WorldWideScience

Sample records for biomolecular reaction networks

  1. Stochastic Simulation of Biomolecular Networks in Dynamic Environments.

    Directory of Open Access Journals (Sweden)

    Margaritis Voliotis

    2016-06-01

    Full Text Available Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.

  2. Cellular automata modelling of biomolecular networks dynamics.

    Science.gov (United States)

    Bonchev, D; Thomas, S; Apte, A; Kier, L B

    2010-01-01

    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  3. The fidelity of dynamic signaling by noisy biomolecular networks.

    Directory of Open Access Journals (Sweden)

    Clive G Bowsher

    Full Text Available Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments.

  4. The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

    Directory of Open Access Journals (Sweden)

    Giulio Caravagna

    Full Text Available After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii a model of enzymatic futile cycle and (iii a genetic toggle switch. In (ii and (iii we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

  5. An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

    Energy Technology Data Exchange (ETDEWEB)

    Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu [Department of Physics, University of California, One Shields Avenue, Davis, California 95616 (United States); Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi [Department of Chemistry, University of California, One Shields Avenue, Davis, California 95616 (United States)

    2013-11-15

    A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

  6. An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support.

    Science.gov (United States)

    Fei, Yiyan; Landry, James P; Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A; Chen, Xi; Zhu, X D

    2013-11-01

    A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400-10,000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

  7. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    DEFF Research Database (Denmark)

    Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

    2008-01-01

    Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes. Conclusion: Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks...... that are significantly affected between or across conditions. Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses. Our Reporter Features analyses of yeast glucose...

  8. Autocatalysis in reaction networks.

    Science.gov (United States)

    Deshpande, Abhishek; Gopalkrishnan, Manoj

    2014-10-01

    The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is that if all reactions are reversible in a weak sense, then no species can go extinct. A notion that has been found useful in thinking about persistence is that of "critical siphon." We explore the combinatorics of critical siphons, with a view toward the persistence conjecture. We introduce the notions of "drainable" and "self-replicable" (or autocatalytic) siphons. We show that: Every minimal critical siphon is either drainable or self-replicable; reaction networks without drainable siphons are persistent; and nonautocatalytic weakly reversible networks are persistent. Our results clarify that the difficulties in proving the persistence conjecture are essentially due to competition between drainable and self-replicable siphons.

  9. Modeling stochasticity in biochemical reaction networks

    Science.gov (United States)

    Constantino, P. H.; Vlysidis, M.; Smadbeck, P.; Kaznessis, Y. N.

    2016-03-01

    Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts.

  10. A simple knowledge-based mining method for exploring hidden key molecules in a human biomolecular network

    Directory of Open Access Journals (Sweden)

    Tsuji Shingo

    2012-09-01

    Full Text Available Abstract Background In the functional genomics analysis domain, various methodologies are available for interpreting the results produced by high-throughput biological experiments. These methods commonly use a list of genes as an analysis input, and most of them produce a more complicated list of genes or pathways as the results of the analysis. Although there are several network-based methods, which detect key nodes in the network, the results tend to include well-studied, major hub genes. Results To mine the molecules that have biological meaning but to fewer degrees than major hubs, we propose, in this study, a new network-based method for selecting these hidden key molecules based on virtual information flows circulating among the input list of genes. The human biomolecular network was constructed from the Pathway Commons database, and a calculation method based on betweenness centrality was newly developed. We validated the method with the ErbB pathway and applied it to practical cancer research data. We were able to confirm that the output genes, despite having fewer edges than major hubs, have biological meanings that were able to be invoked by the input list of genes. Conclusions The developed method, named NetHiKe (Network-based Hidden Key molecule miner, was able to detect potential key molecules by utilizing the human biomolecular network as a knowledge base. Thus, it is hoped that this method will enhance the progress of biological data analysis in the whole-genome research era.

  11. Thermodynamics of random reaction networks.

    Directory of Open Access Journals (Sweden)

    Jakob Fischer

    Full Text Available Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.

  12. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

    Directory of Open Access Journals (Sweden)

    Arjun Verma

    2016-07-01

    Full Text Available We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  13. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

    Science.gov (United States)

    Verma, Arjun; Fratto, Brian E; Privman, Vladimir; Katz, Evgeny

    2016-07-05

    We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  14. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

    Science.gov (United States)

    Verma, Arjun; Fratto, Brian E; Privman, Vladimir; Katz, Evgeny

    2016-01-01

    We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

  15. Programming in Biomolecular Computation:

    DEFF Research Database (Denmark)

    Hartmann, Lars; Jones, Neil; Simonsen, Jakob Grue;

    2011-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem...... conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined...... by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways...

  16. Programmability of Chemical Reaction Networks

    Science.gov (United States)

    Cook, Matthew; Soloveichik, David; Winfree, Erik; Bruck, Jehoshua

    Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior.

  17. Modeling and Analysis of Abnormality Detection in Biomolecular Nano-Networks

    OpenAIRE

    Ghavami, Siavash; Lahouti, Farshad; Masoudi-Nejad, Ali

    2012-01-01

    A scheme for detection of abnormality in molecular nano-networks is proposed. This is motivated by the fact that early diagnosis, classification and detection of diseases such as cancer play a crucial role in their successful treatment. The proposed nano-abnormality detection scheme (NADS) comprises of a two-tier network of sensor nano-machines (SNMs) in the first tier and a data gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells as abnormality that is captured...

  18. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Directory of Open Access Journals (Sweden)

    Recep Colak

    Full Text Available BACKGROUND: Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. METHODOLOGY/PRINCIPAL FINDINGS: We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. CONCLUSION/SIGNIFICANCE: We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze

  19. Limits for Stochastic Reaction Networks

    DEFF Research Database (Denmark)

    Cappelletti, Daniele

    of reactions. Let the rates of degradation of the intermediate species be functions of a parameter N that tends to innity. We consider a reduced system where the intermediate species have been eliminated, and nd conditions on the degradation rate of the intermediates such that the behaviour of the reduced...... network tends to that of the original one. In particular, we prove a uniform punctual convergence in distribution and weak convergence of the integrals of continuous functions along the paths of the two models. Under some extra conditions, we also prove weak convergence of the two processes. The result....... Such species, in the deterministic modelling regime, assume always the same value at any positive steady state. In the stochastic setting, we prove that, if the initial condition is a point in the basin of attraction of a positive steady state of the corresponding deterministic model and tends to innity...

  20. Modeling and Analysis of Abnormality Detection in Biomolecular Nano-Networks

    CERN Document Server

    Ghavami, Siavash; Masoudi-Nejad, Ali

    2012-01-01

    A scheme for detection of abnormality in molecular nano-networks is proposed. This is motivated by the fact that early diagnosis, classification and detection of diseases such as cancer play a crucial role in their successful treatment. The proposed nano-abnormality detection scheme (NADS) comprises of a two-tier network of sensor nano-machines (SNMs) in the first tier and a data gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells as abnormality that is captured by variations in parameters of a nano-communications channel. In the second step, the SNMs transmit micro-scale messages over a noisy micro communications channel (MCC) to the DGN, where a decision is made upon fusing the received signals. The detection performance of each SNM is analyzed by setting up a Neyman-Pearson test. Next, taking into account the effect of the MCC, the overall performance of the proposed NADS is quantified in terms of probabilities of misdetection and false alarm. A design problem is formulated, ...

  1. Genetic Recombination as a Chemical Reaction Network

    OpenAIRE

    Müller, Stefan; Hofbauer, Josef

    2015-01-01

    The process of genetic recombination can be seen as a chemical reaction network with mass-action kinetics. We review the known results on existence, uniqueness, and global stability of an equilibrium in every compatibility class and for all rate constants, from both the population genetics and the reaction networks point of view.

  2. A Networks Approach to Modeling Enzymatic Reactions.

    Science.gov (United States)

    Imhof, P

    2016-01-01

    Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes.

  3. A network dynamics approach to chemical reaction networks

    NARCIS (Netherlands)

    van der Schaft, Abraham; Rao, S.; Jayawardhana, B.

    2016-01-01

    A treatment of chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a ve

  4. Atoms of multistationarity in chemical reaction networks

    CERN Document Server

    Joshi, Badal

    2011-01-01

    Chemical reaction networks taken with mass-action kinetics are dynamical systems that arise in chemical engineering and systems biology. Deciding whether a chemical reaction network admits multiple positive steady states is to determine existence of multiple positive solutions to a system of polynomials with unknown coefficients. In this work, we consider the question of whether the minimal (in a precise sense) networks, which we propose to call `atoms of multistationarity,' characterize the entire set of multistationary networks. We show that if a subnetwork admits multiple nondegenerate positive steady states, then these steady states can be extended to establish multistationarity of a larger network, provided that the two networks share the same stoichiometric subspace. Our result provides the mathematical foundation for a technique used by Siegal-Gaskins et al. of establishing bistability by way of `network ancestry.' Here, our main application is for enumerating small multistationary continuous-flow stir...

  5. Multilayer network analysis of nuclear reactions

    CERN Document Server

    Zhu, Liang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, $^4$He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the $\\beta$-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

  6. Multilayer Network Analysis of Nuclear Reactions.

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, (4)He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  7. Multilayer Network Analysis of Nuclear Reactions

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  8. Multilayer Network Analysis of Nuclear Reactions

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-08-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

  9. Programming in Biomolecular Computation

    DEFF Research Database (Denmark)

    Hartmann, Lars; Jones, Neil; Simonsen, Jakob Grue

    2010-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We introduce a model of computation that is evidently programmable......, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only...... in a strong sense: a universal algorithm exists, that is able to execute any program, and is not asymptotically inefficient. A prototype model has been implemented (for now in silico on a conventional computer). This work opens new perspectives on just how computation may be specified at the biological level....

  10. Law of localization in chemical reaction networks

    CERN Document Server

    Okada, Takashi

    2016-01-01

    In living cells, chemical reactions are connected by sharing their products and substrates, and form complex networks, e.g. metabolic pathways. Here we developed a theory to predict the sensitivity, i.e. the responses of concentrations and fluxes to perturbations of enzymes, from network structure alone. Responses turn out to exhibit two characteristic patterns, $localization$ and $hierarchy$. We present a general theorem connecting sensitivity with network topology that explains these characteristic patterns. Our results imply that network topology is an origin of biological robustness. Finally, we suggest a strategy to determine real networks from experimental measurements.

  11. Law of Localization in Chemical Reaction Networks

    Science.gov (United States)

    Okada, Takashi; Mochizuki, Atsushi

    2016-07-01

    In living cells, chemical reactions are connected by sharing their products and substrates, and form complex networks, e.g., metabolic pathways. Here we developed a theory to predict the sensitivity, i.e., the responses of concentrations and fluxes to perturbations of enzymes, from network structure alone. Nonzero response patterns turn out to exhibit two characteristic features, localization and hierarchy. We present a general theorem connecting sensitivity with network topology that explains these characteristic patterns. Our results imply that network topology is an origin of biological robustness. Finally, we suggest a strategy to determine real networks from experimental measurements.

  12. Markovian Dynamics on Complex Reaction Networks

    CERN Document Server

    Goutsias, John

    2012-01-01

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating...

  13. Markovian dynamics on complex reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

    2013-08-10

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

  14. Characterizing multistationarity regimes in biochemical reaction networks.

    Directory of Open Access Journals (Sweden)

    Irene Otero-Muras

    Full Text Available Switch like responses appear as common strategies in the regulation of cellular systems. Here we present a method to characterize bistable regimes in biochemical reaction networks that can be of use to both direct and reverse engineering of biological switches. In the design of a synthetic biological switch, it is important to study the capability for bistability of the underlying biochemical network structure. Chemical Reaction Network Theory (CRNT may help at this level to decide whether a given network has the capacity for multiple positive equilibria, based on their structural properties. However, in order to build a working switch, we also need to ensure that the bistability property is robust, by studying the conditions leading to the existence of two different steady states. In the reverse engineering of biological switches, knowledge collected about the bistable regimes of the underlying potential model structures can contribute at the model identification stage to a drastic reduction of the feasible region in the parameter space of search. In this work, we make use and extend previous results of the CRNT, aiming not only to discriminate whether a biochemical reaction network can exhibit multiple steady states, but also to determine the regions within the whole space of parameters capable of producing multistationarity. To that purpose we present and justify a condition on the parameters of biochemical networks for the appearance of multistationarity, and propose an efficient and reliable computational method to check its satisfaction through the parameter space.

  15. A network dynamics approach to chemical reaction networks

    Science.gov (United States)

    van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

    2016-04-01

    A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

  16. Retroactivity in the Context of Modularly Structured Biomolecular Systems

    Science.gov (United States)

    Pantoja-Hernández, Libertad; Martínez-García, Juan Carlos

    2015-01-01

    Synthetic biology has intensively promoted the technical implementation of modular strategies in the fabrication of biological devices. Modules are considered as networks of reactions. The behavior displayed by biomolecular systems results from the information processes carried out by the interconnection of the involved modules. However, in natural systems, module wiring is not a free-of-charge process; as a consequence of interconnection, a reactive phenomenon called retroactivity emerges. This phenomenon is characterized by signals that propagate from downstream modules (the modules that receive the incoming signals upon interconnection) to upstream ones (the modules that send the signals upon interconnection). Such retroactivity signals, depending of their strength, may change and sometimes even disrupt the behavior of modular biomolecular systems. Thus, analysis of retroactivity effects in natural biological and biosynthetic systems is crucial to achieve a deeper understanding of how this interconnection between functionally characterized modules takes place and how it impacts the overall behavior of the involved cell. By discussing the modules interconnection in natural and synthetic biomolecular systems, we propose that such systems should be considered as quasi-modular. PMID:26137457

  17. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou

    2011-09-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

  18. An updated nuclear reaction network for BBN

    OpenAIRE

    Serpico, P. D.

    2004-01-01

    The key Standard-Physics inputs of the Big Bang Nucleosynthesis (BBN) are the light nuclei reaction rates. Both the network and the nuclear rates have been recently reanalyzed and updated, and cosmological and New-Physics constraints (taking into account the WMAP Cosmic Microwave Background anisotropies measurement) obtained with a new code are presented.

  19. Combinatorics of reaction-network posets.

    Science.gov (United States)

    Klein, Douglas J; Ivanciuc, Teodora; Ryzhov, Anton; Ivanciuc, Ovidiu

    2008-11-01

    Reaction networks are viewed as derived from ordinary molecular structures related in reactant-product pairs so as to manifest a chemical super-structure. Such super-structures then are candidates for applications in a general combinatoric chemistry. Notable additional characterization of a reaction super-structure occurs when such reaction graphs are directed, as for example when there is progressive substitution (or addition) on a fixed molecular skeleton. Such a set of partially ordered entities is in mathematics termed a poset, which further manifests a number of special properties, as then might be utilized in different applications. Focus on the overall "super-structural" poset goes beyond ordinary molecular structure in attending to how a structure fits into a (reaction) network, and thereby brings an extra "dimension" to conventional stereochemical theory. The possibility that different molecular properties vary smoothly along chains of interconnections in such a super-structure is a natural assumption for a novel approach to molecular property and bioactivity correlations. Different manners to interpolate/extrapolate on a poset network yield quantitative super-structure/activity relationships (QSSARs), with some numerical fits, e.g., for properties of polychlorinated biphenyls (PCBs) seemingly being quite reasonable. There seems to be promise for combinatoric posetic ideas.

  20. Biomolecular Science (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2012-04-01

    A brief fact sheet about NREL Photobiology and Biomolecular Science. The research goal of NREL's Biomolecular Science is to enable cost-competitive advanced lignocellulosic biofuels production by understanding the science critical for overcoming biomass recalcitrance and developing new product and product intermediate pathways. NREL's Photobiology focuses on understanding the capture of solar energy in photosynthetic systems and its use in converting carbon dioxide and water directly into hydrogen and advanced biofuels.

  1. Performance Improvements for Nuclear Reaction Network Integration

    CERN Document Server

    Longland, Richard; José, Jordi

    2014-01-01

    Aims: The aim of this work is to compare the performance of three reaction network integration methods used in stellar nucleosynthesis calculations. These are the Gear's backward differentiation method, Wagoner's method (a 2nd-order Runge-Kutta method), and the Bader-Deuflehard semi-implicit multi-step method. Methods: To investigate the efficiency of each of the integration methods considered here, a test suite of temperature and density versus time profiles is used. This suite provides a range of situations ranging from constant temperature and density to the dramatically varying conditions present in white dwarf mergers, novae, and x-ray bursts. Some of these profiles are obtained separately from full hydrodynamic calculations. The integration efficiencies are investigated with respect to input parameters that constrain the desired accuracy and precision. Results: Gear's backward differentiation method is found to improve accuracy, performance, and stability in integrating nuclear reaction networks. For te...

  2. Ubiquitous "glassy" relaxation in catalytic reaction networks

    OpenAIRE

    Awazu, Akinori; Kaneko, Kunihiko

    2009-01-01

    Study of reversible catalytic reaction networks is important not only as an issue for chemical thermodynamics but also for protocells. From extensive numerical simulations and theoretical analysis, slow relaxation dynamics to sustain nonequlibrium states are commonly observed. These dynamics show two types of salient behaviors that are reminiscent of glassy behavior: slow relaxation along with the logarithmic time dependence of the correlation function and the emergence of plateaus in the rel...

  3. Neural Networks in Chemical Reaction Dynamics

    CERN Document Server

    Raff, Lionel; Hagan, Martin

    2011-01-01

    This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic

  4. Ubiquitous ``glassy'' relaxation in catalytic reaction networks

    Science.gov (United States)

    Awazu, Akinori; Kaneko, Kunihiko

    2009-10-01

    Study of reversible catalytic reaction networks is important not only as an issue for chemical thermodynamics but also for protocells. From extensive numerical simulations and theoretical analysis, slow relaxation dynamics to sustain nonequlibrium states are commonly observed. These dynamics show two types of salient behaviors that are reminiscent of glassy behavior: slow relaxation along with the logarithmic time dependence of the correlation function and the emergence of plateaus in the relaxation-time course. The former behavior is explained by the eigenvalue distribution of a Jacobian matrix around the equilibrium state that depends on the distribution of kinetic coefficients of reactions. The latter behavior is associated with kinetic constraints rather than metastable states and is due to the absence of catalysts for chemicals in excess and the negative correlation between two chemical species. Examples are given and generality is discussed with relevance to bottleneck-type dynamics in biochemical reactions as well.

  5. From Catalytic Reaction Networks to Protocells

    Science.gov (United States)

    Kaneko, Kunihiko

    2013-12-01

    In spite of recent advances, there still remains a large gape between a set of chemical reactions and a biological cell. Here we discuss several theoretical efforts to fill in the gap. The topics cover (i) slow relaxation to equilibrium due to glassy behavior in catalytic reaction networks (ii) consistency between molecule replication and cell growth, as well as energy metabolism (iii) control of a system by minority molecules in mutually catalytic system, which work as a carrier of genetic information, and leading to evolvability (iv) generation of a compartmentalized structure as a cluster of molecules centered around the minority molecule, and division of the cluster accompanied by the replication of minority molecule (v) sequential, logical process over several states from concurrent reaction dynamics, by taking advantage of discreteness in molecule number.

  6. Open complex-balanced mass action chemical reaction networks

    NARCIS (Netherlands)

    Rao, Shodhan; van der Schaft, Arjan; Jayawardhana, Bayu

    2014-01-01

    We consider open chemical reaction networks, i.e. ones with inflows and outflows. We assume that all the inflows to the network are constant and all outflows obey the mass action kinetics rate law. We define a complex-balanced open reaction network as one that admits a complex-balanced steady state.

  7. Nanoconfined β-sheets mechanically reinforce the supra-biomolecular network of robust squid Sucker Ring Teeth.

    Science.gov (United States)

    Guerette, Paul A; Hoon, Shawn; Ding, Dawei; Amini, Shahrouz; Masic, Admir; Ravi, Vydianathan; Venkatesh, Byrappa; Weaver, James C; Miserez, Ali

    2014-07-22

    The predatory efficiency of squid and cuttlefish (superorder Decapodiformes) is enhanced by robust Sucker Ring Teeth (SRT) that perform grappling functions during prey capture. Here, we show that SRT are composed entirely of related structural “suckerin” proteins whose modular designs enable the formation of nanoconfined β-sheet-reinforced polymer networks. Thirty-seven previously undiscovered suckerins were identified from transcriptomes assembled from three distantly related decapodiform cephalopods. Similarity in modular sequence design and exon–intron architecture suggests that suckerins are encoded by a multigene family. Phylogenetic analysis supports this view, revealing that suckerin genes originated in a common ancestor ~350 MYa and indicating that nanoconfined β-sheet reinforcement is an ancient strategy to create robust bulk biomaterials. X-ray diffraction, nanomechanical, and micro-Raman spectroscopy measurements confirm that the modular design of the suckerins facilitates the formation of β-sheets of precise nanoscale dimensions and enables their assembly into structurally robust supramolecular networks stabilized by cooperative hydrogen bonding. The suckerin gene family has likely played a key role in the evolutionary success of decapodiform cephalopods and provides a large molecular toolbox for biomimetic materials engineering. PMID:24911543

  8. Role of biomolecular logic systems in biosensors and bioactuators

    Science.gov (United States)

    Mailloux, Shay; Katz, Evgeny

    2014-09-01

    An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

  9. Biomolecular logic systems: applications to biosensors and bioactuators

    Science.gov (United States)

    Katz, Evgeny

    2014-05-01

    The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

  10. Deterministic Function Computation with Chemical Reaction Networks

    CERN Document Server

    Chen, Ho-Lin; Soloveichik, David

    2012-01-01

    We study the deterministic computation of functions on tuples of natural numbers by chemical reaction networks (CRNs). CRNs have been shown to be efficiently Turing-universal when allowing for a small probability of error. CRNs that are guaranteed to converge on a correct answer, on the other hand, have been shown to decide only the semilinear predicates. We introduce the notion of function, rather than predicate, computation by representing the output of a function f:N^k --> N^l by a count of some molecular species, i.e., if the CRN starts with n_1,...,n_k molecules of some "input" species X_1,...,X_k, the CRN is guaranteed to converge to having f(n_1,...,n_k) molecules of the "output" species Y_1,...,Y_l. We show that a function f:N^k --> N^l is deterministically computed by a CRN if and only if its graph {(x,y) \\in N^k x N^l | f(x) = y} is a semilinear set. Finally, we show that each semilinear function f can be computed on input x in expected time O(polylog |x|).

  11. Safe design of cooled tubular reactors for exothermic multiple reactions: Multiple-reaction networks

    NARCIS (Netherlands)

    Westerink, E.J.; Westerterp, K.R.

    1988-01-01

    The model of the pseudo-homogeneous, one-dimensional cooled tubular reactor is applied to a multiple-reaction network. It is demonstrated for a network which consists of two parallel and two consecutive reactions. Three criteria are developed to obtain an integral yield which does not deviate more t

  12. A statistical mechanical description of biomolecular hydration

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-02-01

    We present an efficient and accurate theoretical description of the structural hydration of biological macromolecules. The hydration of molecules of almost arbitrary size (tRNA, antibody-antigen complexes, photosynthetic reaction centre) can be studied in solution and in the crystal environment. The biomolecular structure obtained from x-ray crystallography, NMR, or modeling is required as input information. The structural arrangement of water molecules near a biomolecular surface is represented by the local water density analogous to the corresponding electron density in an x-ray diffraction experiment. The water-density distribution is approximated in terms of two- and three-particle correlation functions of solute atoms with water using a potentials-of-mean-force expansion.

  13. Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions

    Science.gov (United States)

    Semenov, Sergey N.; Kraft, Lewis J.; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E.; Kang, Kyungtae; Fox, Jerome M.; Whitesides, George M.

    2016-09-01

    Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving

  14. Biomolecular EPR spectroscopy

    CERN Document Server

    Hagen, Wilfred Raymond

    2008-01-01

    Comprehensive, Up-to-Date Coverage of Spectroscopy Theory and its Applications to Biological SystemsAlthough a multitude of books have been published about spectroscopy, most of them only occasionally refer to biological systems and the specific problems of biomolecular EPR (bioEPR). Biomolecular EPR Spectroscopy provides a practical introduction to bioEPR and demonstrates how this remarkable tool allows researchers to delve into the structural, functional, and analytical analysis of paramagnetic molecules found in the biochemistry of all species on the planet. A Must-Have Reference in an Intrinsically Multidisciplinary FieldThis authoritative reference seamlessly covers all important bioEPR applications, including low-spin and high-spin metalloproteins, spin traps and spin lables, interaction between active sites, and redox systems. It is loaded with practical tricks as well as do's and don'ts that are based on the author's 30 years of experience in the field. The book also comes with an unprecedented set of...

  15. On the Complexity of Reconstructing Chemical Reaction Networks

    DEFF Research Database (Denmark)

    Fagerberg, Rolf; Flamm, Christoph; Merkle, Daniel;

    2013-01-01

    The analysis of the structure of chemical reaction networks is crucial for a better understanding of chemical processes. Such networks are well described as hypergraphs. However, due to the available methods, analyses regarding network properties are typically made on standard graphs derived from...... the full hypergraph description, e.g. on the so-called species and reaction graphs. However, a reconstruction of the underlying hypergraph from these graphs is not necessarily unique. In this paper, we address the problem of reconstructing a hypergraph from its species and reaction graph and show NP...

  16. Weber's Law in Autocatalytic Reaction Networks

    CERN Document Server

    Inoue, Masayo

    2011-01-01

    Biological responses often obey Weber's law, according to which the magnitude of the response depends only on the fold change in the external input. In this study, we demonstrate that a system involving a simple autocatalytic reaction shows such response when a chemical is slowly synthesized by the reaction from a faster influx process. We also show that an autocatalytic reaction process occurring in series or in parallel can obey Weber's law with an oscillatory adaptive response. Considering the simplicity and ubiquity of the autocatalytic process, our proposed mechanism is thought to be commonly observed in biological reactions.

  17. Neural networks for the prediction organic chemistry reactions

    CERN Document Server

    Wei, Jennifer N; Aspuru-Guzik, Alán

    2016-01-01

    Reaction prediction remains one of the great challenges for organic chemistry. Solving this problem computationally requires the programming of a vast amount of knowledge and intuition of the rules of organic chemistry and the development of algorithms for their application. It is desirable to develop algorithms that, like humans, "learn" from being exposed to examples of the application of the rules of organic chemistry. In this work, we introduce a novel algorithm for predicting the products of organic chemistry reactions using machine learning to first identify the reaction type. In particular, we trained deep convolutional neural networks to predict the outcome of reactions based example reactions, using a new reaction fingerprint model. Due to the flexibility of neural networks, the system can attempt to predict reactions outside the domain where it was trained. We test this capability on problems from a popular organic chemistry textbook.

  18. Output-input ratio in thermally fluctuating biomolecular machines.

    Science.gov (United States)

    Kurzynski, Michal; Torchala, Mieczyslaw; Chelminiak, Przemyslaw

    2014-01-01

    Biological molecular machines are proteins that operate under isothermal conditions and hence are referred to as free energy transducers. They can be formally considered as enzymes that simultaneously catalyze two chemical reactions: the free energy-donating (input) reaction and the free energy-accepting (output) one. Most if not all biologically active proteins display a slow stochastic dynamics of transitions between a variety of conformational substates composing their native state. This makes the description of the enzymatic reaction kinetics in terms of conventional rate constants insufficient. In the steady state, upon taking advantage of the assumption that each reaction proceeds through a single pair (the gate) of transition conformational substates of the enzyme-substrates complex, the degree of coupling between the output and the input reaction fluxes has been expressed in terms of the mean first-passage times on a conformational transition network between the distinguished substates. The theory is confronted with the results of random-walk simulations on the five-dimensional hypercube. The formal proof is given that, for single input and output gates, the output-input degree of coupling cannot exceed unity. As some experiments suggest such exceeding, looking for the conditions for increasing the degree of coupling value over unity challenges the theory. Performed simulations of random walks on several model networks involving more extended gates indicate that the case of the degree of coupling value higher than 1 is realized in a natural way on critical branching trees extended by long-range shortcuts. Such networks are scale-free and display the property of the small world. For short-range shortcuts, the networks are scale-free and fractal, representing a reasonable model for biomolecular machines displaying tight coupling, i.e., the degree of coupling equal exactly to unity. A hypothesis is stated that the protein conformational transition networks, as

  19. DNA reaction networks: Providing a panoramic view

    Science.gov (United States)

    Wang, Fei; Fan, Chunhai

    2016-08-01

    A quantitative understanding of the functional landscape of a biochemical circuit can reveal the design rules required to optimize the circuit. Now, a high-throughput droplet-based microfluidic platform has been developed which enables high-resolution mapping of bifurcation diagrams for two nonlinear DNA networks.

  20. SABRE: A Tool for Stochastic Analysis of Biochemical Reaction Networks

    CERN Document Server

    Didier, Frederic; Mateescu, Maria; Wolf, Verena

    2010-01-01

    The importance of stochasticity within biological systems has been shown repeatedly during the last years and has raised the need for efficient stochastic tools. We present SABRE, a tool for stochastic analysis of biochemical reaction networks. SABRE implements fast adaptive uniformization (FAU), a direct numerical approximation algorithm for computing transient solutions of biochemical reaction networks. Biochemical reactions networks represent biological systems studied at a molecular level and these reactions can be modeled as transitions of a Markov chain. SABRE accepts as input the formalism of guarded commands, which it interprets either as continuous-time or as discrete-time Markov chains. Besides operating in a stochastic mode, SABRE may also perform a deterministic analysis by directly computing a mean-field approximation of the system under study. We illustrate the different functionalities of SABRE by means of biological case studies.

  1. Turing instability in reaction-diffusion models on complex networks

    Science.gov (United States)

    Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

    2016-09-01

    In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.

  2. Biomolecular detection with a thin membrane transducer.

    Science.gov (United States)

    Cha, Misun; Shin, Jaeha; Kim, June-Hyung; Kim, Ilchaek; Choi, Junbo; Lee, Nahum; Kim, Byung-Gee; Lee, Junghoon

    2008-06-01

    We present a thin membrane transducer (TMT) that can detect nucleic acid based biomolecular reactions including DNA hybridization and protein recognition by aptamers. Specific molecular interactions on an extremely thin and flexible membrane surface cause the deflection of the membrane due to surface stress change which can be measured by a compact capacitive circuit. A gold-coated thin PDMS membrane assembled with metal patterned glass substrate is used to realize the capacitive detection. It is demonstrated that perfect match and mismatch hybridizations can be sharply discriminated with a 16-mer DNA oligonucleotide immobilized on the gold-coated surface. While the mismatched sample caused little capacitance change, the perfectly matched sample caused a well-defined capacitance decrease vs. time due to an upward deformation of the membrane by a compressive surface stress. Additionally, the TMT demonstrated the single nucleotide polymorphism (SNP) capabilities which enabled a detection of mismatching base pairs in the middle of the sequence. It is intriguing that the increase of capacitance, therefore a downward deflection due to tensile stress, was observed with the internal double mismatch hybridization. We further present the detection of thrombin protein through ligand-receptor type recognition with 15-mer thrombin aptamer as a receptor. Key aspects of this detection such as the effect of concentration variation are investigated. This capacitive thin membrane transducer presents a completely new approach for detecting biomolecular reactions with high sensitivity and specificity without molecular labelling and optical measurement. PMID:18497914

  3. Variational Methods for Biomolecular Modeling

    CERN Document Server

    Wei, Guo-Wei

    2016-01-01

    Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrosta...

  4. Neural Networks for the Prediction of Organic Chemistry Reactions

    Science.gov (United States)

    2016-01-01

    Reaction prediction remains one of the major challenges for organic chemistry and is a prerequisite for efficient synthetic planning. It is desirable to develop algorithms that, like humans, “learn” from being exposed to examples of the application of the rules of organic chemistry. We explore the use of neural networks for predicting reaction types, using a new reaction fingerprinting method. We combine this predictor with SMARTS transformations to build a system which, given a set of reagents and reactants, predicts the likely products. We test this method on problems from a popular organic chemistry textbook. PMID:27800555

  5. ARWAR: A network approach for predicting Adverse Drug Reactions.

    Science.gov (United States)

    Rahmani, Hossein; Weiss, Gerhard; Méndez-Lucio, Oscar; Bender, Andreas

    2016-01-01

    Predicting novel drug side-effects, or Adverse Drug Reactions (ADRs), plays an important role in the drug discovery process. Existing methods consider mainly the chemical and biological characteristics of each drug individually, thereby neglecting information hidden in the relationships among drugs. Complementary to the existing individual methods, in this paper, we propose a novel network approach for ADR prediction that is called Augmented Random-WAlk with Restarts (ARWAR). ARWAR, first, applies an existing method to build a network of highly related drugs. Then, it augments the original drug network by adding new nodes and new edges to the network and finally, it applies Random Walks with Restarts to predict novel ADRs. Empirical results show that the ARWAR method presented here outperforms the existing network approach by 20% with respect to average Fmeasure. Furthermore, ARWAR is capable of generating novel hypotheses about drugs with respect to novel and biologically meaningful ADR.

  6. Grid computing and biomolecular simulation.

    Science.gov (United States)

    Woods, Christopher J; Ng, Muan Hong; Johnston, Steven; Murdock, Stuart E; Wu, Bing; Tai, Kaihsu; Fangohr, Hans; Jeffreys, Paul; Cox, Simon; Frey, Jeremy G; Sansom, Mark S P; Essex, Jonathan W

    2005-08-15

    Biomolecular computer simulations are now widely used not only in an academic setting to understand the fundamental role of molecular dynamics on biological function, but also in the industrial context to assist in drug design. In this paper, two applications of Grid computing to this area will be outlined. The first, involving the coupling of distributed computing resources to dedicated Beowulf clusters, is targeted at simulating protein conformational change using the Replica Exchange methodology. In the second, the rationale and design of a database of biomolecular simulation trajectories is described. Both applications illustrate the increasingly important role modern computational methods are playing in the life sciences.

  7. On the steady states of weakly reversible chemical reaction networks

    OpenAIRE

    Deng, Jian; Jones, Christopher; Feinberg, Martin; Nachman, Adrian

    2011-01-01

    A natural condition on the structure of the underlying chemical reaction network, namely weak reversibility, is shown to guarantee the existence of an equilibrium (steady state) in each positive stoichiometric compatibility class for the associated mass-action system. Furthermore, an index formula is given for the set of equilibria in a given stoichiometric compatibility class.

  8. Complex and detailed balancing of chemical reaction networks revisited

    NARCIS (Netherlands)

    van der Schaft, Abraham; Rao, Shodhan; Jayawardhana, Bayu

    2015-01-01

    The characterization of the notions of complex and detailed balancing for mass action kinetics chemical reaction networks is revisited from the perspective of algebraic graph theory, in particular Kirchhoff’s Matrix Tree theorem for directed weighted graphs. This yields an elucidation of previously

  9. Molecular codes in biological and chemical reaction networks.

    Directory of Open Access Journals (Sweden)

    Dennis Görlich

    Full Text Available Shannon's theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio- chemical systems able to process "meaningful" information from those that do not. Here, we present a formal method to assess a system's semantic capacity by analyzing a reaction network's capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries, biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades, an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems possess different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

  10. Switching Dynamics in Reaction Networks Induced by Molecular Discreteness

    CERN Document Server

    Togashi, Y; Kaneko, Kunihiko; Togashi, Yuichi

    2006-01-01

    To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentra...

  11. Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Ziaul Huque

    2007-08-31

    This is the final technical report for the project titled 'Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks'. The aim of the project was to develop an efficient chemistry model for combustion simulations. The reduced chemistry model was developed mathematically without the need of having extensive knowledge of the chemistry involved. To aid in the development of the model, Neural Networks (NN) was used via a new network topology known as Non-linear Principal Components Analysis (NPCA). A commonly used Multilayer Perceptron Neural Network (MLP-NN) was modified to implement NPCA-NN. The training rate of NPCA-NN was improved with the GEneralized Regression Neural Network (GRNN) based on kernel smoothing techniques. Kernel smoothing provides a simple way of finding structure in data set without the imposition of a parametric model. The trajectory data of the reaction mechanism was generated based on the optimization techniques of genetic algorithm (GA). The NPCA-NN algorithm was then used for the reduction of Dimethyl Ether (DME) mechanism. DME is a recently discovered fuel made from natural gas, (and other feedstock such as coal, biomass, and urban wastes) which can be used in compression ignition engines as a substitute for diesel. An in-house two-dimensional Computational Fluid Dynamics (CFD) code was developed based on Meshfree technique and time marching solution algorithm. The project also provided valuable research experience to two graduate students.

  12. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen;

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome...

  13. Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry

    OpenAIRE

    Rappoport, Dmitrij; Galvin, Cooper J.; Zubarev, Dmitry; Aspuru-Guzik, Alan

    2014-01-01

    While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reacti...

  14. A chemical reaction network solver for the astrophysics code NIRVANA

    Science.gov (United States)

    Ziegler, U.

    2016-02-01

    Context. Chemistry often plays an important role in astrophysical gases. It regulates thermal properties by changing species abundances and via ionization processes. This way, time-dependent cooling mechanisms and other chemistry-related energy sources can have a profound influence on the dynamical evolution of an astrophysical system. Modeling those effects with the underlying chemical kinetics in realistic magneto-gasdynamical simulations provide the basis for a better link to observations. Aims: The present work describes the implementation of a chemical reaction network solver into the magneto-gasdynamical code NIRVANA. For this purpose a multispecies structure is installed, and a new module for evolving the rate equations of chemical kinetics is developed and coupled to the dynamical part of the code. A small chemical network for a hydrogen-helium plasma was constructed including associated thermal processes which is used in test problems. Methods: Evolving a chemical network within time-dependent simulations requires the additional solution of a set of coupled advection-reaction equations for species and gas temperature. Second-order Strang-splitting is used to separate the advection part from the reaction part. The ordinary differential equation (ODE) system representing the reaction part is solved with a fourth-order generalized Runge-Kutta method applicable for stiff systems inherent to astrochemistry. Results: A series of tests was performed in order to check the correctness of numerical and technical implementation. Tests include well-known stiff ODE problems from the mathematical literature in order to confirm accuracy properties of the solver used as well as problems combining gasdynamics and chemistry. Overall, very satisfactory results are achieved. Conclusions: The NIRVANA code is now ready to handle astrochemical processes in time-dependent simulations. An easy-to-use interface allows implementation of complex networks including thermal processes

  15. Spreading out of perturbations in reversible reaction networks.

    Science.gov (United States)

    Maslov, Sergei; Sneppen, Kim; Ispolatov, I

    2007-08-17

    Using an example of physical interactions between proteins, we study how a perturbation propagates in the equilibrium of a network of reversible reactions governed by the law of mass action. We introduce a matrix formalism to describe the linear response of all equilibrium concentrations to shifts in total abundances of individual reactants, and reveal its heuristic analogy to the flow of electric current in a network of resistors. Our main conclusion is that, on average, the induced changes in equilibrium concentrations decay exponentially as a function of network distance from the source of perturbation. We analyze how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. We find that the minimal branching of the network, small values of dissociation constants, and low equilibrium free (unbound) concentrations of reacting substances all decrease the decay constant and thus increase the range of propagation. Exact analytic expressions for the decay constant are obtained for the case of equally strong interactions and uniform as well as oscillating concentrations on the Bethe lattice. Our general findings are illustrated using a real network of protein-protein interactions in baker's yeast with experimentally determined protein concentrations. PMID:18046464

  16. Spreading out of perturbations in reversible reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Maslov, Sergei [Department of Condensed Matter Physics, Brookhaven National Laboratory, Upton, NY 11973 (United States); Sneppen, Kim [Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen Oe (Denmark); Ispolatov, I [Ariadne Genomics Inc., 9430 Key West Ave. 113 Rockville, MD 20850 (United States)

    2007-08-15

    Using an example of physical interactions between proteins, we study how a perturbation propagates in the equilibrium of a network of reversible reactions governed by the law of mass action. We introduce a matrix formalism to describe the linear response of all equilibrium concentrations to shifts in total abundances of individual reactants, and reveal its heuristic analogy to the flow of electric current in a network of resistors. Our main conclusion is that, on average, the induced changes in equilibrium concentrations decay exponentially as a function of network distance from the source of perturbation. We analyze how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. We find that the minimal branching of the network, small values of dissociation constants, and low equilibrium free (unbound) concentrations of reacting substances all decrease the decay constant and thus increase the range of propagation. Exact analytic expressions for the decay constant are obtained for the case of equally strong interactions and uniform as well as oscillating concentrations on the Bethe lattice. Our general findings are illustrated using a real network of protein-protein interactions in baker's yeast with experimentally determined protein concentrations.

  17. Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

    Directory of Open Access Journals (Sweden)

    St Laurent Georges

    2010-03-01

    signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology, but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space.

  18. Nonequilibrium phase transitions in biomolecular signal transduction

    Science.gov (United States)

    Smith, Eric; Krishnamurthy, Supriya; Fontana, Walter; Krakauer, David

    2011-11-01

    We study a mechanism for reliable switching in biomolecular signal-transduction cascades. Steady bistable states are created by system-size cooperative effects in populations of proteins, in spite of the fact that the phosphorylation-state transitions of any molecule, by means of which the switch is implemented, are highly stochastic. The emergence of switching is a nonequilibrium phase transition in an energetically driven, dissipative system described by a master equation. We use operator and functional integral methods from reaction-diffusion theory to solve for the phase structure, noise spectrum, and escape trajectories and first-passage times of a class of minimal models of switches, showing how all critical properties for switch behavior can be computed within a unified framework.

  19. Matrix trace operators: from spectral moments of molecular graphs and complex networks to perturbations in synthetic reactions, micelle nanoparticles, and drug ADME processes.

    Science.gov (United States)

    Gonzalez-Diaz, Humberto; Arrasate, Sonia; Juan, Asier Gomez-San; Sotomayor, Nuria; Lete, Esther; Speck-Planche, Alejandro; Ruso, Juan M; Luan, Feng; Cordeiro, Maria Natalia Dias Soeiro

    2014-01-01

    The study of quantitative structure-property relationships (QSPR) is important to study complex networks of chemical reactions in drug synthesis or metabolism or drug-target interaction networks. A difficult but possible goal is the prediction of drug absorption, distribution, metabolism, and excretion (ADME) process with a single QSPR model. For this QSPR modelers need to use flexible structural parameters useful for the description of many different systems at different structural scales (multi-scale parameters). Also they need to use powerful analytical methods able to link in a single multi-scale hypothesis structural parameters of different target systems (multi-target modeling) with different experimental properties of these systems (multi-output models). In this sense, the QSPR study of complex bio-molecular systems may benefit substantially from the combined application of spectral moments of graph representations of complex systems with perturbation theory methods. On one hand, spectral moments are almost universal parameters that can be calculated to many different matrices used to represent the structure of the states of different systems. On the other hand, perturbation methods can be used to add "small" variation terms to parameters of a known state of a given system in order to approach to a solution of another state of the same or similar system with unknown properties. Here we present one state-of-art review about the different applications of spectral moments to describe complex bio-molecular systems. Next, we give some general ideas and formulate plausible linear models for a general-purpose perturbation theory of QSPR problems of complex systems. Last, we develop three new QSPR-Perturbation theory models based on spectral moments for three different problems with multiple in-out boundary conditions that are relevant to biomolecular sciences. The three models developed correctly classify more than pairs 115,600; 48,000; 134,900 cases of the

  20. Bosonic reaction-diffusion processes on scale-free networks

    Science.gov (United States)

    Baronchelli, Andrea; Catanzaro, Michele; Pastor-Satorras, Romualdo

    2008-07-01

    Reaction-diffusion processes can be adopted to model a large number of dynamics on complex networks, such as transport processes or epidemic outbreaks. In most cases, however, they have been studied from a fermionic perspective, in which each vertex can be occupied by at most one particle. While still useful, this approach suffers from some drawbacks, the most important probably being the difficulty to implement reactions involving more than two particles simultaneously. Here we develop a general framework for the study of bosonic reaction-diffusion processes on complex networks, in which there is no restriction on the number of interacting particles that a vertex can host. We describe these processes theoretically by means of continuous-time heterogeneous mean-field theory and divide them into two main classes: steady-state and monotonously decaying processes. We analyze specific examples of both behaviors within the class of one-species processes, comparing the results (whenever possible) with the corresponding fermionic counterparts. We find that the time evolution and critical properties of the particle density are independent of the fermionic or bosonic nature of the process, while differences exist in the functional form of the density of occupied vertices in a given degree class k . We implement a continuous-time Monte Carlo algorithm, well suited for general bosonic simulations, which allows us to confirm the analytical predictions formulated within mean-field theory. Our results, at both the theoretical and numerical levels, can be easily generalized to tackle more complex, multispecies, reaction-diffusion processes and open a promising path for a general study and classification of this kind of dynamical systems on complex networks.

  1. Recent developments in research on catalytic reaction networks

    Directory of Open Access Journals (Sweden)

    Roberto Serra

    2013-09-01

    Full Text Available Over the last years, analyses performed on a stochastic model of catalytic reaction networks have provided some indications about the reasons why wet-lab experiments hardly ever comply with the phase transition typically predicted by theoretical models with regard to the emergence of collectively self-replicating sets of molecule (also defined as autocatalytic sets, ACSs, a phenomenon that is often observed in nature and that is supposed to have played a major role in the emergence of the primitive forms of life. The model at issue has allowed to reveal that the emerging ACSs are characterized by a general dynamical fragility, which might explain the difficulty to observe them in lab experiments. In this work, the main results of the various analyses are reviewed, with particular regard to the factors able to affect the generic properties of catalytic reactions network, for what concerns, not only the probability of ACSs to be observed, but also the overall activity of the system, in terms of production of new species, reactions and matter.

  2. A self-regulating biomolecular comparator for processing oscillatory signals.

    Science.gov (United States)

    Agrawal, Deepak K; Franco, Elisa; Schulman, Rebecca

    2015-10-01

    While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

  3. Attractor for a Reaction-Diffusion System Modeling Cancer Network

    Directory of Open Access Journals (Sweden)

    Xueyong Chen

    2014-01-01

    Full Text Available A reaction-diffusion cancer network regulated by microRNA is considered in this paper. We study the asymptotic behavior of solution and show the existence of global uniformly bounded solution to the system in a bounded domain Ω⊂Rn. Some estimates and asymptotic compactness of the solutions are proved. As a result, we establish the existence of the global attractor in L2(Ω×L2(Ω and prove that the solution converges to stable steady states. These results can help to understand the dynamical character of cancer network and propose a new insight to study the mechanism of cancer. In the end, the numerical simulation shows that the analytical results agree with numerical simulation.

  4. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  5. Can shoulder joint reaction forces be estimated by neural networks?

    Science.gov (United States)

    de Vries, W H K; Veeger, H E J; Baten, C T M; van der Helm, F C T

    2016-01-01

    To facilitate the development of future shoulder endoprostheses, a long term load profile of the shoulder joint is desired. A musculoskeletal model using 3D kinematics and external forces as input can estimate the mechanical load on the glenohumeral joint, in terms of joint reaction forces. For long term ambulatory measurements, these 3D kinematics can be measured by means of Inertial Magnetic Measurement Systems. Recording of external forces under daily conditions is not feasible; estimations of joint loading should preferably be independent of this input. EMG signals reflect the musculoskeletal response and can easily be measured under daily conditions. This study presents the use of a neural network for the prediction of glenohumeral joint reaction forces based upon arm kinematics and shoulder muscle EMG. Several setups were examined for NN training, with varying combinations of type of input, type of motion, and handled weights. When joint reaction forces are predicted by a trained NN, for motion data independent of the training data, results show a high intraclass correlation (ICC up to 0.98) and relative SEM as low as 3%, compared to similar output of a musculoskeletal model. A convenient setup in which kinematics and only one channel of EMG were used as input for the NN׳s showed comparable predictive power as more complex setups. These results are promising and enable long term estimation of shoulder joint reaction forces outside the motion lab, independent of external forces. PMID:26654109

  6. COEL: A Cloud-based Reaction Network Simulator

    Directory of Open Access Journals (Sweden)

    Peter eBanda

    2016-04-01

    Full Text Available Chemical Reaction Networks (CRNs are a formalism to describe the macroscopic behavior of chemical systems. We introduce COEL, a web- and cloud-based CRN simulation framework that does not require a local installation, runs simulations on a large computational grid, provides reliable database storage, and offers a visually pleasing and intuitive user interface. We present an overview of the underlying software, the technologies, and the main architectural approaches employed. Some of COEL's key features include ODE-based simulations of CRNs and multicompartment reaction networks with rich interaction options, a built-in plotting engine, automatic DNA-strand displacement transformation and visualization, SBML/Octave/Matlab export, and a built-in genetic-algorithm-based optimization toolbox for rate constants.COEL is an open-source project hosted on GitHub (http://dx.doi.org/10.5281/zenodo.46544, which allows interested research groups to deploy it on their own sever. Regular users can simply use the web instance at no cost at http://coel-sim.org. The framework is ideally suited for a collaborative use in both research and education.

  7. Experimental (Network) and Evaluated Nuclear Reaction Data at NDS

    International Nuclear Information System (INIS)

    Dr Simakov of Nuclear Data Services Unit in the Nuclear Data Section (NDS) gave a brief overview of the data compilation and evaluation activities in the nuclear data community: experimental nuclear reaction data (EXFOR, http://www-nds.iaea.org/exfor/) and evaluated nuclear reaction data (ENDF, http://www-nds.iaea.org/endf). The International Network of Nuclear Reaction Data Centres (NRDC) coordinated by NDS includes 14 Centres in 8 Countries (China, Hungary, India, Japan, Korea, Russian, Ukraine, USA) and 2 International Organizations (NEA, IAEA). It had the first meeting of four core centres (Brookhaven, Saclay, Obninsk, Vienna) in 1966 and the EXFOR was adopted as an official data exchange format. In 2000, IAEA implemented the EXFOR database as a relational multiform database and the EXFOR is a trusted, increasing and living database with 19100 experimental works (as of September 2011) and 141600 data tables. The EXFOR provides a compilation control system for selection of articles and compilation of data and the NRDC home page provides manuals, documents and codes. The nuclear data can be retrieved by the web-retrieval system or distributed on a DVD on request. The EXFOR data play a critical role in the development of evaluated nuclear reaction data. There are several major general purpose libraries: ENDF (US), CENDL (China), JEFF (EU), JENDL (Japan) and RUSFOND (Russia). In addition, there are special libraries for particular applications: EAF (European Activation File), FENDL (Fusion Evaluated Nuclear Data Library for ITER neutronics), IBANDL (Ion Beam Analysis Nuclear Data Library for surface analysis of solids), IRDF, DXS (Dosimetry, radiation damage and gas production data) and Medical portal. Dr V. Zerkin of NDS demonstrated the data retrieval from the EXFOR database and the ENDF library.

