoscale Simulation and Machine Learning of Asphaltene Aggregation Phase Behavior and Molecular Assembly Landscapes.

PubMed

Wang, Jiang; Gayatri, Mohit A; Ferguson, Andrew L

2017-05-11

Asphaltenes constitute the heaviest fraction of the aromatic group in crude oil. Aggregation and precipitation of asphaltenes during petroleum processing costs the petroleum industry billions of dollars each year due to downtime and production inefficiencies. Asphaltene aggregation proceeds via a hierarchical self-assembly process that is well-described by the Yen-Mullins model. Nevertheless, the microscopic details of the emergent cluster morphologies and their relative stability under different processing conditions remain poorly understood. We perform coarse-grained molecular dynamics simulations of a prototypical asphaltene molecule to establish a phase diagram mapping the self-assembled morphologies as a function of temperature, pressure, and n-heptane:toluene solvent ratio informing how to control asphaltene aggregation by regulating external processing conditions. We then combine our simulations with graph matching and nonlinear manifold learning to determine low-dimensional free energy surfaces governing asphaltene self-assembly. In doing so, we introduce a variant of diffusion maps designed to handle data sets with large local density variations, and report the first application of many-body diffusion maps to molecular self-assembly to recover a pseudo-1D free energy landscape. Increasing pressure only weakly affects the landscape, serving only to destabilize the largest aggregates. Increasing temperature and toluene solvent fraction stabilizes small cluster sizes and loose bonding arrangements. Although the underlying molecular mechanisms differ, the strikingly similar effect of these variables on the free energy landscape suggests that toluene acts upon asphaltene self-assembly as an effective temperature.

Dielectric spectroscopy in aqueous solutions of oligosaccharides: Experiment meets simulation

NASA Astrophysics Data System (ADS)

Weingärtner, Hermann; Knocks, Andrea; Boresch, Stefan; Höchtl, Peter; Steinhauser, Othmar

2001-07-01

We report the frequency-dependent complex dielectric permittivity of aqueous solutions of the homologous saccharides D(+)-glucose, maltose, and maltotriose in the frequency range 200 MHz⩽ν⩽20 GHz. For each solute, solutions having concentrations between 0.01 and 1 mol dm-3 were studied. In all measured spectra two dispersion/loss regions could be discerned. With the exception of the two most concentrated maltotriose solutions, a good description of the spectra by the superposition of two Debye processes was possible. The amplitudes and correlation times of the glucose and maltose solutions determined from fits of the experimental data were compared to those obtained in an earlier molecular dynamics study of such systems; the overall agreement between experiment and simulation is quite satisfactory. A dielectric component analysis of the simulation results permitted a more detailed assignment of the relaxation processes occurring on the molecular level. The physical picture emerging from this analysis is compared with traditional hydration models used in the interpretation of measured dielectric data. It is shown that the usual standard models do not capture an important contribution arising from cross terms due to dipolar interactions between solute and water, as well as between hydration water and bulk water. This finding suggests that conventional approaches to determine molecular dipole moments of the solutes may be problematic. This is certainly the case for solutes with small molecular dipole moments, but strong solute-solvent interactions, such as the saccharides studied here.

Molecular dynamics simulations of β2-microglobulin interaction with hydrophobic surfaces.

PubMed

Dongmo Foumthuim, Cedrix J; Corazza, Alessandra; Esposito, Gennaro; Fogolari, Federico

2017-11-21

Hydrophobic surfaces are known to adsorb and unfold proteins, a process that has been studied only for a few proteins. Here we address the interaction of β2-microglobulin, a paradigmatic protein for the study of amyloidogenesis, with hydrophobic surfaces. A system with 27 copies of the protein surrounded by a model cubic hydrophobic box is studied by implicit solvent molecular dynamics simulations. Most proteins adsorb on the walls of the box without major distortions in local geometry, whereas free molecules maintain proper structures and fluctuations as observed in explicit solvent molecular dynamics simulations. The major conclusions from the simulations are as follows: (i) the adopted implicit solvent model is adequate to describe protein dynamics and thermodynamics; (ii) adsorption occurs readily and is irreversible on the simulated timescale; (iii) the regions most involved in molecular encounters and stable interactions with the walls are the same as those that are important in protein-protein and protein-nanoparticle interactions; (iv) unfolding following adsorption occurs at regions found to be flexible by both experiments and simulations; (v) thermodynamic analysis suggests a very large contribution from van der Waals interactions, whereas unfavorable electrostatic interactions are not found to contribute much to adsorption energy. Surfaces with different degrees of hydrophobicity may occur in vivo. Our simulations show that adsorption is a fast and irreversible process which is accompanied by partial unfolding. The results and the thermodynamic analysis presented here are consistent with and rationalize previous experimental work.

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Lotus Dust Mitigation Coating and Molecular Adsorber Coating

NASA Technical Reports Server (NTRS)

O'Connor, Kenneth M.; Abraham, Nithin S.

2015-01-01

NASA Goddard Space Flight Center has developed two unique coating formulations that will keep surfaces clean and sanitary and contain contaminants.The Lotus Dust Mitigation Coating, modeled after the self-cleaning, water-repellant lotus leaf, disallows buildup of dust, dirt, water, and more on surfaces. This coating, has been successfully tested on painted, aluminum, glass, silica, and some composite surfaces, could aid in keeping medical assets clean.The Molecular Adsorber Coating is a zeolite-based, sprayable molecular adsorber coating, designed to prevent outgassing in materials in vacuums. The coating works well to adsorb volatiles and contaminates in manufacturing and processing, such as in pharmaceutical production. The addition of a biocide would also aid in controlling bacteria levels.

Soot and Spectral Radiation Modeling in ECN Spray A and in Engines

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

Haworth, Daniel C; Ferreyro-Fernandez, Sebastian; Paul, Chandan

The amount of soot formed in a turbulent combustion system is determined by a complex system of coupled nonlinear chemical and physical processes. Different physical subprocesses can dominate, depending on the hydrodynamic and thermochemical environments. Similarly, the relative importance of reabsorption, spectral radiation properties, and molecular gas radiation versus soot radiation varies with thermochemical conditions, and in ways that are difficult to predict for the highly nonhomogeneous in-cylinder mixtures in engines. Here it is shown that transport and mixing play relatively more important roles as rate-determining processes in soot formation at engine-relevant conditions. It is also shown that molecular gasmore » radiation and spectral radiation properties are important for engine-relevant conditions.« less