  8. Integrative NMR for biomolecular research.

    Science.gov (United States)

    Lee, Woonghee; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R; Tonelli, Marco; Westler, William M; Butcher, Samuel E; Henzler-Wildman, Katherine A; Markley, John L

    2016-04-01

    NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html ). PMID:27023095

  9. Microwave spectroscopy of biomolecular building blocks.

    Science.gov (United States)

    Alonso, José L; López, Juan C

    2015-01-01

    Microwave spectroscopy, considered as the most definitive gas phase structural probe, is able to distinguish between different conformational structures of a molecule, because they have unique spectroscopic constants and give rise to distinct individual rotational spectra.Previously, application of this technique was limited to molecular specimens possessing appreciable vapor pressures, thus discarding the possibility of studying many other molecules of biological importance, in particular those with high melting points, which had a tendency to undergo thermal reactions, and ultimately degradation, upon heating.Nowadays, the combination of laser ablation with Fourier transform microwave spectroscopy techniques, in supersonic jets, has enabled the gas-phase study of such systems. In this chapter, these techniques, including broadband spectroscopy, as well as results of their application into the study of the conformational panorama and structure of biomolecular building blocks, such as amino acids, nucleic bases, and monosaccharides, are briefly discussed, and with them, the tools for conformational assignation - rotational constants, nuclear quadrupole coupling interaction, and dipole moment. PMID:25721775

  10. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A.; Pantazis, Yannis

    2015-01-01

    Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in “sloppy” systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over

  11. Biomolecular transport and separation in nanotubular networks.

    Energy Technology Data Exchange (ETDEWEB)

    Stachowiak, Jeanne C.; Stevens, Mark Jackson (Sandia National Laboratories, Albuquerque, NM); Robinson, David B.; Branda, Steven S.; Zendejas, Frank; Meagher, Robert J.; Sasaki, Darryl Yoshio; Bachand, George David (Sandia National Laboratories, Albuquerque, NM); Hayden, Carl C.; Sinha, Anupama; Abate, Elisa; Wang, Julia; Carroll-Portillo, Amanda (Sandia National Laboratories, Albuquerque, NM); Liu, Haiqing (Sandia National Laboratories, Albuquerque, NM)

    2010-09-01

    Cell membranes are dynamic substrates that achieve a diverse array of functions through multi-scale reconfigurations. We explore the morphological changes that occur upon protein interaction to model membrane systems that induce deformation of their planar structure to yield nanotube assemblies. In the two examples shown in this report we will describe the use of membrane adhesion and particle trajectory to form lipid nanotubes via mechanical stretching, and protein adsorption onto domains and the induction of membrane curvature through steric pressure. Through this work the relationship between membrane bending rigidity, protein affinity, and line tension of phase separated structures were examined and their relationship in biological membranes explored.

  12. [Advances in biomolecular machine: methane monooxygenases].

    Science.gov (United States)

    Lu, Jixue; Wang, Shizhen; Fang, Baishan

    2015-07-01

    Methane monooxygenases (MMO), regarded as "an amazing biomolecular machine", catalyze the oxidation of methane to methanol under aerobic conditions. MMO catalyze the oxidation of methane elaborately, which is a novel way to catalyze methane to methanol. Furthermore, MMO can inspire the biomolecular machine design. In this review, we introduced MMO including structure, gene and catalytic mechanism. The history and the taxonomy of MMO were also introduced. PMID:26647577

  13. Defect reaction network in Si-doped InAs. Numerical predictions.

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, Peter A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-05-01

    This Report characterizes the defects in the def ect reaction network in silicon - doped, n - type InAs predicted with first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si - doped InAs , until culminating in immobile reaction p roducts. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon - related defects in the reaction network. This Report serves to extend the results for the properties of intrinsic defects in bulk InAs as colla ted in SAND 2013 - 2477 : Simple intrinsic defects in InAs : Numerical predictions to include Si - containing simple defects likely to be present in a radiation - induced defect reaction sequence . This page intentionally left blank

  14. Properties of Random Complex Chemical Reaction Networks and Their Relevance to Biological Toy Models

    OpenAIRE

    Bigan, Erwan; Steyaert, Jean-Marc; Douady, Stéphane

    2013-01-01

    We investigate the properties of large random conservative chemical reaction networks composed of elementary reactions endowed with either mass-action or saturating kinetics, assigning kinetic parameters in a thermodynamically-consistent manner. We find that such complex networks exhibit qualitatively similar behavior when fed with external nutrient flux. The nutrient is preferentially transformed into one specific chemical that is an intrinsic property of the network. We propose a self-consi...

  15. On the Mathematical Structure of Balanced Chemical Reaction Networks Governed by Mass Action Kinetics

    OpenAIRE

    der Schaft, Arjan van; Rao, Shodhan; Jayawardhana, Bayu

    2011-01-01

    Motivated by recent progress on the interplay between graph theory, dynamics, and systems theory, we revisit the analysis of chemical reaction networks described by mass action kinetics. For reaction networks possessing a thermodynamic equilibrium we derive a compact formulation exhibiting at the same time the structure of the complex graph and the stoichiometry of the network, and which admits a direct thermodynamical interpretation. This formulation allows us to easily characterize the set ...

  16. Global analysis of time-resolved fluorescence microspectroscopy and applications in biomolecular studies

    NARCIS (Netherlands)

    Laptenok, S.

    2009-01-01

    Understanding the properties of biomolecular networks is of central importance in life sciences. Optical microscopy has been very useful to determine the sub-cellular localisation of proteins but it cannot reveal whether proteins interact with one another. Micro-spectroscopic techniques (combining m

  17. Sensitivity of chemical reaction networks: a structural approach 3. Regular multimolecular systems

    CERN Document Server

    Brehm, Bernhard

    2016-01-01

    We present a systematic mathematical analysis of the qualitative steady-state response to rate perturbations in large classes of reaction networks. This includes multimolecular reactions and allows for catalysis, enzymatic reactions, multiple reaction products, nonmonotone rate functions, and non-closed autonomous systems. Our structural sensitivity analysis is based on the stoichiometry of the reaction network, only. It does not require numerical data on reaction rates. Instead, we impose mild and generic nondegeneracy conditions of algebraic type. From the structural data, only, we derive which steady-state concentrations are sensitive to, and hence influenced by, changes of any particular reaction rate - and which are not. We also establish transitivity properties for influences involving rate perturbations. This allows us to derive an influence graph which globally summarizes the influence pattern of the given network. The influence graph allows the computational, but meaningful, automatic identification ...

  18. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

    Directory of Open Access Journals (Sweden)

    Ketki D Verkhedkar

    Full Text Available BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a

  19. Preclusion of switch behavior in reaction networks with mass-action kinetics

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, C.

    2012-01-01

    We study networks taken with mass-action kinetics and provide a Jacobian criterion that applies to an arbitrary network to preclude the existence of multiple positive steady states within any stoichiometric class for any choice of rate constants. We are concerned with the characterization...... precludes the existence of degenerate steady states. Further, we relate injectivity of a network to that of the network obtained by adding outflow, or degradation, reactions for all species....

  20. Piecewise linear and Boolean models of chemical reaction networks.

    Science.gov (United States)

    Veliz-Cuba, Alan; Kumar, Ajit; Josić, Krešimir

    2014-12-01

    Models of biochemical networks are frequently complex and high-dimensional. Reduction methods that preserve important dynamical properties are therefore essential for their study. Interactions in biochemical networks are frequently modeled using Hill functions ([Formula: see text]). Reduced ODEs and Boolean approximations of such model networks have been studied extensively when the exponent [Formula: see text] is large. However, while the case of small constant [Formula: see text] appears in practice, it is not well understood. We provide a mathematical analysis of this limit and show that a reduction to a set of piecewise linear ODEs and Boolean networks can be mathematically justified. The piecewise linear systems have closed-form solutions that closely track those of the fully nonlinear model. The simpler, Boolean network can be used to study the qualitative behavior of the original system. We justify the reduction using geometric singular perturbation theory and compact convergence, and illustrate the results in network models of a toggle switch and an oscillator.

  1. Unravelling the Maillard reaction network by multiresponse kinetic modelling

    OpenAIRE

    Martins, S.I.F.S.

    2003-01-01

    The Maillard reaction is an important reaction in food industry. It is responsible for the formation of colour and aroma, as well as toxic compounds as the recent discovered acrylamide. The knowledge of kinetic parameters, such as rate constants and activation energy, is necessary to predict its extent and, consequently, to optimise it. Each of the chapters presented in this thesis can be seen as a necessary step to succeed in applying multiresponse kinetic modelling in a complex reaction, su...

  2. Conducting polymer based biomolecular electronic devices

    Indian Academy of Sciences (India)

    B D Malhotra; Rahul Singhal

    2003-08-01

    Biomolecular electronics is rapidly evolving from physics, chemistry, biology, electronics and information technology. Organic materials such as proteins, pigments and conducting polymers have been considered as alternatives for carrying out the functions that are presently being performed by semiconductor silicon. Conducting polymers such as polypyrroles, polythiophenes and polyanilines have been projected for applications for a wide range of biomolecular electronic devices such as optical, electronic, drug-delivery, memory and biosensing devices. Our group has been actively working towards the application of conducting polymers to Schottky diodes, metal–insulator–semiconductor (MIS) devices and biosensors for the past 10 years. This paper is a review of some of the results obtained at our laboratory in the area of conducting polymer biomolecular electronics.

  3. Graphical reduction of reaction networks by linear elimination of species

    DEFF Research Database (Denmark)

    Saez Cornellana, Meritxell; Wiuf, Carsten Henrik; Feliu, Elisenda

    2016-01-01

    of the network and its kinetics. We conclude by comparing our approach to an older similar approach by Temkin and co-workers. Finally, we apply the procedure to biological examples such as substrate mechanisms, post-translational modification systems and networks with intermediates (transient) steps....

  4. Flourescence from Gas-Phase Biomolecular Ions

    DEFF Research Database (Denmark)

    Nielsen, Steen Brøndsted

    2013-01-01

    from experiments on dye-derivatised biomolecular ions that provide important information on folding/unfolding processes and local structural changes are presented. Examples included here are a model DNA duplex, the Trp-cage protein, polyproline peptides, and the cytochrome c heme protein. The chapter......This chapter deals with measurements of fluorescence from electronically excited biomolecular ions where there are no interactions with an external environment. Biomolecules with no natural fluorophores are labelled with a dye for such experiments. First, some of the advantages, but also...

  5. Markov propagation of allosteric effects in biomolecular systems: application to GroEL–GroES

    OpenAIRE

    Chennubhotla, Chakra; Bahar, Ivet

    2006-01-01

    We introduce a novel approach for elucidating the potential pathways of allosteric communication in biomolecular systems. The methodology, based on Markov propagation of ‘information' across the structure, permits us to partition the network of interactions into soft clusters distinguished by their coherent stochastics. Probabilistic participation of residues in these clusters defines the communication patterns inherent to the network architecture. Application to bacterial chaperonin complex ...

  6. Synchronization criteria for generalized reaction-diffusion neural networks via periodically intermittent control.

    Science.gov (United States)

    Gan, Qintao; Lv, Tianshi; Fu, Zhenhua

    2016-04-01

    In this paper, the synchronization problem for a class of generalized neural networks with time-varying delays and reaction-diffusion terms is investigated concerning Neumann boundary conditions in terms of p-norm. The proposed generalized neural networks model includes reaction-diffusion local field neural networks and reaction-diffusion static neural networks as its special cases. By establishing a new inequality, some simple and useful conditions are obtained analytically to guarantee the global exponential synchronization of the addressed neural networks under the periodically intermittent control. According to the theoretical results, the influences of diffusion coefficients, diffusion space, and control rate on synchronization are analyzed. Finally, the feasibility and effectiveness of the proposed methods are shown by simulation examples, and by choosing different diffusion coefficients, diffusion spaces, and control rates, different controlled synchronization states can be obtained.

  7. Boundedness and exponential stability for nonautonomous cellular neural networks with reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China); Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)]. E-mail: btcui@sohu.com

    2007-07-15

    Employing Lyapunov functional method, we analyze the ultimate boundedness and global exponential stability of a class of reaction-diffusion cellular neural networks with time-varying delays. Some new criteria are obtained to ensure ultimate boundedness and global exponential stability of delayed reaction-diffusion cellular neural networks (DRCNNs). Without assuming that the activation functions f {sub ijl}(.) are bounded, the results extend and improve the earlier publications.

  8. Stability for delayed reaction-diffusion neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Allegretto, W. [Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1 (Canada)]. E-mail: wallegre@math.ualberta.ca; Papini, D. [Dipartimento di Ingegneria dell' Informazione, Universita degli Studi di Siena, via Roma 56, 53100 Siena (Italy)]. E-mail: papini@dii.unisi.it

    2007-01-15

    We consider a Hopfield neural network model with diffusive terms, non-decreasing and discontinuous neural activation functions, time-dependent delays and time-periodic coefficients. We provide conditions on interconnection matrices and delays which guarantee that for each periodic input the model has a unique periodic solution that is globally exponentially stable. Even in the case without diffusion, such conditions improve recent results on classical delayed Hopfield neural networks with discontinuous activation functions. Numerical examples illustrate the results.

  9. Reaction Networks For Interstellar Chemical Modelling: Improvements and Challenges

    CERN Document Server

    Wakelam, V; Herbst, E; Troe, J; Geppert, W; Linnartz, H; Oberg, K; Roueff, E; Agundez, M; Pernot, P; Cuppen, H M; Loison, J C; Talbi, D

    2010-01-01

    We survey the current situation regarding chemical modelling of the synthesis of molecules in the interstellar medium. The present state of knowledge concerning the rate coefficients and their uncertainties for the major gas-phase processes -- ion-neutral reactions, neutral-neutral reactions, radiative association, and dissociative recombination -- is reviewed. Emphasis is placed on those reactions that have been identified, by sensitivity analyses, as 'crucial' in determining the predicted abundances of the species observed in the interstellar medium. These sensitivity analyses have been carried out for gas-phase models of three representative, molecule-rich, astronomical sources: the cold dense molecular clouds TMC-1 and L134N, and the expanding circumstellar envelope IRC +10216. Our review has led to the proposal of new values and uncertainties for the rate coefficients of many of the key reactions. The impact of these new data on the predicted abundances in TMC-1 and L134N is reported. Interstellar dust p...

  10. On the graph and systems analysis of reversible chemical reaction networks with mass action kinetics

    NARCIS (Netherlands)

    Rao, Shodhan; Jayawardhana, Bayu; Schaft, Arjan van der

    2012-01-01

    Motivated by the recent progresses on the interplay between the graph theory and systems theory, we revisit the analysis of reversible chemical reaction networks described by mass action kinetics by reformulating it using the graph knowledge of the underlying networks. Based on this formulation, we

  11. Perspective: Coarse-grained models for biomolecular systems

    Science.gov (United States)

    Noid, W. G.

    2013-09-01

    By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.

  12. Advances in integrative modeling of biomolecular complexes

    NARCIS (Netherlands)

    Karaca, E.; Bonvin, A.M.J.J.

    2013-01-01

    High-resolution structural information is needed in order to unveil the underlying mechanistic of biomolecular function. Due to the technical limitations or the nature of the underlying complexes, acquiring atomic resolution information is difficult for many challenging systems, while, often, low-re

  13. Programming in Biomolecular Computation: Programs, Self-Interpretation and Visualisation

    Directory of Open Access Journals (Sweden)

    J.G. Simonsen

    2011-01-01

    Full Text Available Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways and without arcane encodings of data and algorithm; it is also uniform: new ``hardware'' is not needed to solve new problems; and (last but not least it is Turing complete in a strong sense: a universal algorithm exists, that is able to execute any program, and is not asymptotically inefficient.

  14. Biochemical filter with sigmoidal response: increasing the complexity of biomolecular logic.

    Science.gov (United States)

    Privman, Vladimir; Halámek, Jan; Arugula, Mary A; Melnikov, Dmitriy; Bocharova, Vera; Katz, Evgeny

    2010-11-11

    The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic research has been achieving scalability for complex network designs. Various logic gates have been realized, but a "toolbox" of analog elements for interconnectivity and signal processing has remained elusive. Filters are important as network elements that allow control of noise in signal transmission and conversion. We report a versatile biochemical filtering mechanism designed to have sigmoidal response in combination with signal-conversion process. Horseradish peroxidase-catalyzed oxidation of chromogenic electron donor by H(2)O(2) was altered by adding ascorbate, allowing to selectively suppress the output signal, modifying the response from convex to sigmoidal. A kinetic model was developed for evaluation of the quality of filtering. The results offer improved capabilities for design of scalable biomolecular information processing systems.

  15. Turing-Hopf instability in biochemical reaction networks arising from pairs of subnetworks.

    Science.gov (United States)

    Mincheva, Maya; Roussel, Marc R

    2012-11-01

    Network conditions for Turing instability in biochemical systems with two biochemical species are well known and involve autocatalysis or self-activation. On the other hand general network conditions for potential Turing instabilities in large biochemical reaction networks are not well developed. A biochemical reaction network with any number of species where only one species moves is represented by a simple digraph and is modeled by a reaction-diffusion system with non-mass action kinetics. A graph-theoretic condition for potential Turing-Hopf instability that arises when a spatially homogeneous equilibrium loses its stability via a single pair of complex eigenvalues is obtained. This novel graph-theoretic condition is closely related to the negative cycle condition for oscillations in ordinary differential equation models and its generalizations, and requires the existence of a pair of subnetworks, each containing an even number of positive cycles. The technique is illustrated with a double-cycle Goodwin type model. PMID:22698892

  16. Reaction-Diffusion Processes on Random and Scale-Free Networks

    Science.gov (United States)

    Banerjee, Subhasis; Mallick, Shrestha Basu; Bose, Indrani

    We study the discrete Gierer-Meinhardt model of reaction-diffusion on three different types of networks: regular, random and scale-free. The model dynamics lead to the formation of stationary Turing patterns in the steady state in certain parameter regions. Some general features of the patterns are studied through numerical simulation. The results for the random and scale-free networks show a marked difference from those in the case of the regular network. The difference may be ascribed to the small world character of the first two types of networks.

  17. The US nuclear reaction data network. Summary of the first meeting, March 13 & 14 1996

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    The first meeting of the US Nuclear Reaction Data Network (USNRDN) was held at the Colorado School of Mines, March 13-14, 1996 chaired by F. Edward Cecil. The Agenda of the meeting is attached. The Network, its mission, products and services; related nuclear data and data networks, members, and organization are described in Attachment 1. The following progress reports from the members of the USNRDN were distributed prior to the meeting and are given as Attachment 2. (1) Measurements and Development of Analytic Techniques for Basic Nuclear Physics and Nuclear Applications; (2) Nuclear Reaction Data Activities at the National Nuclear Data Center; (3) Studies of nuclear reactions at very low energies; (4) Nuclear Reaction Data Activities, Nuclear Data Group; (5) Progress in Neutron Physics at Los Alamos - Experiments; (6) Nuclear Reaction Data Activities in Group T2; (7) Progress Report for the US Nuclear Reaction Data Network Meeting; (8) Nuclear Astrophysics Research Group (ORNL); (9) Progress Report from Ohio University; (10) Exciton Model Phenomenology; and (11) Progress Report for Coordination Meeting USNRDN.

  18. The US nuclear reaction data network. Summary of the first meeting, March 13 ampersand 14 1996

    International Nuclear Information System (INIS)

    The first meeting of the US Nuclear Reaction Data Network (USNRDN) was held at the Colorado School of Mines, March 13-14, 1996 chaired by F. Edward Cecil. The Agenda of the meeting is attached. The Network, its mission, products and services; related nuclear data and data networks, members, and organization are described in Attachment 1. The following progress reports from the members of the USNRDN were distributed prior to the meeting and are given as Attachment 2. (1) Measurements and Development of Analytic Techniques for Basic Nuclear Physics and Nuclear Applications; (2) Nuclear Reaction Data Activities at the National Nuclear Data Center; (3) Studies of nuclear reactions at very low energies; (4) Nuclear Reaction Data Activities, Nuclear Data Group; (5) Progress in Neutron Physics at Los Alamos - Experiments; (6) Nuclear Reaction Data Activities in Group T2; (7) Progress Report for the US Nuclear Reaction Data Network Meeting; (8) Nuclear Astrophysics Research Group (ORNL); (9) Progress Report from Ohio University; (10) Exciton Model Phenomenology; and (11) Progress Report for Coordination Meeting USNRDN

  19. Application of Nanodiamonds in Biomolecular Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Ping Cheng

    2010-03-01

    Full Text Available The combination of nanodiamond (ND with biomolecular mass spectrometry (MS makes rapid, sensitive detection of biopolymers from complex biosamples feasible. Due to its chemical inertness, optical transparency and biocompatibility, the advantage of NDs in MS study is unique. Furthermore, functionalization on the surfaces of NDs expands their application in the fields of proteomics and genomics for specific requirements greatly. This review presents methods of MS analysis based on solid phase extraction and elution on NDs and different application examples including peptide, protein, DNA, glycan and others. Owing to the quick development of nanotechnology, surface chemistry, new MS methods and the intense interest in proteomics and genomics, a huge increase of their applications in biomolecular MS analysis in the near future can be predicted.

  20. Improvements in continuum modeling for biomolecular systems

    CERN Document Server

    Qiao, Yu

    2015-01-01

    Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson-Boltzmann (PB)/Poisson-Nernst-Planck (PNP) equations has made great contributions towards simulation of these processes. However, the model has shortcomings in its commonly used form and cannot capture (or cannot accurately capture) some important physical properties of biological systems. Considerable efforts have been made to improve the continuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulation. This review will summarize recent main improvements in continuum modeling for biomolecular systems, with focus on the size-modified models, the coupling of the classical density functional theory and PNP equations, the coupling of polar and nonpolar interactions, and numerical progress.

  1. A cascade reaction network mimicking the basic functional steps of adaptive immune response

    Science.gov (United States)

    Han, Da; Wu, Cuichen; You, Mingxu; Zhang, Tao; Wan, Shuo; Chen, Tao; Qiu, Liping; Zheng, Zheng; Liang, Hao; Tan, Weihong

    2015-10-01

    Biological systems use complex ‘information-processing cores’ composed of molecular networks to coordinate their external environment and internal states. An example of this is the acquired, or adaptive, immune system (AIS), which is composed of both humoral and cell-mediated components. Here we report the step-by-step construction of a prototype mimic of the AIS that we call an adaptive immune response simulator (AIRS). DNA and enzymes are used as simple artificial analogues of the components of the AIS to create a system that responds to specific molecular stimuli in vitro. We show that this network of reactions can function in a manner that is superficially similar to the most basic responses of the vertebrate AIS, including reaction sequences that mimic both humoral and cellular responses. As such, AIRS provides guidelines for the design and engineering of artificial reaction networks and molecular devices.

  2. Visualization of confocal microscopic biomolecular data

    Science.gov (United States)

    Liu, Zhanping; Moorhead, Robert J., II

    2005-04-01

    Biomolecular visualization facilitates insightful interpretation of molecular structures and complex mechanisms underlying bio-chemical processes. Effective visualization techniques are required to deal with confocal microscopic biomolecular data in which intricate structures, fine features, and obscure patterns might be overlooked without sophisticated data processing and image synthesis. This paper presents major challenges in visualizing confocal microscopic biomolecular data, followed by a survey of related work. We then introduce a case study conducted to investigate the interaction between two proteins contained in a budding yeast saccharomyces cerevisiae by embedding custom modules in Amira. The multi-channel confocal microscopic volume data was first processed using an exponential operator to correct z-drop artifacts introduced during data acquisition. Channel correlation was then exploited to extract the overlap between the proteins as a new channel to represent the interaction while a statistical method was employed to compute the intensity of interaction to locate hot spots. To take advantage of crisp surface representation of region boundaries by iso-surfaces and visually pleasing translucent delineation of dense volumes by volume rendering, we adopted hybrid rendering that incorporates these two methods to display clear-cut protein boundaries, amorphous interior materials, and the scattered interaction in the same view volume with suppressed and highlighted parts selected by the user. The highlighted overlap helped biologists learn where the interaction happens and how it spreads, particularly when the volume was investigated in an immersive Cave Automatic Virtual Environment (CAVE) for intuitive comprehension of the data.

  3. The origin of large molecules in primordial autocatalytic reaction networks

    CERN Document Server

    Giri, Varun

    2011-01-01

    Large molecules such as proteins and nucleic acids are crucial for life, yet their primordial origin remains a major puzzle. The production of large molecules, as we know it today, requires good catalysts, and the only good catalysts we know that can accomplish this task consist of large molecules. Thus the origin of large molecules is a chicken and egg problem in chemistry. Here we present a mechanism, based on autocatalytic sets (ACSs), that is a possible solution to this problem. We discuss a mathematical model describing the population dynamics of molecules in a stylized but prebiotically plausible chemistry. Large molecules can be produced in this chemistry by the coalescing of smaller ones, with the smallest molecules, the `food set', being buffered. Some of the reactions can be catalyzed by molecules within the chemistry with varying catalytic strengths. Normally the concentrations of large molecules in such a scenario are very small, diminishing exponentially with their size. ACSs, if present in the c...

  4. On the graph and systems analysis of reversible chemical reaction networks with mass action kinetics

    OpenAIRE

    Rao, Shodhan; Jayawardhana, Bayu; der Schaft, Arjan van

    2012-01-01

    Motivated by the recent progresses on the interplay between the graph theory and systems theory, we revisit the analysis of reversible chemical reaction networks described by mass action kinetics by reformulating it using the graph knowledge of the underlying networks. Based on this formulation, we can characterize the space of equilibrium points and provide simple dynamical analysis on the state space modulo the space of equilibrium points.

  5. New Approach to the Stability of Chemical Reaction Networks: Piecewise Linear in Rates Lyapunov Functions

    OpenAIRE

    Al-Radhawi, M. Ali; Angeli, David

    2014-01-01

    Piecewise-Linear in Rates (PWLR) Lyapunov functions are introduced for a class of Chemical Reaction Networks (CRNs). In addition to their simple structure, these functions are robust with respect to arbitrary monotone reaction rates, of which mass-action is a special case. The existence of such functions ensures the convergence of trajectories towards equilibria, and guarantee their asymptotic stability with respect to the corresponding stoichiometric compatibility class. We give the definiti...

  6. BRUSLIB and NETGEN: the Brussels nuclear reaction rate library and nuclear network generator for astrophysics

    OpenAIRE

    Aikawa, M.; Arnould, M.; Goriely, S.; Jorissen, A.; Takahashi, K.

    2005-01-01

    Nuclear reaction rates are quantities of fundamental importance in astrophysics. Substantial efforts have been devoted in the last decades to measure or calculate them. The present paper presents for the first time a detailed description of the Brussels nuclear reaction rate library BRUSLIB and of the nuclear network generator NETGEN so as to make these nuclear data packages easily accessible to astrophysicists for a large variety of applications. BRUSLIB is made of two parts. The first one c...

  7. Toward a self-consistent and unitary reaction network for big bang nucleosynthesis

    International Nuclear Information System (INIS)

    Unitarity, the mathematical expression of the conservation of probability in multichannel reactions, is an essential ingredient in the development of accurate nuclear reaction networks appropriate for nucleosynthesis in a variety of environments. We describe our ongoing program to develop a 'unitary reaction network' for the big-bang nucleosynthesis environment and look at an example of the need and power of unitary parametrizations of nuclear scattering and reaction data. Recent attention has been focused on the possible role of the 9B compound nuclear system in the resonant destruction of 7Li during primordial nucleosynthesis. We have studied reactions in the 9B compound system with a multichannel, two-body unitary R-matrix code (EDA) using the known elastic and reaction data, in a four-channel treatment. The data include elastic 6Li(3He,3He)6Li differential cross sections from 0.7 to 2.0 MeV, integrated reaction cross sections for energies from 0.7 to 5.0 MeV for 6Li(3He,p)8Be* and from 0.4 to 5.0 MeV for the 6Li(3He,γ)7Be reaction. Capture data have been added to the previous analysis with integrated cross section measurements from 0.7 to 0.825 MeV for 6Li(3He,γ)9B. The resulting resonance parameters are compared with tabulated values from TUNL Nuclear Data Group analyses. Previously unidentified resonances are noted and the relevance of this analysis and a unitary reaction network for big-bang nucleosynthesis are emphasized. (author)

  8. Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Sheng Li [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China); Yang Huizhong [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: victory8209@yahoo.com.cn; Lou Xuyang [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)

    2009-04-30

    This paper presents an exponential synchronization scheme for a class of neural networks with time-varying and distributed delays and reaction-diffusion terms. An adaptive synchronization controller is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory. At the same time, the update laws of parameters are proposed to guarantee the synchronization of delayed neural networks with all parameters unknown. It is shown that the approaches developed here extend and improve the ideas presented in recent literatures.

  9. A computational framework for the automated construction of glycosylation reaction networks.

    Directory of Open Access Journals (Sweden)

    Gang Liu

    Full Text Available Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS data. The features described above are illustrated using three case studies that examine: i O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii automated N-linked glycosylation pathway construction; and iii the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme

  10. BRUSLIB and NETGEN: the Brussels nuclear reaction rate library and nuclear network generator for astrophysics

    CERN Document Server

    Aikawa, M; Goriely, S; Jorissen, A; Takahashi, K

    2005-01-01

    Nuclear reaction rates are quantities of fundamental importance in astrophysics. Substantial efforts have been devoted in the last decades to measure or calculate them. The present paper presents for the first time a detailed description of the Brussels nuclear reaction rate library BRUSLIB and of the nuclear network generator NETGEN so as to make these nuclear data packages easily accessible to astrophysicists for a large variety of applications. BRUSLIB is made of two parts. The first one contains the 1999 NACRE compilation based on experimental data for 86 reactions with (mainly) stable targets up to Si. The second part of BRUSLIB concerns nuclear reaction rate predictions calculated within a statistical Hauser-Feshbach approximation, which limits the reliability of the rates to reactions producing compound nuclei with a high enough level density. These calculations make use of global and coherent microscopic nuclear models for the quantities entering the rate calculations. The use of such models is utterl...

  11. Biomolecular Assembly of Gold Nanocrystals

    Energy Technology Data Exchange (ETDEWEB)

    Micheel, Christine Marya [Univ. of California, Berkeley, CA (United States)

    2005-05-20

    Over the past ten years, methods have been developed to construct discrete nanostructures using nanocrystals and biomolecules. While these frequently consist of gold nanocrystals and DNA, semiconductor nanocrystals as well as antibodies and enzymes have also been used. One example of discrete nanostructures is dimers of gold nanocrystals linked together with complementary DNA. This type of nanostructure is also known as a nanocrystal molecule. Discrete nanostructures of this kind have a number of potential applications, from highly parallel self-assembly of electronics components and rapid read-out of DNA computations to biological imaging and a variety of bioassays. My research focused in three main areas. The first area, the refinement of electrophoresis as a purification and characterization method, included application of agarose gel electrophoresis to the purification of discrete gold nanocrystal/DNA conjugates and nanocrystal molecules, as well as development of a more detailed understanding of the hydrodynamic behavior of these materials in gels. The second area, the development of methods for quantitative analysis of transmission electron microscope data, used computer programs written to find pair correlations as well as higher order correlations. With these programs, it is possible to reliably locate and measure nanocrystal molecules in TEM images. The final area of research explored the use of DNA ligase in the formation of nanocrystal molecules. Synthesis of dimers of gold particles linked with a single strand of DNA possible through the use of DNA ligase opens the possibility for amplification of nanostructures in a manner similar to polymerase chain reaction. These three areas are discussed in the context of the work in the Alivisatos group, as well as the field as a whole.

  12. Summary report on [IAEA] technical meeting of the International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres was held at the IAEA Headquarters in Vienna from 25 to 26 May 2009. The meeting was attended by 23 participants from 13 cooperating data centres. A summary of the meeting is given in this report, along with the conclusions, actions, and status report of the participating data centres. (author)

  13. Variable elimination in chemical reaction networks with mass-action kinetics

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, C.

    2012-01-01

    We consider chemical reaction networks taken with mass-action kinetics. The steady states of such a system are solutions to a system of polynomial equations. Even for small systems the task of finding the solutions is daunting. We develop an algebraic framework and procedure for linear elimination...

  14. Global asymptotic stability of BAM neural networks with distributed delays and reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122 (China)] e-mail: btcui@sohu.com; Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122 (China)

    2006-03-01

    The global asymptotic stability of bi-directional associative memory neural networks with distributed delays and reaction-diffusion terms are studied by using the analysis technique and Lyapunov functional. A sufficient condition is proposed. Two numerical examples are given to show the correctness of our analysis.

  15. MSU SINP CDFE nuclear data activities in the nuclear reaction data centres network

    International Nuclear Information System (INIS)

    This paper is the progress report of the Centre for Photonuclear Experiments Data, Moscow. It is a short review of the works carried out by the CDFE concerning the IAEA nuclear reaction data centers network activities from May 2001 until May 2002. and the description of the main results obtained. (a.n.)

  16. Pinning Control Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms.

    Science.gov (United States)

    Wang, Jin-Liang; Wu, Huai-Ning; Huang, Tingwen; Ren, Shun-Yan

    2016-04-01

    Two types of coupled neural networks with reaction-diffusion terms are considered in this paper. In the first one, the nodes are coupled through their states. In the second one, the nodes are coupled through the spatial diffusion terms. For the former, utilizing Lyapunov functional method and pinning control technique, we obtain some sufficient conditions to guarantee that network can realize synchronization. In addition, considering that the theoretical coupling strength required for synchronization may be much larger than the needed value, we propose an adaptive strategy to adjust the coupling strength for achieving a suitable value. For the latter, we establish a criterion for synchronization using the designed pinning controllers. It is found that the coupled reaction-diffusion neural networks with state coupling under the given linear feedback pinning controllers can realize synchronization when the coupling strength is very large, which is contrary to the coupled reaction-diffusion neural networks with spatial diffusion coupling. Moreover, a general criterion for ensuring network synchronization is derived by pinning a small fraction of nodes with adaptive feedback controllers. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results.

  17. Nanotube-Based Chemical and Biomolecular Sensors

    Institute of Scientific and Technical Information of China (English)

    J.Koh; B.Kim; S.Hong; H.Lim; H.C.Choi

    2008-01-01

    We present a brief review about recent results regarding carbon nanotube (CNT)-based chemical and biomolecular sensors. For the fabrication of CNT-based sensors, devices containing CNT channels between two metal electrodes are first fabricated usually via chemical vapor deposition (CVD) process or "surface programmed assembly" method. Then, the CNT surfaces are often functionalized to enhance the selectivity of the sensors. Using this process, highly-sensitive CNT-based sensors can be fabricated for the selective detection of various chemical and biological molecules such as hydrogen, ammonia, carbon monoxide, chlorine gas, DNA, glucose, alcohol, and proteins.

  18. Azurin for Biomolecular Electronics: a Reliability Study

    Science.gov (United States)

    Bramanti, Alessandro; Pompa, Pier Paolo; Maruccio, Giuseppe; Calabi, Franco; Arima, Valentina; Cingolani, Roberto; Corni, Stefano; Di Felice, Rosa; De Rienzo, Francesca; Rinaldi, Ross

    2005-09-01

    The metalloprotein azurin, used in biomolecular electronics, is investigated with respect to its resilience to high electric fields and ambient conditions, which are crucial reliability issues. Concerning the effect of electric fields, two models of different complexity agree indicating an unexpectedly high robustness. Experiments in device-like conditions confirm that no structural modifications occur, according to fluorescence spectra, even after a 40-min exposure to tens of MV/m. Ageing is then investigated experimentally, at ambient conditions and without field, over several days. Only a small conformational rearrangement is observed in the first tens of hours, followed by an equilibrium state.

  19. Scalable Molecular Dynamics for Large Biomolecular Systems

    Directory of Open Access Journals (Sweden)

    Robert K. Brunner

    2000-01-01

    Full Text Available We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

  20. Micro and Nanotechnologies Enhanced Biomolecular Sensing

    Directory of Open Access Journals (Sweden)

    Tza-Huei Wang

    2013-07-01

    Full Text Available This editorial summarizes some of the recent advances of micro and nanotechnology-based tools and devices for biomolecular detection. These include the incorporation of nanomaterials into a sensor surface or directly interfacing with molecular probes to enhance target detection via more rapid and sensitive responses, and the use of self-assembled organic/inorganic nanocomposites that inhibit exceptional spectroscopic properties to enable facile homogenous assays with efficient binding kinetics. Discussions also include some insight into microfluidic principles behind the development of an integrated sample preparation and biosensor platform toward a miniaturized and fully functional system for point of care applications.

  1. Toward a self-consistent and unitary reaction network for big-bang nucleosynthesis

    Directory of Open Access Journals (Sweden)

    Paris Mark W.

    2014-04-01

    Full Text Available Unitarity, the mathematical expression of the conservation of probability in multichannel reactions, is an essential ingredient in the development of accurate nuclear reaction networks appropriate for nucleosynthesis in a variety of environments. We describe our ongoing program to develop a “unitary reaction network” for the big-bang nucleosynthesis environment and look at an example of the need and power of unitary parametrizations of nuclear scattering and reaction data. Recent attention has been focused on the possible role of the 9B compound nuclear system in the resonant destruction of 7Li during primordial nucleosynthesis. We have studied reactions in the 9B compound system with a multichannel, two-body unitary R-matrix code (EDA using the known elastic and reaction data, in a four-channel treatment. The data include elastic 6Li(3He,3He6Li differential cross sections from 0.7 to 2.0 MeV, integrated reaction cross sections for energies from 0.7 to 5.0 MeV for 6Li(3He,p8Be* and from 0.4 to 5.0 MeV for the 6Li(3He,d7Be reaction. Capture data have been added to the previous analysis with integrated cross section measurements from 0.7 to 0.825 MeV for 6Li(3He,γ9B. The resulting resonance parameters are compared with tabulated values from TUNL Nuclear Data Group analyses. Previously unidentified resonances are noted and the relevance of this analysis and a unitary reaction network for big-bang nucleosynthesis are emphasized.

  2. Bio-molecular sensors based on guided mode resonance filters

    Science.gov (United States)

    Saleem, M. R.; Ali, R.; Honkanen, S.; Turunen, J.

    2016-08-01

    In this work a low surface roughness and homogenous, high refractive index, and amorphous TiO2 layer on corrugated structures of diffractive optical element is coated by Atomic Layer Deposition (ALD) for biosensors. The design of Guided Mode Resonance Filters (GMRFs) is based on refractive indices and thicknesses of the waveguide biomolecular layers. The designed spectral shifts are calculated by Fourier Modal Method (FMM) and depend on the magnitude of the variations in refractive index of the biomolecular layer on waveguide structures. Furthermore, the sensitivity of the biomolecular sensors depends on the thickness of biomolecular layer and periodicity of the structures. The waveguide structures designed for larger periods show an enhancement in the sensitivity (nm/RIU) of the biomolecular sensor at longer wavelengths. The periodicities of nanophotonic structures are varied from 300 to 500 nm in design calculations with predominance of increase in effective index of the structure to support leaky waveguide modes.

  3. HRSSA - Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

    Science.gov (United States)

    Marchetti, Luca; Priami, Corrado; Thanh, Vo Hong

    2016-07-01

    This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

  4. Coassembly of aromatic dipeptides into biomolecular necklaces.

    Science.gov (United States)

    Yuran, Sivan; Razvag, Yair; Reches, Meital

    2012-11-27

    This paper describes the formation of complex peptide-based structures by the coassembly of two simple peptides, the diphenylalanine peptide and its tert-butyl dicarbonate (Boc) protected analogue. Each of these peptides can self-assemble into a distinct architecture: the diphenylalanine peptide into tubular structures and its analogue into spheres. Integrated together, these peptides coassemble into a construction of beaded strings, where spherical assemblies are connected by elongated elements. Electron and scanning force microscopy demonstrated the morphology of these structures, which we termed "biomolecular necklaces". Additional experiments indicated the reversibility of the coassembly process and the stability of the structures. Furthermore, we suggest a possible mechanism of formation for the biomolecular necklaces. Our suggestion is based on the necklace model for polyelectrolyte chains, which proposes that a necklace structure appears as a result of counterion condensation on the backbone of a polyelectrolyte. Overall, the approach of coassembly, demonstrated using aromatic peptides, can be adapted to any peptides and may lead to the development and discovery of new self-assembled architectures formed by peptides and other biomolecules. PMID:23061818

  5. Improvements in continuum modeling for biomolecular systems

    Science.gov (United States)

    Yu, Qiao; Ben-Zhuo, Lu

    2016-01-01

    Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson- Boltzmann (PB)/Poisson-Nernst-Planck (PNP) equations has made great contributions towards simulation of these processes. However, the model has shortcomings in its commonly used form and cannot capture (or cannot accurately capture) some important physical properties of the biological systems. Considerable efforts have been made to improve the continuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulations. This review will summarize recent main improvements in continuum modeling for biomolecular systems, with focus on the size-modified models, the coupling of the classical density functional theory and the PNP equations, the coupling of polar and nonpolar interactions, and numerical progress. Project supported by the National Natural Science Foundation of China (Grant No. 91230106) and the Chinese Academy of Sciences Program for Cross & Cooperative Team of the Science & Technology Innovation.

  6. Accurate High-Temperature Reaction Networks for Alternative Fuels: Butanol Isomers

    Energy Technology Data Exchange (ETDEWEB)

    Van Geem, K. M.; Pyl, S. P.; Marin, G. B.; Harper, M. R.; Green, W. H.

    2010-11-03

    Oxygenated hydrocarbons, particularly alcohol compounds, are being studied extensively as alternatives and additives to conventional fuels due to their propensity of decreasing soot formation and improving the octane number of gasoline. However, oxygenated fuels also increase the production of toxic byproducts, such as formaldehyde. To gain a better understanding of the oxygenated functional group’s influence on combustion properties—e.g., ignition delay at temperatures above the negative temperature coefficient regime, and the rate of benzene production, which is the common precursor to soot formation—a detailed pressure-dependent reaction network for n-butanol, sec-butanol, and tert-butanol consisting of 281 species and 3608 reactions is presented. The reaction network is validated against shock tube ignition delays and doped methane flame concentration profiles reported previously in the literature, in addition to newly acquired pyrolysis data. Good agreement between simulated and experimental data is achieved in all cases. Flux and sensitivity analyses for each set of experiments have been performed, and high-pressure-limit reaction rate coefficients for important pathways, e.g., the dehydration reactions of the butanol isomers, have been computed using statistical mechanics and quantum chemistry. The different alcohol decomposition pathways, i.e., the pathways from primary, secondary, and tertiary alcohols, are discussed. Furthermore, comparisons between ethanol and n-butanol, two primary alcohols, are presented, as they relate to ignition delay.

  7. Water formation at low temperatures by surface O2 hydrogenation II: the reaction network

    CERN Document Server

    Cuppen, H M; Romanzin, C; Linnartz, H; 10.1039/C0CP00251H

    2010-01-01

    Water is abundantly present in the Universe. It is the main component of interstellar ice mantles and a key ingredient for life. Water in space is mainly formed through surface reactions. Three formation routes have been proposed in the past: hydrogenation of surface O, O2, and O3. In a previous paper [Ioppolo et al., Astrophys. J., 2008, 686, 1474] we discussed an unexpected non-standard zeroth-order H2O2 production behaviour in O2 hydrogenation experiments, which suggests that the proposed reaction network is not complete, and that the reaction channels are probably more interconnected than previously thought. In this paper we aim to derive the full reaction scheme for O2 surface hydrogenation and to constrain the rates of the individual reactions. This is achieved through simultaneous H-atom and O2 deposition under ultra-high vacuum conditions for astronomically relevant temperatures. Different H/O2 ratios are used to trace different stages in the hydrogenation network. The chemical changes in the forming ...

  8. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting), held at the Brookhaven National Laboratory, Upton, NY, USA from 4-7 October 2004. The meeting was attended by 20 participants from 11 co-operating data centres of six Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, status reports of the participating data centres, and a revised technical protocol for the cooperation of the network. (author)

  9. Global exponential stability of Hopfield reaction-diffusion neural networks with time-varying delays

    Institute of Scientific and Technical Information of China (English)

    王林山; 徐道义

    2003-01-01

    The authors analyze the existence of the equilibrium point and global exponential stability for Hopfield reaction-diffusion neural networks with time-varying delays by means of the topological degree theory and generalized Halanay inequality. Since the diffusion phenomena and time delay could not be ignored in neural networks and electric circuits, the model presented here is close to the actual systems, and the sufficient conditions on global exponential stability established in this paper,which are easily verifiable, have a wider adaptive range.

  10. Doubly Periodic Traveling Waves in a Cellular Neural Network with Linear Reaction

    Directory of Open Access Journals (Sweden)

    Lin JianJhong

    2009-01-01

    Full Text Available Szekeley observed that the dynamic pattern of the locomotion of salamanders can be explained by periodic vector sequences generated by logical neural networks. Such sequences can mathematically be described by "doubly periodic traveling waves" and therefore it is of interest to propose dynamic models that may produce such waves. One such dynamic network model is built here based on reaction-diffusion principles and a complete discussion is given for the existence of doubly periodic waves as outputs. Since there are 2 parameters in our model and 4 a priori unknown parameters involved in our search of solutions, our results are nontrivial. The reaction term in our model is a linear function and hence our results can also be interpreted as existence criteria for solutions of a nontrivial linear problem depending on 6 parameters.

  11. Coupling sample paths to the partial thermodynamic limit in stochastic chemical reaction networks

    CERN Document Server

    Levien, Ethan

    2016-01-01

    We present a new technique for reducing the variance in Monte Carlo estimators of stochastic chemical reaction networks. Our method makes use of the fact that many stochastic reaction networks converge to piecewise deterministic Markov processes in the large system-size limit. The statistics of the piecewise deterministic process can be obtained much more efficiently than those of the exact process. By coupling sample paths of the exact model to the piecewise deterministic process we are able to reduce the variance, and hence the computational complexity of the Monte Carlo estimator. In addition to rigorous results concerning the asymptotic behavior of our method, numerical simulations are performed on some simple biological models suggesting that significant computational gains are made for even moderate system-sizes.

  12. Report on the IAEA technical meeting of the International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres was held at IAEA Headquarters, Vienna, Austria, from 8 to 10 October 2007. The meeting was attended by 19 participants from 11 cooperating data centres of six Member States and two international organizations. A summary of the meeting is given in this report, along with the conclusions, actions, and status reports of the participating data centres. (author)

  13. Variable elimination in post-translational modification reaction networks with mass-action kinetics

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, Carsten

    2013-01-01

    We define a subclass of chemical reaction networks called post-translational modification systems. Important biological examples of such systems include MAPK cascades and two-component systems which are well-studied experimentally as well as theoretically. The steady states of such a system are s...... of the species graph and provide conservation laws. A criterion for when a (maximal) set of independent conservation laws can be derived from cuts is given....

  14. Report on the IAEA advisory group meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Advisory Group Meeting (AGM) on Network of Nuclear Reaction Data Centres, hold at the Institute of Physics and Power Engineering, Obninsk, Russia, 15 to 19 May 2000. The meeting was attended by 28 participants from 13 co-operating data centres from seven Member States and two International Organizations. The report contains a meeting summary, the conclusions and actions, progress and status reports of the participating data centres and working papers considered at the meeting. (author)

  15. Summary Report of the Technical Meeting on International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Technical Meeting on the International Network of Nuclear Reaction Data Centres, held at the IAEA Headquarters in Vienna, Austria from 23 to 25 April 2013. The meeting was attended by 24 participants representing 13 cooperative centres from 8 Member States and 2 International Organisations. A summary of the meeting is given in this report along with the conclusions and actions. (author)

  16. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (and the biennial Data Centre Heads' Meeting) was held at the OECD Nuclear Energy Agency, Issy-les-Moulineaux (near Paris), France, from 27 to 30 May 2002. The meeting was attended by 21 participants from 12 co-operating data centres of six Member States and two international organizations. This report contains the meeting summary, conclusions and actions, status reports of the participating data centres, and working papers considered. (author)

  17. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting) was held at IAEA Headquarters, Vienna, Austria, from 25 to 28 September 2006. The meeting was attended by 19 participants from 10 cooperating data centres of six Member States and two international organizations. A summary of the meeting is given in this report, along with the conclusions, actions, and status reports of the participating data centres. (author)

  18. INFLUENCE OF NOISE AND DELAY ON REACTION-DIFFUSION RECURRENT NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Li Wu

    2006-01-01

    In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks (RNNs) with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria.

  19. Stability of Stochastic Reaction-Diffusion Recurrent Neural Networks with Unbounded Distributed Delays

    Directory of Open Access Journals (Sweden)

    Chuangxia Huang

    2011-01-01

    Full Text Available Stability of reaction-diffusion recurrent neural networks (RNNs with continuously distributed delays and stochastic influence are considered. Some new sufficient conditions to guarantee the almost sure exponential stability and mean square exponential stability of an equilibrium solution are obtained, respectively. Lyapunov's functional method, M-matrix properties, some inequality technique, and nonnegative semimartingale convergence theorem are used in our approach. The obtained conclusions improve some published results.

  20. Product-form stationary distributions for deficiency zero chemical reaction networks

    OpenAIRE

    Anderson, David F.; Craciun, Gheorghe; Kurtz, Thomas G.

    2008-01-01

    We consider stochastically modeled chemical reaction systems with mass-action kinetics and prove that a product-form stationary distribution exists for each closed, irreducible subset of the state space if an analogous deterministically modeled system with mass-action kinetics admits a complex balanced equilibrium. Feinberg's deficiency zero theorem then implies that such a distribution exists so long as the corresponding chemical network is weakly reversible and has a deficiency of zero. The...

  1. Report on the IAEA technical meeting on the network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    Results of the IAEA Technical meeting on the Network of Nuclear Reaction Data Centres held at the IAEA Headquarters, Vienna, Austria, 12 to 14 October 2005, are summarized in this report. The meeting was attended by 16 participants from 11 co-operating data centres of six Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, and status reports of the participating data centres. (author)

  2. A reaction-diffusion model of ROS-induced ROS release in a mitochondrial network.

    Directory of Open Access Journals (Sweden)

    Lufang Zhou

    2010-01-01

    Full Text Available Loss of mitochondrial function is a fundamental determinant of cell injury and death. In heart cells under metabolic stress, we have previously described how the abrupt collapse or oscillation of the mitochondrial energy state is synchronized across the mitochondrial network by local interactions dependent upon reactive oxygen species (ROS. Here, we develop a mathematical model of ROS-induced ROS release (RIRR based on reaction-diffusion (RD-RIRR in one- and two-dimensional mitochondrial networks. The nodes of the RD-RIRR network are comprised of models of individual mitochondria that include a mechanism of ROS-dependent oscillation based on the interplay between ROS production, transport, and scavenging; and incorporating the tricarboxylic acid (TCA cycle, oxidative phosphorylation, and Ca(2+ handling. Local mitochondrial interaction is mediated by superoxide (O2.- diffusion and the O2.(--dependent activation of an inner membrane anion channel (IMAC. In a 2D network composed of 500 mitochondria, model simulations reveal DeltaPsi(m depolarization waves similar to those observed when isolated guinea pig cardiomyocytes are subjected to a localized laser-flash or antioxidant depletion. The sensitivity of the propagation rate of the depolarization wave to O(2.- diffusion, production, and scavenging in the reaction-diffusion model is similar to that observed experimentally. In addition, we present novel experimental evidence, obtained in permeabilized cardiomyocytes, confirming that DeltaPsi(m depolarization is mediated specifically by O2.-. The present work demonstrates that the observed emergent macroscopic properties of the mitochondrial network can be reproduced in a reaction-diffusion model of RIRR. Moreover, the findings have uncovered a novel aspect of the synchronization mechanism, which is that clusters of mitochondria that are oscillating can entrain mitochondria that would otherwise display stable dynamics. The work identifies the

  3. On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)

    2015-06-28

    Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

  4. Pattern formation on networks with reactions: A continuous-time random-walk approach

    Science.gov (United States)

    Angstmann, C. N.; Donnelly, I. C.; Henry, B. I.

    2013-03-01

    We derive the generalized master equation for reaction-diffusion on networks from an underlying stochastic process, the continuous time random walk (CTRW). The nontrivial incorporation of the reaction process into the CTRW is achieved by splitting the derivation into two stages. The reactions are treated as birth-death processes and the first stage of the derivation is at the single particle level, taking into account the death process, while the second stage considers an ensemble of these particles including the birth process. Using this model we have investigated different types of pattern formation across the vertices on a range of networks. Importantly, the CTRW defines the Laplacian operator on the network in a non-ad hoc manner and the pattern formation depends on the structure of this Laplacian. Here we focus attention on CTRWs with exponential waiting times for two cases: one in which the rate parameter is constant for all vertices and the other where the rate parameter is proportional to the vertex degree. This results in nonsymmetric and symmetric CTRW Laplacians, respectively. In the case of symmetric Laplacians, pattern formation follows from the Turing instability. However in nonsymmetric Laplacians, pattern formation may be possible with or without a Turing instability.

  5. On the role of conserved moieties in shaping the robustness and production capabilities of reaction networks

    Science.gov (United States)

    DeMartino, A.; Martelli, C.; Massucci, F. A.

    2009-02-01

    We study a simplified, solvable model of a fully connected metabolic network with constrained quenched disorder to mimic the conservation laws imposed by stoichiometry on chemical reactions. Within a spin-glass type of approach, we show that in the presence of a conserved metabolic pool the flux state corresponding to maximal growth is stationary independently of the pool size. In addition, and at odds with the case of unconstrained networks, the volume of optimal flux configurations remains finite, indicating that the frustration imposed by stoichiometric constraints, while reducing growth capabilities, confers robustness and flexibility to the system. These results have a clear biological interpretation and provide a basic, fully analytical explanation to features recently observed in real metabolic networks.

  6. Detection of Hopf bifurcations in chemical reaction networks using convex coordinates

    Science.gov (United States)

    Errami, Hassan; Eiswirth, Markus; Grigoriev, Dima; Seiler, Werner M.; Sturm, Thomas; Weber, Andreas

    2015-06-01

    We present efficient algorithmic methods to detect Hopf bifurcation fixed points in chemical reaction networks with symbolic rate constants, thereby yielding information about the oscillatory behavior of the networks. Our methods use the representations of the systems on convex coordinates that arise from stoichiometric network analysis. One of our methods then reduces the problem of determining the existence of Hopf bifurcation fixed points to a first-order formula over the ordered field of the reals that can be solved using computational logic packages. The second method uses ideas from tropical geometry to formulate a more efficient method that is incomplete in theory but worked very well for the examples that we have attempted; we have shown it to be able to handle systems involving more than 20 species.

  7. Biomolecular Structure Determination with Divide and Concur

    Science.gov (United States)

    Kallus, Yoav; Elser, Veit

    2009-03-01

    Divide and concur (D-C) is a general computational approach, designed for the solution of highly frustrated problems. Recently applied to the problems of disk packing, the kissing number problem, and 3-SAT, it was competitive or outperformed special-purpose methods.ootnotetextS. Gravel and V. Elser, Phys. Rev. E 78, 036706 (2008) We present a method for applying the D-C framework to the problem of biomolecular structure determination. From a list of geometric constraints on groups of atoms in the molecule, we construct a deterministic iterative map that efficiently searches for structures simultaneously satisfying all constraints. As our method eschews an energy function and its minimization to focus on geometric constraints, it can very naturally integrate with the geometric constraints due to chemistry and physics, experimental constraints due to NMR data or many other experimental or biological hints. We present some results of our method.

  8. Biomolecular Markers in Cancer of the Tongue

    Directory of Open Access Journals (Sweden)

    Daris Ferrari

    2009-01-01

    Full Text Available The incidence of tongue cancer is increasing worldwide, and its aggressiveness remains high regardless of treatment. Genetic changes and the expression of abnormal proteins have been frequently reported in the case of head and neck cancers, but the little information that has been published concerning tongue tumours is often contradictory. This review will concentrate on the immunohistochemical expression of biomolecular markers and their relationships with clinical behaviour and prognosis. Most of these proteins are associated with nodal stage, tumour progression and metastases, but there is still controversy concerning their impact on disease-free and overall survival, and treatment response. More extensive clinical studies are needed to identify the patterns of molecular alterations and the most reliable predictors in order to develop tailored anti-tumour strategies based on the targeting of hypoxia markers, vascular and lymphangiogenic factors, epidermal growth factor receptors, intracytoplasmatic signalling and apoptosis.

  9. Micro- and nanodevices integrated with biomolecular probes

    Science.gov (United States)

    Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A.

    2016-01-01

    Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. PMID:26363089

  10. A unified biological modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2013-12-01

    In order to understand the biological response in a cell, a researcher has to create a biological network and design an experiment to prove it. Although biological knowledge has been accumulated, we still don't have enough biological models to explain complex biological phenomena. If a new biological network is to be created, integrated modeling software supporting various biological models is required. In this research, we design and implement a unified biological modeling and simulation system, called ezBioNet, for analyzing biological reaction networks. ezBioNet designs kinetic and Boolean network models and simulates the biological networks using a server-side simulation system with Object Oriented Parallel Accelerator Library framework. The main advantage of ezBioNet is that a user can create a biological network by using unified modeling canvas of kinetic and Boolean models and perform massive simulations, including Ordinary Differential Equation analyses, sensitivity analyses, parameter estimates and Boolean network analysis. ezBioNet integrates useful biological databases, including the BioModels database, by connecting European Bioinformatics Institute servers through Web services Application Programming Interfaces. In addition, we employ Eclipse Rich Client Platform, which is a powerful modularity framework to allow various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool and a simulation system for understanding the control mechanism by monitoring the change of each component in a biological network. The simulation result can be managed and visualized on ezBioNet, which is available free of charge at http://ezbionet.sourceforge.net or http://ezbionet.cbnu.ac.kr.

  11. Spreading of infection in a two species reaction-diffusion process in networks.

    Science.gov (United States)

    Korosoglou, Paschalis; Kittas, Aristotelis; Argyrakis, Panos

    2010-12-01

    We study the dynamics of the infection of a two mobile species reaction from a single infected agent in a population of healthy agents. Historically, the main focus for infection propagation has been through spreading phenomena, where a random location of the system is initially infected and then propagates by successfully infecting its neighbor sites. Here both the infected and healthy agents are mobile, performing classical random walks. This may be a more realistic picture to such epidemiological models, such as the spread of a virus in communication networks of routers, where data travel in packets, the communication time of stations in ad hoc mobile networks, information spreading (such as rumor spreading) in social networks, etc. We monitor the density of healthy particles ρ(t), which we find in all cases to be an exponential function in the long-time limit in two-dimensional and three-dimensional lattices and Erdős-Rényi (ER) and scale-free (SF) networks. We also investigate the scaling of the crossover time t(c) from short- to long-time exponential behavior, which we find to be a power law in lattices and ER networks. This crossover is shown to be absent in SF networks, where we reveal the role of the connectivity of the network in the infection process. We compare this behavior to ER networks and lattices and highlight the significance of various connectivity patterns, as well as the important differences of this process in the various underlying geometries, revealing a more complex behavior of ρ(t). PMID:21230659

  12. BRUSLIB and NETGEN: the Brussels nuclear reaction rate library and nuclear network generator for astrophysics

    Science.gov (United States)

    Aikawa, M.; Arnould, M.; Goriely, S.; Jorissen, A.; Takahashi, K.

    2005-10-01

    Nuclear reaction rates are quantities of fundamental importance in astrophysics. Substantial efforts have been devoted in the last decades to measuring or calculating them. This paper presents a detailed description of the Brussels nuclear reaction rate library BRUSLIB and of the nuclear network generator NETGEN. BRUSLIB is made of two parts. The first one contains the 1999 NACRE compilation based on experimental data for 86 reactions with (mainly) stable targets up to Si. BRUSLIB provides an electronic link to the published, as well as to a large body of unpublished, NACRE data containing adopted rates, as well as lower and upper limits. The second part of BRUSLIB concerns nuclear reaction rate predictions to complement the experimentally-based rates. An electronic access is provided to tables of rates calculated within a statistical Hauser-Feshbach approximation, which limits the reliability of the rates to reactions producing compound nuclei with a high enough level density. These calculations make use of global and coherent microscopic nuclear models for the quantities entering the rate calculations. The use of such models makes the BRUSLIB rate library unique. A description of the Nuclear Network Generator NETGEN that complements the BRUSLIB package is also presented. NETGEN is a tool to generate nuclear reaction rates for temperature grids specified by the user. The information it provides can be used for a large variety of applications, including Big Bang nucleosynthesis, the energy generation and nucleosynthesis associated with the non-explosive and explosive hydrogen to silicon burning stages, or the synthesis of the heavy nuclides through the s-, α- and r-, rp- or p-processes.

  13. Biomolecular simulation on thousands of processors

    Science.gov (United States)

    Phillips, James Christopher

    Classical molecular dynamics simulation is a generally applicable method for the study of biomolecular aggregates of proteins, lipids, and nucleic acids. As experimental techniques have revealed the structures of larger and more complex biomolecular machines, the time required to complete even a single meaningful simulation of such systems has become prohibitive. We have developed the program NAMD to simulate systems of 50,000--500,000 atoms efficiently with full electrostatics on parallel computers with 1000 and more processors. NAMD's scalability is achieved through latency tolerant adaptive message-driven execution and measurement-based load balancing. NAMD is implemented in C++ and uses object-oriented design and threads to shield the basic algorithms from the necessary complexity of high-performance parallel execution. Apolipoprotein A-I is the primary protein constituent of high density lipoprotein particles, which transport cholesterol in the bloodstream. In collaboration with A. Jonas, we have constructed and simulated models of the nascent discoidal form of these particles, providing theoretical insight to the debate regarding the lipid-bound structure of the protein. Recently, S. Sligar and coworkers have created 10 nm phospholipid bilayer nanoparticles comprising a small lipid bilayer disk solubilized by synthetic membrane scaffold proteins derived from apolipoprotein A-I. Membrane proteins may be embedded in the water-soluble disks, with various medical and technological applications. We are working to develop variant scaffold proteins that produce disks of greater size, stability, and homogeneity. Our simulations have demonstrated a significant deviation from idealized cylindrical structure, and are being used in the interpretation of small angle x-ray scattering data.

  14. FERN – a Java framework for stochastic simulation and evaluation of reaction networks

    Science.gov (United States)

    Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

    2008-01-01

    Background Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. Results In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. Conclusion FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand

  15. FERN – a Java framework for stochastic simulation and evaluation of reaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2008-08-01

    Full Text Available Abstract Background Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a do not provide the most efficient simulation algorithms and are difficult to extend, b cannot be easily integrated into other applications or c do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. Results In this article, we present FERN (Framework for Evaluation of Reaction Networks, a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. Conclusion FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward

  16. Biomolecular detection employing the Interferometric Reflectance Imaging Sensor (IRIS).

    Science.gov (United States)

    Lopez, Carlos A; Daaboul, George G; Ahn, Sunmin; Reddington, Alexander P; Monroe, Margo R; Zhang, Xirui; Irani, Rostem J; Yu, Chunxiao; Genco, Caroline A; Cretich, Marina; Chiari, Marcella; Goldberg, Bennett B; Connor, John H; Ünlü, M Selim

    2011-01-01

    The sensitive measurement of biomolecular interactions has use in many fields and industries such as basic biology and microbiology, environmental/agricultural/biodefense monitoring, nanobiotechnology, and more. For diagnostic applications, monitoring (detecting) the presence, absence, or abnormal expression of targeted proteomic or genomic biomarkers found in patient samples can be used to determine treatment approaches or therapy efficacy. In the research arena, information on molecular affinities and specificities are useful for fully characterizing the systems under investigation. Many of the current systems employed to determine molecular concentrations or affinities rely on the use of labels. Examples of these systems include immunoassays such as the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR) techniques, gel electrophoresis assays, and mass spectrometry (MS). Generally, these labels are fluorescent, radiological, or colorimetric in nature and are directly or indirectly attached to the molecular target of interest. Though the use of labels is widely accepted and has some benefits, there are drawbacks which are stimulating the development of new label-free methods for measuring these interactions. These drawbacks include practical facets such as increased assay cost, reagent lifespan and usability, storage and safety concerns, wasted time and effort in labelling, and variability among the different reagents due to the labelling processes or labels themselves. On a scientific research basis, the use of these labels can also introduce difficulties such as concerns with effects on protein functionality/structure due to the presence of the attached labels and the inability to directly measure the interactions in real time. Presented here is the use of a new label-free optical biosensor that is amenable to microarray studies, termed the Interferometric Reflectance Imaging Sensor (IRIS), for detecting proteins, DNA, antigenic material

  17. ezBioNet: A modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2012-10-01

    To achieve robustness against living environments, a living organism is composed of complicated regulatory mechanisms ranging from gene regulations to signal transduction. If such life phenomena are to be understand, an integrated analysis tool that should have modeling and simulation functions for biological reactions, as well as new experimental methods for measuring biological phenomena, is fundamentally required. We have designed and implemented modeling and simulation software (ezBioNet) for analyzing biological reaction networks. The software can simultaneously perform an integrated modeling of various responses occurring in cells, ranging from gene expressions to signaling processes. To support massive analysis of biological networks, we have constructed a server-side simulation system (VCellSim) that can perform ordinary differential equations (ODE) analysis, sensitivity analysis, and parameter estimates. ezBioNet integrates the BioModel database by connecting the european bioinformatics institute (EBI) servers through Web services APIs and supports the handling of systems biology markup language (SBML) files. In addition, we employed eclipse RCP (rich client platform) which is a powerful modularity framework allowing various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool, as well as a simulation system, to understand the control mechanism by monitoring the change of each component in a biological network. A researcher may perform the kinetic modeling and execute the simulation. The simulation result can be managed and visualized on ezBioNet, which is freely available at http://ezbionet.cbnu.ac.kr.

  18. Simulation and fitting of complex reaction network TPR: The key is the objective function

    Science.gov (United States)

    Savara, Aditya

    2016-11-01

    A method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based on the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN-TPR, there is increased importance (relative to simple reaction network TPR) in resolving of peaks prior to fitting, as well as from weighting of experimental data points. Using an implicit ordinary differential equation solver was found to be inadequate for simulating CRN-TPR. The method employed here was capable of attaining improved fits in simulation and fitting of CRN-TPR when starting with a postulated mechanism and physically realistic initial guesses for the kinetic parameters.

  19. The thermodynamic properties of 2-aminobiphenyl (an intermediate in the carbazole/hydrogen reaction network)

    Energy Technology Data Exchange (ETDEWEB)

    Steele, W.V.; Chirico, R.D.; Knipmeyer, S.E.; Nguyen, A.

    1990-12-01

    Catalytic hydrodenitrogenation (HDN) is a key step in upgrading processes for conversion of heavy petroleum, shale oil, tar sands, and the products of the liquefaction of coal to economically viable products. This research program provides accurate experimental thermochemical and thermophysical properties for key organic nitrogen-containing compounds present in the range of alternative feedstocks, and applies the experimental information to thermodynamic analyses of key HDN reaction networks. This report is the first in a series that will lead to an analysis of a three-ring HDN system; the carbazole/hydrogen reaction network. 2-Aminobiphenyl is the initial intermediate in the HDN pathway for carbazole, which consumes the least hydrogen possible. Measurements leading to the calculation of the ideal-gas thermodynamic properties for 2-aminobiphenyl are reported. Experimental methods included combustion calorimetry, adiabatic heat-capacity calorimetry, comparative ebulliometry, inclined-piston gauge manometry, and differential-scanning calorimetry (d.s.c). Entropies, enthalpies, and Gibbs energies of formation were derived for the ideal gas for selected temperatures between 298.15 K and 820 K. The critical temperature and critical density were determined for 2-aminobiphenyl with the d.s.c., and the critical pressure was derived. The Gibbs energies of formation are used in thermodynamic calculations to compare the feasibility of the initial hydrogenolysis step in the carbazole/H{sub 2} network with that of its hydrocarbon and oxygen-containing analogous; i.e., fluorene/H{sub 2} and dibenzofuran/H{sub 2}. Results of the thermodynamic calculations are compared with those of batch-reaction studies reported in the literature. 57 refs., 8 figs., 18 tabs.

  20. A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

    Science.gov (United States)

    Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

    2010-01-01

    A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal. PMID:22163620

  1. A Reaction-Diffusion-Based Coding Rate Control Mechanism for Camera Sensor Networks

    Directory of Open Access Journals (Sweden)

    Naoki Wakamiya

    2010-08-01

    Full Text Available A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

  2. Neural Network Control of CSTR for Reversible Reaction Using Reverence Model Approach

    Directory of Open Access Journals (Sweden)

    Duncan ALOKO

    2007-01-01

    Full Text Available In this work, non-linear control of CSTR for reversible reaction is carried out using Neural Network as design tool. The Model Reverence approach in used to design ANN controller. The idea is to have a control system that will be able to achieve improvement in the level of conversion and to be able to track set point change and reject load disturbance. We use PID control scheme as benchmark to study the performance of the controller. The comparison shows that ANN controller out perform PID in the extreme range of non-linearity.This paper represents a preliminary effort to design a simplified neutral network control scheme for a class of non-linear process. Future works will involve further investigation of the effectiveness of thin approach for the real industrial chemical process

  3. Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality

    Science.gov (United States)

    Grytskyy, Dmytro; Diesmann, Markus; Helias, Moritz

    2016-06-01

    Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate-based model neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the nonlinearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime metastable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated.

  4. Elucidation of Diels-Alder Reaction Network of 2,5-Dimethylfuran and Ethylene on HY Zeolite Catalyst

    Energy Technology Data Exchange (ETDEWEB)

    Do, Phuong T. M. [Univ. of Delaware, Newark, DE (United States); McAtee, Jesse R. [Univ. of Delaware, Newark, DE (United States); Watson, Donald A. [Univ. of Delaware, Newark, DE (United States); Lobo, Raul F. [Univ. of Delaware, Newark, DE (United States)

    2012-12-12

    The reaction of 2,5-dimethylfuran and ethylene to produce p-xylene represents a potentially important route for the conversion of biomass to high-value organic chemicals. Current preparation methods suffer from low selectivity and produce a number of byproducts. Using modern separation and analytical techniques, the structures of many of the byproducts produced in this reaction when HY zeolite is employed as a catalyst have been identified. From these data, a detailed reaction network is proposed, demonstrating that hydrolysis and electrophilic alkylation reactions compete with the desired Diels–Alder/dehydration sequence. This information will allow the rational identification of more selective catalysts and more selective reaction conditions.

  5. Integrated Spintronic Platforms for Biomolecular Recognition Detection

    Science.gov (United States)

    Martins, V. C.; Cardoso, F. A.; Loureiro, J.; Mercier, M.; Germano, J.; Cardoso, S.; Ferreira, R.; Fonseca, L. P.; Sousa, L.; Piedade, M. S.; Freitas, P. P.

    2008-06-01

    This paper covers recent developments in magnetoresistive based biochip platforms fabricated at INESC-MN, and their application to the detection and quantification of pathogenic waterborn microorganisms in water samples for human consumption. Such platforms are intended to give response to the increasing concern related to microbial contaminated water sources. The presented results concern the development of biological active DNA chips and protein chips and the demonstration of the detection capability of the present platforms. Two platforms are described, one including spintronic sensors only (spin-valve based or magnetic tunnel junction based), and the other, a fully scalable platform where each probe site consists of a MTJ in series with a thin film diode (TFD). Two microfluidic systems are described, for cell separation and concentration, and finally, the read out and control integrated electronics are described, allowing the realization of bioassays with a portable point of care unit. The present platforms already allow the detection of complementary biomolecular target recognition with 1 pM concentration.

  6. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  7. Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models

    KAUST Repository

    Moraes, Alvaro

    2015-01-01

    Epidemics have shaped, sometimes more than wars and natural disasters, demo- graphic aspects of human populations around the world, their health habits and their economies. Ebola and the Middle East Respiratory Syndrome (MERS) are clear and current examples of potential hazards at planetary scale. During the spread of an epidemic disease, there are phenomena, like the sudden extinction of the epidemic, that can not be captured by deterministic models. As a consequence, stochastic models have been proposed during the last decades. A typical forward problem in the stochastic setting could be the approximation of the expected number of infected individuals found in one month from now. On the other hand, a typical inverse problem could be, given a discretely observed set of epidemiological data, infer the transmission rate of the epidemic or its basic reproduction number. Markovian epidemic models are stochastic models belonging to a wide class of pure jump processes known as Stochastic Reaction Networks (SRNs), that are intended to describe the time evolution of interacting particle systems where one particle interacts with the others through a finite set of reaction channels. SRNs have been mainly developed to model biochemical reactions but they also have applications in neural networks, virus kinetics, and dynamics of social networks, among others. 4 This PhD thesis is focused on novel fast simulation algorithms and statistical inference methods for SRNs. Our novel Multi-level Monte Carlo (MLMC) hybrid simulation algorithms provide accurate estimates of expected values of a given observable of SRNs at a prescribed final time. They are designed to control the global approximation error up to a user-selected accuracy and up to a certain confidence level, and with near optimal computational work. We also present novel dual-weighted residual expansions for fast estimation of weak and strong errors arising from the MLMC methodology. Regarding the statistical inference

  8. Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic

    CERN Document Server

    Privman, Vladimir; Arugula, Mary A; Melnikov, Dmitriy; Bocharova, Vera; Katz, Evgeny

    2010-01-01

    The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic research has been achieving scalability for complex network designs. Various logic gates have been realized, but a "toolbox" of analog elements for interconnectivity and signal processing has remained elusive. Filters are important as network elements that allow control of noise in signal transmission and conversion. We report a versatile biochemical filtering mechanism designed to have sigmoidal response in combination with signal-conversion process. Horseradish peroxidase-catalyzed oxidation of chromogenic electron donor by hydrogen peroxide, was altered by adding ascorbate, allowing to selectively suppress the output signal, modifying the response from convex to sigmoidal. A kinetic model was developed for evaluation of the quality of filtering. The results offer improved...

  9. Effects of network dissolution changes on pore-to-core upscaled reaction rates for kaolinite and anorthite reactions under acidic conditions

    KAUST Repository

    Kim, Daesang

    2013-11-01

    We have extended reactive flow simulation in pore-network models to include geometric changes in the medium from dissolution effects. These effects include changes in pore volume and reactive surface area, as well as topological changes that open new connections. The computed changes were based upon a mineral map from an X-ray computed tomography image of a sandstone core. We studied the effect of these changes on upscaled (pore-scale to core-scale) reaction rates and compared against the predictions of a continuum model. Specifically, we modeled anorthite and kaolinite reactions under acidic flow conditions during which the anorthite reactions remain far from equilibrium (dissolution only), while the kaolinite reactions can be near-equilibrium. Under dissolution changes, core-scale reaction rates continuously and nonlinearly evolved in time. At higher injection rates, agreement with predictions of the continuum model degraded significantly. For the far-from-equilibrium reaction, our results indicate that the ability to correctly capture the heterogeneity in dissolution changes in the reactive mineral surface area is critical to accurately predict upscaled reaction rates. For the near-equilibrium reaction, the ability to correctly capture the heterogeneity in the saturation state remains critical. Inclusion of a Nernst-Planck term to ensure neutral ionic currents under differential diffusion resulted in at most a 9% correction in upscaled rates.

  10. Propensity approach to nonequilibrium thermodynamics of a chemical reaction network: Controlling single E-coli β-galactosidase enzyme catalysis through the elementary reaction steps

    Energy Technology Data Exchange (ETDEWEB)

    Das, Biswajit; Gangopadhyay, Gautam, E-mail: gautam@bose.res.in [S. N. Bose National Centre For Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata 700 098 (India); Banerjee, Kinshuk [Department of Chemistry, University of Calcutta, 92 A.P.C. Road, Kolkata 700 009 (India)

    2013-12-28

    In this work, we develop an approach to nonequilibrium thermodynamics of an open chemical reaction network in terms of the elementary reaction propensities. The method is akin to the microscopic formulation of the dissipation function in terms of the Kullback-Leibler distance of phase space trajectories in Hamiltonian system. The formalism is applied to a single oligomeric enzyme kinetics at chemiostatic condition that leads the reaction system to a nonequilibrium steady state, characterized by a positive total entropy production rate. Analytical expressions are derived, relating the individual reaction contributions towards the total entropy production rate with experimentally measurable reaction velocity. Taking a real case of Escherichia coli β-galactosidase enzyme obeying Michaelis-Menten kinetics, we thoroughly analyze the temporal as well as the steady state behavior of various thermodynamic quantities for each elementary reaction. This gives a useful insight in the relative magnitudes of various energy terms and the dissipated heat to sustain a steady state of the reaction system operating far-from-equilibrium. It is also observed that, the reaction is entropy-driven at low substrate concentration and becomes energy-driven as the substrate concentration rises.

  11. Biomolecular Modification of Inorganic Crystal Growth

    Energy Technology Data Exchange (ETDEWEB)

    De Yoreo, J J

    2007-04-27

    The fascinating shapes and hierarchical designs of biomineralized structures are an inspiration to materials scientists because of the potential they suggest for biomolecular control over materials synthesis. Conversely, the failure to prevent or limit tissue mineralization in the vascular, skeletal, and urinary systems is a common source of disease. Understanding the mechanisms by which organisms direct or limit crystallization has long been a central challenge to the biomineralization community. One prevailing view is that mineral-associated macromolecules are responsible for either inhibiting crystallization or initiating and stabilizing non-equilibrium crystal polymorphs and morphologies through interactions between anionic moieties and cations in solution or at mineralizing surfaces. In particular, biomolecules that present carboxyl groups to the growing crystal have been implicated as primary modulators of growth. Here we review the results from a combination of in situ atomic force microscopy (AFM) and molecular modeling (MM) studies to investigate the effect of specific interactions between carboxylate-rich biomolecules and atomic steps on crystal surfaces during the growth of carbonates, oxalates and phosphates of calcium. Specifically, we how the growth kinetics and morphology depend on the concentration of additives that include citrate, simple amino acids, synthetic Asp-rich polypeptides, and naturally occurring Asp-rich proteins found in both functional and pathological mineral tissues. The results reveal a consistent picture of shape modification in which stereochemical matching of modifiers to specific atomic steps drives shape modification. Inhibition and other changes in growth kinetics are shown to be due to a range of mechanisms that depend on chemistry and molecular size. Some effects are well described by classic crystal growth theories, but others, such as step acceleration due to peptide charge and hydrophylicity, were previously unrealized

  12. Bridging Nano- and Microtribology in Mechanical and Biomolecular Layers

    Science.gov (United States)

    Tomala, Agnieszka; Göçerler, Hakan; Gebeshuber, Ille C.

    The physical and chemical composition of surfaces determine various important properties of solids such as corrosion rates, adhesive properties, frictional properties, catalytic activity, wettability, contact potential and - finally and most importantly - failure mechanisms. Very thin, weak layers (of man-made and biological origin) on much harder substrates that reduce friction are the focus of the micro- and nanotribological investigations presented in this chapter.Biomolecular layers fulfil various functions in organs of the human body. Examples comprise the skin that provides a protective physical barrier between the body and the environment, preventing unwanted inward and outward passage of water and electrolytes, reducing penetration by destructive chemicals, arresting the penetration of microorganisms and external antigens and absorbing radiation from the sun, or the epithelium of the cornea that blocks the passage of foreign material, such as dust, water and bacteria, into the eye and that contributes to the lubrication layer that ensures smooth movement of the eyelids over the eyeballs.Monomolecular thin films, additive-derived reaction layers and hard coatings are widely used to tailor tribological properties of surfaces. Nanotribological investigations on these substrates can reveal novel properties regarding the orientation of chemisorbed additive layers, development of rubbing films with time and the relation of frictional properties to surface characteristics in diamond coatings.Depending on the questions to be answered with the tribological research, various micro- and nanotribological measurement methods are applied, including scanning probe microscopy (AFM, FFM), scanning electron microscopy, microtribometer investigations, angle-resolved photoelectron spectroscopy and optical microscopy. Thoughts on the feasibility of a unified approach to energy-dissipating systems and how it might be reached (touching upon new ways of scientific publishing

  13. Trade-off between responsiveness and noise suppression in biomolecular system responses to environmental cues.

    Directory of Open Access Journals (Sweden)

    Alexander V Ratushny

    2011-06-01

    Full Text Available When living systems detect changes in their external environment their response must be measured to balance the need to react appropriately with the need to remain stable, ignoring insignificant signals. Because this is a fundamental challenge of all biological systems that execute programs in response to stimuli, we developed a generalized time-frequency analysis (TFA framework to systematically explore the dynamical properties of biomolecular networks. Using TFA, we focused on two well-characterized yeast gene regulatory networks responsive to carbon-source shifts and a mammalian innate immune regulatory network responsive to lipopolysaccharides (LPS. The networks are comprised of two different basic architectures. Dual positive and negative feedback loops make up the yeast galactose network; whereas overlapping positive and negative feed-forward loops are common to the yeast fatty-acid response network and the LPS-induced network of macrophages. TFA revealed remarkably distinct network behaviors in terms of trade-offs in responsiveness and noise suppression that are appropriately tuned to each biological response. The wild type galactose network was found to be highly responsive while the oleate network has greater noise suppression ability. The LPS network appeared more balanced, exhibiting less bias toward noise suppression or responsiveness. Exploration of the network parameter space exposed dramatic differences in system behaviors for each network. These studies highlight fundamental structural and dynamical principles that underlie each network, reveal constrained parameters of positive and negative feedback and feed-forward strengths that tune the networks appropriately for their respective biological roles, and demonstrate the general utility of the TFA approach for systems and synthetic biology.

  14. Evolution of Autocatalytic Sets in Computational Models of Chemical Reaction Networks

    Science.gov (United States)

    Hordijk, Wim

    2016-06-01

    Several computational models of chemical reaction networks have been presented in the literature in the past, showing the appearance and (potential) evolution of autocatalytic sets. However, the notion of autocatalytic sets has been defined differently in different modeling contexts, each one having some shortcoming or limitation. Here, we review four such models and definitions, and then formally describe and analyze them in the context of a mathematical framework for studying autocatalytic sets known as RAF theory. The main results are that: (1) RAF theory can capture the various previous definitions of autocatalytic sets and is therefore more complete and general, (2) the formal framework can be used to efficiently detect and analyze autocatalytic sets in all of these different computational models, (3) autocatalytic (RAF) sets are indeed likely to appear and evolve in such models, and (4) this could have important implications for a possible metabolism-first scenario for the origin of life.

  15. A model for lignin alteration - Part I: A kinetic reaction-network model

    Science.gov (United States)

    Payne, D.F.; Ortoleva, P.J.

    2001-01-01

    A new quantitative model is presented which simulates the maturation of lignin-derived sedimentary organic matter under geologic conditions. In this model, compositionally specific reactants evolve to specific intermediate and mobile products through balanced, nth order processes, by way of a network of sequential and parallel reactions. The chemical kinetic approach is based primarily on published observed structural transformations of naturally matured, lignin-derived, sedimentary organic matter. Assuming that Upper Cretaceous Williams Fork coal in the Piceance Basin is primarily lignin-derived, the model is calibrated for the Multi-Well Experiment(MWX) Site in this basin. This kind of approach may be applied to other selectively preserved chemical components of sedimentary organic matter. ?? 2001 Elsevier Science Ltd. All rights reserved.

  16. Biomolecular crystals for material applications and a mechanistic study of an iron oxide nanoparticle synthesis

    Science.gov (United States)

    Falkner, Joshua Charles

    The three projects within this work address the difficulties of controlling biomolecular crystal formats (i.e. size and shape), producing 3-D ordered composite materials from biomolecular crystal templates, and understanding the mechanism of a practical iron oxide synthesis. The unifying thread consistent throughout these three topics is the development of methods to manipulate nanomaterials using a bottom-up approach. Biomolecular crystals are nanometer to millimeter sized crystals that have well ordered mesoporous solvent channels. The overall physical dimensions of these crystals are highly dependent on crystallization conditions. The controlled growth of micro- and nanoprotein crystals was studied to provide new pathways for creating smaller crystalline protein materials. This method produced tetragonal hen egg-white lysozyme crystals (250--100,000 nm) with near monodisperse size distributions (membranes or templates. In this work, the porous structure of larger cowpea mosaic virus crystals was used to template metal nanoparticle growth within the body centered cubic crystalline network. The final composite material was found to have long range ordering of palladium and platinum nonocrystal aggregates (10nm) with symmetry consistent to the virus template. Nanoparticle synthesis itself is an immense field of study with an array of diverse applications. The final piece of this work investigates the mechanism behind a previously developed iron oxide synthesis to gain more understanding and direction to future synthesis strategies. The particle growth mechanism was found to proceed by the formation of a solvated iron(III)oleate complex followed by a reduction of iron (III) to iron (II). This unstable iron(II) nucleates to form a wustite (FeO) core which serves as an epitaxial surface for the magnetite (Fe3O4) shell growth. This method produces spherical particles (6-60nm) with relative size distributions of less than 15%.

  17. Nanoscale field effect transistor for biomolecular signal amplification

    CERN Document Server

    Chen, Yu; Hong, Mi K; Erramilli, Shyamsunder; Rosenberg, Carol; Mohanty, Pritiraj

    2008-01-01

    We report amplification of biomolecular recognition signal in lithographically defined silicon nanochannel devices. The devices are configured as field effect transistors (FET) in the reversed source-drain bias region. The measurement of the differential conductance of the nanowire channels in the FET allows sensitive detection of changes in the surface potential due to biomolecular binding. Narrower silicon channels demonstrate higher sensitivity to binding due to increased surface-to-volume ratio. The operation of the device in the negative source-drain region demonstrates signal amplification. The equivalence between protein binding and change in the surface potential is described.

  18. A moment-convergence method for stochastic analysis of biochemical reaction networks

    Science.gov (United States)

    Zhang, Jiajun; Nie, Qing; Zhou, Tianshou

    2016-05-01

    Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

  19. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

    OpenAIRE

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2012-01-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking ...

  20. Feature Selection in Detection of Adverse Drug Reactions from the Health Improvement Network (THIN Database

    Directory of Open Access Journals (Sweden)

    Yihui Liu

    2015-02-01

    Full Text Available Adverse drug reaction (ADR is widely concerned for public health issue. ADRs are one of most common causes to withdraw some drugs from market. Prescription event monitoring (PEM is an important approach to detect the adverse drug reactions. The main problem to deal with this method is how to automatically extract the medical events or side effects from high-throughput medical events, which are collected from day to day clinical practice. In this study we propose a novel concept of feature matrix to detect the ADRs. Feature matrix, which is extracted from big medical data from The Health Improvement Network (THIN database, is created to characterize the medical events for the patients who take drugs. Feature matrix builds the foundation for the irregular and big medical data. Then feature selection methods are performed on feature matrix to detect the significant features. Finally the ADRs can be located based on the significant features. The experiments are carried out on three drugs: Atorvastatin, Alendronate, and Metoclopramide. Major side effects for each drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on computerized methods, further investigation is needed.

  1. Engineering intracellular active transport systems as in vivo biomolecular tools.

    Energy Technology Data Exchange (ETDEWEB)

    Bachand, George David; Carroll-Portillo, Amanda

    2006-11-01

    Active transport systems provide essential functions in terms of cell physiology and metastasis. These systems, however, are also co-opted by invading viruses, enabling directed transport of the virus to and from the cell's nucleus (i.e., the site of virus replication). Based on this concept, fundamentally new approaches for interrogating and manipulating the inner workings of living cells may be achievable by co-opting Nature's active transport systems as an in vivo biomolecular tool. The overall goal of this project was to investigate the ability to engineer kinesin-based transport systems for in vivo applications, specifically the collection of effector proteins (e.g., transcriptional regulators) within single cells. In the first part of this project, a chimeric fusion protein consisting of kinesin and a single chain variable fragment (scFv) of an antibody was successfully produced through a recombinant expression system. The kinesin-scFv retained both catalytic and antigenic functionality, enabling selective capture and transport of target antigens. The incorporation of a rabbit IgG-specific scFv into the kinesin established a generalized system for functionalizing kinesin with a wide range of target-selective antibodies raised in rabbits. The second objective was to develop methods of isolating the intact microtubule network from live cells as a platform for evaluating kinesin-based transport within the cytoskeletal architecture of a cell. Successful isolation of intact microtubule networks from two distinct cell types was demonstrated using glutaraldehyde and methanol fixation methods. This work provides a platform for inferring the ability of kinesin-scFv to function in vivo, and may also serve as a three-dimensional scaffold for evaluating and exploiting kinesin-based transport for nanotechnological applications. Overall, the technology developed in this project represents a first-step in engineering active transport system for in vivo

  2. Facing and Overcoming Sensitivity Challenges in Biomolecular NMR Spectroscopy

    DEFF Research Database (Denmark)

    Ardenkjær-Larsen, Jan Henrik; Boebinger, Gregory S.; Comment, Arnaud;

    2015-01-01

    In the Spring of 2013, NMR spectroscopists convened at the Weizmann Institute in Israel to brainstorm on approaches to improve the sensitivity of NMR experiments, particularly when applied in biomolecular settings. This multi‐author interdisciplinary Review presents a state‐of‐the‐art description...

  3. The HADDOCK web server for data-driven biomolecular docking

    NARCIS (Netherlands)

    de Vries, S.J.; van Dijk, M.; Bonvin, A.M.J.J.

    2010-01-01

    Computational docking is the prediction or modeling of the three-dimensional structure of a biomolecular complex, starting from the structures of the individual molecules in their free, unbound form. HADDOC K is a popular docking program that takes a datadriven approach to docking, with support for

  4. From dynamics to structure and function of model biomolecular systems

    NARCIS (Netherlands)

    Fontaine-Vive-Curtaz, F.

    2007-01-01

    The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation method

  5. Neutral-particle emission in collisions of electrons with biomolecular ions in an electrostatic storage ring

    International Nuclear Information System (INIS)

    Electron-biomolecular ion collisions were studied using an electrostatic storage ring with a merging electron beam device. Biomolecular ions produced by an electrospray ion source and accelerated to 20 keV/charge were injected into the ring after being mass-analyzed. The circulating ion beam was then merged with an electron beam. Neutral reaction products in collisions of electrons with ions were detected by a micro-channel plate outside of the ring. Electron-ion collisions were studied for multiply-deprotonated oligonucleotide and peptide anions as well as singly protonated oligonucleotide and peptide cations. For peptide cations, neutrals were resonantly emitted at an electron energy of around 6.5 eV, which was almost independent of the ion masses. This is deduced to come from electron-ion recombination, resulting in the cleavage of a peptide bond. For DNA oligonucleotide cations, resonant neutral particle emission was also observed. In electron and DNA anion collisions, neutrals started to increase from definite threshold energies, where the threshold energies increased in proportion to the ion charge. The same was found for peptide anions. The origin of this phenomenon is discussed

  6. Integer programming-based method for designing synthetic metabolic networks by Minimum Reaction Insertion in a Boolean model.

    Directory of Open Access Journals (Sweden)

    Wei Lu

    Full Text Available In this paper, we consider the Minimum Reaction Insertion (MRI problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at "http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html."

  7. Integer programming-based method for designing synthetic metabolic networks by Minimum Reaction Insertion in a Boolean model.

    Science.gov (United States)

    Lu, Wei; Tamura, Takeyuki; Song, Jiangning; Akutsu, Tatsuya

    2014-01-01

    In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA)-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at "http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html."

  8. Stability Analysis of Stochastic Reaction-Diffusion Cohen-Grossberg Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Chuangxia Huang

    2009-01-01

    Full Text Available This paper is concerned with pth moment exponential stability of stochastic reaction-diffusion Cohen-Grossberg neural networks with time-varying delays. With the help of Lyapunov method, stochastic analysis, and inequality techniques, a set of new suffcient conditions on pth moment exponential stability for the considered system is presented. The proposed results generalized and improved some earlier publications.

  9. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks.

    Science.gov (United States)

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2013-05-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three subnetworks. It turns out that our reaction classifier, which is blind to the biochemical role of pathways, leads to three functionally relevant subnetworks that correspond to input, output, and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality. PMID:23767567

  10. Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement

    Science.gov (United States)

    Srinivas, Niranjan

    Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for

  11. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space

    Science.gov (United States)

    Ruess, Jakob

    2015-12-01

    Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.

  12. Reaction Network of Layer-to-Tunnel Transition of MnO2.

    Science.gov (United States)

    Li, Ye-Fei; Zhu, Sheng-Cai; Liu, Zhi-Pan

    2016-04-27

    As a model system of 2-D oxide material, layered δ-MnO2 has important applications in Li ion battery systems. δ-MnO2 is also widely utilized as a precursor to synthesize other stable structure variants in the MnO2 family, such as α-, β-, R-, and γ-phases, which are 3-D interlinked structures with different tunnels. By utilizing the stochastic surface walking (SSW) pathway sampling method, we here for the first time resolve the atomistic mechanism and the kinetics of the layer-to-tunnel transition of MnO2, that is, from δ-MnO2 to the α-, β-, and R-phases. The SSW sampling determines the lowest-energy pathway from thousands of likely pathways that connects different phases. The reaction barriers of layer-to-tunnel phase transitions are found to be low, being 0.2-0.3 eV per formula unit, which suggests a complex competing reaction network toward different tunnel phases. All the transitions initiate via a common shearing and buckling movement of the MnO2 layer that leads to the breaking of the Mn-O framework and the formation of Mn(3+) at the transition state. Important hints are thus gleaned from these lowest-energy pathways: (i) the large pore size product is unfavorable for the entropic reason; (ii) cations are effective dopants to control the kinetics and selectivity in layer-to-tunnel transitions, which in general lowers the phase transition barrier and facilitates the creation of larger tunnel size; (iii) the phase transition not only changes the electronic structure but also induces the macroscopic morphology changes due to the interfacial strain. PMID:27054525

  13. Population dynamics, information transfer, and spatial organization in a chemical reaction network under spatial confinement and crowding conditions

    Science.gov (United States)

    Bellesia, Giovanni; Bales, Benjamin B.

    2016-10-01

    We investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been "extended" and considered as a prototype reaction-diffusion system. Our results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatial stochastic simulation methods for the study of biochemical networks in vivo where the "well-mixed" approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.

  14. MONITORING POTENTIAL DRUG INTERACTIONS AND REACTIONS VIA NETWORK ANALYSIS OF INSTAGRAM USER TIMELINES.

    Science.gov (United States)

    Correia, Rion Brattig; Li, Lang; Rocha, Luis M

    2016-01-01

    Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this "Bibliome", the universe of social media provides a very promising source of large-scale data that can help identify DDI and ADR in ways that have not been hitherto possible. Given the large number of users, analysis of social media data may be useful to identify under-reported, population-level pathology associated with DDI, thus further contributing to improvements in population health. Moreover, tapping into this data allows us to infer drug interactions with natural products-including cannabis-which constitute an array of DDI very poorly explored by biomedical research thus far. Our goal is to determine the potential of Instagram for public health monitoring and surveillance for DDI, ADR, and behavioral pathology at large. Most social media analysis focuses on Twitter and Facebook, but Instagram is an increasingly important platform, especially among teens, with unrestricted access of public posts, high availability of posts with geolocation coordinates, and images to supplement textual analysis. Using drug, symptom, and natural product dictionaries for identification of the various types of DDI and ADR evidence, we have collected close to 7000 user timelines spanning from October 2010 to June 2015.We report on 1) the development of a monitoring tool to easily observe user-level timelines associated with drug and symptom terms of interest, and 2) population-level behavior via the analysis of co-occurrence networks computed from user timelines at three different scales: monthly, weekly, and daily occurrences. Analysis of these networks further reveals 3) drug and symptom direct and indirect associations with greater support in user timelines, as well as 4) clusters of symptoms and drugs revealed by the collective behavior of the observed population. This demonstrates that Instagram

  15. Variance-reduced simulation of lattice discrete-time Markov chains with applications in reaction networks

    Science.gov (United States)

    Maginnis, P. A.; West, M.; Dullerud, G. E.

    2016-10-01

    We propose an algorithm to accelerate Monte Carlo simulation for a broad class of stochastic processes. Specifically, the class of countable-state, discrete-time Markov chains driven by additive Poisson noise, or lattice discrete-time Markov chains. In particular, this class includes simulation of reaction networks via the tau-leaping algorithm. To produce the speedup, we simulate pairs of fair-draw trajectories that are negatively correlated. Thus, when averaged, these paths produce an unbiased Monte Carlo estimator that has reduced variance and, therefore, reduced error. Numerical results for three example systems included in this work demonstrate two to four orders of magnitude reduction of mean-square error. The numerical examples were chosen to illustrate different application areas and levels of system complexity. The areas are: gene expression (affine state-dependent rates), aerosol particle coagulation with emission and human immunodeficiency virus infection (both with nonlinear state-dependent rates). Our algorithm views the system dynamics as a "black-box", i.e., we only require control of pseudorandom number generator inputs. As a result, typical codes can be retrofitted with our algorithm using only minor changes. We prove several analytical results. Among these, we characterize the relationship of covariances between paths in the general nonlinear state-dependent intensity rates case, and we prove variance reduction of mean estimators in the special case of affine intensity rates.

  16. Advances in modeling of biomolecular interactions

    Institute of Scientific and Technical Information of China (English)

    Cong-zhongCAI; Ze-rongLI; Wan-luWANG; Yu-zongCHEN

    2004-01-01

    Modeling of molecular interactions is increasingly used in life science research and biotechnology development.Examples are computer aided drug design, prediction of protein interactions with other molecules, and simulation of networks of biomolecules in a particular process in human body. This article reviews recent progress in the related fields and provides a brief overview on the methods used in molecular modeling of biological systems.

  17. Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks

    KAUST Repository

    Ben Hammouda, Chiheb

    2015-05-12

    In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for

  18. Physics at the biomolecular interface fundamentals for molecular targeted therapy

    CERN Document Server

    Fernández, Ariel

    2016-01-01

    This book focuses primarily on the role of interfacial forces in understanding biological phenomena at the molecular scale. By providing a suitable statistical mechanical apparatus to handle the biomolecular interface, the book becomes uniquely positioned to address core problems in molecular biophysics. It highlights the importance of interfacial tension in delineating a solution to the protein folding problem, in unravelling the physico-chemical basis of enzyme catalysis and protein associations, and in rationally designing molecular targeted therapies. Thus grounded in fundamental science, the book develops a powerful technological platform for drug discovery, while it is set to inspire scientists at any level in their careers determined to address the major challenges in molecular biophysics. The acknowledgment of how exquisitely the structure and dynamics of proteins and their aqueous environment are related attests to the overdue recognition that biomolecular phenomena cannot be effectively understood w...

  19. Graph-theoretical identification of dissociation pathways on free energy landscapes of biomolecular interaction.

    Science.gov (United States)

    Wang, Ling; Stumm, Boris; Helms, Volkhard

    2010-03-01

    Biomolecular association and dissociation reactions take place on complicated interaction free energy landscapes that are still very hard to characterize computationally. For large enough distances, though, it often suffices to consider the six relative translational and rotational degrees of freedom of the two particles treated as rigid bodies. Here, we computed the six-dimensional free energy surface of a dimer of water-soluble alpha-helices by scanning these six degrees of freedom in about one million grid points. In each point, the relative free energy difference was computed as the sum of the polar and nonpolar solvation free energies of the helix dimer and of the intermolecular coulombic interaction energy. The Dijkstra graph algorithm was then applied to search for the lowest cost dissociation pathways based on a weighted, directed graph, where the vertices represent the grid points, the edges connect the grid points and their neighbors, and the weights are the reaction costs between adjacent pairs of grid points. As an example, the configuration of the bound state was chosen as the source node, and the eight corners of the translational cube were chosen as the destination nodes. With the strong electrostatic interaction of the two helices giving rise to a clearly funnel-shaped energy landscape, the eight lowest-energy cost pathways coming from different orientations converge into a well-defined pathway for association. We believe that the methodology presented here will prove useful for identifying low-energy association and dissociation pathways in future studies of complicated free energy landscapes for biomolecular interaction. PMID:19603501

  20. Association of Biomolecular Resource Facilities Survey: Service Laboratory Funding

    OpenAIRE

    Ogorzalek Loo, Rachel; Nicolet, Charles M.; Niece, Ronald L.; Young, Mary; Simpson, John T.

    2009-01-01

    In 2007, The Association of Biomolecular Resource Facilities (ABRF) Survey Committee surveyed the ABRF membership and scientists at-large concerning the current state of funding in service-oriented laboratories. Questions pertained to services offered, cost recovery, capital equipment funding, and future outlook. The web-based survey, available for 3 weeks, achieved participation from 209 respondents in 13 countries, 77% of which represented academic laboratories. Most respondents (75%) direc...

  1. Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor (IRIS)

    OpenAIRE

    Carlos A Lopez; George G Daaboul; Ahn, Sunmin; Reddington, Alexander P.; Monroe, Margo R.; Zhang, Xirui; Irani, Rostem J.; Yu, Chunxiao; Genco, Caroline A.; Cretich, Marina; Chiari, Marcella; Goldberg, Bennett B.; Connor, John H.; Ünlü, M. Selim

    2011-01-01

    The sensitive measurement of biomolecular interactions has use in many fields and industries such as basic biology and microbiology, environmental/agricultural/biodefense monitoring, nanobiotechnology, and more. For diagnostic applications, monitoring (detecting) the presence, absence, or abnormal expression of targeted proteomic or genomic biomarkers found in patient samples can be used to determine treatment approaches or therapy efficacy. In the research arena, information on molecular aff...

  2. Dynamic Presentation of Immobilized Ligands Regulated through Biomolecular Recognition

    OpenAIRE

    Liu, Bo; Liu, Yang; Riesberg, Jeremiah J.; Shen, Wei

    2010-01-01

    To mimic the dynamic regulation of signaling ligands immobilized on extracellular matrices or on the surfaces of neighboring cells for guidance of cell behavior and fate selection, we have harnessed biomolecular recognition in combination with polymer engineering to create dynamic surfaces on which the accessibility of immobilized ligands to cell surface receptors can be reversibly interconverted under physiological conditions. The cell-adhesive RGD peptide is chosen as a model ligand. RGD is...

  3. Interfacial reaction of silver ultra-thin film deposited on interpenetrating polymer network substrate by liquor-phase reduction

    International Nuclear Information System (INIS)

    The interfacial reaction, metal transformations, and nonmetal bond types of silver ultra-thin film deposited on polyurethane (PU) based interpenetrating polymer networks (IPN) substrate by the liquor-phase reduction at room temperatures were studied by atomic force microscope (AFM), X-ray photoelectron spectroscopy (XPS) and attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR). The IPN substrate was prepared by dip-pulling precursors onto a silicon wafer or a glass plate, followed by solidification at room temperature. The interpenetrate structures of IPN with two crosslinked networks restricted the aggregation of silver during the reduction and deposition. The devised -OH terminal group in PU simplified the determination of reactive site in IPN and reinforced the adhesion between IPN and silver through interfacial reaction. The XPS results, which matched well with the ATR-FTIR results, verified the chemical reactive site of PU in IPN with silver in the oxide state.

  4. Interfacial reaction of silver ultra-thin film deposited on interpenetrating polymer network substrate by liquor-phase reduction

    Energy Technology Data Exchange (ETDEWEB)

    Tang Dongyan, E-mail: dytang@hit.edu.cn [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China); Guo Yudi [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China); Zhang Xiaohong [College of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150001 (China); Yin Yuelong [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China)

    2010-08-01

    The interfacial reaction, metal transformations, and nonmetal bond types of silver ultra-thin film deposited on polyurethane (PU) based interpenetrating polymer networks (IPN) substrate by the liquor-phase reduction at room temperatures were studied by atomic force microscope (AFM), X-ray photoelectron spectroscopy (XPS) and attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR). The IPN substrate was prepared by dip-pulling precursors onto a silicon wafer or a glass plate, followed by solidification at room temperature. The interpenetrate structures of IPN with two crosslinked networks restricted the aggregation of silver during the reduction and deposition. The devised -OH terminal group in PU simplified the determination of reactive site in IPN and reinforced the adhesion between IPN and silver through interfacial reaction. The XPS results, which matched well with the ATR-FTIR results, verified the chemical reactive site of PU in IPN with silver in the oxide state.

  5. Portable, On-Demand Biomolecular Manufacturing.

    Science.gov (United States)

    Pardee, Keith; Slomovic, Shimyn; Nguyen, Peter Q; Lee, Jeong Wook; Donghia, Nina; Burrill, Devin; Ferrante, Tom; McSorley, Fern R; Furuta, Yoshikazu; Vernet, Andyna; Lewandowski, Michael; Boddy, Christopher N; Joshi, Neel S; Collins, James J

    2016-09-22

    Synthetic biology uses living cells as molecular foundries for the biosynthesis of drugs, therapeutic proteins, and other commodities. However, the need for specialized equipment and refrigeration for production and distribution poses a challenge for the delivery of these technologies to the field and to low-resource areas. Here, we present a portable platform that provides the means for on-site, on-demand manufacturing of therapeutics and biomolecules. This flexible system is based on reaction pellets composed of freeze-dried, cell-free transcription and translation machinery, which can be easily hydrated and utilized for biosynthesis through the addition of DNA encoding the desired output. We demonstrate this approach with the manufacture and functional validation of antimicrobial peptides and vaccines and present combinatorial methods for the production of antibody conjugates and small molecules. This synthetic biology platform resolves important practical limitations in the production and distribution of therapeutics and molecular tools, both to the developed and developing world. PMID:27662092

  6. Weber's law for biological responses in autocatalytic networks of chemical reactions.

    Science.gov (United States)

    Inoue, Masayo; Kaneko, Kunihiko

    2011-07-22

    Biological responses often obey Weber's law, according to which the magnitude of the response depends only on the fold change in the external input. In this study, we demonstrate that a system involving a simple autocatalytic reaction shows such a response when a chemical is slowly synthesized by the reaction from a faster influx process. We also show that an autocatalytic reaction process occurring in series or in parallel can obey Weber's law with an oscillatory adaptive response. Considering the simplicity and ubiquity of the autocatalytic process, our proposed mechanism is thought to be commonly observed in biological reactions. PMID:21867048

  7. Characterizing and prototyping genetic networks with cell-free transcription-translation reactions.

    Science.gov (United States)

    Takahashi, Melissa K; Hayes, Clarmyra A; Chappell, James; Sun, Zachary Z; Murray, Richard M; Noireaux, Vincent; Lucks, Julius B

    2015-09-15

    A central goal of synthetic biology is to engineer cellular behavior by engineering synthetic gene networks for a variety of biotechnology and medical applications. The process of engineering gene networks often involves an iterative 'design-build-test' cycle, whereby the parts and connections that make up the network are built, characterized and varied until the desired network function is reached. Many advances have been made in the design and build portions of this cycle. However, the slow process of in vivo characterization of network function often limits the timescale of the testing step. Cell-free transcription-translation (TX-TL) systems offer a simple and fast alternative to performing these characterizations in cells. Here we provide an overview of a cell-free TX-TL system that utilizes the native Escherichia coli TX-TL machinery, thereby allowing a large repertoire of parts and networks to be characterized. As a way to demonstrate the utility of cell-free TX-TL, we illustrate the characterization of two genetic networks: an RNA transcriptional cascade and a protein regulated incoherent feed-forward loop. We also provide guidelines for designing TX-TL experiments to characterize new genetic networks. We end with a discussion of current and emerging applications of cell free systems.

  8. Theoretical models for the emergence of biomolecular homochirality

    Science.gov (United States)

    Walker, Sara Imari

    Little is known about the emergence of life from nonliving precursors. A key missing-piece is the origin of homochirality: nearly all life is characterized by exclusively dextrorotary sugars and levorotary amino acids. The research presented in this thesis addresses the challenge of uncovering mechanisms for chiral symmetry breaking in a prebiotic environment and implications for the origin of life on Earth. Expanding on a well-known model for chiral selection through polymerization, and modeling the spatiotemporal dynamics starting from near-racemic initial conditions, it is demonstrated that the net chirality of molecular building blocks grows with the longest polymer in the reaction network (of length N) with critical behavior for the onset of chiral asymmetry determined by the value of N. This surprising result indicates that significant chiral asymmetry occurs only for systems which permit growth of long polymers. Expanding on this work, the effects of environmental disturbances on the evolution of chirality in prebiotic reaction-diffusion networks are studied via the implementation of a stochastic spatiotemporal Langevin equation. The results show that environmental interactions can have significant impact on the evolution of prebiotic chirality: the history of prebiotic chirality is therefore interwoven with the Earths early environmental history in a mechanism we call punctuated chirality. This result establishes that the onset of homochirality is not an isolated phenomenon: chiral selection must occur in tandem with the transition from chemistry to biology, otherwise the prebiotic soup is unstable to environmental events. Addressing the challenge of understanding the role of chirality in the transition from non-life to life, the diffusive slowdown of reaction networks induced, for example, through tidal cycles or evaporating pools, is modeled. The results of this study demonstrate that such diffusive slowdown leads to the stabilization of homochiral

  9. Resonance Reaction in Diffusion-Influenced Bimolecular Reactions

    CERN Document Server

    Kolb, Jakob J; Dzubiella, Joachim

    2016-01-01

    We investigate the influence of a stochastically fluctuating step-barrier potential on bimolecular reaction rates by exact analytical theory and stochastic simulations. We demonstrate that the system exhibits a new resonant reaction behavior with rate enhancement if an appropriately defined fluctuation decay length is of the order of the system size. Importantly, we find that in the proximity of resonance the standard reciprocal additivity law for diffusion and surface reaction rates is violated due to the dynamical coupling of multiple kinetic processes. Together, these findings may have important repercussions on the correct interpretation of various kinetic reaction problems in complex systems, as, e.g., in biomolecular association or catalysis.

  10. Thermal coupling at aqueous and biomolecular interfaces

    Science.gov (United States)

    Shenogina, Natalia B.

    Heat flow in the materials with nanoscopic features is dominated by thermal properties of the interfaces. While thermal properties of the solid-solid and solid-liquid interfaces are well studied, research of the thermal transport properties across soft (liquid-liquid) interfaces is very limited. Such interfaces are, however, plentiful in biological systems. In such systems the temperature control is of a great importance, because biochemical reactions, conformation of biomolecules as well as processes in biological cells and membranes have strong temperature sensitivity. The critical ingredient to temperature control in biological systems is the understanding of heat flow and thermal coupling across soft interfaces. To investigate heat transfer across biological and aqueous interfaces we chose to study a number of soft interfacial systems by means of molecular dynamic simulations. One of the interfaces under our investigation is the interface between protein (specifically green fluorescent protein) and water. Using this model we concentrated on the importance of vibrational frequency on coupling between water and proteins, and on significant differences between the roles of low and high frequency vibrations. Our thermal interfacial analysis allowed us to shed new light on to the issue of protein to water slaving, i.e., the concept of water controlling protein dynamics. Considering that the surface of the protein is composed of a complicated mixture of the hydrophobic and hydrophilic domains, to systematically explore the role of interfacial interactions we studied less complicated models with homogenous interfaces whith interfacial chemistry that could be changed in a controlled manner. We demonstrated that thermal transport measurements can be used to probe interfacial environments and to quantify interfacial bonding strength. Such ability provides a unique opportunity to characterize a variety of interfaces, which can be difficult to achieve with more direct

  11. Modeling dual-scale epidemic dynamics on complex networks with reaction diffusion processes

    Institute of Scientific and Technical Information of China (English)

    Xiao-gang JIN; Yong MIN

    2014-01-01

    The frequent outbreak of severe foodborne diseases (e.g., haemolytic uraemic syndrome and Listeriosis) in 2011 warns of a potential threat that world trade could spread fatal pathogens (e.g., enterohemorrhagic Escherichia coli). The epidemic potential from trade involves both intra-proliferation and inter-diffusion. Here, we present a worldwide vegetable trade network and a stochastic computational model to simulate global trade-mediated epidemics by considering the weighted nodes and edges of the network and the dual-scale dynamics of epidemics. We address two basic issues of network structural impact in global epi-demic patterns:(1) in contrast to the prediction of heterogeneous network models, the broad variability of node degree and edge weights of the vegetable trade network do not determine the threshold of global epidemics;(2) a‘penetration effect’, by which community structures do not restrict propagation at the global scale, quickly facilitates bridging the edges between communities, and leads to synchronized diffusion throughout the entire network. We have also defined an appropriate metric that combines dual-scale behavior and enables quantification of the critical role of bridging edges in disease diffusion from widespread trading. The unusual structure mechanisms of the trade network model may be useful in producing strategies for adaptive immunity and reducing international trade frictions.

  12. Scanning probe and optical tweezer investigations of biomolecular interactions

    Energy Technology Data Exchange (ETDEWEB)

    Rigby-Singleton, Shellie

    2002-07-01

    A complex array of intermolecular forces controls the interactions between and within biological molecules. The desire to empirically explore the fundamental forces has led to the development of several biophysical techniques. Of these, the atomic force microscope (AFM) and the optical tweezers have been employed throughout this thesis to monitor the intermolecular forces involved in biomolecular interactions. The AFM is a well-established force sensing technique capable of measuring biomolecular interactions at a single molecule level. However, its versatility has not been extrapolated to the investigation of a drug-enzyme complex. The energy landscape for the force induced dissociation of the DHFR-methotrexate complex was studied. Revealing an energy barrier to dissociation located {approx}0.3 nm from the bound state. Unfortunately, the AFM has a limited range of accessible loading rates and in order to profile the complete energy landscape alternative force sensing instrumentation should be considered, for example the BFP and optical tweezers. Thus, this thesis outlines the development and construction an optical trap capable of measuring intermolecular forces between biomolecules at the single molecule level. To demonstrate the force sensing abilities of the optical set up, proof of principle measurements were performed which investigate the interactions between proteins and polymer surfaces subjected to varying degrees of argon plasma treatment. Complementary data was gained from measurements performed independently by the AFM. Changes in polymer resistance to proteins as a response to changes in polymer surface chemistry were detected utilising both AFM and optical tweezers measurements. Finally, the AFM and optical tweezers were employed as ultrasensitive biosensors. Single molecule investigations of the antibody-antigen interaction between the cardiac troponin I marker and its complementary antibody, reveals the impact therapeutic concentrations of heparin

  13. Delay-induced Turing-like waves for one-species reaction-diffusion model on a network

    Science.gov (United States)

    Petit, Julien; Carletti, Timoteo; Asllani, Malbor; Fanelli, Duccio

    2015-09-01

    A one-species time-delay reaction-diffusion system defined on a complex network is studied. Traveling waves are predicted to occur following a symmetry-breaking instability of a homogeneous stationary stable solution, subject to an external nonhomogeneous perturbation. These are generalized Turing-like waves that materialize in a single-species populations dynamics model, as the unexpected byproduct of the imposed delay in the diffusion part. Sufficient conditions for the onset of the instability are mathematically provided by performing a linear stability analysis adapted to time-delayed differential equations. The method here developed exploits the properties of the Lambert W-function. The prediction of the theory are confirmed by direct numerical simulation carried out for a modified version of the classical Fisher model, defined on a Watts-Strogatz network and with the inclusion of the delay.

  14. Formulation of a Network and the Study of Reaction Paths for the Sustainable Reduction of CO2 Emissions

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Kongpanna, Pichayapan; Roh, Kosan;

    carbonate (DMC) [2]. In this work, through a computer-aided framework for process network synthesis-design, a network of conversion processes that all use emitted CO2 is investigated. CO2 is emitted into the environment from various sources: power generation, industrial processes, transportation...... and commercial processes. Within these there are high-purity emissions and low-purity emissions. Rather than sending these to the atmosphere, it is possible to collect them and use them for other purposes. Targeting some of the largest contributors: power generation, manufacturing, chemical industry...... through the reactions. Studies and detailed simulations have been performed on CO2 conversion to methanol, synthesis gas processes, dimethyl carbonate production, and other processes. The detailed simulations are performed on the paths that are selected based on basic calculations on each path. Then...

  15. Pattern formation in a two-component reaction-diffusion system with delayed processes on a network

    Science.gov (United States)

    Petit, Julien; Asllani, Malbor; Fanelli, Duccio; Lauwens, Ben; Carletti, Timoteo

    2016-11-01

    Reaction-diffusion systems with time-delay defined on complex networks have been studied in the framework of the emergence of Turing instabilities. The use of the Lambert W-function allowed us to get explicit analytic conditions for the onset of patterns as a function of the main involved parameters, the time-delay, the network topology and the diffusion coefficients. Depending on these parameters, the analysis predicts whether the system will evolve towards a stationary Turing pattern or rather to a wave pattern associated to a Hopf bifurcation. The possible outcomes of the linear analysis overcome the respective limitations of the single-species case with delay, and that of the classical activator-inhibitor variant without delay. Numerical results gained from the Mimura-Murray model support the theoretical approach.

  16. Report on the IAEA technical meeting on co-ordination of the network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    Results of the IAEA Technical Meeting on the Co-ordination of the Network of Nuclear Reaction Data Centres held at the IAEA Headquarters, Vienna, Austria, 17 to 19 June 2003, are summarised in this report. The meeting was attended by 14 participants from 9 cooperating data centres of five member states and two International Organizations. A meeting summary, the conclusions and actions, progress and status reports of the participating data centres, and working papers considered at the meeting, are given in the relevant sections. (author)

  17. Sign conditions for injectivity of generalized polynomial maps with applications to chemical reaction networks and real algebraic geometry

    DEFF Research Database (Denmark)

    Müller, Stefan; Feliu, Elisenda; Regensburger, Georg;

    2016-01-01

    We give necessary and sufficient conditions in terms of sign vectors for the injectivity of families of polynomials maps with arbitrary real exponents defined on the positive orthant. Our work relates and extends existing injectivity conditions expressed in terms of Jacobian matrices and determin...... and determinants. In the context of chemical reaction networks with power-law kinetics, our results can be used to preclude as well as to guarantee multiple positive steady states. In the context of real algebraic geometry, our results reveal the first ...

  18. A ladder network modelling the electrochemical impedance of the diffusion and reaction processes in semi-infinite space.

    Science.gov (United States)

    Moya, A A

    2016-02-01

    The Gerischer impedance, i.e., the diffusion-reaction impedance of an ionic species in semi-infinite space, has been modelled by means of a novel simple equivalent ladder electric circuit constituted by a finite number of resistors and capacitors, which corresponds to the Cauer structure obtained from development into continued fractions. The Nyquist plots of the impedance of the ladder network or Cauer circuit and the deviation with respect to the Gerischer impedance have been originally analysed as a function of the number of circuit elements. From the Cauer equivalent circuit, a new and simple expression modelling the Gerischer impedance at the limit of the lowest frequencies has been derived.

  19. MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

    Science.gov (United States)

    Vergara-Perez, Sandra; Marucho, Marcelo

    2016-01-01

    One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

  20. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    Science.gov (United States)

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying

    2011-06-01

    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  1. A palladium-doped ceria@carbon core-sheath nanowire network: a promising catalyst support for alcohol electrooxidation reactions

    Science.gov (United States)

    Tan, Qiang; Du, Chunyu; Sun, Yongrong; Du, Lei; Yin, Geping; Gao, Yunzhi

    2015-08-01

    A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells.A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique

  2. Combined Geometric and Neural Network Approach to Generic Fault Diagnosis in Satellite Reaction Wheels

    DEFF Research Database (Denmark)

    Baldi, P.; Blanke, Mogens; Castaldi, P.;

    2015-01-01

    to allow design of generalized fault estimation filters, which do not need a priori information about the faults internal model. Simulation results with a detailed nonlinear spacecraft model, which includes disturbances, show that the proposed diagnosis scheme can deal with faults affecting both reaction......This paper suggests a novel diagnosis scheme for detection, isolation and estimation of faults affecting satellite reaction wheels. Both spin rate measurements and actuation torque defects are dealt with. The proposed system consists of a fault detection and isolation module composed by a bank...

  3. Molecular Dynamics Simulations of Polymer Networks Undergoing Sequential Cross-Linking and Scission Reactions

    DEFF Research Database (Denmark)

    Rottach, Dana R.; Curro, John G.; Budzien, Joanne;

    2007-01-01

    , a fraction (quantified by the stress transfer function gif" border="0">) of the second-stage cross-links contribute to the effective first-stage cross-link density. The stress transfer functions extracted from the MD simulations of the reacting networks are found to be in very...

  4. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    Science.gov (United States)

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M.

    2016-01-01

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.

  5. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    Energy Technology Data Exchange (ETDEWEB)

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M., E-mail: abel@utk.edu [Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996 (United States)

    2016-01-07

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.

  6. Automatic reaction to a chemical event detected by a low-cost wireless chemical sensing network

    OpenAIRE

    Beirne, Stephen; Lau, King-Tong; Corcoran, Brian; Diamond, Dermot

    2009-01-01

    A test-scale wireless chemical sensor network (WCSN) has been deployed within a controlled Environmental Chamber (EC). The combined signals from the WCSN were used to initiate a controllable response to the detected chemical event. When a particular sensor response pattern was obtained, a purging cycle was initiated. Sensor data were continuously checked against user-defined action limits, to determine if a chemical event had occurred. An acidic contaminant was used to demonstrate the respons...

  7. Systematic evaluation of bundled SPC water for biomolecular simulations.

    Science.gov (United States)

    Gopal, Srinivasa M; Kuhn, Alexander B; Schäfer, Lars V

    2015-04-01

    In bundled SPC water models, the relative motion of groups of four water molecules is restrained by distance-dependent potentials. Bundled SPC models have been used in hybrid all-atom/coarse-grained (AA/CG) multiscale simulations, since they enable to couple atomistic SPC water with supra-molecular CG water models that effectively represent more than a single water molecule. In the present work, we systematically validated and critically tested bundled SPC water models as solvent for biomolecular simulations. To that aim, we investigated both thermodynamic and structural properties of various biomolecular systems through molecular dynamics (MD) simulations. Potentials of mean force of dimerization of pairs of amino acid side chains as well as hydration free energies of single side chains obtained with bundled SPC and standard (unrestrained) SPC water agree closely with each other and with experimental data. Decomposition of the hydration free energies into enthalpic and entropic contributions reveals that in bundled SPC, this favorable agreement of the free energies is due to a larger degree of error compensation between hydration enthalpy and entropy. The Ramachandran maps of Ala3, Ala5, and Ala7 peptides are similar in bundled and unrestrained SPC, whereas for the (GS)2 peptide, bundled water leads to a slight overpopulation of extended conformations. Analysis of the end-to-end distance autocorrelation times of the Ala5 and (GS)2 peptides shows that sampling in more viscous bundled SPC water is about two times slower. Pronounced differences between the water models were found for the structure of a coiled-coil dimer, which is instable in bundled SPC but not in standard SPC. In addition, the hydration of the active site of the serine protease α-chymotrypsin depends on the water model. Bundled SPC leads to an increased hydration of the active site region, more hydrogen bonds between water and catalytic triad residues, and a significantly slower exchange of water

  8. Gait Phases Recognition from Accelerations and Ground Reaction Forces: Application of Neural Networks

    Directory of Open Access Journals (Sweden)

    S. Rafajlović

    2009-06-01

    Full Text Available The goal of this study was to test the applicability of accelerometer as the sensor for assessment of the walking. We present here the comparison of gait phases detected from the data recorded by force sensing resistors mounted in the shoe insoles, non-processed acceleration and processed acceleration perpendicular to the direction of the foot. The gait phases in all three cases were detected by means of a neural network. The output from the neural network was the gait phase, while the inputs were data from the sensors. The results show that the errors were in the ranges: 30 ms (2.7% – force sensors; 150 ms (13.6% – nonprocessed acceleration, and 120 ms (11% – processed acceleration data. This result suggests that it is possible to use the accelerometer as the gait phase detector, however, with the knowledge that the gait phases are time shifted for about 100 ms with respect the neural network predicted times.

  9. Reproduction of a Protocell by Replication of Minority Molecule in Catalytic Reaction Network

    OpenAIRE

    Kamimura, Atsushi; Kaneko, Kunihiko

    2010-01-01

    For understanding the origin of life, it is essential to explain the development of a compartmentalized structure, which undergoes growth and division, from a set of chemical reactions. In this study, a hypercycle with two chemicals that mutually catalyze each other is considered in order to show that the reproduction of a protocell with a growth-division process naturally occurs when the replication speed of one chemical is considerably slower than that of the other chemical. It is observed ...

  10. Compartmentalization and Cell Division through Molecular Discreteness and Crowding in a Catalytic Reaction Network

    OpenAIRE

    Atsushi Kamimura; Kunihiko Kaneko

    2014-01-01

    Explanation of the emergence of primitive cellular structures from a set of chemical reactions is necessary to unveil the origin of life and to experimentally synthesize protocells. By simulating a cellular automaton model with a two-species hypercycle, we demonstrate the reproduction of a localized cluster; that is, a protocell with a growth-division process emerges when the replication and degradation speeds of one species are respectively slower than those of the other species, because of ...

  11. Stochastic innovation as a mechanism by which catalysts might self-assemble into chemical reaction networks

    OpenAIRE

    Bradford, Justin A; Dill, Ken A.

    2007-01-01

    We develop a computer model for how two different chemical catalysts in solution, A and B, could be driven to form AB complexes, based on the concentration gradients of a substrate or product that they share in common. If A's product is B's substrate, B will be attracted to A, mediated by a common resource that is not otherwise plentiful in the environment. By this simple physicochemical mechanism, chemical reactions could spontaneously associate to become chained together in solution. Accord...

  12. Stochastic focusing coupled with negative feedback enables robust regulation in biochemical reaction networks.

    Science.gov (United States)

    Milias-Argeitis, Andreas; Engblom, Stefan; Bauer, Pavol; Khammash, Mustafa

    2015-12-01

    Nature presents multiple intriguing examples of processes that proceed with high precision and regularity. This remarkable stability is frequently counter to modellers' experience with the inherent stochasticity of chemical reactions in the regime of low-copy numbers. Moreover, the effects of noise and nonlinearities can lead to 'counterintuitive' behaviour, as demonstrated for a basic enzymatic reaction scheme that can display stochastic focusing (SF). Under the assumption of rapid signal fluctuations, SF has been shown to convert a graded response into a threshold mechanism, thus attenuating the detrimental effects of signal noise. However, when the rapid fluctuation assumption is violated, this gain in sensitivity is generally obtained at the cost of very large product variance, and this unpredictable behaviour may be one possible explanation of why, more than a decade after its introduction, SF has still not been observed in real biochemical systems. In this work, we explore the noise properties of a simple enzymatic reaction mechanism with a small and fluctuating number of active enzymes that behaves as a high-gain, noisy amplifier due to SF caused by slow enzyme fluctuations. We then show that the inclusion of a plausible negative feedback mechanism turns the system from a noisy signal detector to a strong homeostatic mechanism by exchanging high gain with strong attenuation in output noise and robustness to parameter variations. Moreover, we observe that the discrepancy between deterministic and stochastic descriptions of stochastically focused systems in the evolution of the means almost completely disappears, despite very low molecule counts and the additional nonlinearity due to feedback. The reaction mechanism considered here can provide a possible resolution to the apparent conflict between intrinsic noise and high precision in critical intracellular processes. PMID:26609065

  13. Effect of gel network on pattern formation in the ferrocyanide-iodate-sulfite reaction.

    Science.gov (United States)

    Ueno, Tomonaga; Yoshida, Ryo

    2011-06-01

    Stationary patterns have been researched experimentally since the discovery of the Turing pattern in the chlorite-iodide-malonic acid (CIMA) reaction and the self-replicating spot pattern in the ferrocyanide-iodate-sulfite (FIS) reaction. In this study, we reproduced the pattern formation in the FIS reaction by using poly(acrylamide) gels. Gels with different swelling ratios were prepared to use as a medium. The effect of the swelling ratio was compared with the effect of thickness. It was found that the swelling ratio greatly influenced pattern formation. Oscillating spot patterns appeared at high swelling ratios, and lamellar patterns appeared at a low swelling ratio. Self-replicating spot patterns appeared in between the two areas. The front velocities, which were observed in the initial stage of pattern formation, depended on the swelling ratio. Furthermore, this dependence obeys the free volume theory of diffusion. These results provide evidence that the change in front velocities is caused by a change in diffusion. Pattern formation can be controlled not only by thickness but also by swelling ratio, which may be useful for creating novel pattern templates. PMID:21557556

  14. The biomolecular corona of nanoparticles in circulating biological media

    Science.gov (United States)

    Pozzi, D.; Caracciolo, G.; Digiacomo, L.; Colapicchioni, V.; Palchetti, S.; Capriotti, A. L.; Cavaliere, C.; Zenezini Chiozzi, R.; Puglisi, A.; Laganà, A.

    2015-08-01

    When nanoparticles come into contact with biological media, they are covered by a biomolecular `corona', which confers a new identity to the particles. In all the studies reported so far nanoparticles are incubated with isolated plasma or serum that are used as a model for protein adsorption. Anyway, bodily fluids are dynamic in nature so the question arises on whether the incubation protocol, i.e. dynamic vs. static incubation, could affect the composition and structure of the biomolecular corona. Here we let multicomponent liposomes interact with fetal bovine serum (FBS) both statically and dynamically, i.e. in contact with circulating FBS (~40 cm s-1). The structure and composition of the liposome-protein corona, as determined by dynamic light scattering, electrophoretic light scattering and liquid chromatography tandem mass spectrometry, were found to be dependent on the incubation protocol. Specifically, following dynamic exposure to FBS, multicomponent liposomes were less enriched in complement proteins and appreciably more enriched in apolipoproteins and acute phase proteins (e.g. alpha-1-antitrypsin and inter-alpha-trypsin inhibitor heavy chain H3) that are involved in relevant interactions between nanoparticles and living systems. Supported by our results, we speculate that efficient predictive modeling of nanoparticle behavior in vivo will require accurate knowledge of nanoparticle-specific protein fingerprints in circulating biological media.When nanoparticles come into contact with biological media, they are covered by a biomolecular `corona', which confers a new identity to the particles. In all the studies reported so far nanoparticles are incubated with isolated plasma or serum that are used as a model for protein adsorption. Anyway, bodily fluids are dynamic in nature so the question arises on whether the incubation protocol, i.e. dynamic vs. static incubation, could affect the composition and structure of the biomolecular corona. Here we let

  15. Biomolecular Simulation of Base Excision Repair and Protein Signaling

    Energy Technology Data Exchange (ETDEWEB)

    Straatsma, TP; McCammon, J A; Miller, John H; Smith, Paul E; Vorpagel, Erich R; Wong, Chung F; Zacharias, Martin W

    2006-03-03

    The goal of the Biomolecular Simulation of Base Excision Repair and Protein Signaling project is to enhance our understanding of the mechanism of human polymerase-β, one of the key enzymes in base excision repair (BER) and the cell-signaling enzymes cyclic-AMP-dependent protein kinase. This work used molecular modeling and simulation studies to specifically focus on the • dynamics of DNA and damaged DNA • dynamics and energetics of base flipping in DNA • mechanism and fidelity of nucleotide insertion by BER enzyme human polymerase-β • mechanism and inhibitor design for cyclic-AMP-dependent protein kinase. Molecular dynamics simulations and electronic structure calculations have been performed using the computer resources at the Molecular Science Computing Facility at the Environmental Molecular Sciences Laboratory.

  16. Insights into cancer severity from biomolecular interaction mechanisms

    Science.gov (United States)

    Raimondi, Francesco; Singh, Gurdeep; Betts, Matthew J.; Apic, Gordana; Vukotic, Ranka; Andreone, Pietro; Stein, Lincoln; Russell, Robert B.

    2016-01-01

    To attain a deeper understanding of diseases like cancer, it is critical to couple genetics with biomolecular mechanisms. High-throughput sequencing has identified thousands of somatic mutations across dozens of cancers, and there is a pressing need to identify the few that are pathologically relevant. Here we use protein structure and interaction data to interrogate nonsynonymous somatic cancer mutations, identifying a set of 213 molecular interfaces (protein-protein, -small molecule or –nucleic acid) most often perturbed in cancer, highlighting several potentially novel cancer genes. Over half of these interfaces involve protein-small-molecule interactions highlighting their overall importance in cancer. We found distinct differences in the predominance of perturbed interfaces between cancers and histological subtypes and presence or absence of certain interfaces appears to correlate with cancer severity. PMID:27698488

  17. Simulation of Parallel Logical Operations with Biomolecular Computing

    Directory of Open Access Journals (Sweden)

    Mahnaz Kadkhoda

    2008-01-01

    Full Text Available Biomolecular computing is the computational method that uses the potential of DNA as a parallel computing device. DNA computing can be used to solve NP-complete problems. An appropriate application of DNA computation is large-scale evaluation of parallel computation models such as Boolean Circuits. In this study, we present a molecular-based algorithm for evaluation of Nand-based Boolean Circuits. The contribution of this paper is that the proposed algorithm has been implemented using only three molecular operations and the number of passes in each level is decreased to less than half of previously addressed in the literature. Thus, the proposed algorithm is much easier to implement in the laboratory.

  18. Structure and Interactions of Isolated Biomolecular Building Blocks.

    Science.gov (United States)

    de Vries, Mattanjah

    2006-03-01

    We investigate biomolecular building blocks and their clusters with each other and with water on a single molecular level. The motivation is the need to distinguish between intrinsic molecular properties and those that result from the biological environment. This is achieved by a combination of laser desorption and jet cooling, applied to aromatic amino acids, small peptides containing those, nucleobases and nucleosides. This approach is coupled with a number of laser spectroscopic techniques, including resonant multi-photon ionization, spectral hole burning and infra-red ion-dip spectroscopy. We will discuss examples illustrating how information can be obtained on spatial structure of individual biomolecules, including peptide conformations and details of DNA base-pairing.

  19. Perspective: Markov Models for Long-Timescale Biomolecular Dynamics

    CERN Document Server

    Schwantes, Christian R; Pande, Vijay S

    2014-01-01

    Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

  20. EVA reactive blending with Si-H terminated polysiloxane by carbonyl hydrosilylation reaction: From compatibilised blends to crosslinking networks

    Energy Technology Data Exchange (ETDEWEB)

    Bonnet, J.; Bounor-Legare, V.; Alcouffe, P. [Universite de Lyon, 69003 Lyon (France); Universite de Lyon 1, CNRS UMR5223, Ingenierie des Materiaux Polymeres, 15 Boulevard Latarjet, F-69622 Villeurbanne (France); Cassagnau, P., E-mail: philippe.cassagnau@univ-lyon1.fr [Universite de Lyon, 69003 Lyon (France); Universite de Lyon 1, CNRS UMR5223, Ingenierie des Materiaux Polymeres, 15 Boulevard Latarjet, F-69622 Villeurbanne (France)

    2012-10-15

    A new and original method based on carbonyl hydrosilylation was developed to prepare ethylene-vinyl acetate (EVA)/polysiloxane polymer blends. This focused on the addition of hydrogenosilane groups (SiH) from polysiloxane to the carbonyl groups of EVA. The influence of the nature of the polysiloxane on blend properties was investigated by rheology and scanning electron microscopy. Mixing of a low viscosity polysiloxane with a high viscosity EVA matrix produced a two-phase morphology. The occurrence of the hydrosilylation reaction at the EVA/polysiloxane interface promoted a homogenisation of the blend depending on the molar ratio SiH/vinyl acetate groups, [SiH]/[VA], and the viscosity ratio of the blend. Two distinct behaviours were observed. The formation of a crosslinked network under shear was obtained for a low viscosity ratio between polysiloxane and EVA ({lambda}{sub polysiloxane/EVA} = 4.0 Multiplication-Sign 10{sup -6}) with a high concentration of SiH groups ([SiH]/[VA] = 0.5), while the formation of a compatibilised blend was observed for high molar mass polysiloxanes (Mn > 15,000 g mol{sup -1}) with a low concentration of SiH ([SiH]/[VA] < 4.0 Multiplication-Sign 10{sup -3}). -- Highlights: Black-Right-Pointing-Pointer Carbonyl hydrosilylation reaction was found to enhance EVA/polysiloxane immiscible blends. Black-Right-Pointing-Pointer EVA crosslinking was obtained with a low molar mass polysiloxane. Black-Right-Pointing-Pointer EVA compatibilisation was obtained with a high molar mass polysiloxane. Black-Right-Pointing-Pointer Shear rate was found to improve the hydrosilylation reaction at the interface. Black-Right-Pointing-Pointer A two-phase morphology of the blends was observed after reaction with fine polysiloxane nodules.

  1. A ladder network modelling the electrochemical impedance of the diffusion and reaction processes in semi-infinite space.

    Science.gov (United States)

    Moya, A A

    2016-02-01

    The Gerischer impedance, i.e., the diffusion-reaction impedance of an ionic species in semi-infinite space, has been modelled by means of a novel simple equivalent ladder electric circuit constituted by a finite number of resistors and capacitors, which corresponds to the Cauer structure obtained from development into continued fractions. The Nyquist plots of the impedance of the ladder network or Cauer circuit and the deviation with respect to the Gerischer impedance have been originally analysed as a function of the number of circuit elements. From the Cauer equivalent circuit, a new and simple expression modelling the Gerischer impedance at the limit of the lowest frequencies has been derived. PMID:26763107

  2. Global exponential stability of reaction-diffusion neural networks with discrete and distributed time-varying delays

    Institute of Scientific and Technical Information of China (English)

    Zhang Wei-Yuan; Li Jun-Min

    2011-01-01

    This paper investigates the global exponential stability of reaction-diffusion neural networks with discrete and distributed time-varying delays. By constructing a more general type of Lyapunov-Krasovskii functional combined with a free-weighting matrix approach and analysis techniques, delay-dependent exponential stability criteria are derived in the form of linear matrix inequalities. The obtained results are dependent on the size of the time-varying delays and the measure of the space, which are usually less conservative than delay-independent and space-independent ones. These results are easy to check, and improve upon the existing stability results. Some remarks are given to show the advantages of the obtained results over the previous results. A numerical example has been presented to show the usefulness of the derived linear matrix inequality (LMI)-based stability conditions.

  3. Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics

    CERN Document Server

    Hamann, Heiko; Schmickl, Thomas; Crailsheim, Karl

    2010-01-01

    The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modu...

  4. Photochemical Production of Interpenetrating Polymer Networks; Simultaneous Initiation of Radical and Cationic Polymerization Reactions

    Directory of Open Access Journals (Sweden)

    Jean Pierre Fouassier

    2014-10-01

    Full Text Available In this paper, we propose to review the ways to produce, through photopolymerization, interpenetrating polymer networks (IPN based, e.g., on acrylate/epoxide or acrylate/vinylether blends and to outline the recent developments that allows a one-step procedure (concomitant radical/cationic polymerization, under air or in laminate, under various irradiation conditions (UV/visible/near IR; high/low intensity sources; monochromatic/polychromatic sources; household lamps/laser diodes/Light Emitting Diodes (LEDs. The paper illustrates the encountered mechanisms and the polymerization profiles. A short survey on the available monomer systems and some brief examples of the attained final properties of the IPNs is also provided.

  5. Model reduction and parameter estimation of non-linear dynamical biochemical reaction networks.

    Science.gov (United States)

    Sun, Xiaodian; Medvedovic, Mario

    2016-02-01

    Parameter estimation for high dimension complex dynamic system is a hot topic. However, the current statistical model and inference approach is known as a large p small n problem. How to reduce the dimension of the dynamic model and improve the accuracy of estimation is more important. To address this question, the authors take some known parameters and structure of system as priori knowledge and incorporate it into dynamic model. At the same time, they decompose the whole dynamic model into subset network modules, based on different modules, and then they apply different estimation approaches. This technique is called Rao-Blackwellised particle filters decomposition methods. To evaluate the performance of this method, the authors apply it to synthetic data generated from repressilator model and experimental data of the JAK-STAT pathway, but this method can be easily extended to large-scale cases.

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

    Science.gov (United States)

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

    2015-12-15

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

  7. Compartmentalization and Cell Division through Molecular Discreteness and Crowding in a Catalytic Reaction Network

    Directory of Open Access Journals (Sweden)

    Atsushi Kamimura

    2014-10-01

    Full Text Available Explanation of the emergence of primitive cellular structures from a set of chemical reactions is necessary to unveil the origin of life and to experimentally synthesize protocells. By simulating a cellular automaton model with a two-species hypercycle, we demonstrate the reproduction of a localized cluster; that is, a protocell with a growth-division process emerges when the replication and degradation speeds of one species are respectively slower than those of the other species, because of overcrowding of molecules as a natural outcome of the replication. The protocell exhibits synchrony between its division process and replication of the minority molecule. We discuss the effects of the crowding molecule on the formation of primitive structures. The generality of this result is demonstrated through the extension of our model to a hypercycle with three molecular species, where a localized layered structure of molecules continues to divide, triggered by the replication of a minority molecule at the center.

  8. Reproduction of a Protocell by Replication of a Minority Molecule in a Catalytic Reaction Network

    Science.gov (United States)

    Kamimura, Atsushi; Kaneko, Kunihiko

    2010-12-01

    For understanding the origin of life, it is essential to explain the development of a compartmentalized structure, which undergoes growth and division, from a set of chemical reactions. In this study, a hypercycle with two chemicals that mutually catalyze each other is considered in order to show that the reproduction of a protocell with a growth-division process naturally occurs when the replication speed of one chemical is considerably slower than that of the other chemical, and molecules are crowded as a result of replication. It is observed that the protocell divides after a minority molecule is replicated at a slow synthesis rate, and thus, a synchrony between the reproduction of a cell and molecule replication is achieved. The robustness of such protocells against the invasion of parasitic molecules is also demonstrated.

  9. Symmetry breaking in a bulk-surface reaction-diffusion model for signalling networks

    Science.gov (United States)

    Rätz, Andreas; Röger, Matthias

    2014-08-01

    Signalling molecules play an important role for many cellular functions. We investigate here a general system of two membrane reaction-diffusion equations coupled to a diffusion equation inside the cell by a Robin-type boundary condition and a flux term in the membrane equations. A specific model of this form was recently proposed by the authors for the GTPase cycle in cells. We investigate here a putative role of diffusive instabilities in cell polarization. By a linearized stability analysis, we identify two different mechanisms. The first resembles a classical Turing instability for the membrane subsystem and requires (unrealistically) large differences in the lateral diffusion of activator and substrate. On the other hand, the second possibility is induced by the difference in cytosolic and lateral diffusion and appears much more realistic. We complement our theoretical analysis by numerical simulations that confirm the new stability mechanism and allow us to investigate the evolution beyond the regime where the linearization applies.

  10. A coarse-grained model for the simulations of biomolecular interactions in cellular environments

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao, E-mail: yinghao.wu@einstein.yu.edu [Department of Systems and Computational Biology, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Avenue, Bronx, New York 10461 (United States)

    2014-02-07

    The interactions of bio-molecules constitute the key steps of cellular functions. However, in vivo binding properties differ significantly from their in vitro measurements due to the heterogeneity of cellular environments. Here we introduce a coarse-grained model based on rigid-body representation to study how factors such as cellular crowding and membrane confinement affect molecular binding. The macroscopic parameters such as the equilibrium constant and the kinetic rate constant are calibrated by adjusting the microscopic coefficients used in the numerical simulations. By changing these model parameters that are experimentally approachable, we are able to study the kinetic and thermodynamic properties of molecular binding, as well as the effects caused by specific cellular environments. We investigate the volumetric effects of crowded intracellular space on bio-molecular diffusion and diffusion-limited reactions. Furthermore, the binding constants of membrane proteins are currently difficult to measure. We provide quantitative estimations about how the binding of membrane proteins deviates from soluble proteins under different degrees of membrane confinements. The simulation results provide biological insights to the functions of membrane receptors on cell surfaces. Overall, our studies establish a connection between the details of molecular interactions and the heterogeneity of cellular environments.

  11. Computational Recipe for Efficient Description of Large-Scale Conformational Changes in Biomolecular Systems.

    Science.gov (United States)

    Moradi, Mahmoud; Tajkhorshid, Emad

    2014-07-01

    Characterizing large-scale structural transitions in biomolecular systems poses major technical challenges to both experimental and computational approaches. On the computational side, efficient sampling of the configuration space along the transition pathway remains the most daunting challenge. Recognizing this issue, we introduce a knowledge-based computational approach toward describing large-scale conformational transitions using (i) nonequilibrium, driven simulations combined with work measurements and (ii) free energy calculations using empirically optimized biasing protocols. The first part is based on designing mechanistically relevant, system-specific reaction coordinates whose usefulness and applicability in inducing the transition of interest are examined using knowledge-based, qualitative assessments along with nonequilirbrium work measurements which provide an empirical framework for optimizing the biasing protocol. The second part employs the optimized biasing protocol resulting from the first part to initiate free energy calculations and characterize the transition quantitatively. Using a biasing protocol fine-tuned to a particular transition not only improves the accuracy of the resulting free energies but also speeds up the convergence. The efficiency of the sampling will be assessed by employing dimensionality reduction techniques to help detect possible flaws and provide potential improvements in the design of the biasing protocol. Structural transition of a membrane transporter will be used as an example to illustrate the workings of the proposed approach.

  12. Calculating free-energy profiles in biomolecular systems from fast nonequilibrium processes

    Science.gov (United States)

    Forney, Michael W.; Janosi, Lorant; Kosztin, Ioan

    2008-11-01

    Often gaining insight into the functioning of biomolecular systems requires to follow their dynamics along a microscopic reaction coordinate (RC) on a macroscopic time scale, which is beyond the reach of current all atom molecular dynamics (MD) simulations. A practical approach to this inherently multiscale problem is to model the system as a fictitious overdamped Brownian particle that diffuses along the RC in the presence of an effective potential of mean force (PMF) due to the rest of the system. By employing the recently proposed FR method [I. Kosztin , J. Chem. Phys. 124, 064106 (2006)], which requires only a small number of fast nonequilibrium MD simulations of the system in both forward and time reversed directions along the RC, we reconstruct the PMF: (1) of deca-alanine as a function of its end-to-end distance, and (2) that guides the motion of potassium ions through the gramicidin A channel. In both cases the computed PMFs are found to be in good agreement with previous results obtained by different methods. Our approach appears to be about one order of magnitude faster than the other PMF calculation methods and, in addition, it also provides the position-dependent diffusion coefficient along the RC. Thus, the obtained PMF and diffusion coefficient can be used in an overdamped Brownian model to estimate important characteristics of the studied systems, e.g., the mean folding time of the stretched deca-alanine and the mean diffusion time of the potassium ion through gramicidin A.

  13. Calculating free energy profiles in biomolecular systems from fast non-equilibrium processes

    CERN Document Server

    Forney, Michael; Kosztin, Ioan

    2008-01-01

    Often gaining insight into the functioning of biomolecular systems requires to follow their dynamics along a microscopic reaction coordinate (RC) on a macroscopic time scale, which is beyond the reach of current all atom molecular dynamics (MD) simulations. A practical approach to this inherently multiscale problem is to model the system as a fictitious overdamped Brownian particle that diffuses along the RC in the presence of an effective potential of mean force (PMF) due to the rest of the system. By employing the recently proposed FR method [I. Kosztin et al., J. of Chem. Phys. 124, 064106 (2006)], which requires only a small number of fast nonequilibrium MD simulations of the system in both forward and time reversed directions along the RC, we reconstruct the PMF: (1) of deca-alanine as a function of its end-to-end distance, and (2) that guides the motion of potassium ions through the gramicidin A channel. In both cases the computed PMFs are found to be in good agreement with previous results obtained by ...

  14. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  15. On global exponential stability and existence of periodic solutions for BAM neural networks with distributed delays and reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: louxuyang28945@163.com; Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: btcui@sohu.com; Wu Wei [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)

    2008-05-15

    Both exponential stability and existence of periodic solutions are considered for a class of bi-directional associative memory (BAM) neural networks with distributed delays and reaction-diffusion terms by constructing suitable Lyapunov functional and Young inequality technique. The general sufficient conditions are given ensuring the global exponential stability and existence of periodic solutions of BAM neural networks with distributed delays and reaction-diffusion terms. The earlier results are extended and improved, and an illustrative example is given to demonstrate the effectiveness of the results in this paper.

  16. Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

    CERN Document Server

    2014-01-01

    Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

  17. Differential geometry-based solvation and electrolyte transport models for biomolecular modeling: a review

    OpenAIRE

    Wei, Guo Wei; Baker, Nathan A.

    2014-01-01

    This chapter reviews the differential geometry-based solvation and electrolyte transport for biomolecular solvation that have been developed over the past decade. A key component of these methods is the differential geometry of surfaces theory, as applied to the solvent-solute boundary. In these approaches, the solvent-solute boundary is determined by a variational principle that determines the major physical observables of interest, for example, biomolecular surface area, enclosed volume, el...

  18. Levoglucosan formation from crystalline cellulose: importance of a hydrogen bonding network in the reaction.

    Science.gov (United States)

    Hosoya, Takashi; Sakaki, Shigeyoshi

    2013-12-01

    Levoglucosan (1,6-anhydro-β-D-glucopyranose) formation by the thermal degradation of native cellulose was investigated by MP4(SDQ)//DFT(B3LYP) and DFT(M06-2X)//DFT(B3LYP) level computations. The computational results of dimer models lead to the conclusion that the degradation occurs by a concerted mechanism similar to the degradation of methyl β-D-glucoside reported in our previous study. One-chain models of glucose hexamer, in which the interchain hydrogen bonds of real cellulose crystals are absent, do not exhibit the correct reaction behavior of levoglucosan formation; for instance, the activation enthalpy (Ea =≈38 kcal mol(-1) ) is considerably underestimated compared to the experimental value (48-60 kcal mol(-1) ). This problem is solved with the use of two-chain models that contain interchain hydrogen bonds. The theoretical study of this model clearly shows that the degradation of the internal glucosyl residue leads to the formation of a levoglucosan precursor at the chain end and levoglucosan is selectively formed from this levoglucosan end. The calculated Ea (56-62 kcal mol(-1) ) agrees well with the experimental value. The computational results of three-chain models indicate that this degradation occurs selectively on the crystalline surface. All these computational results provide a comprehensive understanding of several experimental facts, the mechanisms of which have not yet been elucidated.

  19. Electron spin and the origin of Bio-homochirality II. Prebiotic inorganic-organic reaction model

    CERN Document Server

    Wang, Wei

    2014-01-01

    The emergence of biomolecular homochirality is a critically important question about life phenomenon and the origins of life. In a previous paper (arXiv:1309.1229), I tentatively put forward a new hypothesis that the emergence of a single chiral form of biomolecules in living organisms is specifically determined by the electron spin state during their enzyme-catalyzed synthesis processes. However, how a homochirality world of biomolecules could have formed in the absence of enzymatic networks before the origins of life remains unanswered. Here I discussed the electron spin properties in Fe3S4, ZnS, and transition metal doped dilute magnetic ZnS, and their possible roles in the prebiotic synthesis of chiral molecules. Since the existence of these minerals in hydrothermal vent systems is matter of fact, the suggested prebiotic inorganic-organic reaction model, if can be experimentally demonstrated, may help explain where and how life originated on early Earth.

  20. Constrained approximation of effective generators for multiscale stochastic reaction networks and application to conditioned path sampling

    Science.gov (United States)

    Cotter, Simon L.

    2016-10-01

    Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement to the constrained approach, which is a method for computing effective dynamics of slowly changing quantities in these systems, but which does not rely on the quasi-steady-state assumption (QSSA). The QSSA can cause errors in the estimation of effective dynamics for systems where the difference in timescales between the "fast" and "slow" variables is not so pronounced. This new application of the constrained approach allows us to compute the effective generator of the slow variables, without the need for expensive stochastic simulations. This is achieved by finding the null space of the generator of the constrained system. For complex systems where this is not possible, or where the constrained subsystem is itself multiscale, the constrained approach can then be applied iteratively. This results in breaking the problem down into finding the solutions to many small eigenvalue problems, which can be efficiently solved using standard methods. Since this methodology does not rely on the quasi steady-state assumption, the effective dynamics that are approximated are highly accurate, and in the case of systems with only monomolecular reactions, are exact. We will demonstrate this with some numerics, and also use the effective generators to sample paths of the slow variables which are conditioned on their endpoints, a task which would be computationally intractable for the generator of the full system.

  1. Bioelectronic Interface Connecting Reversible Logic Gates Based on Enzyme and DNA Reactions.

    Science.gov (United States)

    Guz, Nataliia; Fedotova, Tatiana A; Fratto, Brian E; Schlesinger, Orr; Alfonta, Lital; Kolpashchikov, Dmitry M; Katz, Evgeny

    2016-07-18

    It is believed that connecting biomolecular computation elements in complex networks of communicating molecules may eventually lead to a biocomputer that can be used for diagnostics and/or the cure of physiological and genetic disorders. Here, a bioelectronic interface based on biomolecule-modified electrodes has been designed to bridge reversible enzymatic logic gates with reversible DNA-based logic gates. The enzyme-based Fredkin gate with three input and three output signals was connected to the DNA-based Feynman gate with two input and two output signals-both representing logically reversible computing elements. In the reversible Fredkin gate, the routing of two data signals between two output channels was controlled by the control signal (third channel). The two data output signals generated by the Fredkin gate were directed toward two electrochemical flow cells, responding to the output signals by releasing DNA molecules that serve as the input signals for the next Feynman logic gate based on the DNA reacting cascade, producing, in turn, two final output signals. The Feynman gate operated as the controlled NOT gate (CNOT), where one of the input channels controlled a NOT operation on another channel. Both logic gates represented a highly sophisticated combination of input-controlled signal-routing logic operations, resulting in redirecting chemical signals in different channels and performing orchestrated computing processes. The biomolecular reaction cascade responsible for the signal processing was realized by moving the solution from one reacting cell to another, including the reacting flow cells and electrochemical flow cells, which were organized in a specific network mimicking electronic computing circuitries. The designed system represents the first example of high complexity biocomputing processes integrating enzyme and DNA reactions and performing logically reversible signal processing. PMID:27145731

  2. Bioelectronic Interface Connecting Reversible Logic Gates Based on Enzyme and DNA Reactions.

    Science.gov (United States)

    Guz, Nataliia; Fedotova, Tatiana A; Fratto, Brian E; Schlesinger, Orr; Alfonta, Lital; Kolpashchikov, Dmitry M; Katz, Evgeny

    2016-07-18

    It is believed that connecting biomolecular computation elements in complex networks of communicating molecules may eventually lead to a biocomputer that can be used for diagnostics and/or the cure of physiological and genetic disorders. Here, a bioelectronic interface based on biomolecule-modified electrodes has been designed to bridge reversible enzymatic logic gates with reversible DNA-based logic gates. The enzyme-based Fredkin gate with three input and three output signals was connected to the DNA-based Feynman gate with two input and two output signals-both representing logically reversible computing elements. In the reversible Fredkin gate, the routing of two data signals between two output channels was controlled by the control signal (third channel). The two data output signals generated by the Fredkin gate were directed toward two electrochemical flow cells, responding to the output signals by releasing DNA molecules that serve as the input signals for the next Feynman logic gate based on the DNA reacting cascade, producing, in turn, two final output signals. The Feynman gate operated as the controlled NOT gate (CNOT), where one of the input channels controlled a NOT operation on another channel. Both logic gates represented a highly sophisticated combination of input-controlled signal-routing logic operations, resulting in redirecting chemical signals in different channels and performing orchestrated computing processes. The biomolecular reaction cascade responsible for the signal processing was realized by moving the solution from one reacting cell to another, including the reacting flow cells and electrochemical flow cells, which were organized in a specific network mimicking electronic computing circuitries. The designed system represents the first example of high complexity biocomputing processes integrating enzyme and DNA reactions and performing logically reversible signal processing.

  3. Wind-driven gas networks and star formation in galaxies: reaction-advection hydrodynamic simulations

    Science.gov (United States)

    Chappell, David; Scalo, John

    2001-07-01

    The effects of wind-driven star formation feedback on the spatio-temporal organization of stars and gas in galaxies is studied using two-dimensional intermediate-representational quasi-hydrodynamical simulations. The model retains only a reduced subset of the physics, including mass and momentum conservation, fully non-linear fluid advection, inelastic macroscopic interactions, threshold star formation, and momentum forcing by winds from young star clusters on the surrounding gas. Expanding shells of swept-up gas evolve through the action of fluid advection to form a `turbulent' network of interacting shell fragments which have the overall appearance of a web of filaments (in two dimensions). A new star cluster is formed whenever the column density through a filament exceeds a critical threshold based on the gravitational instability criterion for an expanding shell, which then generates a new expanding shell after some time delay. A filament-finding algorithm is developed to locate the potential sites of new star formation. The major result is the dominance of multiple interactions between advectively distorted shells in controlling the gas and star morphology, gas velocity distribution and mass spectrum of high mass density peaks, and the global star formation history. The gas morphology strongly resembles the model envisioned by Norman & Silk, and observations of gas in the Large Magellanic Cloud (LMC)Q1 and local molecular clouds. The dependence of the frequency distribution of present-to-past average global star formation rate on a number of parameters is investigated. Bursts of star formation only occur when the time-averaged star formation rate per unit area is low, or the system is small. Percolation does not play a role. The broad distribution observed in late-type galaxies can be understood as a result of either small size or small metallicity, resulting in larger shell column densities required for gravitational instability. The star formation rate

  4. Function of Amphiphilic Biomolecular Machines: Elastic Protein-based Polymers

    Science.gov (United States)

    Urry, Dan W.

    2000-03-01

    Elastic protein-based polymers function as biomolecular machines due to inverse temperature transitions of hydrophobic folding and assembly. The transitions occur either on raising the temperature from below to above the transition temperature, Tt, or on isothermally lowering Tt from above to below an operating temperature. The inverse temperature transition involves a decrease in entropy of the polymer component of the system on raising the temperature and a larger increase in solvent entropy on hydrophobic association. Tt depends on the quantity of hydrophobic hydration that undergoes transition to bulk water. Designed amphiphilic polymers perform free energy transductions involving the intensive variables of mechanical force, pressure, temperature, chemical potential, electrochemical potential and electromagnetic radiation and define a set of five axioms for their function as machines. The physical basis for these diverse energy conversions is competition for hydration between apolar (hydrophobic) and polar (e.g., charged) moieties. The effectiveness of these Tt-type entropic elastic protein-based machines is due to repeating peptide sequences that form regular, dynamic repeating structures and exhibit damping of backbone torsional oscillations on extension.

  5. [Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). Implications for pathology].

    Science.gov (United States)

    Viertler, C; Zatloukal, K

    2008-11-01

    High quality human biological samples (e.g. blood, tissue or DNA) with associated, well documented clinical and research data are key resources for advancement of life sciences, biotechnology, clinical medicine, drug development and also molecular pathology. Millions of samples of diseased tissues have been collected in the context of routine histopathological diagnosis and are stored in the archives of hospitals and institutes of pathology. A concerted effort is necessary to overcome the current fragmentation of the European biobanking community in order to tap the full research potential of existing biobanks. A pan-European research infrastructure for biobanking and biomolecular resources (BBMRI) is currently in its planning phase. The mission is to link and provide access to local biobanks of different formats, including tissue collections, harmonize standards, establish operational procedures which properly consider ethical, legal, societal aspects, and to secure sustainable funding. Pathology plays a key role in development and administration of tissue banks and is, thus, a major partner for collaboration, expertise and construction of this pan-European research infrastructure.

  6. A programmable biomolecular computing machine with bacterial phenotype output.

    Science.gov (United States)

    Kossoy, Elizaveta; Lavid, Noa; Soreni-Harari, Michal; Shoham, Yuval; Keinan, Ehud

    2007-07-23

    The main advantage of autonomous biomolecular computing devices over electronic computers is their ability to interact directly with biological systems. No interface is required since all components of molecular computers, including hardware, software, input, and output are molecules that interact in solution along a cascade of programmable chemical events. Here, we demonstrate for the first time that the output of a computation preduced by a molecular finite automaton can be a visible bacterial phenotype. Our 2-symbol-2-state finite automaton utilized linear double-stranded DNA inputs that were prepared by inserting a string of six base pair symbols into the lacZ gene on the pUC18 plasmid. The computation resulted in a circular plasmid that differed from the original pUC18 by either a 9 base pair (accepting state) or 11 base pair insert (unaccepting state) within the lacZ alpha region gene. Upon transformation and expression of the resultant plasmids in E. coli, the accepting state was represented by production of functional beta-galactosidase and formation of blue colonies on X-gal medium. In contrast, the unaccepting state was represented by white colonies due to a shift in the open reading frame of lacZ. PMID:17562552

  7. MOVING OBJECTS TRAJECTOTY PREDICTION BASED ON ARTIFICIAL NEURAL NETWORK APPROXIMATOR BY CONSIDERING INSTANTANEOUS REACTION TIME, CASE STUDY: CAR FOLLOWING

    Directory of Open Access Journals (Sweden)

    M. Poor Arab Moghadam

    2015-12-01

    Full Text Available Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network approximator was used to introduce a trajectory model for vehicle movements. In this regard, the Levenberg-Marquardt back propagation function and the hyperbolic tangent sigmoid function were employed as the training and the transfer functions, respectively. One of the important aspects in identifying driver behavior is the reaction time. This parameter shows the period between the time the driver recognizes a stimulus and the time a suitable response is shown to that stimulus. In this paper, the actual data on car following from the NGSIM project was used to determine the performance of the proposed model. This dataset was used for the purpose of expanding behavioral algorithm in micro simulation. Sixty percent of the data was entered into the designed artificial neural network approximator as the training data, twenty percent as the testing data, and twenty percent as the evaluation data. A statistical and a micro simulation method were employed to show the accuracy of the proposed model. Moreover, the two popular Gipps and Helly models were implemented. Finally, it was shown that the accuracy of the proposed model was much higher - and its computational costs were lower - than those of other models when calibration operations were not performed on these models. Therefore, the proposed model can be used for displaying and predicting trajectories of moving

  8. Moving Objects Trajectoty Prediction Based on Artificial Neural Network Approximator by Considering Instantaneous Reaction Time, Case Study: CAR Following

    Science.gov (United States)

    Poor Arab Moghadam, M.; Pahlavani, P.

    2015-12-01

    Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network approximator was used to introduce a trajectory model for vehicle movements. In this regard, the Levenberg-Marquardt back propagation function and the hyperbolic tangent sigmoid function were employed as the training and the transfer functions, respectively. One of the important aspects in identifying driver behavior is the reaction time. This parameter shows the period between the time the driver recognizes a stimulus and the time a suitable response is shown to that stimulus. In this paper, the actual data on car following from the NGSIM project was used to determine the performance of the proposed model. This dataset was used for the purpose of expanding behavioral algorithm in micro simulation. Sixty percent of the data was entered into the designed artificial neural network approximator as the training data, twenty percent as the testing data, and twenty percent as the evaluation data. A statistical and a micro simulation method were employed to show the accuracy of the proposed model. Moreover, the two popular Gipps and Helly models were implemented. Finally, it was shown that the accuracy of the proposed model was much higher - and its computational costs were lower - than those of other models when calibration operations were not performed on these models. Therefore, the proposed model can be used for displaying and predicting trajectories of moving objects being

  9. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    Science.gov (United States)

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

  10. Electrospun interconnected Fe-N/C nanofiber networks as efficient electrocatalysts for oxygen reduction reaction in acidic media

    Science.gov (United States)

    Wu, Nan; Wang, Yingde; Lei, Yongpeng; Wang, Bing; Han, Cheng; Gou, Yanzi; Shi, Qi; Fang, Dong

    2015-11-01

    One-dimensional electrospun nanofibers have emerged as a potential candidate for high-performance oxygen reduction reaction (ORR) catalysts. However, contact resistance among the neighbouring nanofibers hinders the electron transport. Here, we report the preparation of interconnected Fe-N/C nanofiber networks (Fe-N/C NNs) with low electrical resistance via electrospinning followed by maturing and pyrolysis. The Fe-N/C NNs show excellent ORR activity with onset and half-wave potential of 55 and 108 mV less than those of Pt/C catalyst in 0.5 M H2SO4. Intriguingly, the resulting Fe-N/C NNs exhibit 34% higher peak current density and superior durability than generic Fe-N/C ones with similar microstructure and chemical compositions. Additionally, it also displays much better durability and methanol tolerance than Pt/C catalyst. The higher electroactivity is mainly due to the more effective electron transport between the interconnected nanofibers. Thus, our findings provide a novel insight into the design of functional electrospun nanofibers for the application in energy storage and conversion fields.

  11. Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

    Science.gov (United States)

    Thibault, J C; Roe, D R; Eilbeck, K; Cheatham Iii, T E; Facelli, J C

    2015-01-01

    Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations. PMID:26387907

  12. Biomolecular detection using a metal semiconductor field effect transistor

    Science.gov (United States)

    Estephan, Elias; Saab, Marie-Belle; Buzatu, Petre; Aulombard, Roger; Cuisinier, Frédéric J. G.; Gergely, Csilla; Cloitre, Thierry

    2010-04-01

    In this work, our attention was drawn towards developing affinity-based electrical biosensors, using a MESFET (Metal Semiconductor Field Effect Transistor). Semiconductor (SC) surfaces must be prepared before the incubations with biomolecules. The peptides route was adapted to exceed and bypass the limits revealed by other types of surface modification due to the unwanted unspecific interactions. As these peptides reveal specific recognition of materials, then controlled functionalization can be achieved. Peptides were produced by phage display technology using a library of M13 bacteriophage. After several rounds of bio-panning, the phages presenting affinities for GaAs SC were isolated; the DNA of these specific phages were sequenced, and the peptide with the highest affinity was synthesized and biotinylated. To explore the possibility of electrical detection, the MESFET fabricated with the GaAs SC were used to detect the streptavidin via the biotinylated peptide in the presence of the bovine Serum Albumin. After each surface modification step, the IDS (current between the drain and the source) of the transistor was measured and a decrease in the intensity was detected. Furthermore, fluorescent microscopy was used in order to prove the specificity of this peptide and the specific localisation of biomolecules. In conclusion, the feasibility of producing an electrical biosensor using a MESFET has been demonstrated. Controlled placement, specific localization and detection of biomolecules on a MESFET transistor were achieved without covering the drain and the source. This method of functionalization and detection can be of great utility for biosensing application opening a new way for developing bioFETs (Biomolecular Field-Effect Transistor).

  13. Recent applications of AC electrokinetics in biomolecular analysis on microfluidic devices.

    Science.gov (United States)

    Sasaki, Naoki

    2012-01-01

    AC electrokinetics is a generic term that refers to an induced motion of particles and fluids under nonuniform AC electric fields. The AC electric fields are formed by application of AC voltages to microelectrodes, which can be easily integrated into microfluidic devices by standard microfabrication techniques. Moreover, the magnitude of the motion is large enough to control the mass transfer on the devices. These advantages are attractive for biomolecular analysis on the microfluidic devices, in which the characteristics of small space and microfluidics have been mainly employed. In this review, I describe recent applications of AC electrokinetics in biomolecular analysis on microfluidic devices. The applications include fluid pumping and mixing by AC electrokinetic flow, and manipulation of biomolecules such as DNA and proteins by various AC electrokinetic techniques. Future prospects for highly functional biomolecular analysis on microfluidic devices with the aid of AC electrokinetics are also discussed.

  14. Multiple Features Based Approach to Extract Bio-molecular Event Triggers Using Conditional Random Field

    Directory of Open Access Journals (Sweden)

    Amit Majumder

    2012-11-01

    Full Text Available The purpose of Biomedical Natural Language Processing (BioNLP is to capture biomedical phenomena from textual data by extracting relevant entities, information and relations between biomedical entities (i.e. proteins and genes. In general, in most of the published papers, only binary relations were extracted. In a recent past, the focus is shifted towards extracting more complex relations in the form of bio-molecular events that may include several entities or other relations. In this paper we propose an approach that enables event trigger extraction of relatively complex bio-molecular events. We approach this problem as a detection of bio-molecular event trigger using the well-known algorithm, namely Conditional Random Field (CRF. We apply our experiments on development set. It shows the overall average recall, precision and F-measure values of 64.27504%, 69.97559% and 67.00429%, respectively for the event detection.

  15. Inorganic nanoparticles for the spatial and temporal control of organic reactions: Applications to radical degradation of biopolymer networks

    Science.gov (United States)

    Walker, Joan Marie

    Nanoparticles of gold and iron oxide not only possess remarkable optical and magnetic properties, respectively, but are also capable of influencing their local environment with an astounding degree of precision. Using nanoparticles to direct the reactivity of organic molecules near their surface provides a unique method of spatial and temporal control. Enediynes represent an exceptional class of compounds that are thermally reactive to produce a diradical intermediate via Bergman cycloaromatization. While natural product enediynes are famously cytotoxic, a rich chemistry of synthetic enediynes has developed utilizing creative means to control this reactivity through structure, electronics, metal chelation, and external triggering mechanisms. In a heretofore unexplored arena for Bergman cyclization, we have investigated the reactivity of enediynes in connection with inorganic nanoparticles in which the physical properties of the nanomaterial are directly excited to thermally promote aromatization. As the first example of this methodology, gold nanoparticles conjugated with (Z)-octa-4-en-2,6-diyne-1,8-dithiol were excited with 514 nm laser irradiation. The formation of aromatic and polymeric products was confirmed through Raman spectroscopy and electron microscopy. Water soluble analogues Au-PEG-EDDA and Fe3O4-PEG-EDDA (EDDA = (Z)-octa-4-en-2,6-diyne-1,8-diamine) show similar reactivity under laser irradiation or alternating magnetic field excitation, respectively. Furthermore, we have used these functionalized nanoparticles to attack proteinaceous substrates including fibrin and extracellular matrix proteins, capitalizing on the ability of diradicals to disrupt peptidic bonds. By delivering a locally high payload of reactive molecules and thermal energy to the large biopolymer, network restructuring and collapse is achieved. As a synthetic extension towards multifunctional nanoparticles, noble metal seed-decorated iron oxides have also been prepared and assessed for

  16. Output-input coupling in thermally fluctuating biomolecular machines

    CERN Document Server

    Kurzynski, Michal; Chelminiak, Przemyslaw

    2011-01-01

    Biological molecular machines are proteins that operate under isothermal conditions hence are referred to as free energy transducers. They can be formally considered as enzymes that simultaneously catalyze two chemical reactions: the free energy-donating reaction and the free energy-accepting one. Most if not all biologically active proteins display a slow stochastic dynamics of transitions between a variety of conformational substates composing their native state. In the steady state, this dynamics is characterized by mean first-passage times between transition substates of the catalyzed reactions. On taking advantage of the assumption that each reaction proceeds through a single pair (the gate) of conformational transition substates of the enzyme-substrates complex, analytical formulas were derived for the flux-force dependence of the both reactions, the respective stalling forces and the degree of coupling between the free energy-accepting (output) reaction flux and the free energy-donating (input) one. Th...

  17. iBIOMES: managing and sharing biomolecular simulation data in a distributed environment.

    Science.gov (United States)

    Thibault, Julien C; Facelli, Julio C; Cheatham, Thomas E

    2013-03-25

    Biomolecular simulations, which were once batch queue or compute limited, have now become data analysis and management limited. In this paper we introduce a new management system for large biomolecular simulation and computational chemistry data sets. The system can be easily deployed on distributed servers to create a mini-grid at the researcher's site. The system not only offers a simple data deposition mechanism but also a way to register data into the system without moving the data from their original location. Any registered data set can be searched and downloaded using a set of defined metadata for molecular dynamics and quantum mechanics and visualized through a dynamic Web interface.

  18. The Chemical Master Equation Approach to Nonequilibrium Steady-State of Open Biochemical Systems: Linear Single-Molecule Enzyme Kinetics and Nonlinear Biochemical Reaction Networks

    Directory of Open Access Journals (Sweden)

    Lisa M. Bishop

    2010-09-01

    Full Text Available We develop the stochastic, chemical master equation as a unifying approach to the dynamics of biochemical reaction systems in a mesoscopic volume under a living environment. A living environment provides a continuous chemical energy input that sustains the reaction system in a nonequilibrium steady state with concentration fluctuations. We discuss the linear, unimolecular single-molecule enzyme kinetics, phosphorylation-dephosphorylation cycle (PdPC with bistability, and network exhibiting oscillations. Emphasis is paid to the comparison between the stochastic dynamics and the prediction based on the traditional approach based on the Law of Mass Action. We introduce the difference between nonlinear bistability and stochastic bistability, the latter has no deterministic counterpart. For systems with nonlinear bistability, there are three different time scales: (a individual biochemical reactions, (b nonlinear network dynamics approaching to attractors, and (c cellular evolution. For mesoscopic systems with size of a living cell, dynamics in (a and (c are stochastic while that with (b is dominantly deterministic. Both (b and (c are emergent properties of a dynamic biochemical network; We suggest that the (c is most relevant to major cellular biochemical processes such as epi-genetic regulation, apoptosis, and cancer immunoediting. The cellular evolution proceeds with transitions among the attractors of (b in a “punctuated equilibrium” manner.

  19. The chemical master equation approach to nonequilibrium steady-state of open biochemical systems: linear single-molecule enzyme kinetics and nonlinear biochemical reaction networks.

    Science.gov (United States)

    Qian, Hong; Bishop, Lisa M

    2010-01-01

    We develop the stochastic, chemical master equation as a unifying approach to the dynamics of biochemical reaction systems in a mesoscopic volume under a living environment. A living environment provides a continuous chemical energy input that sustains the reaction system in a nonequilibrium steady state with concentration fluctuations. We discuss the linear, unimolecular single-molecule enzyme kinetics, phosphorylation-dephosphorylation cycle (PdPC) with bistability, and network exhibiting oscillations. Emphasis is paid to the comparison between the stochastic dynamics and the prediction based on the traditional approach based on the Law of Mass Action. We introduce the difference between nonlinear bistability and stochastic bistability, the latter has no deterministic counterpart. For systems with nonlinear bistability, there are three different time scales: (a) individual biochemical reactions, (b) nonlinear network dynamics approaching to attractors, and (c) cellular evolution. For mesoscopic systems with size of a living cell, dynamics in (a) and (c) are stochastic while that with (b) is dominantly deterministic. Both (b) and (c) are emergent properties of a dynamic biochemical network; We suggest that the (c) is most relevant to major cellular biochemical processes such as epi-genetic regulation, apoptosis, and cancer immunoediting. The cellular evolution proceeds with transitions among the attractors of (b) in a "punctuated equilibrium" manner. PMID:20957107

  20. Transition metal bioconjugates with an organometallic link between the metal and the biomolecular scaffold

    OpenAIRE

    Monney, Angèle; Albrecht, Martin

    2013-01-01

    This overview compiles recent advances in the synthesis and application of organometallic bioconjugates that comprise a metal–carbon linkage between the metal and the biomolecular scaffold. This specific area of bioorganometallic chemistry has been spurred by the discovery of naturally occurring bioorganometallic compounds and afforded organometallic bioconjugates from transition metals binding to amino acids, nucleic acids and other biomolecules. These artificial bioorganometallic compounds ...

  1. Conformation of bovine submaxillary mucin layers on hydrophobic surface as studied by biomolecular probes

    DEFF Research Database (Denmark)

    Pakkanen, Kirsi I.; Madsen, Jan Busk; Lee, Seunghwan

    2015-01-01

    In the present study, the conformational changes of bovine submaxillary mucin (BSM) adsorbed on a hydrophobic surface (polystyrene (PS)) as a function of concentration in bulk solution (up to 2mg/mL) have been investigated with biomolecular probe-based approaches, including bicinchoninic acid (BC...

  2. Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

    Science.gov (United States)

    Likic, Vladimir A.

    2006-01-01

    This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

  3. Optical Coherence Tomography and Biomolecular Imaging with Coherent Raman Scattering Microscopy

    DEFF Research Database (Denmark)

    Andersson-Engels, Stefan; Andersen, Peter E.

    2014-01-01

    The Special Section on Selected Topics in Biophotonics: Optical Coherence Tomography and Biomolecular Imaging with Coherent Raman Scattering Microscopy comprises two invited review papers and several contributed papers from the summer school Biophotonics ’13, as well as contributed papers within...

  4. In situ construction of three anion-dependent cu(i) coordination networks as promising heterogeneous catalysts for azide-alkyne "click" reactions.

    Science.gov (United States)

    Xu, Zhenghu; Han, Lu Lu; Zhuang, Gui Lin; Bai, Jing; Sun, Di

    2015-05-18

    Three Cu(I) coordination networks, namely, {[Cu2(bpz)2(CN)X]·CH3CN}n, (X = Cl, 1; I, 3), {[Cu6(bpz)6(CH3CN)3(CN)3Br]·2OH·14CH3CN}n, (2, bpz = 3,3',5,5'-tetramethyl-4,4'-bipyrazole), were prepared by using solvothermal method. The cyanide ligands in these networks were generated in situ by cleavage of C-C bond of MeCN under solvothermal condition. The structures of these networks are dependent on halogen anions. Complex 1 is a ladderlike structure with μ2-CN(-) as rung and μ2-bpz as armrest. The Cl(-) in 1 is at terminal position but does not extend the one-dimensional (1D) ladder to higher dimensionalities. Complex 2 is a three-dimensional (3D) framework comprised of novel planar [Cu3Br] triangle and single Cu nodes, which are extended by μ2-bpz and μ2-CN(-) to form a novel (3,9)-connected gfy network. Density functional theory calculations showed that single-electron delocalization of Br atom induces the plane structure of [Cu3Br]. Complex 3 also possesses a similar ladderlike subunit as in 1, but the I(-) acts as bidentate bridge to extend the ladder to 3D framework with a four-connected sra topology. The three networks show notable catalytic activity on the click reaction. The compared catalytic results demonstrate that complex 2 possesses the best catalysis performance among three complexes, which is ascribed to the largest solvent-accessible void (porosity: 2 (29.4%) > 1 (25.7%) > 3 (17.6%)) and the more Cu(I) active sites in 2. The present combined structure-property studies provide not only a new synthetic route to obtain a new kind of catalyst for click reaction but also the new insights on catalyst structure-function relationships. PMID:25941881

  5. A random walk solution for modeling solute transport with network reactions and multi-rate mass transfer in heterogeneous systems: Impact of biofilms

    Science.gov (United States)

    Henri, Christopher V.; Fernàndez-Garcia, Daniel

    2015-12-01

    The interplay between the spatial variability of the aquifer hydraulic properties, mass transfer due to sub-grid heterogeneity and chemical reactions often complicates reactive transport simulations. It is well documented that hydro-biochemical properties are ubiquitously heterogeneous and that diffusion and slow advection at the sub-grid scale typically leads to the conceptualization of an aquifer as a multi-porosity system. Within this context, chemical reactions taking place in mobile/immobile water regions can be substantially different between each other. This paper presents a particle-based method that can efficiently simulate heterogeneity, network reactions and multi-rate mass transfer. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and mobile/immobile domain at a given time will be transformed into another species and mobile/immobile domain afterwards. The joint effect of mass transfer and sequential degradation is shown to be non-trivial. A characteristic rebound of degradation products can be observed. This late rebound of concentrations is not driven by any change in the flow regime (e.g., pumping ceases in the pump-and-treat remediation strategy) but due to the natural interplay between mass transfer and chemical reactions. To illustrate that the method can simultaneously represent mass transfer, spatially varying properties and network reactions without numerical problems, we have simulated the degradation of tetrachloroethylene (PCE) in a three-dimensional fully heterogeneous aquifer subjected to rate-limited mass transfer. Two types of degradation modes were considered to compare the effect of an active biofilm with that of clay pods present in the aquifer. Results of the two scenarios display significantly differences. Biofilms that promote the degradation of compounds in an immobile region are shown to significantly enhance degradation, rapidly producing

  6. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  7. ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining

    OpenAIRE

    Sivachenko Andrey Y; Huan Tianxiao; Harrison Scott H; Chen Jake Y

    2008-01-01

    Abstract Background New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of c...

  8. Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurodegenerative diseases

    OpenAIRE

    Maia, Pedro D; Kutz, J Nathan

    2016-01-01

    The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurodegenerative diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (...

  9. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; de Fries, Louise Skovlund

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social...

  10. In situ (α-Al2O3+ZrB2)/Al composites with network distribution fabricated by reaction hot pressing

    Institute of Scientific and Technical Information of China (English)

    El Oualid Mokhnache; Gui-song Wang; Lin Geng; Kaveendran Balasubramaniam; Abdelkhalek Henniche; Noureddine Ramdani

    2015-01-01

    In situ (α-Al2O3+ZrB2)/Al composites with network distribution were fabricated using low-energy ball milling and reaction hot pressing. Differential thermal analysis (DTA) was used to study the reaction mechanisms in the Al–ZrO2–B system. X-ray diffraction (XRD) and scanning electron microscopy (SEM) in conjunction with energy-dispersive X-ray spectroscopy (EDX) were used to investigate the composite phases, morphology, and microstructure of the composites. The effect of matrix network size on the microstructure and mechani-cal properties was investigated.The results show that the optimum sintering parameters to complete reactions in the Al–ZrO2–B system are 850℃ and 60 min.In situ-synthesizedα-Al2O3 and ZrB2 particles are dispersed uniformly around Al particles, forming a network micro-structure; the diameters of theα-Al2O3 and ZrB2 particles are approximately 1–3μm. When the size of Al powder increases from 60–110μm to 150–300μm, the overall surface contact between Al powders and reactants decreases, thereby increasing the local volume fraction of re-inforcements from 12% to 21%. This increase of the local volume leads to a significant increase in microhardness of thein situ (α-Al2O3–ZrB2)/Al composites from Hv 163 to Hv 251.

  11. Reactive monolayers for surface gradients and biomolecular patterned interfaces

    NARCIS (Netherlands)

    Nicosia, C.

    2013-01-01

    Self-assembled monolayers (SAMs) are an excellent platform to implement and develop interfacial reactions for the preparation of versatile materials of pivotal importance for the fabrication of, among others, biochips, sensors, catalysts, smart surfaces and electronic devices. The development of met

  12. Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Yong S.; Singh, Rahul; Zhang, Jing; Balasubramanian, Ganesh; Sturgeon, Matthew R.; Katahira, Rui; Chupka, Gina; Beckham, Gregg T.; Shanks, Brent H.

    2016-01-01

    Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation. The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.

  13. Chemical networks*

    OpenAIRE

    Thi Wing-Fai

    2015-01-01

    This chapter discusses the fundamental ideas of how chemical networks are build, their strengths and limitations. The chemical reactions that occur in disks combine the cold phase reactions used to model cold molecular clouds with the hot chemistry applied to planetary atmosphere models. With a general understanding of the different types of reactions that can occur, one can proceed in building a network of chemical reactions and use it to explain the abundance of species seen in disks. One o...

  14. Constructing Bio-molecular Databases on a DNA-based Computer

    CERN Document Server

    Chang, Weng-Long; Ho,; Guo, Minyi

    2007-01-01

    Codd [Codd 1970] wrote the first paper in which the model of a relational database was proposed. Adleman [Adleman 1994] wrote the first paper in which DNA strands in a test tube were used to solve an instance of the Hamiltonian path problem. From [Adleman 1994], it is obviously indicated that for storing information in molecules of DNA allows for an information density of approximately 1 bit per cubic nm (nanometer) and a dramatic improvement over existing storage media such as video tape which store information at a density of approximately 1 bit per 1012 cubic nanometers. This paper demonstrates that biological operations can be applied to construct bio-molecular databases where data records in relational tables are encoded as DNA strands. In order to achieve the goal, DNA algorithms are proposed to perform eight operations of relational algebra (calculus) on bio-molecular relational databases, which include Cartesian product, union, set difference, selection, projection, intersection, join and division. Fu...

  15. PREFACE: India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation

    Science.gov (United States)

    Onoda, Mitsuyoshi; Malhotra, Bansi D.

    2012-04-01

    The 'India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation' (IJWBME 2011) will be held on 7-10 December 2011 at EGRET Himeji, Himeji, Hyogo, Japan. This workshop was held for the first time on 17-19 December 2009 at NPL, New Delhi. Keeping in mind the importance of organic nanotechnology and biomolecular electronics for environmental preservation and their anticipated impact on the economics of both the developing and the developed world, IJWBME 2009 was jointly organized by the Department of Biological Functions, Graduate School of Life Sciences and Systems Engineering, the Kyushu Institute of Technology (KIT), Kitakyushu, Japan, and the Department of Science & Technology Centre on Biomolecular Electronics (DSTCBE), National Physical Laboratory (NPL). Much progress in the field of biomolecular electronics and organic nanotechnology for environmental preservation is expected for the 21st Century. Organic optoelectronic devices, such as organic electroluminescent devices, organic thin-film transistors, organic sensors, biological systems and so on have especially attracted much attention. The main purpose of this workshop is to provide an opportunity for researchers interested in biomolecular electronics and organic nanotechnology for environmental preservation, to come together in an informal and friendly atmosphere and exchange technical knowledge and experience. We are sure that this workshop will be very useful and fruitful for all participants in summarizing the recent progress in biomolecular electronics and organic nanotechnology for environmental preservation and preparing new ground for the next generation. Many papers have been submitted from India and Japan and more than 30 papers have been accepted for presentation. The main topics of interest are as follows: Bioelectronics Biomolecular Electronics Fabrication Techniques Self-assembled Monolayers Nano-sensors Environmental Monitoring Organic Devices

  16. Effect of antibody modifications on its biomolecular binding as determined by surface plasmon resonance.

    Science.gov (United States)

    Vashist, Sandeep Kumar

    2012-02-01

    A surface plasmon resonance (SPR)-based procedure was developed to determine the effect of antibody modifications on its biomolecular binding behavior. Mouse immunoglobulin G (IgG) was immobilized on a protein A-functionalized gold-coated SPR chip. Goat anti-mouse IgG and its various commercially available modifications (i.e., conjugated with atto 550, atto 647, tetramethylrhodamine isothiocyanate [TRITC], horseradish peroxidase [HRP], or biotin) were employed in exactly the same concentration for the detection of mouse IgG. The various modifications of goat anti-mouse IgG decreased its biomolecular binding to mouse IgG in the order of unmodified>HRP-labeled>atto 550-labeled>biotinylated>TRITC-labeled>atto 647-labeled. PMID:22093612

  17. Classification of Modern and Old Río Tinto Sedimentary Deposits Through the Biomolecular Record Using a Life Marker Biochip: Implications for Detecting Life on Mars

    Science.gov (United States)

    Parro, Victor; Fernández-Remolar, David; Rodríguez-Manfredi, José A.; Cruz-Gil, Patricia; Rivas, Luis A.; Ruiz-Bermejo, Marta; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Gómez-Ortiz, David; Blanco-López, Yolanda; Menor-Salván, César; Prieto-Ballesteros, Olga; Gómez-Elvira, Javier

    2011-01-01

    The particular mineralogy formed in the acidic conditions of the Río Tinto has proven to be a first-order analogue for the acid-sulfate aqueous environments of Mars. Therefore, studies about the formation and preservation of biosignatures in the Río Tinto will provide insights into equivalent processes on Mars. We characterized the biomolecular patterns recorded in samples of modern and old fluvial sediments along a segment of the river by means of an antibody microarray containing more than 200 antibodies (LDCHIP200, for Life Detector Chip) against whole microorganisms, universal biomolecules, or environmental extracts. Samples containing 0.3-0.5g of solid material were automatically analyzed in situ by the Signs Of LIfe Detector instrument (SOLID2), and the results were corroborated by extensive analysis in the laboratory. Positive antigen-antibody reactions indicated the presence of microbial strains or high-molecular-weight biopolymers that originated from them. The LDCHIP200 results were quantified and subjected to a multivariate analysis for immunoprofiling. We associated similar immunopatterns, and biomolecular markers, to samples with similar sedimentary age. Phyllosilicate-rich samples from modern fluvial sediments gave strong positive reactions with antibodies against bacteria of the genus Acidithiobacillus and against biochemical extracts from Río Tinto sediments and biofilms. These samples contained high amounts of sugars (mostly polysaccharides) with monosaccharides like glucose, rhamnose, fucose, and so on. By contrast, the older deposits, which are a mix of clastic sands and evaporites, showed only a few positives with LDCHIP200, consistent with lower protein and sugar content. We conclude that LDCHIP200 results can establish a correlation between microenvironments, diagenetic stages, and age with the biomarker profile associated with a sample. Our results would help in the search for putative martian biomarkers in acidic deposits with similar

  18. Classification of modern and old Río Tinto sedimentary deposits through the biomolecular record using a life marker biochip: implications for detecting life on Mars.

    Science.gov (United States)

    Parro, Victor; Fernández-Remolar, David; Rodríguez-Manfredi, José A; Cruz-Gil, Patricia; Rivas, Luis A; Ruiz-Bermejo, Marta; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Gómez-Ortiz, David; Blanco-López, Yolanda; Menor-Salván, César; Prieto-Ballesteros, Olga; Gómez-Elvira, Javier

    2011-01-01

    The particular mineralogy formed in the acidic conditions of the Río Tinto has proven to be a first-order analogue for the acid-sulfate aqueous environments of Mars. Therefore, studies about the formation and preservation of biosignatures in the Río Tinto will provide insights into equivalent processes on Mars. We characterized the biomolecular patterns recorded in samples of modern and old fluvial sediments along a segment of the river by means of an antibody microarray containing more than 200 antibodies (LDCHIP200, for Life Detector Chip) against whole microorganisms, universal biomolecules, or environmental extracts. Samples containing 0.3-0.5 g of solid material were automatically analyzed in situ by the Signs Of LIfe Detector instrument (SOLID2), and the results were corroborated by extensive analysis in the laboratory. Positive antigen-antibody reactions indicated the presence of microbial strains or high-molecular-weight biopolymers that originated from them. The LDCHIP200 results were quantified and subjected to a multivariate analysis for immunoprofiling. We associated similar immunopatterns, and biomolecular markers, to samples with similar sedimentary age. Phyllosilicate-rich samples from modern fluvial sediments gave strong positive reactions with antibodies against bacteria of the genus Acidithiobacillus and against biochemical extracts from Río Tinto sediments and biofilms. These samples contained high amounts of sugars (mostly polysaccharides) with monosaccharides like glucose, rhamnose, fucose, and so on. By contrast, the older deposits, which are a mix of clastic sands and evaporites, showed only a few positives with LDCHIP200, consistent with lower protein and sugar content. We conclude that LDCHIP200 results can establish a correlation between microenvironments, diagenetic stages, and age with the biomarker profile associated with a sample. Our results would help in the search for putative martian biomarkers in acidic deposits with similar

  19. Bridge- and Solvent-Mediated Intramolecular Electronic Communications in Ubiquinone-Based Biomolecular Wires

    OpenAIRE

    Liu, Xiao-Yuan; Ma, Wei; Zhou, Hao; Cao, Xiao-Ming; Long, Yi-Tao

    2015-01-01

    Intramolecular electronic communications of molecular wires play a crucial role for developing molecular devices. In the present work, we describe different degrees of intramolecular electronic communications in the redox processes of three ubiquinone-based biomolecular wires (Bis-CoQ0s) evaluated by electrochemistry and Density Functional Theory (DFT) methods in different solvents. We found that the bridges linkers have a significant effect on the electronic communications between the two pe...

  20. Extension of the GLYCAM06 Biomolecular Force Field to Lipids, Lipid Bilayers and Glycolipids

    OpenAIRE

    Tessier, Matthew B; DeMarco, Mari L.; Yongye, Austin B.; Woods, Robert J.

    2008-01-01

    GLYCAM06 is a generalisable biomolecular force field that is extendible to diverse molecular classes in the spirit of a small-molecule force field. Here we report parameters for lipids, lipid bilayers and glycolipids for use with GLYCAM06. Only three lipid-specific atom types have been introduced, in keeping with the general philosophy of transferable parameter development. Bond stretching, angle bending, and torsional force constants were derived by fitting to quantum mechanical data for a c...

  1. Atomic force microscopy of self-assembled biomolecular structures and their interaction with metallic nanoparticles.

    OpenAIRE

    Gysemans, Maarten

    2009-01-01

    We applied AFM to study biomolecular wires, both out of interest in thei r biological functions and in the framework of nanotechnology based fabr ication. We have focused on two different kinds of protein wires: Insuli n fibrils and microtubules. Microtubules are an important constituent of the cytoskeleton and fulfill multiple vital functions in the cell. Insu lin fibrils on the other hand are amyloid fibrils without a clear biolog ical role, but with intriguing polymerization properties tha...

  2. Assembly of single wall carbon nanotube-metal nanohybrids using biomolecular components

    Science.gov (United States)

    Kim, Sang Nyon; Slocik, Joseph M.; Naik, Rajesh R.

    2010-08-01

    Biomaterials such as nucleic acids and proteins can be exploited to create higher order structures. The biomolecular components such as DNA and peptides have been used to assemble nanoparticles with high fidelity. Here, we use DNA and peptides, and their preferential interaction with inorganic and carbon nanomaterials to form homogeneous hybrids. The enhanced binding of Pt ions to both DNA and peptide functionalized nanoparticles mediates the assembly of carbon nanotubes functionalized with DNA with peptide coated gold nanoparticles.

  3. ssDNA-Functionalized Nanoceria: A Redox-Active Aptaswitch for Biomolecular Recognition.

    Science.gov (United States)

    Bülbül, Gonca; Hayat, Akhtar; Andreescu, Silvana

    2016-04-01

    Quantification of biomolecular binding events is a critical step for the development of biorecognition assays for diagnostics and therapeutic applications. This paper reports the design of redox-active switches based on aptamer conjugated nanoceria for detection and quantification of biomolecular recognition. It is shown that the conformational transition state of the aptamer on nanoceria, combined with the redox properties of these particles can be used to create surface based structure switchable aptasensing platforms. Changes in the redox properties at the nanoceria surface upon binding of the ssDNA and its target analyte enables rapid and highly sensitive measurement of biomolecular interactions. This concept is demonstrated as a general applicable method to the colorimetric detection of DNA binding events. An example of a nanoceria aptaswitch for the colorimetric sensing of Ochratoxin A (OTA) and applicability to other targets is provided. The system can sensitively and selectivity detect as low as 0.15 × 10(-9) m OTA. This novel assay is simple in design and does not involve oligonucleotide labeling or elaborate nanoparticle modification steps. The proposed mechanism discovered here opens up a new way of designing optical sensing methods based on aptamer recognition. This approach can be broadly applicable to many bimolecular recognition processes and related applications. PMID:26844813

  4. Changes in biomolecular profile in a single nucleolus during cell fixation.

    Science.gov (United States)

    Kuzmin, Andrey N; Pliss, Artem; Prasad, Paras N

    2014-11-01

    Fixation of biological sample is an essential technique applied in order to "freeze" in time the intracellular molecular content. However, fixation induces changes of the cellular molecular structure, which mask physiological distribution of biomolecules and bias interpretation of results. Accurate, sensitive, and comprehensive characterization of changes in biomolecular composition, occurring during fixation, is crucial for proper analysis of experimental data. Here we apply biomolecular component analysis for Raman spectra measured in the same nucleoli of HeLa cells before and after fixation by either formaldehyde solution or by chilled ethanol. It is found that fixation in formaldehyde does not strongly affect the Raman spectra of nucleolar biomolecular components, but may significantly decrease the nucleolar RNA concentration. At the same time, ethanol fixation leads to a proportional increase (up to 40%) in concentrations of nucleolar proteins and RNA, most likely due to cell shrinkage occurring in the presence of coagulant fixative. Ethanol fixation also triggers changes in composition of nucleolar proteome, as indicated by an overall reduction of the α-helical structure of proteins and increase in the concentration of proteins containing the β-sheet conformation. We conclude that cross-linking fixation is a more appropriate protocol for mapping of proteins in situ. At the same time, ethanol fixation is preferential for studies of RNA-containing macromolecules. We supplemented our quantitative Raman spectroscopic measurements with mapping of the protein and lipid macromolecular groups in live and fixed cells using coherent anti-Stokes Raman scattering nonlinear optical imaging.

  5. Rational Design of Biomolecular Templates for Synthesizing Multifunctional Noble Metal Nanoclusters toward Personalized Theranostic Applications.

    Science.gov (United States)

    Yu, Yong; Mok, Beverly Y L; Loh, Xian Jun; Tan, Yen Nee

    2016-08-01

    Biomolecule-templated or biotemplated metal nanoclusters (NCs) are ultrasmall (<2 nm) metal (Au, Ag) particles stabilized by a certain type of biomolecular template (e.g., peptides, proteins, and DNA). Due to their unique physiochemical properties, biotemplated metal NCs have been widely used in sensing, imaging, delivery and therapy. The overwhelming applications in these individual areas imply the great promise of harnessing biotemplated metal NCs in more advanced biomedical aspects such as theranostics. Although applications of biotemplated metal NCs as theranostic agents are trending, the rational design of biomolecular templates suitable for the synthesis of multifunctional metal NCs for theranostics is comparatively underexplored. This progress report first identifies the essential attributes of biotemplated metal NCs for theranostics by reviewing the state-of-art applications in each of the four modalities of theranostics, namely sensing, imaging, delivery and therapy. To achieve high efficacy in these modalities, we elucidate the design principles underlying the use of biomolecules (proteins, peptides and nucleic acids) to control the NC size, emission color and surface chemistries for post-functionalization of therapeutic moieties. We then propose a unified strategy to engineer biomolecular templates that combine all these modalities to produce multifunctional biotemplated metal NCs that can serve as the next-generation personalized theranostic agents.

  6. Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

    Science.gov (United States)

    Cole, Daniel J; Vilseck, Jonah Z; Tirado-Rives, Julian; Payne, Mike C; Jorgensen, William L

    2016-05-10

    Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme. PMID:27057643

  7. An improved simple polarisable water model for use in biomolecular simulation

    Energy Technology Data Exchange (ETDEWEB)

    Bachmann, Stephan J.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch [Laboratory of Physical Chemistry, ETH Zürich, CH-8093 Zürich (Switzerland)

    2014-12-14

    The accuracy of biomolecular simulations depends to some degree on the accuracy of the water model used to solvate the biomolecules. Because many biomolecules such as proteins are electrostatically rather inhomogeneous, containing apolar, polar, and charged moieties or side chains, a water model should be able to represent the polarisation response to a local electrostatic field, while being compatible with the force field used to model the biomolecules or protein. The two polarisable water models, COS/G2 and COS/D, that are compatible with the GROMOS biomolecular force fields leave room for improvement. The COS/G2 model has a slightly too large dielectric permittivity and the COS/D model displays a much too slow dynamics. The proposed COS/D2 model has four interaction sites: only one Lennard-Jones interaction site, the oxygen atom, and three permanent charge sites, the two hydrogens, and one massless off-atom site that also serves as charge-on-spring (COS) polarisable site with a damped or sub-linear dependence of the induced dipole on the electric field strength for large values of the latter. These properties make it a cheap and yet realistic water model for biomolecular solvation.

  8. Multiresolution persistent homology for excessively large biomolecular datasets

    Science.gov (United States)

    Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei

    2015-10-01

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

  9. Multiresolution persistent homology for excessively large biomolecular datasets

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin; Zhao, Zhixiong [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824 (United States)

    2015-10-07

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

  10. Towards a calculus of biomolecular complexes at equilibrium.

    Science.gov (United States)

    Mjolsness, Eric

    2007-07-01

    An overview is presented of the construction and use of algebraic partition functions to represent the equilibrium statistical mechanics of multimolecular complexes and their action within a larger regulatory network. Unlike many applications of equilibrium statistical mechanics, multimolecular complexes may operate with various subsets of their components present and connected to the others, the rest remaining in solution. Thus they are variable-structure systems. This aspect of their behavior may be accounted for by the use of 'fugacity' variables as a representation within the partition functions. Four principles are proposed by which the combinatorics of molecular complex construction can be reflected in the construction of their partition functions. The corresponding algebraic operations on partition functions are multiplication, addition, function composition and a less commonly used operation called contraction. Each has a natural interpretation in terms of probability distributions on multimolecular structures. Possible generalizations to nonequilibrium statistical mechanics are briefly discussed.

  11. N,P-Codoped Carbon Networks as Efficient Metal-free Bifunctional Catalysts for Oxygen Reduction and Hydrogen Evolution Reactions.

    Science.gov (United States)

    Zhang, Jintao; Qu, Liangti; Shi, Gaoquan; Liu, Jiangyong; Chen, Jianfeng; Dai, Liming

    2016-02-01

    The high cost and scarcity of noble metal catalysts, such as Pt, have hindered the hydrogen production from electrochemical water splitting, the oxygen reduction in fuel cells and batteries. Herein, we developed a simple template-free approach to three-dimensional porous carbon networks codoped with nitrogen and phosphorus by pyrolysis of a supermolecular aggregate of self-assembled melamine, phytic acid, and graphene oxide (MPSA/GO). The pyrolyzed MPSA/GO acted as the first metal-free bifunctional catalyst with high activities for both oxygen reduction and hydrogen evolution. Zn-air batteries with the pyrolyzed MPSA/GO air electrode showed a high peak power density (310 W g(-1) ) and an excellent durability. Thus, the pyrolyzed MPSA/GO is a promising bifunctional catalyst for renewable energy technologies, particularly regenerative fuel cells. PMID:26709954

  12. A nitrogen-doped mesoporous carbon containing an embedded network of carbon nanotubes as a highly efficient catalyst for the oxygen reduction reaction.

    Science.gov (United States)

    Li, Jin-Cheng; Zhao, Shi-Yong; Hou, Peng-Xiang; Fang, Ruo-Pian; Liu, Chang; Liang, Ji; Luan, Jian; Shan, Xu-Yi; Cheng, Hui-Ming

    2015-12-01

    A nitrogen-doped mesoporous carbon containing a network of carbon nanotubes (CNTs) was produced for use as a catalyst for the oxygen reduction reaction (ORR). SiO2 nanoparticles were decorated with clusters of Fe atoms to act as catalyst seeds for CNT growth, after which the material was impregnated with aniline. After polymerization of the aniline, the material was pyrolysed and the SiO2 was removed by acid treatment. The resulting carbon-based hybrid also contained some Fe from the CNT growth catalyst and was doped with N from the aniline. The Fe-N species act as active catalytic sites and the CNT network enables efficient electron transport in the material. Mesopores left by the removal of the SiO2 template provide short transport pathways and easy access to ions. As a result, the catalyst showed not only excellent ORR activity, with 59 mV more positive onset potential and 30 mV more positive half-wave potential than a Pt/C catalyst, but also much longer durability and stronger tolerance to methanol crossover than a Pt/C catalyst.

  13. Research on the Reaction Mechanism of Network Public Opinion Related to Procuratorate%涉检网络舆情反应机制研究

    Institute of Scientific and Technical Information of China (English)

    张亚力; 余芳

    2011-01-01

    新形势下的舆论环境要求检察机关提高处置网络舆情危机的能力。只有建立涉检网络舆情反应机制,敏锐地把握、驾驭应对舆论的能力,及时、坦诚地公开检务信息,才能培养人民群众对司法权威的认同感,提高检察工作的执法公信力,化解社会矛盾、维护社会和谐稳定。%Procuratorial organs are required to improve their abilities to deal with the crisis of network public opinion under the new situation. Only by establishing the reaction mechanism of network public opinion, mastering how to handle the public opinion keenly, opening the procuratorial information timely and frankly, people's sense of identity to judicial authority can be educated, the law enforcement credibility of procuratorial work can be improved, social contradictions can be defused, social harmony and stability can be maintained.

  14. Databases and tools for nuclear astrophysics applications BRUSsels Nuclear LIBrary (BRUSLIB), Nuclear Astrophysics Compilation of REactions II (NACRE II) and Nuclear NETwork GENerator (NETGEN)

    CERN Document Server

    Xu, Yi; Jorissen, Alain; Chen, Guangling; Arnould, Marcel; 10.1051/0004-6361/201220537

    2012-01-01

    An update of a previous description of the BRUSLIB+NACRE package of nuclear data for astrophysics and of the web-based nuclear network generator NETGEN is presented. The new version of BRUSLIB contains the latest predictions of a wide variety of nuclear data based on the most recent version of the Brussels-Montreal Skyrme-HFB model. The nuclear masses, radii, spin/parities, deformations, single-particle schemes, matter densities, nuclear level densities, E1 strength functions, fission properties, and partition functions are provided for all nuclei lying between the proton and neutron drip lines over the 8<=Z<=110 range, whose evaluation is based on a unique microscopic model that ensures a good compromise between accuracy, reliability, and feasibility. In addition, these various ingredients are used to calculate about 100000 Hauser-Feshbach n-, p-, a-, and gamma-induced reaction rates based on the reaction code TALYS. NACRE is superseded by the NACRE II compilation for 15 charged-particle transfer react...

  15. Assessment of nitric oxide (NO) redox reactions contribution to nitrous oxide (N2 O) formation during nitrification using a multispecies metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Chandran, Kartik; Villas-Boas, Silas G; Singhal, Naresh

    2016-05-01

    Over the coming decades nitrous oxide (N2O) is expected to become a dominant greenhouse gas and atmospheric ozone depleting substance. In wastewater treatment systems, N2O is majorly produced by nitrifying microbes through biochemical reduction of nitrite (NO2(-)) and nitric oxide (NO). However it is unknown if the amount of N2O formed is affected by alternative NO redox reactions catalyzed by oxidative nitrite oxidoreductase (NirK), cytochromes (i.e., P460 [CytP460] and 554 [Cyt554 ]) and flavohemoglobins (Hmp) in ammonia- and nitrite-oxidizing bacteria (AOB and NOB, respectively). In this study, a mathematical model is developed to assess how N2O formation is affected by such alternative nitrogen redox transformations. The developed multispecies metabolic network model captures the nitrogen respiratory pathways inferred from genomes of eight AOB and NOB species. The performance of model variants, obtained as different combinations of active NO redox reactions, was assessed against nine experimental datasets for nitrifying cultures producing N2O at different concentration of electron donor and acceptor. Model predicted metabolic fluxes show that only variants that included NO oxidation to NO2(-) by CytP460 and Hmp in AOB gave statistically similar estimates to observed production rates of N2O, NO, NO2(-) and nitrate (NO3(-)), together with fractions of AOB and NOB species in biomass. Simulations showed that NO oxidation to NO2(-) decreased N2O formation by 60% without changing culture's NO2(-) production rate. Model variants including NO reduction to N2O by Cyt554 and cNor in NOB did not improve the accuracy of experimental datasets estimates, suggesting null N2O production by NOB during nitrification. Finally, the analysis shows that in nitrifying cultures transitioning from dissolved oxygen levels above 3.8 ± 0.38 to oxidize the NO produced by AOB through reactions catalyzed by oxidative NirK. PMID:26551878

  16. Raman spectroscopy detects biomolecular changes associated with nanoencapsulated hesperetin treatment in experimental oral carcinogenesis

    Science.gov (United States)

    Gurushankar, K.; Gohulkumar, M.; Kumar, Piyush; Krishna, C. Murali; Krishnakumar, N.

    2016-03-01

    Recently it has been shown that Raman spectroscopy possesses great potential in the investigation of biomolecular changes of tumor tissues with therapeutic drug response in a non-invasive and label-free manner. The present study is designed to investigate the antitumor effect of hespertin-loaded nanoparticles (HETNPs) relative to the efficacy of native hesperetin (HET) in modifying the biomolecular changes during 7,12-dimethyl benz(a)anthracene (DMBA)-induced oral carcinogenesis using a Raman spectroscopic technique. Significant differences in the intensity and shape of the Raman spectra between the control and the experimental tissues at 1800-500 cm-1 were observed. Tumor tissues are characterized by an increase in the relative amount of proteins, nucleic acids, tryptophan and phenylalanine and a decrease in the percentage of lipids when compared to the control tissues. Further, oral administration of HET and its nanoparticulates restored the status of the lipids and significantly decreased the levels of protein and nucleic acid content. Treatment with HETNPs showed a more potent antitumor effect than treatment with native HET, which resulted in an overall reduction in the intensity of several biochemical Raman bands in DMBA-induced oral carcinogenesis being observed. Principal component and linear discriminant analysis (PC-LDA), together with leave-one-out cross validation (LOOCV) on Raman spectra yielded diagnostic sensitivities of 100%, 80%, 91.6% and 65% and specificities of 100%, 65%, 60% and 55% for classification of control versus DMBA, DMBA versus DMBA  +  HET, DMBA versus DMBA  +  HETNPs and DMBA  +  HET versus DMBA  +  HETNPs treated tissue groups, respectively. These results further demonstrate that Raman spectroscopy associated with multivariate statistical algorithms could be a valuable tool for developing a comprehensive understanding of the process of biomolecular changes, and could reveal the signatures of the

  17. Interacting with the biomolecular solvent accessible surface via a haptic feedback device

    Directory of Open Access Journals (Sweden)

    Hayward Steven

    2009-10-01

    Full Text Available Abstract Background From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation. Results A haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations. Conclusion By using the software, named HaptiMol ISAS (available from http://www.haptimol.co.uk, one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water

  18. In situ monitoring of biomolecular processes in living systems using surface-enhanced Raman scattering

    Science.gov (United States)

    Altunbek, Mine; Kelestemur, Seda; Culha, Mustafa

    2015-12-01

    Surface-enhanced Raman scattering (SERS) continues to strive to gather molecular level information from dynamic biological systems. It is our ongoing effort to utilize the technique for understanding of the biomolecular processes in living systems such as eukaryotic and prokaryotic cells. In this study, the technique is investigated to identify cell death mechanisms in 2D and 3D in vitro cell culture models, which is a very important process in tissue engineering and pharmaceutical applications. Second, in situ biofilm formation monitoring is investigated to understand how microorganisms respond to the environmental stimuli, which inferred information can be used to interfere with biofilm formation and fight against their pathogenic activity.

  19. Surface-plasmon-enhanced fluorescence from periodic quantum dot arrays through distance control using biomolecular linkers

    International Nuclear Information System (INIS)

    We have developed a protein-enabled strategy to fabricate quantum dot (QD) nanoarrays where up to a 15-fold increase in surface-plasmon-enhanced fluorescence has been achieved. This approach permits a comprehensive control both laterally (via lithographically defined gold nanoarrays) and vertically (via the QD-metal distance) of the collectively behaving assemblies of QDs and gold nanoarrays by way of biomolecular recognition. Specifically, we demonstrated the spectral tuning of plasmon resonant metal nanoarrays and self-assembly of protein-functionalized QDs in a stepwise fashion with a concomitant incremental increase in separation from the metal surface through biotin-streptavidin spacer units.

  20. The use of gold nanoparticle aggregation for DNA computing and logic-based biomolecular detection

    Energy Technology Data Exchange (ETDEWEB)

    Lee, In-Hee; Yang, Kyung-Ae; Zhang, Byoung-Tak [School of Computer Science and Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Lee, Ji-Hoon [Center for Bioinformation Technology, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Park, Ji-Yoon; Chai, Young Gyu [Division of Molecular and Life Sciences, Hanyang University, 1271 Sa-dong, Sangnok-gu, Ansan, Gyeonggi-do 426-791 (Korea, Republic of); Lee, Jae-Hoon [Fachgebiet Mikrobiologie und Genetik, Institut fuer Biotechnologie, Technische Universitaet Berlin, Gustav-Meyer Allee 25, D-13355 Berlin (Germany)], E-mail: btzhang@bi.snu.ac.kr

    2008-10-01

    The use of DNA molecules as a physical computational material has attracted much interest, especially in the area of DNA computing. DNAs are also useful for logical control and analysis of biological systems if efficient visualization methods are available. Here we present a quick and simple visualization technique that displays the results of the DNA computing process based on a colorimetric change induced by gold nanoparticle aggregation, and we apply it to the logic-based detection of biomolecules. Our results demonstrate its effectiveness in both DNA-based logical computation and logic-based biomolecular detection.

  1. A benchmark for reaction coordinates in the transition path ensemble.

    Science.gov (United States)

    Li, Wenjin; Ma, Ao

    2016-04-01

    The molecular mechanism of a reaction is embedded in its transition path ensemble, the complete collection of reactive trajectories. Utilizing the information in the transition path ensemble alone, we developed a novel metric, which we termed the emergent potential energy, for distinguishing reaction coordinates from the bath modes. The emergent potential energy can be understood as the average energy cost for making a displacement of a coordinate in the transition path ensemble. Where displacing a bath mode invokes essentially no cost, it costs significantly to move the reaction coordinate. Based on some general assumptions of the behaviors of reaction and bath coordinates in the transition path ensemble, we proved theoretically with statistical mechanics that the emergent potential energy could serve as a benchmark of reaction coordinates and demonstrated its effectiveness by applying it to a prototypical system of biomolecular dynamics. Using the emergent potential energy as guidance, we developed a committor-free and intuition-independent method for identifying reaction coordinates in complex systems. We expect this method to be applicable to a wide range of reaction processes in complex biomolecular systems.

  2. Effects of Clear Kefir on Biomolecular Aspects of Glycemic Status of Type 2 Diabetes Mellitus (T2DM Patients in Bandung, West Java [Study on Human Blood Glucose, c Peptide and Insulin

    Directory of Open Access Journals (Sweden)

    Judiono J

    2014-08-01

    Full Text Available Background: Diabetes Mellitus (DM triggers an excessive reaction of free-radicals. It increases reactive oxygen species and reduces antioxidants status as well as the β cell damage. Clear kefir was used for DM therapies, however it limited biomolecular exploration of its bioactive roles. Research aimed to investigate the effects of clear kefir on the biomolecular nature of the glycemic status of T2DM in Bandung. Methods: The randomized pretest-posttest control group was conducted by 106 T2DM patients. Research was done in several hospitals in Bandung and Cimahi, West Java from 2012–2013. Samples were divided randomly into three groups: (1 T2DM with HbA1c 7 fed standard diet and supplemented 200 ml/day by clear kefir, (3 T2DM with HbA1c was fed a standard diet as a control group. Dose response was obtained from a preeliminary vivo study, and then converted to human dosage by year 2011. Intervention was effectively done for 30 days. HbA1c was measured by HPLC. Fasting blood glucose (FBG and Postprandial blood glucose levels (PBG were measured by enzymes levels. C Peptide and insulin were measured by Elisa. Data was analyzed by a statictics programme by significance p<0,05. Study was approved by ethic committee. Results : HbA1c was significantly reduced in delta level (p<0.01 and FBG (p<0.015 among kefir groups. PBG was not significantly reduced among groups. C-Peptide was significantly increased in delta level, except in control group (p<0.014. Insulin was reduced significantly, except in control group (p<0.003. Conclusions : Supplementation of clear kefir reduced blood glucose levels (HbA1c, FBG, PBG and increased c-peptide. Clear kefir’s biomolecular mechanisms and chemistry characterization is a challenge for future studies.

  3. Biomolecular solid state NMR with magic-angle spinning at 25 K

    Science.gov (United States)

    Thurber, Kent R.; Tycko, Robert

    2009-01-01

    A magic-angle spinning (MAS) probe has been constructed which allows the sample to be cooled with helium, while the MAS bearing and drive gases are nitrogen. The sample can be cooled to 25 K using roughly 3 liters/hour of liquid helium, while the 4 mm diameter rotor spins at 6.7 kHz with good stability (±5 Hz) for many hours. Proton decoupling fields up to at least 130 kHz can be applied. This helium-cooled MAS probe enables a variety of one-dimensional and two-dimensional NMR experiments on biomolecular solids and other materials at low temperatures, with signal-to-noise proportional to 1/T. We show examples of low-temperature 13C NMR data for two biomolecular samples, namely the peptide Aβ14–23 in the form of amyloid fibrils and the protein HP35 in frozen glycerol/water solution. Issues related to temperature calibration, spin-lattice relaxation at low temperatures, paramagnetic doping of frozen solutions, and 13C MAS NMR linewidths are discussed. PMID:18922715

  4. Time-resolved methods in biophysics. 9. Laser temperature-jump methods for investigating biomolecular dynamics.

    Science.gov (United States)

    Kubelka, Jan

    2009-04-01

    Many important biochemical processes occur on the time-scales of nanoseconds and microseconds. The introduction of the laser temperature-jump (T-jump) to biophysics more than a decade ago opened these previously inaccessible time regimes up to direct experimental observation. Since then, laser T-jump methodology has evolved into one of the most versatile and generally applicable methods for studying fast biomolecular kinetics. This perspective is a review of the principles and applications of the laser T-jump technique in biophysics. A brief overview of the T-jump relaxation kinetics and the historical development of laser T-jump methodology is presented. The physical principles and practical experimental considerations that are important for the design of the laser T-jump experiments are summarized. These include the Raman conversion for generating heating pulses, considerations of size, duration and uniformity of the temperature jump, as well as potential adverse effects due to photo-acoustic waves, cavitation and thermal lensing, and their elimination. The laser T-jump apparatus developed at the NIH Laboratory of Chemical Physics is described in detail along with a brief survey of other laser T-jump designs in use today. Finally, applications of the laser T-jump in biophysics are reviewed, with an emphasis on the broad range of problems where the laser T-jump methodology has provided important new results and insights into the dynamics of the biomolecular processes.

  5. DockScreen: A Database of In Silico Biomolecular Interactions to Support Computational Toxicology

    Directory of Open Access Journals (Sweden)

    Michael-Rock Goldsmith

    2014-01-01

    Full Text Available We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme binding scores calculated by molecular docking of more than 1000 chemicals into 150 protein targets and contains nearly 135 thousand unique ligand/target binding scores. Obtaining this dataset was achieved using eHiTS (Simbiosys Inc., a fragment-based molecular docking approach with an exhaustive search algorithm, on a heterogeneous distributed high-performance computing framework. The chemical landscape covered in DockScreen comprises selected environmental and therapeutic chemicals. The target landscape covered in DockScreen was selected based on the availability of high-quality crystal structures that covered the assay space of phase I ToxCast in vitro assays. This in silico data provides continuous information that establishes a means for quantitatively comparing, on a structural biophysical basis, a chemical’s profile of biomolecular interactions. The combined minimum-score chemical/target matrix is provided.

  6. The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

    Science.gov (United States)

    van Zundert, G C P; Rodrigues, J P G L M; Trellet, M; Schmitz, C; Kastritis, P L; Karaca, E; Melquiond, A S J; van Dijk, M; de Vries, S J; Bonvin, A M J J

    2016-02-22

    The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2.

  7. Submicrometer Hall sensors for detection of magnetic nanoparticles in biomolecular sensing

    Science.gov (United States)

    Mihajlovic, Goran; Xiong, P.; von Molnar, S.; Ohtani, K.; Ohno, H.; Field, M.; Sullivan, G. J.

    2006-03-01

    Significant progress has been made in the recent years in synthesis and biomolecular functionalization of magnetic nanoparticles. These magnetic bio-nanolabels can be utilized as protein or gene markers in biomolecular sensing assays, in contrast to the much larger micron sized magnetic beads that are usually limited to cell labeling. However, the low magnetic moments of individual nanoparticles (10^4-10^5 μB) render their sensitive detection still a challenging task. In order to address this issue we are developing miniaturized Hall sensors from InAs/AlSb quantum well semiconductor heterostructures with active Hall cross areas down to 300 nm x 300 nm. Our preliminary characterization measurements performed at room temperature show functional devices with magnetic field resolution < 100 μT/√Hz at frequencies above 100 Hz, yielding a moment sensitivity ˜ 10^5 μB. In addition to the progress in improving the moment sensitivity of the submicrometer Hall detectors, we will also present efforts in device integration with on-chip microcoils for the generation of local magnetic excitation fields. Results on nanoparticle detection will also be presented.

  8. The detection of specific biomolecular interactions with micro-Hall magnetic sensors

    Science.gov (United States)

    Manandhar, Pradeep; Chen, Kan-Sheng; Aledealat, Khaled; Mihajlović, Goran; Yun, C. Steven; Field, Mark; Sullivan, Gerard J.; Strouse, Geoffrey F.; Bryant Chase, P.; von Molnár, Stephan; Xiong, Peng

    2009-09-01

    The detection of reagent-free specific biomolecular interactions through sensing of nanoscopic magnetic labels provides one of the most promising routes to biosensing with solid-state devices. In particular, Hall sensors based on semiconductor heterostructures have shown exceptional magnetic moment sensitivity over a large dynamic field range suitable for magnetic biosensing using superparamagnetic labels. Here we demonstrate the capability of such micro-Hall sensors to detect specific molecular binding using biotin-streptavidin as a model system. We apply dip-pen nanolithography to selectively biotinylate the active areas of InAs micro-Hall devices with nanoscale precision. Specific binding of complementarily functionalized streptavidin-coated superparamagnetic beads to the Hall crosses occurs via molecular recognition, and magnetic detection of the assembled beads is achieved at room temperature using phase sensitive micro-Hall magnetometry. The experiment constitutes the first unambiguous demonstration of magnetic detection of specific biomolecular interactions with semiconductor micro-Hall sensors, and the selective molecular functionalization and resulting localized bead assembly demonstrate the possibility of multiplexed sensing of multiple target molecules using a single device with an array of micro-Hall sensors.

  9. Dynamics of simple gene-network motifs subject to extrinsic fluctuations

    Science.gov (United States)

    Roberts, Elijah; Be'er, Shay; Bohrer, Chris; Sharma, Rati; Assaf, Michael

    2015-12-01

    Cellular processes do not follow deterministic rules; even in identical environments genetically identical cells can make random choices leading to different phenotypes. This randomness originates from fluctuations present in the biomolecular interaction networks. Most previous work has been focused on the intrinsic noise (IN) of these networks. Yet, especially for high-copy-number biomolecules, extrinsic or environmental noise (EN) has been experimentally shown to dominate the variation. Here, we develop an analytical formalism that allows for calculation of the effect of EN on gene-expression motifs. We introduce a method for modeling bounded EN as an auxiliary species in the master equation. The method is fully generic and is not limited to systems with small EN magnitudes. We focus our study on motifs that can be viewed as the building blocks of genetic switches: a nonregulated gene, a self-inhibiting gene, and a self-promoting gene. The role of the EN properties (magnitude, correlation time, and distribution) on the statistics of interest are systematically investigated, and the effect of fluctuations in different reaction rates is compared. Due to its analytical nature, our formalism can be used to quantify the effect of EN on the dynamics of biochemical networks and can also be used to improve the interpretation of data from single-cell gene-expression experiments.

  10. Combination of artificial neural networks with statistics for prediction of yields in organic reactions%人工神经网络与统计方法集成预测有机反应产率

    Institute of Scientific and Technical Information of China (English)

    朱京科; 苏云

    2001-01-01

    在应用人工神经网络预测有机反应产率中,由于结合了统计方法,使人工神经网络易产生的随机性和过拟合作用造成的不利影响减小,从而提高了预测可靠性。%This work presents a backpropagation neural network trained toreproduce the reaction yield of aryl fluorides by the halex technique. The work shows that a ten-dimensional input space is able to reproduce reasonably the observed reaction yields by employing statistics in artificial neural system. By means of a number of multilayer feedforward (MLF) networks rather than one, the disadvantages caused by network randomness are limited greatly, and therefore the prediction quality is improved. The combined approach is suitable for relatively small training set, which often causes overfitting and leads to unreliable prediction results.

  11. A developmental systems perspective on epistasis: computational exploration of mutational interactions in model developmental regulatory networks.

    Directory of Open Access Journals (Sweden)

    Jayson Gutiérrez

    Full Text Available The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks. Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/- feedback and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1 the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2 the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of

  12. Assessment of nitric oxide (NO) redox reactions contribution to nitrous oxide (N2 O) formation during nitrification using a multispecies metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Chandran, Kartik; Villas-Boas, Silas G; Singhal, Naresh

    2016-05-01

    Over the coming decades nitrous oxide (N2O) is expected to become a dominant greenhouse gas and atmospheric ozone depleting substance. In wastewater treatment systems, N2O is majorly produced by nitrifying microbes through biochemical reduction of nitrite (NO2(-)) and nitric oxide (NO). However it is unknown if the amount of N2O formed is affected by alternative NO redox reactions catalyzed by oxidative nitrite oxidoreductase (NirK), cytochromes (i.e., P460 [CytP460] and 554 [Cyt554 ]) and flavohemoglobins (Hmp) in ammonia- and nitrite-oxidizing bacteria (AOB and NOB, respectively). In this study, a mathematical model is developed to assess how N2O formation is affected by such alternative nitrogen redox transformations. The developed multispecies metabolic network model captures the nitrogen respiratory pathways inferred from genomes of eight AOB and NOB species. The performance of model variants, obtained as different combinations of active NO redox reactions, was assessed against nine experimental datasets for nitrifying cultures producing N2O at different concentration of electron donor and acceptor. Model predicted metabolic fluxes show that only variants that included NO oxidation to NO2(-) by CytP460 and Hmp in AOB gave statistically similar estimates to observed production rates of N2O, NO, NO2(-) and nitrate (NO3(-)), together with fractions of AOB and NOB species in biomass. Simulations showed that NO oxidation to NO2(-) decreased N2O formation by 60% without changing culture's NO2(-) production rate. Model variants including NO reduction to N2O by Cyt554 and cNor in NOB did not improve the accuracy of experimental datasets estimates, suggesting null N2O production by NOB during nitrification. Finally, the analysis shows that in nitrifying cultures transitioning from dissolved oxygen levels above 3.8 ± 0.38 to <1.5 ± 0.8 mg/L, NOB cells can oxidize the NO produced by AOB through reactions catalyzed by oxidative NirK.

  13. Databases and tools for nuclear astrophysics applications. BRUSsels Nuclear LIBrary (BRUSLIB), Nuclear Astrophysics Compilation of REactions II (NACRE II) and Nuclear NETwork GENerator (NETGEN)

    Science.gov (United States)

    Xu, Y.; Goriely, S.; Jorissen, A.; Chen, G. L.; Arnould, M.

    2013-01-01

    An update of a previous description of the BRUSLIB + NACRE package of nuclear data for astrophysics and of the web-based nuclear network generator NETGEN is presented. The new version of BRUSLIB contains the latest predictions of a wide variety of nuclear data based on the most recent version of the Brussels-Montreal Skyrme-Hartree-Fock-Bogoliubov model. The nuclear masses, radii, spin/parities, deformations, single-particle schemes, matter densities, nuclear level densities, E1 strength functions, fission properties, and partition functions are provided for all nuclei lying between the proton and neutron drip lines over the 8 ≤ Z ≤ 110 range, whose evaluation is based on a unique microscopic model that ensures a good compromise between accuracy, reliability, and feasibility. In addition, these various ingredients are used to calculate about 100 000 Hauser-Feshbach neutron-, proton-, α-, and γ-induced reaction rates based on the reaction code TALYS. NACRE is superseded by the NACRE II compilation for 15 charged-particle transfer reactions and 19 charged-particle radiative captures on stable targets with mass numbers A < 16. NACRE II features the inclusion of experimental data made available after the publication of NACRE in 1999 and up to 2011. In addition, the extrapolation of the available data to the very low energies of astrophysical relevance is improved through the systematic use of phenomenological potential models. Uncertainties in the rates are also evaluated on this basis. Finally, the latest release v10.0 of the web-based tool NETGEN is presented. In addition to the data already used in the previous NETGEN package, it contains in a fully documented form the new BRUSLIB and NACRE II data, as well as new experiment-based radiative neutron capture cross sections. The full new versions of BRUSLIB, NACRE II, and NETGEN are available electronically from the nuclear database at http://www.astro.ulb.ac.be/NuclearData. The nuclear material is presented in

  14. Chemistry and photochemistry of 2,6-bis(2-hydroxybenzilidene)cyclohexanone. An example of a compound following the anthocyanins network of chemical reactions.

    Science.gov (United States)

    Moro, Artur J; Pana, Ana-Maria; Cseh, Liliana; Costisor, Otilia; Parola, Jorge; Cunha-Silva, L; Puttreddy, Rakesh; Rissanen, Kari; Pina, Fernando

    2014-08-14

    The kinetics and thermodynamics of the 2,6-bis(2-hydroxybenzilidene)cyclohexanone chemical reactions network was studied at different pH values using NMR, UV-vis, continuous irradiation, and flash photolysis. The chemical behavior of the system partially resembles anthocyanins and their analogue compounds. 2,6-Bis(2-hydroxybenzilidene)cyclohexanone exhibits a slow color change from yellow to red styrylflavylium under extreme acidic conditions. The rate constant for this process (5 × 10(-5) s(-1)) is pH independent and controlled by the cis-trans isomerization barrier. However, the interesting feature is the appearance of the colorless compound, 7,8-dihydro-6H-chromeno[3,2-d]xanthene, isolated from solutions of acid to neutral range, characterized by (1)H NMR and single crystal X-ray diffraction. Light absorption by 2,6-bis(2-hydroxybenzilidene)cyclohexanone solutions immediately after preparation exclusively results in cis-isomer as photoproduct, which via hemiketal formation yields (i) red styrylflavylium by dehydration under extremely acidic solutions (pH < 1) and (ii) colorless 7,8-dihydro-6H-chromeno[3,2-d]xanthene by cyclization in solutions of acid to neutral range.

  15. Electrochemical sensor for multiplex screening of genetically modified DNA: identification of biotech crops by logic-based biomolecular analysis.

    Science.gov (United States)

    Liao, Wei-Ching; Chuang, Min-Chieh; Ho, Ja-An Annie

    2013-12-15

    Genetically modified (GM) technique, one of the modern biomolecular engineering technologies, has been deemed as profitable strategy to fight against global starvation. Yet rapid and reliable analytical method is deficient to evaluate the quality and potential risk of such resulting GM products. We herein present a biomolecular analytical system constructed with distinct biochemical activities to expedite the computational detection of genetically modified organisms (GMOs). The computational mechanism provides an alternative to the complex procedures commonly involved in the screening of GMOs. Given that the bioanalytical system is capable of processing promoter, coding and species genes, affirmative interpretations succeed to identify specified GM event in terms of both electrochemical and optical fashions. The biomolecular computational assay exhibits detection capability of genetically modified DNA below sub-nanomolar level and is found interference-free by abundant coexistence of non-GM DNA. This bioanalytical system, furthermore, sophisticates in array fashion operating multiplex screening against variable GM events. Such a biomolecular computational assay and biosensor holds great promise for rapid, cost-effective, and high-fidelity screening of GMO.

  16. Urban networks and Arctic outlands: Craft specialists and reindeer antler in Viking towns

    DEFF Research Database (Denmark)

    Ashby, Steven P.; Coutu, Ashley N.; Sindbæk, Søren Michael

    2015-01-01

    This paper presents the results of the use of a minimally destructive biomolecular technique to explore the resource networks behind one of the first specialized urban crafts in early mediaeval northern Europe: the manufacture of composite combs of deer antler. The research incorporates the largest...

  17. Biosensors with Built-In Biomolecular Logic Gates for Practical Applications

    Directory of Open Access Journals (Sweden)

    Yu-Hsuan Lai

    2014-08-01

    Full Text Available Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems.

  18. Using Nature's "Tricks" To Rationally Tune the Binding Properties of Biomolecular Receptors.

    Science.gov (United States)

    Ricci, Francesco; Vallée-Bélisle, Alexis; Simon, Anna J; Porchetta, Alessandro; Plaxco, Kevin W

    2016-09-20

    The biosensor community has long focused on achieving the lowest possible detection limits, with specificity (the ability to differentiate between closely similar target molecules) and sensitivity (the ability to differentiate between closely similar target concentrations) largely being relegated to secondary considerations and solved by the inclusion of cumbersome washing and dilution steps or via careful control experimental conditions. Nature, in contrast, cannot afford the luxury of washing and dilution steps, nor can she arbitrarily change the conditions (temperature, pH, ionic strength) under which binding occurs in the homeostatically maintained environment within the cell. This forces evolution to focus at least as much effort on achieving optimal sensitivity and specificity as on achieving low detection limits, leading to the "invention" of a number of mechanisms, such as allostery and cooperativity, by which the useful dynamic range of receptors can be tuned, extended, narrowed, or otherwise optimized by design, rather than by sample manipulation. As the use of biomolecular receptors in artificial technologies matures (i.e., moves away from multistep, laboratory-bound processes and toward, for example, systems supporting continuous in vivo measurement) and these technologies begin to mimic the reagentless single-step convenience of naturally occurring chemoperception systems, the ability to artificially design receptors of enhanced sensitivity and specificity will likely also grow in importance. Thus motivated, we have begun to explore the adaptation of nature's solutions to these problems to the biomolecular receptors often employed in artificial biotechnologies. Using the population-shift mechanism, for example, we have generated nested sets of receptors and allosteric inhibitors that greatly expanded the normally limited (less than 100-fold) useful dynamic range of unmodified molecular and aptamer beacons, enabling the single-step (e.g., dilution

  19. Astronomy with Radioactivities: Chapter 9, Nuclear Reactions

    OpenAIRE

    Wiescher, M.; Rauscher, T.

    2010-01-01

    Nuclear reaction rates determine the abundances of isotopes in stellar burning processes. A multitude of reactions determine the reaction flow pattern which is described in terms of reaction network simulations. The reaction rates are determined by laboratory experiments supplemented by nuclear reaction and structure theory. We will discuss the experimental approach as well as the theoretical tools for obtaining the stellar reaction rates. A detailed analysis of a reaction is only possible fo...

  20. Effect of temperature and magnetic field on the photocurrent response of biomolecular bulk-hetero junction

    Science.gov (United States)

    Tajima, Hiroyuki; Sekiguchi, Yusuke; Matsuda, Masaki

    2012-02-01

    The photocurrent responses were investigated for the biomolecular bulk-hetero junction of chlorophyll α (Chl-α) and 1-(3-methoxycarbonyl)-propyl-1-phenyl-1-phenyl-(6,6)C61 (PCBM) in the temperature range between 300 K and 1.5 K under the magnetic field up to 8 T. The chopped-light photocurrent decreases on lowering the temperature. Below 10 K, photocurrent decrease was observed under the applied magnetic field. Decay of the photocurrent observed at 10 K was ascribed to the formation of the charged trap under light irradiation. The magnetic field effect (MFE) observed in this device was found to be very similar to that observed in P3HT:PCBM bulk-hetero junction at low temperatures.

  1. Biomolecular papain thin films grown by matrix assisted and conventional pulsed laser deposition: A comparative study

    Science.gov (United States)

    György, E.; Pérez del Pino, A.; Sauthier, G.; Figueras, A.

    2009-12-01

    Biomolecular papain thin films were grown both by matrix assisted pulsed laser evaporation (MAPLE) and conventional pulsed laser deposition (PLD) techniques with the aid of an UV KrF∗ (λ =248 nm, τFWHM≅20 ns) excimer laser source. For the MAPLE experiments the targets submitted to laser radiation consisted on frozen composites obtained by dissolving the biomaterial powder in distilled water at 10 wt % concentration. Conventional pressed biomaterial powder targets were used in the PLD experiments. The surface morphology of the obtained thin films was studied by atomic force microscopy and their structure and composition were investigated by Fourier transform infrared spectroscopy. The possible physical mechanisms implied in the ablation processes of the two techniques, under comparable experimental conditions were identified. The results showed that the growth mode, surface morphology as well as structure of the deposited biomaterial thin films are determined both by the incident laser fluence value as well as target preparation procedure.

  2. Advances in biomolecular surface meshing and its applications to mathematical modeling

    Institute of Scientific and Technical Information of China (English)

    CHEN MinXin; LU BenZhuo

    2013-01-01

    In the field of molecular modeling and simulation,molecular surface meshes are necessary for many problems,such as molecular structure visualization and analysis,docking problem and implicit solvent modeling and simulation.Recently,with the developments of advanced mathematical modeling in the field of implicit solvent modeling and simulation,providing surface meshes with good qualities efficiently for large real biomolecular systems becomes an urgent issue beyond its traditional purposes for visualization and geometry analyses for molecular structure.In this review,we summarize recent works on this issue.First,various definitions of molecular surfaces and corresponding meshing methods are introduced.Second,our recent meshing tool,TMSmesh,and its performances are presented.Finally,we show the applications of the molecular surface mesh in implicit solvent modeling and simulations using boundary element method (BEM) and finite element method (FEM).

  3. A Review of Salam Phase Transition in Protein Amino Acids Implication for Biomolecular Homochirality

    CERN Document Server

    Bai, F; Bai, Fan; Wang, Wenqing

    2002-01-01

    The origin of chirality, closely related to the evolution of life on the earth, has long been debated. In 1991, Abdus Salam suggested a novel approach to achieve biomolecular homochirality by a phase transition. In his subsequent publication, he predicted that this phase transition could eventually change D-amino acids to L-amino acids as C -H bond would break and H atom became a superconductive atom. Since many experiments denied the configuration change in amino acids, Salam hypothesis aroused suspicion. This paper is aimed to provide direct experimental evidence of a phase transition in alanine, valine single crystals but deny the configuration change of D- to L- enantiomers. New views on Salam phase transition are presented to revalidate its great importance in the origin of homochirality.

  4. Overcoming the solubility limit with solubility-enhancement tags: successful applications in biomolecular NMR studies

    International Nuclear Information System (INIS)

    Although the rapid progress of NMR technology has significantly expanded the range of NMR-trackable systems, preparation of NMR-suitable samples that are highly soluble and stable remains a bottleneck for studies of many biological systems. The application of solubility-enhancement tags (SETs) has been highly effective in overcoming solubility and sample stability issues and has enabled structural studies of important biological systems previously deemed unapproachable by solution NMR techniques. In this review, we provide a brief survey of the development and successful applications of the SET strategy in biomolecular NMR. We also comment on the criteria for choosing optimal SETs, such as for differently charged target proteins, and recent new developments on NMR-invisible SETs.

  5. Settlement specifics: Effective induction of abalone settlement and metamorphosis corresponds to biomolecular composition of natural cues.

    Science.gov (United States)

    Williams, Elizabeth A; Cummins, Scott; Degnan, Sandie M

    2009-07-01

    Chemical signaling plays a major role in shaping life history processes that drive ecology and evolution in marine systems, notably including habitat selection by marine invertebrate larvae that must settle out of the plankton onto the benthos.1 For larvae, the identification of appropriate habitats in which to settle and undergo metamorphosis to the adult form relies heavily on the recognition of cues indicative of a favorable environment. By documenting settlement responses of larvae of the tropical abalone, Haliotis asinina, to a range of coralline algae species, we recently highlighted the species-specific nature of this interaction.2 Here, we demonstrate that this specificity is likely driven by chemical, rather than physical, properties of the algae. Our initial characterization of the surface cell biomarkers from three different algal species shows that inductive cue biomolecular composition correlates with variations in larval settlement response.

  6. Biomolecular ion detection using high-temperature superconducting MgB2 strips

    Science.gov (United States)

    Zen, N.; Shibata, H.; Mawatari, Y.; Koike, M.; Ohkubo, M.

    2015-06-01

    Superconducting strip ion detectors (SSIDs) are promising for realization of ideal ion detection with 100% efficiency and nanosecond-scale time response in time-of-flight mass spectrometry. We have detected single biomolecular ions in the keV range using a 10-nm-thick and 250-nm-wide strip of a high temperature superconductor, magnesium diboride (MgB2), at temperatures of up to 13 K. The output pulse shape is explained remarkably well using circuit simulations and time-dependent Ginzburg-Landau simulations coupled with a heat diffusion equation. The simulations show that the hot spot model is applicable to the proposed MgB2-SSIDs and the normal region expansion is completed within 16 ps, which corresponds to a maximum length of 1010 nm.

  7. A program to calculate non-bonded interaction energy in biomolecular aggregates.

    Science.gov (United States)

    Sundaram, K; Prasad, C V

    1982-02-01

    This paper describes a program to calculate intermolecular as well as intramolecular electronic potential energy resulting from non-bonded interactions. The underlying theory is obtained by the application of Rayleigh-Schroedinger perturbation theory to non-overlap regions of a molecular system. The rigorous theoretical expressions for the energy terms are simplified by approximations consistent with those commonly employed in semi-empirical molecular orbital theories. The program is particularly suited for the study of biomolecular assemblies, and in situations where insight into contributions to total energy from various component interaction types is desired. The inclusion of the non-additive dispersion effects in this approach makes it especially interesting for the study of cooperative phenomena in the light of a recent finding [1]. PMID:7067416

  8. Biomolecular Characterization of Diazotrophs Isolated from the Tropical Soil in Malaysia

    Directory of Open Access Journals (Sweden)

    Zulkifli H Shamsuddin

    2013-08-01

    Full Text Available This study was conducted to evaluate selected biomolecular characteristics of rice root-associated diazotrophs isolated from the Tanjong Karang rice irrigation project area of Malaysia. Soil and rice plant samples were collected from seven soil series belonging to order Inceptisol (USDA soil taxonomy. A total of 38 diazotrophs were isolated using a nitrogen-free medium. The biochemical properties of the isolated bacteria, such as nitrogenase activity, indoleacetic acid (IAA production and sugar utilization, were measured. According to a cluster analysis of Jaccard’s similarity coefficients, the genetic similarities among the isolated diazotrophs ranged from 10% to 100%. A dendogram constructed using the unweighted pair-group method with arithmetic mean (UPGMA showed that the isolated diazotrophs clustered into 12 groups. The genomic DNA rep-PCR data were subjected to a principal component analysis, and the first four principal components (PC accounted for 52.46% of the total variation among the 38 diazotrophs. The 10 diazotrophs that tested highly positive in the acetylene reduction assay (ARA were identified as Bacillus spp. (9 diazotrophs and Burkholderia sp. (Sb16 using the partial 16S rRNA gene sequence analysis. In the analysis of the biochemical characteristics, three principal components were accounted for approximately 85% of the total variation among the identified diazotrophs. The examination of root colonization using scanning electron microscopy (SEM and transmission electron microscopy (TEM proved that two of the isolated diazotrophs (Sb16 and Sb26 were able to colonize the surface and interior of rice roots and fixed 22%–24% of the total tissue nitrogen from the atmosphere. In general, the tropical soils (Inceptisols of the Tanjong Karang rice irrigation project area in Malaysia harbor a diverse group of diazotrophs that exhibit a large variation of biomolecular characteristics.

  9. Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

    KAUST Repository

    Sobhy, M. A.

    2011-11-07

    Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation and detection is a key experimental feature that is under continuous development. In this paper, we describe in detail the design and the construction of a sophisticated and versatile multi-color excitation and emission fluorescence instrument for studying biomolecular dynamics at the single-molecule level. The setup is novel, economical and compact, where two inverted microscopes share a laser combiner module with six individual laser sources that extend from 400 to 640 nm. Nonetheless, each microscope can independently and in a flexible manner select the combinations, sequences, and intensities of the excitation wavelengths. This high flexibility is achieved by the replacement of conventional mechanical shutters with acousto-optic tunable filter (AOTF). The use of AOTF provides major advancement by controlling the intensities, duration, and selection of up to eight different wavelengths with microsecond alternation time in a transparent and easy manner for the end user. To our knowledge this is the first time AOTF is applied to wide-field total internal reflection fluorescence (TIRF) microscopy even though it has been commonly used in multi-wavelength confocal microscopy. The laser outputs from the combiner module are coupled to the microscopes by two sets of four single-mode optic fibers in order to allow for the optimization of the TIRF angle for each wavelength independently. The emission is split into two or four spectral channels to allow for the simultaneous detection of up to four different fluorophores of wide selection and using many possible excitation and photoactivation schemes. We demonstrate the performance of this new setup by conducting two-color alternating excitation single-molecule fluorescence resonance energy

  10. A New Selective Neural Network Ensemble Method Based on Error Vectorization and Its Application in High-density Polyethylene (HDPE) Cascade Reaction Process%A New Selective Neural Network Ensemble Method Based on Error Vectorization and Its Application in High-density Polyethylene (HDPE) Cascade Reaction Process

    Institute of Scientific and Technical Information of China (English)

    朱群雄; 赵乃伟; 徐圆

    2012-01-01

    Chemical processes are complex, for which traditional neural network models usually can not lead to satisfactory accuracy. Selective neural network ensemble is an effective way to enhance the generalization accuracy of networks, but there are some problems, e.g., lacking of unified definition of diversity among component neural networks and difficult to improve the accuracy by selecting if the diversities of available networks are small. In this study, the output errors of networks are vectorized, the diversity of networks is defined based on the error vectors, and the size of ensemble is analyzed. Then an error vectorization based selective neural network ensemble (EVSNE) is proposed, in which the error vector of each network can offset that of the other networks by training the component networks orderly. Thus the component networks have large diversity. Experiments and comparisons over standard data sets and actual chemical process data set for production of high-density polyethylene demonstrate that EVSNE performs better in generalization ability.

  11. Detection and kinetic studies of triplex formation by oligodeoxynucleotides using real-time biomolecular interaction analysis (BIA).

    OpenAIRE

    Bates, P. J.; Dosanjh, H. S.; S. Kumar; Jenkins, T. C.; Laughton, C A; Neidle, S

    1995-01-01

    Real-time biomolecular interaction analysis (BIA) has been applied to triplex formation between oligodeoxynucleotides. 5'-Biotinylated oligonucleotides were immobilised on the streptavidin-coated surface of a biosensor chip and subsequently hybridised to their complementary strand. Sequence-specific triplex formation was observed when a suitable third-strand oligopyrimidine was injected over the surface-bound duplex. In addition, a single-stranded oligonucleotide immobilised on the chip surfa...

  12. A model of protocell based on the introduction of a semi-permeable membrane in a stochastic model of catalytic reaction networks

    Directory of Open Access Journals (Sweden)

    Marco Villani

    2013-09-01

    Full Text Available In this work we introduce some preliminary analyses on the role of a semi-permeable membrane in the dynamics of a stochastic model of catalytic reaction sets (CRSs of molecules. The results of the simulations performed on ensembles of randomly generated reaction schemes highlight remarkable differences between this very simple protocell description model and the classical case of the continuous stirred-tank reactor (CSTR. In particular, in the CSTR case, distinct simulations with the same reaction scheme reach the same dynamical equilibrium, whereas, in the protocell case, simulations with identical reaction schemes can reach very different dynamical states, despite starting from the same initial conditions.

  13. Single-Molecule Pull-down FRET (SiMPull-FRET) to dissect the mechanisms of biomolecular machines

    Science.gov (United States)

    Kahlscheuer, Matthew L.; Widom, Julia; Walter, Nils G.

    2016-01-01

    Spliceosomes are multi-megadalton RNA-protein complexes responsible for the faithful removal of non-coding segments (introns) from pre-messenger RNAs (pre-mRNAs), a process critical for the maturation of eukaryotic mRNAs for subsequent translation by the ribosome. Both the spliceosome and ribosome, as well as many other RNA and DNA processing machineries, contain central RNA components that endow biomolecular complexes with precise, sequence-specific nucleic acid recognition and versatile structural dynamics. Single molecule fluorescence (or Förster) resonance energy transfer (smFRET) microscopy is a powerful tool for the study of local and global conformational changes of both simple and complex biomolecular systems involving RNA. The integration of biochemical tools such as immunoprecipitation with advanced methods in smFRET microscopy and data analysis has opened up entirely new avenues towards studying the mechanisms of biomolecular machines isolated directly from complex biological specimens such as cell extracts. Here we detail the general steps for using prism-based total internal reflection fluorescence (TIRF) microscopy in exemplary single molecule pull-down FRET (SiMPull-FRET) studies of the yeast spliceosome and discuss the broad application potential of this technique. PMID:26068753

  14. A Quick-responsive DNA Nanotechnology Device for Bio-molecular Homeostasis Regulation

    Science.gov (United States)

    Wu, Songlin; Wang, Pei; Xiao, Chen; Li, Zheng; Yang, Bing; Fu, Jieyang; Chen, Jing; Wan, Neng; Ma, Cong; Li, Maoteng; Yang, Xiangliang; Zhan, Yi

    2016-01-01

    Physiological processes such as metabolism, cell apoptosis and immune responses, must be strictly regulated to maintain their homeostasis and achieve their normal physiological functions. The speed with which bio-molecular homeostatic regulation occurs directly determines the ability of an organism to adapt to conditional changes. To produce a quick-responsive regulatory system that can be easily utilized for various types of homeostasis, a device called nano-fingers that facilitates the regulation of physiological processes was constructed using DNA origami nanotechnology. This nano-fingers device functioned in linked open and closed phases using two types of DNA tweezers, which were covalently coupled with aptamers that captured specific molecules when the tweezer arms were sufficiently close. Via this specific interaction mechanism, certain physiological processes could be simultaneously regulated from two directions by capturing one biofactor and releasing the other to enhance the regulatory capacity of the device. To validate the universal application of this device, regulation of the homeostasis of the blood coagulant thrombin was attempted using the nano-fingers device. It was successfully demonstrated that this nano-fingers device achieved coagulation buffering upon the input of fuel DNA. This nano-device could also be utilized to regulate the homeostasis of other types of bio-molecules. PMID:27506964

  15. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

    Science.gov (United States)

    Pardee, Keith; Green, Alexander A; Takahashi, Melissa K; Braff, Dana; Lambert, Guillaume; Lee, Jeong Wook; Ferrante, Tom; Ma, Duo; Donghia, Nina; Fan, Melina; Daringer, Nichole M; Bosch, Irene; Dudley, Dawn M; O'Connor, David H; Gehrke, Lee; Collins, James J

    2016-05-19

    The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP. PMID:27160350

  16. A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis.

    Science.gov (United States)

    Larimer, Curtis; Winder, Eric; Jeters, Robert; Prowant, Matthew; Nettleship, Ian; Addleman, Raymond Shane; Bonheyo, George T

    2016-01-01

    The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms.

  17. Toxicity evaluation of PEDOT/biomolecular composites intended for neural communication electrodes

    Energy Technology Data Exchange (ETDEWEB)

    Asplund, M; Thaning, E; Von Holst, H [Division of Neuronic Engineering, School of Technology and Health, Royal Institute of Technology, SE-14152 Huddinge (Sweden); Lundberg, J [Section for Neuroradiology, R2:02 NKK-lab, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Solna, SE-171 76, Stockholm (Sweden); Sandberg-Nordqvist, A C [Section of Clinical CNS Research, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Solna, SE-171 76, Stockholm (Sweden); Kostyszyn, B [Center for Hearing and Communication Research, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, M1:01, SE-171 76 Stockholm (Sweden); Inganaes, O, E-mail: maria.asplund@sth.kth.s [Biomolecular and Organic Electronics, IFM, Linkoeping University, SE-581 83 Linkoeping (Sweden)

    2009-08-15

    Electrodes coated with the conducting polymer poly(3,4-ethylene dioxythiophene) (PEDOT) possess attractive electrochemical properties for stimulation or recording in the nervous system. Biomolecules, added as counter ions in electropolymerization, could further improve the biomaterial properties, eliminating the need for surfactant counter ions in the process. Such PEDOT/biomolecular composites, using heparin or hyaluronic acid, have previously been investigated electrochemically. In the present study, their biocompatibility is evaluated. An agarose overlay assay using L929 fibroblasts, and elution and direct contact tests on human neuroblastoma SH-SY5Y cells are applied to investigate cytotoxicity in vitro. PEDOT:heparin was further evaluated in vivo through polymer-coated implants in rodent cortex. No cytotoxic response was seen to any of the PEDOT materials tested. The examination of cortical tissue exposed to polymer-coated implants showed extensive glial scarring irrespective of implant material (Pt:polymer or Pt). However, quantification of immunological response, through distance measurements from implant site to closest neuron and counting of ED1+ cell density around implant, was comparable to those of platinum controls. These results indicate that PEDOT:heparin surfaces were non-cytotoxic and show no marked difference in immunological response in cortical tissue compared to pure platinum controls.

  18. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

    Science.gov (United States)

    Pardee, Keith; Green, Alexander A; Takahashi, Melissa K; Braff, Dana; Lambert, Guillaume; Lee, Jeong Wook; Ferrante, Tom; Ma, Duo; Donghia, Nina; Fan, Melina; Daringer, Nichole M; Bosch, Irene; Dudley, Dawn M; O'Connor, David H; Gehrke, Lee; Collins, James J

    2016-05-19

    The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP.

  19. A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis.

    Science.gov (United States)

    Larimer, Curtis; Winder, Eric; Jeters, Robert; Prowant, Matthew; Nettleship, Ian; Addleman, Raymond Shane; Bonheyo, George T

    2016-01-01

    The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms. PMID:26643074

  20. AFMPB: An adaptive fast multipole Poisson-Boltzmann solver for calculating electrostatics in biomolecular systems

    Science.gov (United States)

    Lu, Benzhuo; Cheng, Xiaolin; Huang, Jingfang; McCammon, J. Andrew

    2013-11-01

    A Fortran program package is introduced for rapid evaluation of the electrostatic potentials and forces in biomolecular systems modeled by the linearized Poisson-Boltzmann equation. The numerical solver utilizes a well-conditioned boundary integral equation (BIE) formulation, a node-patch discretization scheme, a Krylov subspace iterative solver package with reverse communication protocols, and an adaptive new version of the fast multipole method in which the exponential expansions are used to diagonalize the multipole-to-local translations. The program and its full description, as well as several closely related libraries and utility tools are available at http://lsec.cc.ac.cn/~lubz/afmpb.html and a mirror site at http://mccammon.ucsd.edu/. This paper is a brief summary of the program: the algorithms, the implementation and the usage. Restrictions: Only three or six significant digits options are provided in this version. Unusual features: Most of the codes are in Fortran77 style. Memory allocation functions from Fortran90 and above are used in a few subroutines. Additional comments: The current version of the codes is designed and written for single core/processor desktop machines. Check http://lsec.cc.ac.cn/lubz/afmpb.html for updates and changes. Running time: The running time varies with the number of discretized elements (N) in the system and their distributions. In most cases, it scales linearly as a function of N.

  1. Amplified Immunoassay of Human IgG Using Real-time Biomolecular Interaction Analysis (BIA) Technology

    Institute of Scientific and Technical Information of China (English)

    PEI,Ren-Jun(裴仁军); CUI,Xiao-Qiang(崔小强); YANG,Xiu-Rong(杨秀荣); WANG,Er-Kang(汪尔康)

    2002-01-01

    An automated biomolecular interaction analysis instrument (BIAcore) based on surface plasmon resonance (SPR) has been used to determine human immunoglobulin G (IgG) in real time. Polyclonal anti-human IgG antibody was covalently immobilized to a carboxymethyldextran-modified gold film surface. The samples of human IgG prepared in HBS buffer were poured over the immobilized surface. The signal amplification antibody was applied to amplify the response signal. After each measurement, the surface was regenerated with 0.1 mol/L H3PO4. The assay was rapid, requiring only 30 min for antibody immobilization and 20 min for each subsequent process of immune binding, antibody amplification and regeneration. The antibody immobilized surface had good response to human IgG in the range of 0.12-60 nmol/L with a detection limit of 60 pmoL/L. The same antibody immobilized surface could be used for more than 110 cycles of binding, amplificafion and regeneration. The results demonstrate that the sensitivity, specificity and reproducibility of amplified immunoassay using real-time BIA technology are satisfactory.

  2. Biomolecular environment, quantification, and intracellular interaction of multifunctional magnetic SERS nanoprobes.

    Science.gov (United States)

    Büchner, Tina; Drescher, Daniela; Merk, Virginia; Traub, Heike; Guttmann, Peter; Werner, Stephan; Jakubowski, Norbert; Schneider, Gerd; Kneipp, Janina

    2016-08-15

    Multifunctional composite nanoprobes consisting of iron oxide nanoparticles linked to silver and gold nanoparticles, Ag-Magnetite and Au-Magnetite, respectively, were introduced by endocytic uptake into cultured fibroblast cells. The cells containing the non-toxic nanoprobes were shown to be displaceable in an external magnetic field and can be manipulated in microfluidic channels. The distribution of the composite nanostructures that are contained in the endosomal system is discussed on the basis of surface-enhanced Raman scattering (SERS) mapping, quantitative laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) micromapping, and cryo soft X-ray tomography (cryo soft-XRT). Cryo soft-XRT of intact, vitrified cells reveals that the composite nanoprobes form intra-endosomal aggregates. The nanoprobes provide SERS signals from the biomolecular composition of their surface in the endosomal environment. The SERS data indicate the high stability of the nanoprobes and of their plasmonic properties in the harsh environment of endosomes and lysosomes. The spectra point at the molecular composition at the surface of the Ag-Magnetite and Au-Magnetite nanostructures that is very similar to that of other composite structures, but different from the composition of pure silver and gold SERS nanoprobes used for intracellular investigations. As shown by the LA-ICP-MS data, the uptake efficiency of the magnetite composites is approximately two to three times higher than that of the pure gold and silver nanoparticles. PMID:27353290

  3. Biomolecular Nano-Flow-Sensor to Measure Near-Surface Flow

    Directory of Open Access Journals (Sweden)

    Noji Hiroyuki

    2009-01-01

    Full Text Available Abstract We have proposed and experimentally demonstrated that the measurement of the near-surface flow at the interface between a liquid and solid using a 10 nm-sized biomolecular motor of F1-ATPase as a nano-flow-sensor. For this purpose, we developed a microfluidic test-bed chip to precisely control the liquid flow acting on the F1-ATPase. In order to visualize the rotation of F1-ATPase, several hundreds nanometer-sized particle was immobilized at the rotational axis of F1-ATPase to enhance the rotation to be detected by optical microscopy. The rotational motion of F1-ATPase, which was immobilized on an inner surface of the test-bed chip, was measured to obtain the correlation between the near-surface flow and the rotation speed of F1-ATPase. As a result, we obtained the relationship that the rotation speed of F1-ATPase was linearly decelerated with increasing flow velocity. The mechanism of the correlation between the rotation speed and the near-surface flow remains unclear, however the concept to use biomolecule as a nano-flow-sensor was proofed successfully. (See supplementary material 1 Electronic supplementary material The online version of this article (doi:10.1007/s11671-009-9479-3 contains supplementary material, which is available to authorized users. Click here for file

  4. Nanoscale Biomolecular Detection Limit for Gold Nanoparticles Based on Near-Infrared Response

    Directory of Open Access Journals (Sweden)

    Mario D’Acunto

    2012-01-01

    Full Text Available Gold nanoparticles have been widely used during the past few years in various technical and biomedical applications. In particular, the resonance optical properties of nanometer-sized particles have been employed to design biochips and biosensors used as analytical tools. The optical properties of nonfunctionalized gold nanoparticles and core-gold nanoshells play a crucial role for the design of biosensors where gold surface is used as a sensing component. Gold nanoparticles exhibit excellent optical tunability at visible and near-infrared frequencies leading to sharp peaks in their spectral extinction. In this paper, we study how the optical properties of gold nanoparticles and core-gold nanoshells are changed as a function of different sizes, shapes, composition, and biomolecular coating with characteristic shifts towards the near-infrared region. We show that the optical tenability can be carefully tailored for particle sizes falling in the range 100–150 nm. The results should improve the design of sensors working at the detection limit.

  5. Solving the 0/1 Knapsack Problem by a Biomolecular DNA Computer

    Directory of Open Access Journals (Sweden)

    Hassan Taghipour

    2013-01-01

    Full Text Available Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.

  6. Extension of the GLYCAM06 Biomolecular Force Field to Lipids, Lipid Bilayers and Glycolipids.

    Science.gov (United States)

    Tessier, Matthew B; Demarco, Mari L; Yongye, Austin B; Woods, Robert J

    2008-01-01

    GLYCAM06 is a generalisable biomolecular force field that is extendible to diverse molecular classes in the spirit of a small-molecule force field. Here we report parameters for lipids, lipid bilayers and glycolipids for use with GLYCAM06. Only three lipid-specific atom types have been introduced, in keeping with the general philosophy of transferable parameter development. Bond stretching, angle bending, and torsional force constants were derived by fitting to quantum mechanical data for a collection of minimal molecular fragments and related small molecules. Partial atomic charges were computed by fitting to ensemble-averaged quantum-computed molecular electrostatic potentials.In addition to reproducing quantum mechanical internal rotational energies and experimental valence geometries for an array of small molecules, condensed-phase simulations employing the new parameters are shown to reproduce the bulk physical properties of a DMPC lipid bilayer. The new parameters allow for molecular dynamics simulations of complex systems containing lipids, lipid bilayers, glycolipids, and carbohydrates, using an internally consistent force field. By combining the AMBER parameters for proteins with the GLYCAM06 parameters, it is also possible to simulate protein-lipid complexes and proteins in biologically relevant membrane-like environments. PMID:22247593

  7. Bio-objectifying European bodies: standardisation of biobanks in the Biobanking and Biomolecular Resources Research Infrastructure.

    Science.gov (United States)

    Tamminen, Sakari

    2015-01-01

    The article traces the genealogy of the Minimum Information About Biobank Data Sharing model, created in the European Biobanking and Biomolecular Resources Research Infrastructure to facilitate collaboration among biobanks and to foster the exchange of biological samples and data. This information model is aimed at the identification of biobanks; unification of databases; and objectification of the information, samples, and related studies - to create a completely new 'bio-object infrastructure' within the EU. The paper discusses key challenges in creating a 'universal' information model of such a kind, the most important technical translations of European research policy needed for a standardised model for biobank information, and how this model creates new bio-objects. The author claims that this amounts to redefinition of biobanks and technical governance over virtually bio-objectified European populations. It is argued here that old governance models based on the nation-state need radical reconsideration so that we are prepared for a new and changing situation wherein bodies of information that lack organs flow from one database to another with a click of a mouse. PMID:26626620

  8. Indirect readout in protein-peptide recognition: a different story from classical biomolecular recognition.

    Science.gov (United States)

    Yu, Hua; Zhou, Peng; Deng, Maolin; Shang, Zhicai

    2014-07-28

    Protein-peptide interactions are prevalent and play essential roles in many living activities. Peptides recognize their protein partners by direct nonbonded interactions and indirect adjustment of conformations. Although processes of protein-peptide recognition have been comprehensively studied in both sequences and structures recently, flexibility of peptides and the configuration entropy penalty in recognition did not get enough attention. In this study, 20 protein-peptide complexes and their corresponding unbound peptides were investigated by molecular dynamics simulations. Energy analysis revealed that configurational entropy penalty introduced by restriction of the degrees of freedom of peptides in indirect readout process of protein-peptide recognition is significant. Configurational entropy penalty has become the main content of the indirect readout energy in protein-peptide recognition instead of deformation energy which is the main source of the indirect readout energy in classical biomolecular recognition phenomena, such as protein-DNA binding. These results provide us a better understanding of protein-peptide recognition and give us some implications in peptide ligand design.

  9. Magneto-optical relaxation measurements for the characterization of biomolecular interactions

    International Nuclear Information System (INIS)

    Measurements of the magneto-optical relaxation of ferrofluids (MORFF) were applied as a novel homogeneous immunoassay for the investigation of biomolecular interactions. The technique is based on magnetic nanoparticles (MNP) functionalized with antibodies. The relaxation time of the optical birefringence that occurs when a pulsed magnetic field is applied to the nanoparticle suspension depends on the particle size. This enables the detection of particle aggregates formed after the addition of the antigen coupling partner. MORFF size measurements on the original ferrofluid and its fractions obtained by magnetic fractionation are comparable with results from other methods such as atomic force microscopy and photon correlation spectroscopy. In kinetic studies, the binding properties of five antigens and their polyclonal antibodies were investigated: human immunoglobulin G (hIgG), human immunoglobulin M (hIgM), human Eotaxin (hEotaxin), human carcinoembryonic antigen (hCEA), and human insulin (hInsulin). The enlargement of the relaxation time observed during the coupling experiments is expressed in terms of a size distribution function, which includes MNP monomers as well as aggregates. The kinetic process can be described by a model of stepwise polymerization. The kinetic parameters obtained are compared to results of surface plasmon resonance measurements

  10. Bridge- and Solvent-Mediated Intramolecular Electronic Communications in Ubiquinone-Based Biomolecular Wires

    Science.gov (United States)

    Liu, Xiao-Yuan; Ma, Wei; Zhou, Hao; Cao, Xiao-Ming; Long, Yi-Tao

    2015-05-01

    Intramolecular electronic communications of molecular wires play a crucial role for developing molecular devices. In the present work, we describe different degrees of intramolecular electronic communications in the redox processes of three ubiquinone-based biomolecular wires (Bis-CoQ0s) evaluated by electrochemistry and Density Functional Theory (DFT) methods in different solvents. We found that the bridges linkers have a significant effect on the electronic communications between the two peripheral ubiquinone moieties and solvents effects are limited and mostly depend on the nature of solvents. The DFT calculations for the first time indicate the intensity of the electronic communications during the redox processes rely on the molecular orbital elements VL for electron transfer (half of the energy splitting of the LUMO and LUMO+1), which is could be affected by the bridges linkers. The DFT calculations also demonstrates the effect of solvents on the latter two-electron transfer of Bis-CoQ0s is more significant than the former two electrons transfer as the observed electrochemical behaviors of three Bis-CoQ0s. In addition, the electrochemistry and theoretical calculations reveal the intramolecular electronic communications vary in the four-electron redox processes of three Bis-CoQ0s.

  11. Potential-of-mean-force description of ionic interactions and structural hydration in biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Hummer, G.; Garcia, A.E. [Los Alamos National Lab., NM (United States). Theoretical Biology and Biophysics Group; Soumpasis, D.M. [Max-Planck-Inst for Biophysical Chemistry, Goettingen (Germany). Biocomputation Group

    1994-10-01

    To understand the functioning of living organisms on a molecular level, it is crucial to dissect the intricate interplay of the immense number of biological molecules. Most of the biochemical processes in cells occur in a liquid environment formed mainly by water and ions. This solvent environment plays an important role in biological systems. The potential-of-mean-force (PMF) formalism attempts to describe quantitatively the interactions of the solvent with biological macromolecules on the basis of an approximate statistical-mechanical representation. At its current status of development, it deals with ionic effects on the biomolecular structure and with the structural hydration of biomolecules. The underlying idea of the PMF formalism is to identify the dominant sources of interactions and incorporate these interactions into the theoretical formalism using PMF`s (or particle correlation functions) extracted from bulk-liquid systems. In the following, the authors shall briefly outline the statistical-mechanical foundation of the PMF formalism and introduce the PMF expansion formalism, which is intimately linked to superposition approximations for higher-order particle correlation functions. The authors shall then sketch applications, which describe the effects of the ionic environment on nucleic-acid structure. Finally, the authors shall present the more recent extension of the PMF idea to describe quantitatively the structural hydration of biomolecules. Results for the interface of ice and water and for the hydration of deoxyribonucleic acid (DNA) will be discussed.

  12. Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads

    Science.gov (United States)

    Stone, John E.; Hallock, Michael J.; Phillips, James C.; Peterson, Joseph R.; Luthey-Schulten, Zaida; Schulten, Klaus

    2016-01-01

    Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers.

  13. An Atomic Force Microscope with Dual Actuation Capability for Biomolecular Experiments

    Science.gov (United States)

    Sevim, Semih; Shamsudhin, Naveen; Ozer, Sevil; Feng, Luying; Fakhraee, Arielle; Ergeneman, Olgaç; Pané, Salvador; Nelson, Bradley J.; Torun, Hamdi

    2016-06-01

    We report a modular atomic force microscope (AFM) design for biomolecular experiments. The AFM head uses readily available components and incorporates deflection-based optics and a piezotube-based cantilever actuator. Jetted-polymers have been used in the mechanical assembly, which allows rapid manufacturing. In addition, a FeCo-tipped electromagnet provides high-force cantilever actuation with vertical magnetic fields up to 0.55 T. Magnetic field calibration has been performed with a micro-hall sensor, which corresponds well with results from finite element magnetostatics simulations. An integrated force resolution of 1.82 and 2.98 pN, in air and in DI water, respectively was achieved in 1 kHz bandwidth with commercially available cantilevers made of Silicon Nitride. The controller and user interface are implemented on modular hardware to ensure scalability. The AFM can be operated in different modes, such as molecular pulling or force-clamp, by actuating the cantilever with the available actuators. The electromagnetic and piezoelectric actuation capabilities have been demonstrated in unbinding experiments of the biotin-streptavidin complex.

  14. A new source for quantum optics with biomolecules and biomolecular clusters

    Science.gov (United States)

    Marksteiner, Markus; Haslinger, Philipp; Ulbricht, Hendrik; Arndt, Markus

    2008-03-01

    We present recent progress towards matter wave experiments with amino acids, polypeptides and large biomolecular clusters. All successful experiments on macromolecule interferometry so far, with fullerenes, fullerene derivates and large perfluoroalkyl-functionalized azobenzenes used effusive beam sources. The combination of Stark deflectometry with quantum interferometry also allowed us to create a new device for precisely measuring electric susceptibilities of large molecules in the gas phase. In order to apply quantum interference to molecules of biological interest, we have now implemented a pulsed laser desorption source. The combination of UV laser desorption into an intense noble gas jet and single-photon ionization by a VUV excimer laser (157nm) allows us to observe intense neutral jets of amino acids (e.g. Tryptophan), nucleotides (e.g. Guanin) and polypeptides ranging from tri-peptides to Gramicidin. Remarkably, we also found a new method for producing large neutral amino acid clusters, such as for instance Trp30, with masses exceeding 6000 amu: the addition of alkaline Earth salts in the desorption process leads to the inclusion of at least one metal atom per complex and is sufficient to catalyze the cluster formation process.

  15. Drug Transport Microdevice Mimicking an Idealized Nanoscale Bio-molecular Motor

    Institute of Scientific and Technical Information of China (English)

    Jae Hwan Lee; Ramana M. Pidaparti

    2011-01-01

    Molecular motors are nature's nano-devices and the essential agents of movement that are an integral part of many living organisms.The supramolecular motor,called Nuclear Pore Complex (NPC),controls the transport of all cellular material between the cytoplasm and the nucleus that occurs naturally in biological cells of many organisms.In order to understand the design characteristics of the NPC,we developed a microdevice for drug/fluidic transport mimicking the coarse-grained representation of the NPC geometry through computational fluid dynamic analysis and optimization.Specifically,the role of the central plug in active fluidic/particle transport and passive transport (without central plug) was investigated.Results of flow rate,pressure and velocity profiles obtained from the models indicate that the central plug plays a major role in transport through this biomolecular machine.The results of this investigation show that fluidic transport and flow passages are important factors in designing NPC based nano- and micro-devices for drug delivery.

  16. Polymerase Chain Reaction on a Viral Nanoparticle.

    Science.gov (United States)

    Carr-Smith, James; Pacheco-Gómez, Raúl; Little, Haydn A; Hicks, Matthew R; Sandhu, Sandeep; Steinke, Nadja; Smith, David J; Rodger, Alison; Goodchild, Sarah A; Lukaszewski, Roman A; Tucker, James H R; Dafforn, Timothy R

    2015-12-18

    The field of synthetic biology includes studies that aim to develop new materials and devices from biomolecules. In recent years, much work has been carried out using a range of biomolecular chassis including α-helical coiled coils, β-sheet amyloids and even viral particles. In this work, we show how hybrid bionanoparticles can be produced from a viral M13 bacteriophage scaffold through conjugation with DNA primers that can template a polymerase chain reaction (PCR). This unprecedented example of a PCR on a virus particle has been studied by flow aligned linear dichroism spectroscopy, which gives information on the structure of the product as well as a new protototype methodology for DNA detection. We propose that this demonstration of PCR on the surface of a bionanoparticle is a useful addition to ways in which hybrid assemblies may be constructed using synthetic biology.

  17. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    Science.gov (United States)

    Doster, W.; Nakagawa, H.; Appavou, M. S.

    2013-07-01

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at Td from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature Tg. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature Td.

  18. Morbillivirus infection in cetaceans stranded along the Italian coastline: pathological, immunohistochemical and biomolecular findings.

    Science.gov (United States)

    Di Guardo, Giovanni; Di Francesco, Cristina Esmeralda; Eleni, Claudia; Cocumelli, Cristiano; Scholl, Francesco; Casalone, Cristina; Peletto, Simone; Mignone, Walter; Tittarelli, Cristiana; Di Nocera, Fabio; Leonardi, Leonardo; Fernández, Antonio; Marcer, Federica; Mazzariol, Sandro

    2013-02-01

    Morbilliviruses are recognized as biological agents highly impacting the health and conservation status of free-ranging cetaceans worldwide, as clearly exemplified by the two Dolphin Morbillivirus (DMV) epidemics of 1990-1992 and 2006-2008 among Mediterranean striped dolphins (Stenella coeruleoalba). After these two epidemics, morbilliviral infection (MI) cases with peculiar neurobiological features were reported in striped dolphins stranded along the Spanish coastline. Affected cetaceans showed a subacute-to-chronic, non-suppurative encephalitis, with brain lesions strongly resembling those found in human "subacute sclerosing panencephalitis" and "old dog encephalitis". Brain was the only tissue in which morbilliviral antigen and/or genome could be detected. Beside a case of morbilliviral encephalitis in a striped dolphin's calf stranded in 2009, we observed 5 additional MI cases in 2 striped dolphins, 1 bottlenose dolphin (Tursiops truncatus) and 2 fin whales (Balaenoptera physalus), all stranded in 2011 along the Italian coastline. Noteworthy, 3 of these animals (2 striped dolphins and 1 bottlenose dolphin) showed immunohistochemical (IHC) and/or biomolecular (PCR) evidence of morbilliviral antigen and/or genome exclusively in their brain, with 1 striped dolphin and 1 bottlenose dolphin also exhibiting a non-suppurative encephalitis. Furthermore, simultaneous IHC and PCR evidence of a Toxoplasma gondii coinfection was obtained in 1 fin whale. The above results are consistent with those reported in striped dolphins after the two MI epidemics of 1990-92 and 2006-2008, with evidence of morbilliviral antigen and/or genome being found exclusively in the brain tissue from affected animals.

  19. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    Energy Technology Data Exchange (ETDEWEB)

    Doster, W. [Physik-Department, Technische Universität München, D-85748 Garching (Germany); Nakagawa, H. [Jülich Centre for Neutron Science, Forschungszentrum Jülich GmbH, Outstation at MLZ, Lichtenbergstraße 1, 85747 Garching (Germany); Japan Atomic Energy Agency, Quantum Beam Science Directorate, Tokai, Ibaraki 319-1195 (Japan); Appavou, M. S. [Jülich Centre for Neutron Science, Forschungszentrum Jülich GmbH, Outstation at MLZ, Lichtenbergstraße 1, 85747 Garching (Germany)

    2013-07-28

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at T{sub d} from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature T{sub g}. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature T{sub d}.

  20. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    International Nuclear Information System (INIS)

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at Td from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature Tg. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature Td

  1. Improved model of hydrated calcium ion for molecular dynamics simulations using classical biomolecular force fields.

    Science.gov (United States)

    Yoo, Jejoong; Wilson, James; Aksimentiev, Aleksei

    2016-10-01

    Calcium ions (Ca(2+) ) play key roles in various fundamental biological processes such as cell signaling and brain function. Molecular dynamics (MD) simulations have been used to study such interactions, however, the accuracy of the Ca(2+) models provided by the standard MD force fields has not been rigorously tested. Here, we assess the performance of the Ca(2+) models from the most popular classical force fields AMBER and CHARMM by computing the osmotic pressure of model compounds and the free energy of DNA-DNA interactions. In the simulations performed using the two standard models, Ca(2+) ions are seen to form artificial clusters with chloride, acetate, and phosphate species; the osmotic pressure of CaAc2 and CaCl2 solutions is a small fraction of the experimental values for both force fields. Using the standard parameterization of Ca(2+) ions in the simulations of Ca(2+) -mediated DNA-DNA interactions leads to qualitatively wrong outcomes: both AMBER and CHARMM simulations suggest strong inter-DNA attraction whereas, in experiment, DNA molecules repel one another. The artificial attraction of Ca(2+) to DNA phosphate is strong enough to affect the direction of the electric field-driven translocation of DNA through a solid-state nanopore. To address these shortcomings of the standard Ca(2+) model, we introduce a custom model of a hydrated Ca(2+) ion and show that using our model brings the results of the above MD simulations in quantitative agreement with experiment. Our improved model of Ca(2+) can be readily applied to MD simulations of various biomolecular systems, including nucleic acids, proteins and lipid bilayer membranes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 752-763, 2016. PMID:27144470

  2. An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution

    Energy Technology Data Exchange (ETDEWEB)

    Fluitt, Aaron M. [Univ. of Chicago, IL (United States); de Pablo, Juan J. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2015-09-01

    Polyglutamine (polyQ) peptides are a useful model system for biophysical studies of protein folding and aggregation, both for their intriguing aggregation properties and their own relevance to human disease. The genetic expansion of a polyQ tract triggers the formation of amyloid aggregates associated with nine neurodegenerative diseases. Several clearly identifiable and separable factors, notably the length of the polyQ tract, influence the mechanism of aggregation, its associated kinetics, and the ensemble of structures formed. Atomistic simulations are well positioned to answer open questions regarding the thermodynamics and kinetics of polyQ folding and aggregation. The additional, explicit representation of water permits deeper investigation of the role of solvent dynamics, and it permits a direct comparison of simulation results with infrared spectroscopy experiments. The generation of meaningful simulation results hinges on satisfying two essential criteria: achieving sufficient conformational sampling to draw statistically valid conclusions, and accurately reproducing the intermolecular forces that govern system structure and dynamics. In this work, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30-residue polyQ peptide (Q30) in explicit water. In addition to secondary and tertiary structure, we consider generic structural properties of polymers that provide additional dimensions for analysis of the highly degenerate disordered states of the molecule. We find that the 12 force fields produce a wide range of predictions. We identify AMBER ff99SB, AMBER ff99SB*, and OPLS-AA/L to be most suitable for studies of polyQ folding and aggregation.

  3. Enthalpy-entropy compensation in biomolecular halogen bonds measured in DNA junctions.

    Science.gov (United States)

    Carter, Megan; Voth, Andrea Regier; Scholfield, Matthew R; Rummel, Brittany; Sowers, Lawrence C; Ho, P Shing

    2013-07-23

    Interest in noncovalent interactions involving halogens, particularly halogen bonds (X-bonds), has grown dramatically in the past decade, propelled by the use of X-bonding in molecular engineering and drug design. However, it is clear that a complete analysis of the structure-energy relationship must be established in biological systems to fully exploit X-bonds for biomolecular engineering. We present here the first comprehensive experimental study to correlate geometries with their stabilizing potentials for fluorine (F), chlorine (Cl), bromine (Br), or iodine (I) X-bonds in a biological context. For these studies, we determine the single-crystal structures of DNA Holliday junctions containing halogenated uracil bases that compete X-bonds against classic hydrogen bonds (H-bonds), estimate the enthalpic energies of the competing interactions in the crystal system through crystallographic titrations, and compare the enthalpic and entropic energies of bromine and iodine X-bonds in solution by differential scanning calorimetry. The culmination of these studies demonstrates that enthalpic stabilization of X-bonds increases with increasing polarizability from F to Cl to Br to I, which is consistent with the σ-hole theory of X-bonding. Furthermore, an increase in the X-bonding potential is seen to direct the interaction toward a more ideal geometry. However, the entropic contributions to the total free energies must also be considered to determine how each halogen potentially contributes to the overall stability of the interaction. We find that bromine has the optimal balance between enthalpic and entropic energy components, resulting in the lowest free energy for X-bonding in this DNA system. The X-bond formed by iodine is more enthalpically stable, but this comes with an entropic cost, which we attribute to crowding effects. Thus, the overall free energy of an X-bonding interaction balances the stabilizing electrostatic effects of the σ-hole against the competing

  4. Biomolecularly capped uniformly sized nanocrystalline materials: glutathione-capped ZnS nanocrystals

    Science.gov (United States)

    Torres-Martínez, Claudia L.; Nguyen, Liem; Kho, Richard; Bae, Weon; Bozhilov, Krassimir; Klimov, Victor; Mehra, Rajesh K.

    1999-09-01

    Micro-organisms such as bacteria and yeasts form CdS to detoxify toxic cadmium ions. Frequently, CdS particles formed in yeasts and bacteria were found to be associated with specific biomolecules. It was later determined that these biomolecules were present at the surface of CdS. This coating caused a restriction in the growth of CdS particles and resulted in the formation of nanometre-sized semiconductors (NCs) that exhibited typical quantum confinement properties. Glutathione and related phytochelatin peptides were shown to be the biomolecules that capped CdS nanocrystallites synthesized by yeasts Candida glabrata and Schizosaccharomyces pombe. Although early studies showed the existence of specific biochemical pathways for the synthesis of biomolecularly capped CdS NCs, these NCs could be formed in vitro under appropriate conditions. We have recently shown that cysteine and cysteine-containing peptides such as glutathione and phytochelatins can be used in vitro to dictate the formation of discrete sizes of CdS and ZnS nanocrystals. We have evolved protocols for the synthesis of ZnS or CdS nanocrystals within a narrow size distribution range. These procedures involve three steps: (1) formation of metallo-complexes of cysteine or cysteine-containing peptides, (2) introduction of stoichiometric amounts of inorganic sulfide into the metallo-complexes to initiate the formation of nanocrystallites and finally (3) size-selective precipitation of NCs with ethanol in the presence of Na+. The resulting NCs were characterized by optical spectroscopy, high-resolution transmission electron microscopy (HRTEM), x-ray diffraction and electron diffraction. HRTEM showed that the diameter of the ZnS-glutathione nanocrystals was 3.45+/-0.5 nm. X-ray diffraction and electron diffraction analyses indicated ZnS-glutathione to be hexagonal. Photocatalytic studies suggest that glutathione-capped ZnS nanocrystals prepared by our procedure are highly efficient in degrading a test model

  5. Reaction mechanism and reaction coordinates from the viewpoint of energy flow.

    Science.gov (United States)

    Li, Wenjin; Ma, Ao

    2016-03-21

    Reaction coordinates are of central importance for correct understanding of reaction dynamics in complex systems, but their counter-intuitive nature made it a daunting challenge to identify them. Starting from an energetic view of a reaction process as stochastic energy flows biased towards preferred channels, which we deemed the reaction coordinates, we developed a rigorous scheme for decomposing energy changes of a system, both potential and kinetic, into pairwise components. The pairwise energy flows between different coordinates provide a concrete statistical mechanical language for depicting reaction mechanisms. Application of this scheme to the C7eq → C7ax transition of the alanine dipeptide in vacuum revealed novel and intriguing mechanisms that eluded previous investigations of this well studied prototype system for biomolecular conformational dynamics. Using a cost function developed from the energy decomposition components by proper averaging over the transition path ensemble, we were able to identify signatures of the reaction coordinates of this system without requiring any input from human intuition.

  6. Reaction mechanism and reaction coordinates from the viewpoint of energy flow

    Science.gov (United States)

    Li, Wenjin; Ma, Ao

    2016-03-01

    Reaction coordinates are of central importance for correct understanding of reaction dynamics in complex systems, but their counter-intuitive nature made it a daunting challenge to identify them. Starting from an energetic view of a reaction process as stochastic energy flows biased towards preferred channels, which we deemed the reaction coordinates, we developed a rigorous scheme for decomposing energy changes of a system, both potential and kinetic, into pairwise components. The pairwise energy flows between different coordinates provide a concrete statistical mechanical language for depicting reaction mechanisms. Application of this scheme to the C7eq → C7ax transition of the alanine dipeptide in vacuum revealed novel and intriguing mechanisms that eluded previous investigations of this well studied prototype system for biomolecular conformational dynamics. Using a cost function developed from the energy decomposition components by proper averaging over the transition path ensemble, we were able to identify signatures of the reaction coordinates of this system without requiring any input from human intuition.

  7. Evaluation of kinetic constants of biomolecular interaction on optical surface plasmon resonance sensor with Newton Iteration Method

    Science.gov (United States)

    Zhao, Yuanyuan; Jiang, Guoliang; Hu, Jiandong; Hu, Fengjiang; Wei, Jianguang; Shi, Liang

    2010-10-01

    In the immunology, there are two important types of biomolecular interaction: antigens-antibodies and receptors-ligands. Monitoring the response rate and affinity of biomolecular interaction can help analyze the protein function, drug discover, genomics and proteomics research. Moreover the association rate constant and dissociation rate constant of receptors-ligands are the important parameters for the study of signal transmission between cells. Recent advances in bioanalyzer instruments have greatly simplified the measurement of the kinetics of molecular interactions. Non-destructive and real-time monitoring the response to evaluate the parameters between antigens and antibodies can be performed by using optical surface plasmon resonance (SPR) biosensor technology. This technology provides a quantitative analysis that is carried out rapidly with label-free high-throughput detection using the binding curves of antigens-antibodies. Consequently, the kinetic parameters of interaction between antigens and antibodies can be obtained. This article presents a low cost integrated SPR-based bioanalyzer (HPSPR-6000) designed by ourselves. This bioanalyzer is mainly composed of a biosensor TSPR1K23, a touch-screen monitor, a microprocessor PIC24F128, a microflow cell with three channels, a clamp and a photoelectric conversion device. To obtain the kinetic parameters, sensorgrams may be modeled using one of several binding models provided with BIAevaluation software 3.0, SensiQ or Autolab. This allows calculation of the association rate constant (ka) and the dissociation rate constant (kd). The ratio of ka to kd can be used to estimate the equilibrium constant. Another kind is the analysis software OriginPro, which can process the obtained data by nonlinear fitting and then get some correlative parameters, but it can't be embedded into the bioanalyzer, so the bioanalyzer don't support the use of OriginPro. This paper proposes a novel method to evaluate the kinetic parameters

  8. Heuristics-Guided Exploration of Reaction Mechanisms

    CERN Document Server

    Bergeler, Maike; Proppe, Jonny; Reiher, Markus

    2015-01-01

    For the investigation of chemical reaction networks, the efficient and accurate determination of all relevant intermediates and elementary reactions is inevitable. The complexity of such a network may grow rapidly, in particular if reactive species are involved that might cause a myriad of side reactions. Without automation, a complete investigation of complex reaction mechanisms is tedious and possibly unfeasible. Therefore, only the expected dominant reaction paths of a chemical reaction network (e.g., a catalytic cycle or an enzymatic cascade) are usually explored in practice. Here, we present a computational protocol that constructs such networks in a parallelized and automated manner. Molecular structures of reactive complexes are generated based on heuristic rules and subsequently optimized by electronic-structure methods. Pairs of reactive complexes related by an elementary reaction are then automatically detected and subjected to an automated search for the connecting transition state. The results are...

  9. Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

    Directory of Open Access Journals (Sweden)

    Kaznessis Yiannis N

    2007-01-01

    Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

  10. Catalytic Oxidized Reaction of Paraffin Wax Based on BP Neural Network%基于BP神经网络的石蜡催化氧化反应的研究

    Institute of Scientific and Technical Information of China (English)

    黄玮; 丛玉凤; 郭大鹏

    2012-01-01

    The oxidized wax was prepared by catalytic oxidized reaction of paraffin wax which used BP neural network to build mathematical model of acid value and saponification value influenced by the amount of reactive catalyst and accessory ingredient, airflow rate, reaction temperature and time, and utilized the model of neutral network to calculate the technology condition of preparing oxidized wax through catalyzing and oxidizing paraffin wax. Consequently, optimum technology conditions were gained in order to achieve the objective of reducing experimental number of times.%在石蜡催化氧化反应制备氧化蜡的研究中,利用BP神经网络建立反应催化剂用量、助剂用量、空气流量、反应温度和反应时间对酸值和皂化值影响的数学模型,并利用该神经网络模型对石蜡催化氧化制备氧化蜡的工艺条件进行预测,从而获得最优工艺条件,达到缩短实验次数的目的.

  11. The network of antigen-antibody reactions in adult women with breast cancer or benign breast pathology or without breast pathology.

    Directory of Open Access Journals (Sweden)

    Tania Romo-González

    Full Text Available The Immunoglobulin G (IgG antibody response to different protein antigens of the mammary ductal carcinoma by adult women affected by Breast Cancer (BC distinguishes at least 103 proteins that differ in their molecular weights (MW. The IgG producing cell clones (nodes coexist with each other in each individual organism and share energy resources among themselves, as well as factors that control the level of expression and Specificity of their IgG antibodies. So, it can be proposed that among them there is a Network of interconnections (links unveiled by the antigens, which specifically react with the IgG antibodies produced by the clones. This Network possibly regulates IgG antibodies' activity and effectiveness. We describe the Network of nodes and links that exists between the different antigens and their respective IgG producing cell clones against the extracted protein antigens from the cells of the T47D Cell-Line, in 50 women with BC, 50 women with Benign Breast Pathology (BBP and 50 women without breast pathology (H. We have found that women with BBP have the highest number of Links, followed by the H group and, lastly, the women with BC, a finding which suggests that cancer interferes with the Connectivity between the IgG producing cell clones and blocks the expression of 322 links in women with BBP and 32 links in women with H. It is also plausible that the largest number of links in the women with BBP indicates the Network's state of arousal that provides protection against BC. On the other hand, there were many missing links in the BC group of women; the clone which lost more links in the BC group was the hub 24, which point to some of the antigens of T47D as potentially useful as vaccines, as the immune system of women with BBP is well aware of them.

  12. Unraveling the biomolecular snapshots of mitosis in healthy and cancer cells using plasmonically-enhanced Raman spectroscopy.

    Science.gov (United States)

    Panikkanvalappil, Sajanlal R; Hira, Steven M; Mahmoud, Mahmoud A; El-Sayed, Mostafa A

    2014-11-12

    Owing to the dynamic and complex nature of mitosis, precise and timely executions of biomolecular events are critical for high fidelity cell division. In this context, visualization of such complex events at the molecular level can provide vital information on the biomolecular processes in abnormal cells. Here, we explored the plasmonically enhanced light scattering properties of functionalized gold nanocubes (AuNCs) together with surface-enhanced Raman spectroscopy (SERS) to unravel the complex and dynamic biological processes involved in mitosis of healthy and cancerous cells from its molecular perspectives. By monitoring various stages of mitosis using SERS, we noticed that relatively high rate of conversion of mitotic proteins from their α-helix structure to β-sheet conformation is likely in the cancer cells during meta-, ana-, and telophases. Unique biochemical modifications to the lipid and amino acid moieties, associated with the observed protein conformational modifications, were also identified. However, in healthy cells, the existence of proteins in their β conformation was momentary and was largely in the α-helix form. The role of abnormal conformational modifications of mitotic proteins on the development of anomalous mitotic activities was further confirmed by looking at plasmonic nanoparticle-induced cytokinesis failure in cancer cells. Our findings illustrate the vast possibilities of SERS in real-time tracking of complex, subtle, and momentary modifications of biomolecules in live cells, which could provide new insights to the role of protein conformation dynamics during mitosis on the development of cancer and many other diseases.

  13. Real-time and label-free detection of biomolecular interactions by oblique-incidence reflectivity difference method

    Science.gov (United States)

    Wang, Xu; Lu, Heng; Dai, Jun; Wen, Juan; Yuan, Kun; Lü, Hui-Bin; Jin, Kui-Juan; Zhou, Yue-Liang; Yang, Guo-Zhen

    2011-01-01

    We successfully conduct the label-free and real-time detection of the interactions between epoxy groups and rabbit IgG and 5' CTT CAG GTC ATG AGC CTG AT 3' oligonucleotide, and between the hybridization of 5' CTT CAG GTC ATG AGC CTG AT 3' and its complementary 3' GAA GTC CAG TAC TCG GAC TA 5' oligonucleotide, by the oblique-incidence reflectivity difference (OI-RD) method. The dynamic curves of OI-RD signals, corresponding to the kinetic processes of biomolecular combination or hybridization, are acquired. In our case, the combination of epoxy groups with rabbit IgG and 5' CTT CAG GTC ATG AGC CTG AT 3' oligonucleotide need almost one and a half hours and about two hundred seconds, respectively; and the hybridization of the two oligonucleotides needs about five hundred seconds. The experimental results show that the OI-RD is a promising method for the real-time and label-free detection of biomolecular interactions.

  14. Production and detection of neutral molecular beams : from single amino acids to biomolecular complexes

    International Nuclear Information System (INIS)

    biomolecular complexes. The largest observed complex is a gramicidin tetramer with a mass of 7,536amu. Furthermore, desorption of tryptophan together with alkaline earth salts, such as calcium-carbonate results in the formation of two different kinds of massive tryptophan clusters: Tryptophan clusters containing a single calcium atom with a mass of up to 6,800amu and also pure clusters with a mass of up to 7,100amu are observed. The inclusion of a metal atom into tryptophan clusters is observed also for strontium, barium ,sodium and copper. The cluster formation is studied additionally for other amino acids such as phenylalanine, the tripeptide tyrosine-tryptophan-glycine and the nucleotide guanine. The cluster formation between two different molecular species was observed after the simultaneous desorption of gramicidin and tryptophan and resulted in the attachment of tryptophan molecules to a single gramicidin. An alternative detection method to photo-ionization is examined by testing a superconducting single photon detector (SSPD) for its ability to detect individual neutral molecules. The sensitivity of the nanostructured SSPD seems not to be limited to small molecules. The superconducting detector is able to record velocity distributions of neutral insulin (∼5,700amu), myoglobin(∼17 kDa) and hemoglobin (∼66 kDa) beams. A check if the intact molecules leave the source is missing due to the lack of alternative detection methods for these molecules. The working principle of the SSPD relies on the fact, that an impinging particle leads to a breakdown of superconductivity. Further developments of the SSPD appear possible and promising in order to increase the mass range of detected neutral organic molecules, which cannot be detected in photo-ionization. The source is developed in order to fulfil the criteria needed for a combination with a Talbot-Lau interferometer. Interference of biomolecules is, beside the prove of the wave-particle duality, interesting for the

  15. Expanding the scope of CE reactor to ssDNA-binding protein-ssDNA complexes as exemplified for a tool for direct measurement of dissociation kinetics of biomolecular complexes.

    Science.gov (United States)

    Takahashi, Toru; Ohtsuka, Kei-Ichirou; Tomiya, Yoriyuki; Iki, Nobuhiko; Hoshino, Hitoshi

    2009-09-01

    CE reactor (CER), which was developed as a tool for direct measurement of the dissociation kinetics of metal complexes, was successfully applied to the complexes of Escherichia coli ssDNA-binding protein (SSB) with ssDNA. The basic concept of CER is the application of CE separation process as a dissociation kinetic reactor for the complex, and the observation of the on-capillary dissociation reaction profile of the complex as the decrease of the peak height of the complex with increase of the migration time. The peak height of [SSB-ssDNA] decreases as the migration time increases since the degree of the decrease of [SSB-ssDNA] through the on-capillary dissociation reaction is proportional to the degree of the decrease of the peak height of [SSB-ssDNA]. The dissociation degree-time profiles for the complexes are quantitatively described by analyzing a set of electropherograms with different migration times. Dissociation rate constants of [SSB-ssDNA] consisting of 20-mer, 25-mer and 31-mer ssDNA were directly determined to be 3.99x10(-4), 4.82x10(-4) and 1.50x10(-3)/s, respectively. CER is a concise and effective tool for dissociation kinetic analysis of biomolecular complexes.

  16. Survey of Network-Based Approaches to Research of Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Anida Sarajlić

    2014-01-01

    Full Text Available Cardiovascular diseases (CVDs are the leading health problem worldwide. Investigating causes and mechanisms of CVDs calls for an integrative approach that would take into account its complex etiology. Biological networks generated from available data on biomolecular interactions are an excellent platform for understanding interconnectedness of all processes within a living cell, including processes that underlie diseases. Consequently, topology of biological networks has successfully been used for identifying genes, pathways, and modules that govern molecular actions underlying various complex diseases. Here, we review approaches that explore and use relationships between topological properties of biological networks and mechanisms underlying CVDs.

  17. Study of castor oil polyurethane - poly(methyl methacrylate semi-interpenetrating polymer network (SIPN reaction parameters using a 2³ factorial experimental design

    Directory of Open Access Journals (Sweden)

    Fernanda Oliveira Vieira da Cunha

    2004-12-01

    Full Text Available In this work was employed a 2³ factorial experiment design to evaluate the castor oil polyurethane-poly(methyl methacrylate semi-IPN synthesis. The reaction parameters used as independent variables were NCO/OH molar ratio, polyurethane polymerization time and methyl methacrylate (MMA content. The semi-IPNs were cured over 28 h using two thermal treatments. The polymers were characterized by infrared and Raman spectroscopy, thermal analysis and swelling profiles in n-hexane. The glass transition temperature (Tg and the swelling were more affect by the NCO/OH molar ratio variation. The semi-IPNs showed Tg from - 27 to - 6 °C and the swelling range was from 3 to 22%, according to the crosslink density. The IPN mechanical properties were dependent on the cure temperature and MMA content in it. Lower elastic modulus values were observed in IPNs cured at room temperature.

  18. 利用回声状态网络建立管式聚合反应的灰箱模型%An approach of grey-box modeling with echo state network for tubular polymerization reaction

    Institute of Scientific and Technical Information of China (English)

    秦松; 曹柳林

    2014-01-01

    提出一种利用回声状态网络(echo state network, ESN)建立复杂分布参数系统模型的灰箱建模方法。此建模方法可以充分利用已知机理模型的结构信息和回声状态网络的逼近能力,可更好地描述和解释出系统各变量之间的因果关系,使模型的“灰箱”化程度更高。首先,根据系统方程和先验知识将初始系统特征团引入ESN储备池中,赋予网络节点实际物理意义,并以此建立结构逼近神经网络模型;然后,通过逐步回归分析方法,结合递归最小二乘算法选择最优系统特征团,并对网络结构进行优化,建立起描述系统特性关系的灰箱模型。本文以实验室规模的管式聚合反应过程作为实验对象,建立以温度分布为输出的数学模型,结果表明所提出的灰箱建模方法行之有效。%An approach of grey-box modeling with Echo State Network (ESN) is developed for modeling dynamic processes with nonlinear characteristics. This method can take full advantage of the already known structural information of the mechanism model at the early stage of modeling and make better use of the approximation ability of neural networks, thus resulting in higher accuracy of grey-box modeling. By combination the prior knowledge and systematic equations into ESN state pool, structure approaching neural network (SAAN) is established based on system feature block, and it is given actual significance. Then the optimal fundamental genes were chosen through recursive least square method with stepwise regression analysis to optimize the structure of SANN, so as to get the grey-box model. Detailed process of modeling was described in modeling of tubular polymerization reaction in laboratory scale. The simulation result proves that the approach is effective.ocesses heat exchanger network synthesis by taking place.

  19. PUPIL: A Software Integration System for Multi-Scale QM/MM-MD Simulations and Its Application to Biomolecular Systems.

    Science.gov (United States)

    Torras, Juan; Roberts, Benjamin P; Seabra, Gustavo M; Trickey, Samuel B

    2015-01-01

    PUPIL (Program for User Package Interfacing and Linking) implements a distinctive multi-scale approach to hybrid quantum mechanical/molecular mechanical molecular dynamics (QM/MM-MD) simulations. Originally developed to interface different external programs for multi-scale simulation with applications in the materials sciences, PUPIL is finding increasing use in the study of complex biological systems. Advanced MD techniques from the external packages can be applied readily to a hybrid QM/MM treatment in which the forces and energy for the QM region can be computed by any of the QM methods available in any of the other external packages. Here, we give a survey of PUPIL design philosophy, main features, and key implementation decisions, with an orientation to biomolecular simulation. We discuss recently implemented features which enable highly realistic simulations of complex biological systems which have more than one active site that must be treated concurrently. Examples are given.

  20. Diffusion Monte Carlo applied to weak interactions - hydrogen bonding and aromatic stacking in (bio-)molecular model systems

    Science.gov (United States)

    Fuchs, M.; Ireta, J.; Scheffler, M.; Filippi, C.

    2006-03-01

    Dispersion (Van der Waals) forces are important in many molecular phenomena such as self-assembly of molecular crystals or peptide folding. Calculating this nonlocal correlation effect requires accurate electronic structure methods. Usual density-functional theory with generalized gradient functionals (GGA-DFT) fails unless empirical corrections are added that still need extensive validation. Quantum chemical methods like MP2 and coupled cluster are more accurate, yet limited to rather small systems by their unfavorable computational scaling. Diffusion Monte Carlo (DMC) can provide accurate molecular total energies and remains feasible also for larger systems. Here we apply the fixed-node DMC method to (bio-)molecular model systems where dispersion forces are significant: (dimethyl-) formamide and benzene dimers, and adenine-thymine DNA base pairs. Our DMC binding energies agree well with data from coupled cluster (CCSD(T)), in particular for stacked geometries where GGA-DFT fails qualitatively and MP2 predicts too strong binding.

  1. Biomolecular solvation study of proteins in liquid water by a wide range gigahertz-to-terahertz spectroscopy

    Science.gov (United States)

    Charkhesht, Ali; George, Deepu; Nguyen, Vinh

    Solvent dynamics within biomolecular solvation layers play a major role in enzyme activity, but obtaining an accurate and quantitative picture of solvent activity around proteins is challenging. Due to the strong absorption of water in the gigahertz-to-terahertz frequencies, it is challenging to study properties of the solvent dynamics as well as conformational changes protein in water. We have developed a highly sensitive dielectric gigahertz-to-terahertz frequency-domain spectroscopy system for probing the collective dynamics of proteins and solvent. Using this technique, we investigate the complex dielectric response of bovine serum albumin and lysozyme proteins in aqueous environment on a wide frequency range from 0.1 GHz up to 2 THz. We explore the conformation flexibility of proteins and compare the hydration dynamics around proteins to understand the effects of surface-mediated solvent dynamics, relationships among different measures of interfacial solvent dynamics, and protein-mediated solvent dynamics.

  2. Evaluation of Pore Networks in Caprocks at Geologic Storage Sites: A Combined Study using High Temperature and Pressure Reaction Experiments, Small Angle Neutron Scattering, and Focused Ion Beam-Scanning Electron Microscopy

    Science.gov (United States)

    Mouzakis, K. M.; Sitchler, A.; Wang, X.; McCray, J. E.; Kaszuba, J. P.; Rother, G.; Dewers, T. A.; Heath, J. E.

    2011-12-01

    Low permeability rock units, often shales or mudstones, that overlie geologic formations under consideration for CO2 sequestration will help contain injected CO2. CO2 that does flow through these rocks will dissolve into the porewaters, creating carbonic acid lowering the pH. This perturbation of the system may result in mineral dissolution or precipitation, which can change the pore structure and impact the flow properties of the caprocks. In order to investigate the impacts that reaction can have on caprock pore structure, we performed a combination of high pressure high temperature reaction experiments, small angle neutron scattering (SANS) experiments and high resolution focused ion beam-scanning electron microscope (FIB-SEM) imaging on samples from the Gothic shale and Marine Tuscaloosa Group. Small angle neutron scattering was performed on unreacted and reacted caprocks at the High Flux Isotope Reactor at Oak Ridge National Laboratory. New precipitates and pores are observed in high-resolution images of the reacted samples. The precipitates have been preliminarily identified as gypsum or anhydrite, and sulfide minerals. Results from small angle neutron scattering, a technique that provides information about pores and pore/mineral interfaces at scales ~ 5 to 300 nm, show an increased porosity and specific surface area after reaction with brine and CO2. However, there appear to be differences in how the pore networks change between the two samples that are related to sample mineralogy and original pore network structure. Changes to pores and formation of new pores may lead to different capillary sealing behavior and permeability. This combination of controlled laboratory experiments, neutron scattering and high-resolution imaging provides detailed information about the geochemical processes that occur at the pore scale as CO2 reacts with rocks underground. Such information is integral to the evaluation of large-scale CO2 sequestration as a feasible technology

  3. Flavin mononucleotide biomolecular laser: longitudinal mode structure, polarization, and temporal characteristics as probes of local chemical environment.

    Science.gov (United States)

    Rivera, José A; Eden, J Gary

    2016-05-16

    A detailed characterization of the flavin mononucleotide (FMN) biomolecular laser, optically pumped in a stable resonator, is reported here. Photoexcitation of the molecule at 355 nm results in lasing over the ~566.5-573.5 nm spectral region, and the threshold pump energy density is measured to be 110 ± 10 µJ/mm2 for a 10 mM FMN/water solution. Over twenty longitudinal modes are observed when the cavity length L and the energy pump fluence Ep are 375 µm and 300 µJ/mm2, respectively. Partial substitution of glycerol for water as the solvent results in a factor of four reduction in the threshold pump energy fluence (to 2) and a quadrupling of the slope efficiency. This effect is attributed to the O2 - mediated photoconversion of FMN molecules in the triplet state to the singlet species. For pump intensities a factor of 2.5 above threshold, the laser pulse width is ~2 ns FWHM, and the output intensity decays exponentially with a photon lifetime of 1.7 ns. The addition of glycerol to a FMN/water solution also suppresses s-polarized emission (yielding P = 0.78 ± 0.08), presumably as a result of the inhibition of FMN rotational diffusion. The sensitivity of the spectral and optical properties of this and other biomolecular lasers to the chemical environment underscores the value of coherent emission as a biochemical or biomedical diagnostic tool, particularly insofar as molecule-molecule interactions are concerned. PMID:27409906

  4. A Unified Monte Carlo Treatment of Gas-Grain Chemistry for Large Reaction Networks. II. A Multiphase Gas-Surface-Layered Bulk Model

    CERN Document Server

    Vasyunin, A I

    2012-01-01

    The observed gas-phase molecular inventory of hot cores is believed to be significantly impacted by the products of chemistry in interstellar ices. In this study, we report the construction of a full macroscopic Monte Carlo model of both the gas-phase chemistry and the chemistry occurring in the icy mantles of interstellar grains. Our model treats icy grain mantles in a layer-by-layer manner, which incorporates laboratory data on ice desorption correctly. The ice treatment includes a distinction between a reactive ice surface and an inert bulk. The treatment also distinguishes between zeroth and first order desorption, and includes the entrapment of volatile species in more refractory ice mantles. We apply the model to the investigation of the chemistry in hot cores, in which a thick ice mantle built up during the previous cold phase of protostellar evolution undergoes surface reactions and is eventually evaporated. For the first time, the impact of a detailed multilayer approach to grain mantle formation on ...

  5. High energy halogen atom reactions activated by nuclear transformations. Progress report, February 15, 1980-February 14, 1981

    International Nuclear Information System (INIS)

    The stereochemistry of high energy 18F, /sup 34m/Cl, and 76Br substitution reactions involving enantiomeric molecules in the gas and condensed phase is studied. The gas to condensed state transition in halogen high energy chemistry, involving chlorine, bromine, and iodine activated by the (n,γ) and (I.T.) processes in halomethanes, saturated and unsaturated hydrocarbons is being investigated in more detail. Special attention is given to defining the nature of the enhancement yields in the condensed phase. High energy halogen reactions in liquid and frozen aqueous solutions of organic and biomolecular solutes are studied in an attempt to learn more about these reactions. The applications of high energy chemistry techniques and theory to neutron activation analysis of biological systems are being continued. Special attention is given to developing procedures for trace molecular determinations in biological systems. The applications of hot halogen atoms as indicators of solute-solute interactions in liquid and frozen aqueous solutions of halogenated bases and nucleosides are being developed. Experiments are designed to explain the mechanisms of the radioprotection offered biomolecular solutes trapped within the frozen ice lattice. Reactions of bromine and iodine activated by isomeric transition with halogenated biomolecular solutes in liquid and frozen aqueous solutions are studied. The high energy reactions of iodine with the isomers of pentene have been studied in low pressure gaseous systems employing additives and rare gas moderators and liquid systems. Reactivity of excited complex formation and structural effects of electrophilic iodine attack on the pi-bond systems are studied

  6. Piezonuclear Reactions

    CERN Document Server

    Cardone, Fabio; Petrucci, Andrea

    2010-01-01

    In this paper, we deal with the subject of piezonuclear reactions, namely nuclear reactions (of new type) triggered by pressure waves. We discuss the experimental evidences obtained in the last two decades, which can be summarized essentially as follows: experiments in cavitation of liquids, where transmutation of elements, creation of elements and emission of neutrons have been observed; emission of neutrons in brittle failure of solids subjected to mechanical pressure; alteration of the lifetime of un unstable element (thorium) subjected to cavitation. A theoretical model to explain these facts is proposed. Future perspectives of these experimental and theoretical investigations are also underlined.

  7. "Clickable" Polymeric Nanofibers through Hydrophilic-Hydrophobic Balance: Fabrication of Robust Biomolecular Immobilization Platforms.

    Science.gov (United States)

    Kalaoglu-Altan, Ozlem I; Sanyal, Rana; Sanyal, Amitav

    2015-05-11

    Fabrication of hydrophilic polymeric nanofibers that undergo facile and selective functionalization through metal catalyst-free Diels-Alder "click" reaction in aqueous environment is outlined. Electrospinning of copolymers containing an electron-rich furan moiety, hydrophobic methyl methacrylate units and hydrophilic poly(ethylene glycol)s as side chains provide specifically functionalizable yet antibiofouling fibers that remain stable in aqueous media due to appropriate hydrophobic hydrophilic balance. Efficient functionalization of these nanofibers is accomplished through the Diels-Alder reaction by exposing them to maleimide-containing molecules and ligands. Diels-Alder conjugation based functionalization is demonstrated through attachment of fluorescein-maleimide and a maleimide tethered biotin ligand. Biotinylated nanofibers were utilized to mediate immobilization of the protein streptavidin, as well as streptavidin coated quantum dots. Facile fabrication from readily available polymers and their effective functionalization under mild and reagent-free conditions in aqueous media make these "clickable" nanofibers attractive candidates as functionalizable scaffolds for various biomedical applications.

  8. Networks in cognitive science.

    Science.gov (United States)

    Baronchelli, Andrea; Ferrer-i-Cancho, Ramon; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

    2013-07-01

    Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences.

  9. Networks in Cognitive Science

    CERN Document Server

    Baronchelli, Andrea; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

    2013-01-01

    Networks of interconnected nodes have long played a key role in cognitive science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions or collaborations among scientists. Today, the inclusion of network theory into cognitive sciences, and the expansion of complex systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the cognitive sciences.

  10. GraphAlignment: Bayesian pairwise alignment of biological networks

    Directory of Open Access Journals (Sweden)

    Kolář Michal

    2012-11-01

    Full Text Available Abstract Background With increased experimental availability and accuracy of bio-molecular networks, tools for their comparative and evolutionary analysis are needed. A key component for such studies is the alignment of networks. Results We introduce the Bioconductor package GraphAlignment for pairwise alignment of bio-molecular networks. The alignment incorporates information both from network vertices and network edges and is based on an explicit evolutionary model, allowing inference of all scoring parameters directly from empirical data. We compare the performance of our algorithm to an alternative algorithm, Græmlin 2.0. On simulated data, GraphAlignment outperforms Græmlin 2.0 in several benchmarks except for computational complexity. When there is little or no noise in the data, GraphAlignment is slower than Græmlin 2.0. It is faster than Græmlin 2.0 when processing noisy data containing spurious vertex associations. Its typical case complexity grows approximately as O(N2.6. On empirical bacterial protein-protein interaction networks (PIN and gene co-expression networks, GraphAlignment outperforms Græmlin 2.0 with respect to coverage and specificity, albeit by a small margin. On large eukaryotic PIN, Græmlin 2.0 outperforms GraphAlignment. Conclusions The GraphAlignment algorithm is robust to spurious vertex associations, correctly resolves paralogs, and shows very good performance in identification of homologous vertices defined by high vertex and/or interaction similarity. The simplicity and generality of GraphAlignment edge scoring makes the algorithm an appropriate choice for global alignment of networks.

  11. Application of isothermal titration calorimetry for characterizing thermodynamic parameters of biomolecular interactions: peptide self-assembly and protein adsorption case studies.

    Science.gov (United States)

    Kabiri, Maryam; Unsworth, Larry D

    2014-10-13

    The complex nature of macromolecular interactions usually makes it very hard to identify the molecular-level mechanisms that ultimately dictate the result of these interactions. This is especially evident in the case of biological systems, where the complex interaction of molecules in various situations may be responsible for driving biomolecular interactions themselves but also has a broader effect at the cell and/or tissue level. This review will endeavor to further the understanding of biomolecular interactions utilizing the isothermal titration calorimetry (ITC) technique for thermodynamic characterization of two extremely important biomaterial systems, viz., peptide self-assembly and nonfouling polymer-modified surfaces. The advantages and shortcomings of this technique will be presented along with a thorough review of the recent application of ITC to these two areas. Furthermore, the controversies associated with the enthalpy-entropy compensation effect as well as thermodynamic equilibrium state for such interactions will be discussed.

  12. Networks in cognitive science

    OpenAIRE

    Andrea Baronchelli; Ramon Ferrer-i-Cancho; Romualdo Pastor-Satorras; Nick Chater; Christiansen, Morten H.

    2013-01-01

    Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural net- works to spreading activation models of semantic mem- ory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex- s...

  13. PREFACE: 1st Nano-IBCT Conference 2011 - Radiation Damage of Biomolecular Systems: Nanoscale Insights into Ion Beam Cancer Therapy

    Science.gov (United States)

    Huber, Bernd A.; Malot, Christiane; Domaracka, Alicja; Solov'yov, Andrey V.

    2012-07-01

    The 1st Nano-IBCT Conference entitled 'Radiation Damage in Biomolecular Systems: Nanoscale Insights into Ion Beam Cancer Therapy' was held in Caen, France, in October 2011. The Meeting was organised in the framework of the COST Action MP1002 (Nano-IBCT) which was launched in December 2010 (http://fias.uni-frankfurt.de/nano-ibct). This action aims to promote the understanding of mechanisms and processes underlying the radiation damage of biomolecular systems at the molecular and nanoscopic level and to use the findings to improve the strategy of Ion Beam Cancer Therapy. In the hope of achieving this, participants from different disciplines were invited to represent the fields of physics, biology, medicine and chemistry, and also included those from industry and the operators of hadron therapy centres. Ion beam therapy offers the possibility of excellent dose localization for treatment of malignant tumours, minimizing radiation damage in normal healthy tissue, while maximizing cell killing within the tumour. Several ion beam cancer therapy clinical centres are now operating in Europe and elsewhere. However, the full potential of such therapy can only be exploited by better understanding the physical, chemical and biological mechanisms that lead to cell death under ion irradiation. Considering a range of spatio-temporal scales, the proposed action therefore aims to combine the unique experimental and theoretical expertise available within Europe to acquire greater insight at the nanoscopic and molecular level into radiation damage induced by ion impact. Success in this endeavour will be both an important scientific breakthrough and give great impetus to the practical improvement of this innovative therapeutic technique. Ion therapy potentially provides an important advance in cancer therapy and the COST action MP1002 will be very significant in ensuring Europe's leadership in this field, providing the scientific background, required data and mechanistic insight which

  14. Event Detection and Sub-state Discovery from Bio-molecular Simulations Using Higher-Order Statistics: Application To Enzyme Adenylate Kinase

    OpenAIRE

    Ramanathan, Arvind; Savol, Andrej J.; Agarwal, Pratul K.; Chennubhotla, Chakra S.

    2012-01-01

    Biomolecular simulations at milli-second and longer timescales can provide vital insights into functional mechanisms. Since post-simulation analyses of such large trajectory data-sets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA)...

  15. Histopathological, immunohistochemical and biomolecular diagnosis of myocarditis due to Clostridium chauvoei in a bovine

    Directory of Open Access Journals (Sweden)

    Renata Assis Casagrande

    2015-08-01

    Full Text Available The aim of this study was to report a case of clostridial myocarditis in a bovine in Brazil with emphasis on the pathological findings, isolation and molecular identification associated with the in situ localization of C. chauvoei. The animal, a male Brangus bull with nine months of age, was found dead without prior clinical signs. Multifocal and coalescent areas of necrosis were observed in the myocardium. Rod cells in the cardiac muscle fibers were positive immunostaining for C. chauvoei, while this bacterium was also isolated and identified by polymerase chain reaction (PCR.

  16. Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

    Energy Technology Data Exchange (ETDEWEB)

    Trewhella, J.; Cross, T.A.; Unkefer, C.J. [eds.

    1994-12-01

    Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database.

  17. Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

    International Nuclear Information System (INIS)

    Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database

  18. Context-dependent metabolic networks

    CERN Document Server

    Beguerisse-Díaz, Mariano; Oyarzún, Diego; Picó, Jesús; Barahona, Mauricio

    2016-01-01

    Cells adapt their metabolism to survive changes in their environment. We present a framework for the construction and analysis of metabolic reaction networks that can be tailored to reflect different environmental conditions. Using context-dependent flux distributions from Flux Balance Analysis (FBA), we produce directed networks with weighted links representing the amount of metabolite flowing from a source reaction to a target reaction per unit time. Such networks are analyzed with tools from network theory to reveal salient features of metabolite flows in each biological context. We illustrate our approach with the directed network of the central carbon metabolism of Escherichia coli, and study its properties in four relevant biological scenarios. Our results show that both flow and network structure depend drastically on the environment: networks produced from the same metabolic model in different contexts have different edges, components, and flow communities, capturing the biological re-routing of metab...

  19. LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

  20. Photoabsorption and resonance energy transfer phenomenon in CdTe-protein bioconjugates: an insight into QD-biomolecular interactions.

    Science.gov (United States)

    Vinayaka, Aaydha C; Thakur, Munna S

    2011-05-18

    Luminescent quantum dots (QDs) possess unique photophysical properties, which are advantageous in the development of new generation robust fluorescent probes based on Forster resonance energy transfer (FRET) phenomena. Bioconjugation of these QDs with biomolecules create hybrid materials having unique photophysical properties along with biological activity. The present study is aimed at characterizing QD bioconjugates in terms of optical behavior. Colloidal CdTe QDs capped with 3-mercaptopropionic acid (MPA) were conjugated to different proteins by the carbodiimide protocol using N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC) and a coupling reagent like N-hydroxysuccinimide (NHS). The photoabsorption of these QD-protein bioconjugates demonstrated an effective coupling of electronic orbitals of constituents. A linear variation in absorbance of bioconjugates at 330 nm proportionate to conjugation suggests a covalent attachment as confirmed by gel electrophoresis. A red shift in the fluorescence of bovine serum albumin (BSA) due to conjugation inferred a decrease in Stokes shift and solvent polarization effects on protein. A proportionate quenching in BSA fluorescence followed by an enhancement of QD fluorescence point toward nonradiative dipolar interactions. Further, reduction in photobleaching of BSA suggests QD-biomolecular interactions. Bioconjugation has significantly influenced the photoabsorption spectrum of QD bioconjugates suggesting the formation of a possible protein shell on the surface of QD. The experimental result suggests that these bioconjugates can be considered nanoparticle (NP) superstructures for the development of a new generation of robust nanoprobes. PMID:21452896

  1. Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the influence of conformational uncertainty in biomolecular solvation

    Energy Technology Data Exchange (ETDEWEB)

    Lei, Huan; Yang, Xiu; Zheng, Bin; Baker, Nathan A.

    2015-11-05

    Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

  2. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

    Science.gov (United States)

    Cosic, Irena; Cosic, Drasko; Lazar, Katarina

    2016-01-01

    The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

  3. Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation

    Energy Technology Data Exchange (ETDEWEB)

    Lei, Huan; Yang, Xiu; Zheng, Bin; Lin, Guang; Baker, Nathan A.

    2015-12-31

    Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

  4. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

    Directory of Open Access Journals (Sweden)

    Irena Cosic

    2016-06-01

    Full Text Available The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM. The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1 the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2 the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3 the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4 the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

  5. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

    Science.gov (United States)

    Cosic, Irena; Cosic, Drasko; Lazar, Katarina

    2016-01-01

    The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

  6. Tailored surface-enhanced Raman nanopillar arrays fabricated by laser-assisted replication for biomolecular detection using organic semiconductor lasers.

    Science.gov (United States)

    Liu, Xin; Lebedkin, Sergei; Besser, Heino; Pfleging, Wilhelm; Prinz, Stephan; Wissmann, Markus; Schwab, Patrick M; Nazarenko, Irina; Guttmann, Markus; Kappes, Manfred M; Lemmer, Uli

    2015-01-27

    Organic semiconductor distributed feedback (DFB) lasers are of interest as external or chip-integrated excitation sources in the visible spectral range for miniaturized Raman-on-chip biomolecular detection systems. However, the inherently limited excitation power of such lasers as well as oftentimes low analyte concentrations requires efficient Raman detection schemes. We present an approach using surface-enhanced Raman scattering (SERS) substrates, which has the potential to significantly improve the sensitivity of on-chip Raman detection systems. Instead of lithographically fabricated Au/Ag-coated periodic nanostructures on Si/SiO2 wafers, which can provide large SERS enhancements but are expensive and time-consuming to fabricate, we use low-cost and large-area SERS substrates made via laser-assisted nanoreplication. These substrates comprise gold-coated cyclic olefin copolymer (COC) nanopillar arrays, which show an estimated SERS enhancement factor of up to ∼ 10(7). The effect of the nanopillar diameter (60-260 nm) and interpillar spacing (10-190 nm) on the local electromagnetic field enhancement is studied by finite-difference-time-domain (FDTD) modeling. The favorable SERS detection capability of this setup is verified by using rhodamine 6G and adenosine as analytes and an organic semiconductor DFB laser with an emission wavelength of 631.4 nm as the external fiber-coupled excitation source.

  7. Extension of the CHARMM General Force Field to sulfonyl-containing compounds and its utility in biomolecular simulations.

    Science.gov (United States)

    Yu, Wenbo; He, Xibing; Vanommeslaeghe, Kenno; MacKerell, Alexander D

    2012-12-01

    Presented is an extension of the CHARMM General Force Field (CGenFF) to enable the modeling of sulfonyl-containing compounds. Model compounds containing chemical moieties such as sulfone, sulfonamide, sulfonate, and sulfamate were used as the basis for the parameter optimization. Targeting high-level quantum mechanical and experimental crystal data, the new parameters were optimized in a hierarchical fashion designed to maintain compatibility with the remainder of the CHARMM additive force field. The optimized parameters satisfactorily reproduced equilibrium geometries, vibrational frequencies, interactions with water, gas phase dipole moments, and dihedral potential energy scans. Validation involved both crystalline and liquid phase calculations showing the newly developed parameters to satisfactorily reproduce experimental unit cell geometries, crystal intramolecular geometries, and pure solvent densities. The force field was subsequently applied to study conformational preference of a sulfonamide based peptide system. Good agreement with experimental IR/NMR data further validated the newly developed CGenFF parameters as a tool to investigate the dynamic behavior of sulfonyl groups in a biological environment. CGenFF now covers sulfonyl group containing moieties allowing for modeling and simulation of sulfonyl-containing compounds in the context of biomolecular systems including compounds of medicinal interest. PMID:22821581

  8. Biomolecular urease thin films grown by laser techniques for blood diagnostic applications

    International Nuclear Information System (INIS)

    Matrix assisted pulsed laser evaporation (MAPLE) was used for growing urease thin films designed for bio-sensor applications in clinical diagnostics. The targets exposed to laser radiation were made from a frozen composite manufactured by dissolving biomaterials in distilled water. We used a UV KrF* (λ = 248 nm, τFWHM ≅ 30 ns, ν = 10 Hz) excimer source for multipulse laser irradiation of the frozen targets cooled with Peltier elements. The laser source was operated at an incident fluence of 0.4 J/cm2. Urease activity and kinetics were assayed by the Worthington method that monitors urea hydrolysis by coupling ammonia production to a glutamate dehydrogenase reaction. A decrease in absorbance was measured at 340 nm and correlated with the enzymatic activity of urease. We show that the urease films obtained by MAPLE techniques remain active up to three months after deposition.

  9. Structure network analysis to gain insights into GPCR function.

    Science.gov (United States)

    Fanelli, Francesca; Felline, Angelo; Raimondi, Francesco; Seeber, Michele

    2016-04-15

    G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM-NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor. PMID:27068978

  10. Ion interaction with biomolecular systems and the effect of the environment

    International Nuclear Information System (INIS)

    To fully understand the mechanisms of radiation damage in living tissues, a detailed knowledge of the processes occurring at the molecular level is needed. In the gas phase, most of the investigations concerning the ionization and fragmentation of biologically relevant molecular systems are performed with isolated molecules. The importance of such studies is limited to the intrinsic properties of these molecules because of the lack of a chemical environment. To probe the effect of such an environment on the behavior of small biomolecules under irradiation, the molecules (α-amino acids, adenine) were embedded into clusters. The present results, obtained with multiply charged ions, clearly indicate the protective role of the clusters since the total fragmentation yield is reduced for all systems. The surrounding molecules allow for a redistribution of the excess energy and of the charge within the cluster. In the case of adenine clusters, a new fragmentation channel is identified. Moreover, for hydrated adenine clusters, low-energy ion induced chemical reactions are observed, namely the proton transfer from the water cluster to the adenine molecule.

  11. Membraneless organelles can melt nucleic acid duplexes and act as biomolecular filters

    Science.gov (United States)

    Nott, Timothy J.; Craggs, Timothy D.; Baldwin, Andrew J.

    2016-06-01

    Membraneless organelles are cellular compartments made from drops of liquid protein inside a cell. These compartments assemble via the phase separation of disordered regions of proteins in response to changes in the cellular environment and the cell cycle. Here we demonstrate that the solvent environment within the interior of these cellular bodies behaves more like an organic solvent than like water. One of the most-stable biological structures known, the DNA double helix, can be melted once inside the liquid droplet, and simultaneously structures formed from regulatory single-stranded nucleic acids are stabilized. Moreover, proteins are shown to have a wide range of absorption or exclusion from these bodies, and can act as importers for otherwise-excluded nucleic acids, which suggests the existence of a protein-mediated trafficking system. A common strategy in organic chemistry is to utilize different solvents to influence the behaviour of molecules and reactions. These results reveal that cells have also evolved this capability by exploiting the interiors of membraneless organelles.

  12. REACH coarse-grained biomolecular simulation: transferability between different protein structural classes.

    Science.gov (United States)

    Moritsugu, Kei; Smith, Jeremy C

    2008-08-01

    Coarse graining of protein interactions provides a means of simulating large biological systems. The REACH (Realistic Extension Algorithm via Covariance Hessian) coarse-graining method, in which the force constants of a residue-scale elastic network model are calculated from the variance-covariance matrix obtained from atomistic molecular dynamics (MD) simulation, involves direct mapping between scales without the need for iterative optimization. Here, the transferability of the REACH force field is examined between protein molecules of different structural classes. As test cases, myoglobin (all alpha), plastocyanin (all beta), and dihydrofolate reductase (alpha/beta) are taken. The force constants derived are found to be closely similar in all three proteins. An MD version of REACH is presented, and low-temperature coarse-grained (CG) REACH MD simulations of the three proteins are compared with atomistic MD results. The mean-square fluctuations of the atomistic MD are well reproduced by the CGMD. Model functions for the CG interactions, derived by averaging over the three proteins, are also shown to produce fluctuations in good agreement with the atomistic MD. The results indicate that, similarly to the use of atomistic force fields, it is now possible to use a single, generic REACH force field for all protein studies, without having first to derive parameters from atomistic MD simulation for each individual system studied. The REACH method is thus likely to be a reliable way of determining spatiotemporal motion of a variety of proteins without the need for expensive computation of long atomistic MD simulations. PMID:18469078

  13. AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis

    Directory of Open Access Journals (Sweden)

    Burger Gertraud

    2003-12-01

    Full Text Available Abstract Background Sequence data analyses such as gene identification, structure modeling or phylogenetic tree inference involve a variety of bioinformatics software tools. Due to the heterogeneity of bioinformatics tools in usage and data requirements, scientists spend much effort on technical issues including data format, storage and management of input and output, and memorization of numerous parameters and multi-step analysis procedures. Results In this paper, we present the design and implementation of AnaBench, an interactive, Web-based bioinformatics Analysis workBench allowing streamlined data analysis. Our philosophy was to minimize the technical effort not only for the scientist who uses this environment to analyze data, but also for the administrator who manages and maintains the workbench. With new bioinformatics tools published daily, AnaBench permits easy incorporation of additional tools. This flexibility is achieved by employing a three-tier distributed architecture and recent technologies including CORBA middleware, Java, JDBC, and JSP. A CORBA server permits transparent access to a workbench management database, which stores information about the users, their data, as well as the description of all bioinformatics applications that can be launched from the workbench. Conclusion AnaBench is an efficient and intuitive interactive bioinformatics environment, which offers scientists application-driven, data-driven and protocol-driven analysis approaches. The prototype of AnaBench, managed by a team at the Université de Montréal, is accessible on-line at: http://malawimonas.bcm.umontreal.ca:8091/anabench. Please contact the authors for details about setting up a local-network AnaBench site elsewhere.

  14. Altered Micro-RNA Degradation Promotes Tumor Heterogeneity: A Result from Boolean Network Modeling.

    Science.gov (United States)

    Wu, Yunyi; Krueger, Gerhard R F; Wang, Guanyu

    2016-02-01

    Cancer heterogeneity may reflect differential dynamical outcomes of the regulatory network encompassing biomolecules at both transcriptional and post-transcriptional levels. In other words, differential gene-expression profiles may correspond to different stable steady states of a mathematical model for simulation of biomolecular networks. To test this hypothesis, we simplified a regulatory network that is important for soft-tissue sarcoma metastasis and heterogeneity, comprising of transcription factors, micro-RNAs, and signaling components of the NOTCH pathway. We then used a Boolean network model to simulate the dynamics of this network, and particularly investigated the consequences of differential miRNA degradation modes. We found that efficient miRNA degradation is crucial for sustaining a homogenous and healthy phenotype, while defective miRNA degradation may lead to multiple stable steady states and ultimately to carcinogenesis and heterogeneity.

  15. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  16. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011). Learning Networks, Networked Learning. Presentation at Annual Assembly of the European Society for the Systemic Innovation of Education - ESSIE. May, 27, 2011, Leuven, Belgium: Open University in the Netherlands.

  17. Macromolecular networks and intelligence in microorganisms

    Science.gov (United States)

    Westerhoff, Hans V.; Brooks, Aaron N.; Simeonidis, Evangelos; García-Contreras, Rodolfo; He, Fei; Boogerd, Fred C.; Jackson, Victoria J.; Goncharuk, Valeri; Kolodkin, Alexey

    2014-01-01

    Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity – particularly activity of the human brain – with a phenomenon we call “intelligence.” Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as “human” and “brain” out of the defining features of “intelligence,” all forms of life – from microbes to humans – exhibit some or all characteristics consistent with “intelligence.” We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo. PMID:25101076

  18. Chain reaction

    International Nuclear Information System (INIS)

    Chain Reaction is a work of recent American political history. It seeks to explain how and why America came to depend so heavily on its experts after World War II, how those experts translated that authority into political clout, and why that authority and political discretion declined in the 1970s. The author's research into the internal memoranda of the Atomic Energy Commission substantiates his argument in historical detail. It was not the ravages of American anti-intellectualism, as so many scholars have argued, that brought the experts back down to earth. Rather, their decline can be traced to the very roots of their success after World War II. The need to over-state anticipated results in order to garner public support, incessant professional and bureaucratic specialization, and the sheer proliferation of expertise pushed arcane and insulated debates between experts into public forums at the same time that a broad cross section of political participants found it easier to gain access to their own expertise. These tendencies ultimately undermined the political influence of all experts. (author)

  19. Study on Disproportionation Reaction of FCC Gasoline on Acid Catalyst

    Institute of Scientific and Technical Information of China (English)

    Xu Youhao; Wang Xieqing

    2004-01-01

    Based on the experimental data relating to the reaction of FCC gasoline on acid catalyst the analysis of product distribution, and composition of gasoline and diesel fractions have been analyzed. The occurrence of disproportionation reaction of FCC gasoline on acid catalyst and the network of disproportionation reaction have been identified. Study has also shown that different reaction temperatures can result in different pathways of disproportionation reactions on acid catalyst.

  20. Inhibition of zinc-dependent peptidases by Maillard reaction products

    OpenAIRE

    Missagia de Marco, Leticia

    2015-01-01

    The Maillard reaction is a network of different non-enzymatic reactions between carbonyl groups of reducing sugars and amino groups from amino acids, peptides, or proteins, which progresses in three major stages and originates a very heterogeneous mixture of reaction products. It is also known as non-enzymatic browning, due to the brown macromolecular pigments formed in the final stage of the reaction. The chemistry underlying the Maillard reaction is complex. It encloses not only one reactio...

  1. Biomolecular Analysis Capability for Cellular and Omics Research on the International Space Station

    Science.gov (United States)

    Guinart-Ramirez, Y.; Cooley, V. M.; Love, J. E.

    2016-01-01

    International Space Station (ISS) assembly complete ushered a new era focused on utilization of this state-of-the-art orbiting laboratory to advance science and technology research in a wide array of disciplines, with benefits to Earth and space exploration. ISS enabling capability for research in cellular and molecular biology includes equipment for in situ, on-orbit analysis of biomolecules. Applications of this growing capability range from biomedicine and biotechnology to the emerging field of Omics. For example, Biomolecule Sequencer is a space-based miniature DNA sequencer that provides nucleotide sequence data for entire samples, which may be used for purposes such as microorganism identification and astrobiology. It complements the use of WetLab-2 SmartCycler"TradeMark", which extracts RNA and provides real-time quantitative gene expression data analysis from biospecimens sampled or cultured onboard the ISS, for downlink to ground investigators, with applications ranging from clinical tissue evaluation to multigenerational assessment of organismal alterations. And the Genes in Space-1 investigation, aimed at examining epigenetic changes, employs polymerase chain reaction to detect immune system alterations. In addition, an increasing assortment of tools to visualize the subcellular distribution of tagged macromolecules is becoming available onboard the ISS. For instance, the NASA LMM (Light Microscopy Module) is a flexible light microscopy imaging facility that enables imaging of physical and biological microscopic phenomena in microgravity. Another light microscopy system modified for use in space to image life sciences payloads is initially used by the Heart Cells investigation ("Effects of Microgravity on Stem Cell-Derived Cardiomyocytes for Human Cardiovascular Disease Modeling and Drug Discovery"). Also, the JAXA Microscope system can perform remotely controllable light, phase-contrast, and fluorescent observations. And upcoming confocal microscopy

  2. Dynamic analysis of biochemical network using complex network method

    Directory of Open Access Journals (Sweden)

    Wang Shuqiang

    2015-01-01

    Full Text Available In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger information capacity and is more efficient in information transmission. This is consistent with theory of evolution.

  3. Applicability of carbon and boron nitride nanotubes as biosensors: Effect of biomolecular adsorption on the transport properties of carbon and boron nitride nanotubes

    Science.gov (United States)

    Zhong, Xiaoliang; Mukhopadhyay, Saikat; Gowtham, S.; Pandey, Ravindra; Karna, Shashi P.

    2013-04-01

    The effect of molecular adsorption on the transport properties of single walled carbon and boron nitride nanotubes (CNTs and BNNTs) is investigated using density functional theory and non-equilibrium Green's function methods. The calculated I-V characteristics predict noticeable changes in the conductivity of semiconducting BNNTs due to physisorption of nucleic acid base molecules. Specifically, guanine which binds to the side wall of BNNT significantly enhances its conductivity by introducing conduction channels near the Fermi energy of the bioconjugated system. For metallic CNTs, a large background current masks relatively small changes in current due to the biomolecular adsorption. The results therefore suggest the suitability of BNNTs for biosensing applications.

  4. Asian collaboration on nuclear reaction data compilation

    International Nuclear Information System (INIS)

    Nuclear reaction data are essential for research and development in nuclear engineering, radiation therapy, nuclear physics and astrophysics. Experimental data must be compiled in a database and be accessible to nuclear data users. One of the nuclear reaction databases is the EXFOR database maintained by the International Network of Nuclear Reaction Data Centres (NRDC) under the auspices of the International Atomic Energy Agency. Recently, collaboration among the Asian NRDC members is being further developed under the support of the Asia-Africa Science Platform Program of the Japan Society for the Promotion of Science. We report the activity for three years to develop the Asian collaboration on nuclear reaction data compilation. (author)

  5. Network Potentials

    OpenAIRE

    Chakrabarti, Subhadip; Gilles, Robert Paul

    2005-01-01

    A network payoff function assigns a utility to all participants in a (social) network. In this paper we discuss properties of such network payoff functions that guarantee the existence of certain types of pairwise stable networks and the convergence of certain network formation processes. In particular we investigate network payoff functions that admit an exact network potential or an ordinal network potential. We relate these network potentials to exact and ordinal potentials of a non-cooper...

  6. Complex networks: Patterns of complexity

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Vespignani, Alessandro

    2010-07-01

    The Turing mechanism provides a paradigm for the spontaneous generation of patterns in reaction-diffusion systems. A framework that describes Turing-pattern formation in the context of complex networks should provide a new basis for studying the phenomenon.

  7. Network Competition with Local Network

    OpenAIRE

    Oystein Fjeldstad; Moen, Espen R; Christian Riis

    2007-01-01

    Local network externalities are present when the network externalities associated with entering a certain network depends not only on the total number of agents in the network, but on the identity of the agents in the network. We explore the consequences of local network externalities within a framework where two networks compete on the Hotelling circle. We first show that local network externalities, in contrast to global network externalities, do not sharpen competition. Then we show that t...

  8. Controls of functional group chemistry on calcium carbonate nucleation: Insights into systematics of biomolecular innovations for skeletal mineralization?

    Science.gov (United States)

    Dove, P. M.; Hamm, L. M.; Giuffre, A. J.

    2012-12-01

    Living organisms produce skeletal structures within a complex matrix of organic macromolecules that guide the nucleation and growth of crystalline structures into the organic-inorganic composites we know as biominerals. This type of biomolecule-directed mineralization is an ancient process as evidenced by structures in the fossil record that date to the Ediacaran (ca. 549 Ma). Our understanding of template-directed biomineralization, however, is largely based upon assumptions from studies that: 1) qualitatively demonstrate some chemical functionalities influence the nucleating mineral phase and morphology; 2) propose proteins are the primary driver to template-directed mineralization and 3) propose the ubiquitous polysaccharides are inert components. Thus, a mechanistic basis for how the underlying chemistry of macromolecules controls nucleation kinetics and thermodynamics in template-directed nucleation is not well established. Moreover, there is not yet a good appreciation for how patterns of skeletal mineralization evolved with biochemical innovations in response to environmental changes over geologic timescales. In small steps toward understanding biochemical controls on biomineralization, we test the hypothesis that the kinetics and thermodynamics of calcium carbonate (CaCO3) formation is regulated by a systematic relationship to the functional group chemistry of macromolecules. A long-term goal is to establish the energetic basis for biochemical motifs that are seen (and not seen) at sites of calcification across the phylogenetic tree. Two types of studies were conducted. The first measured nucleation rates on model biomolecular substrates with termini that are found in proteins associated with sites of calcification (-COOH, -PO4, and -SH) and two alkanethiol chain lengths (16-C and 11-C) at a variety of chemical driving forces. The measurements show functional group chemistry and molecule conformation regulate rates by a predictable relation to interfacial

  9. Network modeling of membrane-based artificial cellular systems

    Science.gov (United States)

    Freeman, Eric C.; Philen, Michael K.; Leo, Donald J.

    2013-04-01

    Computational models are derived for predicting the behavior of artificial cellular networks for engineering applications. The systems simulated involve the use of a biomolecular unit cell, a multiphase material that incorporates a lipid bilayer between two hydrophilic compartments. These unit cells may be considered building blocks that enable the fabrication of complex electrochemical networks. These networks can incorporate a variety of stimuli-responsive biomolecules to enable a diverse range of multifunctional behavior. Through the collective properties of these biomolecules, the system demonstrates abilities that recreate natural cellular phenomena such as mechanotransduction, optoelectronic response, and response to chemical gradients. A crucial step to increase the utility of these biomolecular networks is to develop mathematical models of their stimuli-responsive behavior. While models have been constructed deriving from the classical Hodgkin-Huxley model focusing on describing the system as a combination of traditional electrical components (capacitors and resistors), these electrical elements do not sufficiently describe the phenomena seen in experiment as they are not linked to the molecular scale processes. From this realization an advanced model is proposed that links the traditional unit cell parameters such as conductance and capacitance to the molecular structure of the system. Rather than approaching the membrane as an isolated parallel plate capacitor, the model seeks to link the electrical properties to the underlying chemical characteristics. This model is then applied towards experimental cases in order that a more complete picture of the underlying phenomena responsible for the desired sensing mechanisms may be constructed. In this way the stimuli-responsive characteristics may be understood and optimized.

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

    Science.gov (United States)

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

    2012-07-01

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

  11. Organic & Biomolecular Chemistry

    OpenAIRE

    Zhang, Wenyu; Bryson, David I.; Crumpton, Jason B.; Wynn, Jessica; Santos, Webster L.

    2013-01-01

    On-bead high-throughput screening of a medium-sized (1000_2000 Da) branched peptideboronic acid (BPBA) library consisting of 46 656 unique sequences against HIV-1 RRE RNA generated peptides with binding affinities in the low micromolar range. In particular, BPBA1 had a Kd of 1.4 _M with RRE IIB, preference for RNA over DNA (27 fold), and selectivity of up to >75 fold against a panel of RRE IIB variants. Structure_activity studies suggest that the boronic acid moiety and ͐branching in peptide...

  12. Abstractions for biomolecular computations

    CERN Document Server

    Okunoye, Babatunde O

    2008-01-01

    Deoxyribonucleic acid is increasingly being understood to be an informational molecule, capable of information processing.It has found application in the determination of non-deterministic algorithms and in the design of molecular computing devices. This is a theoretical analysis of the mathematical properties and relations of the molecules which constituting DNA, which explains in part why DNA is a successful computing molecule.

  13. Introduction. Biomolecular simulation.

    Science.gov (United States)

    Mulholland, Adrian J

    2008-12-01

    'Everything that living things do can be understood in terms of the jigglings and wigglings of atoms' as Richard Feynman provocatively stated nearly 50 years ago. But how can we 'see' this wiggling and jiggling and understand how it drives biology? Increasingly, computer simulations of biological macromolecules are helping to meet this challenge.

  14. Biomolecular computation for bionanotechnology

    CERN Document Server

    Liu, Jian-Qin

    2006-01-01

    Computers built with moleware? The drive toward non-silicon computing is underway, and this first-of-its-kind guide to molecular computation gives researchers a firm grasp of the technologies, biochemical details, and theoretical models at the cutting edge. It explores advances in molecular biology and nanotechnology and illuminates how the convergence of various technologies is propelling computational capacity beyond the limitations of traditional hardware technology and into the realm of moleware.

  15. Controlling Hybridization Chain Reactions with pH.

    Science.gov (United States)

    Idili, Andrea; Porchetta, Alessandro; Amodio, Alessia; Vallée-Bélisle, Alexis; Ricci, Francesco

    2015-08-12

    By taking inspiration from nature, where self-organization of biomolecular species into complex systems is finely controlled through different stimuli, we propose here a rational approach by which the assembly and disassembly of DNA-based concatemers can be controlled through pH changes. To do so we used the hybridization chain reaction (HCR), a process that, upon the addition of an initiator strand, allows to create DNA-based concatemers in a controlled fashion. We re-engineered the functional units of HCR through the addition of pH-dependent clamp-like triplex-forming domains that can either inhibit or activate the polymerization reaction at different pHs. This allows to finely regulate the HCR-induced assembly and disassembly of DNA concatemers at either basic or acidic pHs in a reversible way. The strategies we present here appear particularly promising as novel tools to achieve better spatiotemporal control of self-assembly processes of DNA-based nanostructures. PMID:26177980

  16. Prebiotic metabolic networks?

    OpenAIRE

    Luisi, Pier Luigi

    2014-01-01

    A prebiotic origin of metabolism has been proposed as one of several scenarios for the origin of life. In their recent work, Ralser and colleagues (Keller et al, 2014) observe an enzyme‐free, metabolism‐like reaction network under conditions reproducing a possible prebiotic environment.

  17. Catalysis of Photochemical Reactions.

    Science.gov (United States)

    Albini, A.

    1986-01-01

    Offers a classification system of catalytic effects in photochemical reactions, contrasting characteristic properties of photochemical and thermal reactions. Discusses catalysis and sensitization, examples of catalyzed reactions of excepted states, complexing ground state substrates, and catalysis of primary photoproducts. (JM)

  18. Reactive biomolecular divergence in genetically altered yeast cells and isolated mitochondria as measured by biocavity laser spectroscopy : a rapid diagnostic method for studying cellular responses to stress and disease.

    Energy Technology Data Exchange (ETDEWEB)

    Yaffe, Michael P. (University of California, San Diego, CA); Gourley, Paul Lee; Copeland, Robert Guild; McDonald, Anthony Eugene; Hendricks, Judy K.; Naviaux, Robert K. (Univesity of California, San Diego, CA)

    2006-12-01

    We report an analysis of four strains of baker's yeast (Saccharomyces cerevisiae) using biocavity laser spectroscopy. The four strains are grouped in two pairs (wild type and altered), in which one strain differs genetically at a single locus, affecting mitochondrial function. In one pair, the wild-type rho+ and a rho0 strain differ by complete removal of mitochondrial DNA (mtDNA). In the second pair, the wild-type rho+ and a rho- strain differ by knock-out of the nuclear gene encoding Cox4, an essential subunit of cytochrome c oxidase. The biocavity laser is used to measure the biophysical optic parameter Deltalambda, a laser wavelength shift relating to the optical density of cell or mitochondria that uniquely reflects its size and biomolecular composition. As such, Deltalambda is a powerful parameter that rapidly interrogates the biomolecular state of single cells and mitochondria. Wild-type cells and mitochondria produce Gaussian-like distributions with a single peak. In contrast, mutant cells and mitochondria produce leptokurtotic distributions that are asymmetric and highly skewed to the right. These distribution changes could be self-consistently modeled with a single, log-normal distribution undergoing a thousand-fold increase in variance of biomolecular composition. These features reflect a new state of stressed or diseased cells that we call a reactive biomolecular divergence (RBD) that reflects the vital interdependence of mitochondria and the nucleus.

  19. On thermonuclear reaction rates

    OpenAIRE

    Hans J. Haubold; Mathai, Arak Mathai

    1996-01-01

    Nuclear reactions govern major aspects of the chemical evolution of galaxies and stars. Analytic study of the reaction rates and reaction probability integrals is attempted here. Exact expressions for the reaction rates and reaction probability integrals for nuclear reactions in the cases of nonresonant, modified nonresonant, screened nonresonant and resonant cases are given. These are expressed in terms of H-functions, G-functions and in computable series forms. Computational aspects are als...

  20. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  1. Physics and chemistry on the surface of interstellar dust grains : the effect of O-atom diffusion and chemical desorption on the H-C-N-O reaction network

    OpenAIRE

    Minissale, Marco

    2014-01-01

    The interstellar medium is the matter that exists in the space between the star systems in a galaxy. It is composed of gas and elongated tiny dust grains. To date, plenty of molecules (> 170) are known to exist in the interstellar medium. The presence of most of them can be understood in terms of gas phase reactions but the synthesis of some key species (H2, H2O, CO2) need the intervention of solid-state reactions on dust grains surface. The aims of this thesis are to understand what are the ...

  2. Thermo-responsive cell culture carriers based on poly(vinyl methyl ether)—the effect of biomolecular ligands to balance cell adhesion and stimulated detachment

    Science.gov (United States)

    Teichmann, Juliane; Nitschke, Mirko; Pette, Dagmar; Valtink, Monika; Gramm, Stefan; Härtel, Frauke V.; Noll, Thomas; Funk, Richard H. W.; Engelmann, Katrin; Werner, Carsten

    2015-08-01

    Two established material systems for thermally stimulated detachment of adherent cells were combined in a cross-linked polymer blend to merge favorable properties. Through this approach poly(N-isopropylacrylamide) (PNiPAAm) with its superior switching characteristic was paired with a poly(vinyl methyl ether)-based composition that allows adjusting physico-chemical and biomolecular properties in a wide range. Beyond pure PNiPAAm, the proposed thermo-responsive coating provides thickness, stiffness and swelling behavior, as well as an apposite density of reactive sites for biomolecular functionalization, as effective tuning parameters to meet specific requirements of a particular cell type regarding initial adhesion and ease of detachment. To illustrate the strength of this approach, the novel cell culture carrier was applied to generate transplantable sheets of human corneal endothelial cells (HCEC). Sheets were grown, detached, and transferred onto planar targets. Cell morphology, viability and functionality were analyzed by immunocytochemistry and determination of transepithelial electrical resistance (TEER) before and after sheet detachment and transfer. HCEC layers showed regular morphology with appropriate TEER. Cells were positive for function-associated marker proteins ZO-1, Na+/K+-ATPase, and paxillin, and extracellular matrix proteins fibronectin, laminin and collagen type IV before and after transfer. Sheet detachment and transfer did not impair cell viability. Subsequently, a potential application in ophthalmology was demonstrated by transplantation onto de-endothelialized porcine corneas in vitro. The novel thermo-responsive cell culture carrier facilitates the generation and transfer of functional HCEC sheets. This paves the way to generate tissue engineered human corneal endothelium as an alternative transplant source for endothelial keratoplasty.

  3. Practice Gaps: Drug Reactions.

    Science.gov (United States)

    Wolverton, Stephen E

    2016-07-01

    The term "drug reactions" is relevant to dermatology in three categories of reactions: cutaneous drug reactions without systemic features, cutaneous drug reactions with systemic features, and systemic drugs prescribed by the dermatologist with systematic adverse effects. This article uses examples from each of these categories to illustrate several important principles central to drug reaction diagnosis and management. The information presented will help clinicians attain the highest possible level of certainty before making clinical decisions. PMID:27363888

  4. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter;

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  5. A Topological Characterization of Medium-Dependent Essential Metabolic Reactions

    OpenAIRE

    Nikolaus Sonnenschein; Carsten Marr; Marc-Thorsten Hütt

    2012-01-01

    Metabolism has frequently been analyzed from a network perspective. A major question is how network properties correlate with biological features like growth rates, flux patterns and enzyme essentiality. Using methods from graph theory as well as established topological categories of metabolic systems, we analyze the essentiality of metabolic reactions depending on the growth medium and identify the topological footprint of these reactions. We find that the typical topological context of a me...

  6. Allosteric transitions of supramolecular systems explored by network models: application to chaperonin GroEL.

    Directory of Open Access Journals (Sweden)

    Zheng Yang

    2009-04-01

    Full Text Available Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM, for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s, most of which involve conserved residues.

  7. Ultrananocrystalline diamond thin films functionalized with therapeutically active collagen networks.

    Energy Technology Data Exchange (ETDEWEB)

    Huang, H.; Chen, M.; Bruno, P.; Lam, R.; Robinson, E.; Gruen, D.; Ho, D.; Materials Science Division; Northwestern Univ.

    2009-01-01

    The fabrication of biologically amenable interfaces in medicine bridges translational technologies with their surrounding biological environment. Functionalized nanomaterials catalyze this coalescence through the creation of biomimetic and active substrates upon which a spectrum of therapeutic elements can be delivered to adherent cells to address biomolecular processes in cancer, inflammation, etc. Here, we demonstrate the robust functionalization of ultrananocrystalline diamond (UNCD) with type I collagen and dexamethasone (Dex), an anti-inflammatory drug, to fabricate a hybrid therapeutically active substrate for localized drug delivery. UNCD oxidation coupled with a pH-mediated collagen adsorption process generated a comprehensive interface between the two materials, and subsequent Dex integration, activity, and elution were confirmed through inflammatory gene expression assays. These studies confer a translational relevance to the biofunctionalized UNCD in its role as an active therapeutic network for potent regulation of cellular activity toward applications in nanomedicine.

  8. 基于废料最少的反应器网络综合(Ⅰ)同时进行反应与混合的几何表达%SYNTHESIS OF REACTOR NETWORK FOR WASTE MINIMIZATION(Ⅰ) GEOMETRY EXPRESSION OF REACTION AND MIXING PROCESS

    Institute of Scientific and Technical Information of China (English)

    赵文; 周传光; 韩方煜; 李成岳

    2001-01-01

    将废料最少问题分别等同于选择性、相对选择性和瞬时选择性等多个目标,根据目标函数的定义和在状态空间内反应、混合加工的几何特征,导出了全混流反应器(CSTR)和微分侧流反应器(DSR)两种极限情况下的浓度变化轨迹方程,同时满足这两个方程,可作为反应器系统选择性最大的判据.%A new method is proposed for waste minimization of reactor network system according to the basic principles of attainable region method used in reactor network synthesis. By this method it is meant that, the targeting of the waste minimization is divided into selectivity, relative selectivity and instant selectivity maximization. Based on those different objective functions, the optimization calculation is carried out directly in the convex region formed by arbitrary reaction and mixing, then CSTR equation and DSR equation in two and three-dimensional concentration spaces are thus attained. In the view of geometry, the CSTR locus and DSR trajectory are the smooth connection curves of reaction and mixing process; while by physical concept, every state point in the CSTR locus and DSR trajectory are the extreme value point of selectivity and instant selectivity respectively. On the basis of these studies, it's suggested that a state point in reactor system has maximum selectivity if it satisfies both CSTR and DSR equation simultaneously, and that changing along the CSTR locus or DSR trajectory, the reaction path and the production distribution can be improved.

  9. On the Positive Reaction to Network Police-related Public Opinion-Taking Fenghuang 9.4 Case as an Example%论网络涉警舆情的主动性应对——以凤凰“9·4案件”为例

    Institute of Scientific and Technical Information of China (English)

    刘劲青

    2011-01-01

    With the rapid development of modern network,network police-related public opinion tends to increase in amount,which provides new opportunities for the construction of police-related public opinion while posing new challenges for public security administration and law enforcement.This paper mainly discusses the positive reaction of police to network police-related public opinion by taking Fenghuang 9.4 case as an example and proposes ways for the cultivation of police good image.%随着现代网络的快速发展,网络涉警舆情也大量增加,既为警察公共关系建设创造了新的机遇,也为公安行政与执法带来了新挑战。应吸取凤凰"9·4案件"教训,警察应顺势而为,掌握涉警舆情应对主动权,以塑造警察良好形象。

  10. Avoiding Buffer Interference in ITC Experiments: A Case Study from the Analysis of Entropy-Driven Reactions of Glucose-6-Phosphate Dehydrogenase.

    Science.gov (United States)

    Bianconi, M Lucia

    2016-01-01

    Isothermal titration calorimetry (ITC) is a label-free technique that allows the direct determination of the heat absorbed or released in a reaction. Frequently used to determining binding parameters in biomolecular interactions, it is very useful to address enzyme-catalyzed reactions as both kinetic and thermodynamic parameters can be obtained. Since calorimetry measures the total heat effects of a reaction, it is important to consider the contribution of the heat of protonation/deprotonation that is possibly taking place. Here, we show a case study of the reaction catalyzed by the glucose-6-phosphate dehydrogenase (G6PD) from Leuconostoc mesenteroides. This enzyme is able to use either NAD(+) or NADP(+) as a cofactor. The reactions were done in five buffers of different enthalpy of protonation. Depending on the buffer used, the observed calorimetric enthalpy (ΔH(cal)) of the reaction varied from -22.93 kJ/mol (Tris) to 19.37 kJ/mol (phosphate) for the NADP(+)-linked reaction, and -11.67 kJ/mol (Tris) to 7.32 kcal/mol or 30.63 kJ/mol (phosphate) for the NAD(+) reaction. We will use this system as an example of how to extract proton-independent reaction enthalpies from kinetic data to ensure that the reported accurately represent the intrinsic heat of reaction.

  11. Classical swine fever virus detection: results of a real-time reverse transcription polymerase chain reaction ring trial conducted in the framework of the European network of excellence for epizootic disease diagnosis and control

    DEFF Research Database (Denmark)

    Hoffmann, Bernd; Blome, Sandra; Bonilauri, Paolo;

    2011-01-01

    The current study reports on a real-time reverse transcription polymerase chain reaction (real-time RT-PCR) ring trial for the detection of Classical swine fever virus (CSFV) genomic RNA undertaken by 10 European laboratories. All laboratories were asked to use their routine in-house real-time RT-PCR...... and specificity values. Nevertheless, some in-house systems had unspecific reactions or suboptimal sensitivity with only a single CSFV genotype. Follow-up actions involved either improvement of suboptimal assays or replacement of specific laboratory assays with the FLI protocol, with or without modifications....... In conclusion, the ring trial showed reliability of classical swine fever diagnosis on an international level and helped to optimize CSFV-specific RT-PCR diagnostics....

  12. Linking Drugs to Obscure Illnesses: Lessons from Pure Red Cell Aplasia, Nephrogenic Systemic Fibrosis, and Reye’s Syndrome. A Report From the Southern Network on Adverse Reactions (SONAR)

    OpenAIRE

    Bennett, Charles L.; Starko, Karen M.; Thomsen, Henrik S; Cowper, Shawn; Sartor, Oliver; Macdougall, Iain C.; Qureshi, Zaina P; Bookstaver, P. Brandon; Miller, April D; Norris, LeAnn B.; Xirasagar, Sudha; Trenery, Alyssa; Lopez, Isaac; Kahn, Adam; Murday, Alanna

    2012-01-01

    Identification of serious adverse drug reactions (sADRS) associated with commonly used drugs can elude detection for years. Reye’s syndrome (RS), nephrogenic systemic fibrosis (NSF), and pure red cell aplasia (PRCA) among chronic kidney disease (CKD) patients were recognized in 1951, 2000, and 1998, respectively. Reports associating these syndromes with aspirin, gadodiamide, and epoetin, were published 29, 6, and 4 years later, respectively. We obtained primary information from clinicians who...

  13. Green networking

    CERN Document Server

    Krief, Francine

    2012-01-01

    This book focuses on green networking, which is an important topic for the scientific community composed of engineers, academics, researchers and industrialists working in the networking field. Reducing the environmental impact of the communications infrastructure has become essential with the ever increasing cost of energy and the need for reducing global CO2 emissions to protect our environment.Recent advances and future directions in green networking are presented in this book, including energy efficient networks (wired networks, wireless networks, mobile networks), adaptive networ

  14. Simultaneous optimization of transit network and public bicycle station network

    Institute of Scientific and Technical Information of China (English)

    刘洋; 朱宁; 马寿峰

    2015-01-01

    The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization (CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container. Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

  15. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.;

    2003-01-01

    and the environment were included. A total of 708 structural open reading frames (ORFs) were accounted for in the reconstructed network, corresponding to 1035 metabolic reactions. Further, 140 reactions were included on the basis of biochemical evidence resulting in a genome-scale reconstructed metabolic network...... with Escherichia coli. The reconstructed metabolic network is the first comprehensive network for a eukaryotic organism, and it may be used as the basis for in silico analysis of phenotypic functions....

  16. Microfluidic chemical reaction circuits

    Science.gov (United States)

    Lee, Chung-cheng; Sui, Guodong; Elizarov, Arkadij; Kolb, Hartmuth C.; Huang, Jiang; Heath, James R.; Phelps, Michael E.; Quake, Stephen R.; Tseng, Hsian-rong; Wyatt, Paul; Daridon, Antoine

    2012-06-26

    New microfluidic devices, useful for carrying out chemical reactions, are provided. The devices are adapted for on-chip solvent exchange, chemical processes requiring multiple chemical reactions, and rapid concentration of reagents.

  17. Common Reactions After Trauma

    Science.gov (United States)

    ... here Enter ZIP code here Common Reactions After Trauma Public This section is for Veterans, General Public, Family, & Friends Common Reactions After Trauma Available in Spanish: Reacciones Comunes Después de un ...

  18. Anaphylaxis-Like Reactions

    Science.gov (United States)

    ... be "primed" by previous exposure to cause anaphylaxis, anaphylactoid reactions can occur with no previous exposure at all. ... an X-ray. Although the mechanism of an anaphylactoid reaction is different, the treatment is the same as ...

  19. Microscale Thermite Reactions.

    Science.gov (United States)

    Arnaiz, Francisco J.; Aguado, Rafael; Arnaiz, Susana

    1998-01-01

    Describes the adaptation of thermite (aluminum with metal oxides) reactions from whole-class demonstrations to student-run micro-reactions. Lists detailed directions and possible variations of the experiment. (WRM)

  20. Preequilibrium Nuclear Reactions

    International Nuclear Information System (INIS)

    After a survey on existing experimental data on precompound reactions and a description of preequilibrium reactions, theoretical models and quantum mechanical theories of preequilibrium emission are presented. The 25 papers of this meeting are analyzed separately