Detailed Enzyme Kinetics in Terms of Biochemical Species: Study of Citrate Synthase

The compulsory-ordered ternary catalytic mechanism for two-substrate two-product enzymes is analyzed to account for binding of inhibitors to each of the four enzyme states and to maintain the relationship between the kinetic constants and the reaction equilibrium constant. The developed quasi-steady flux expression is applied to the analysis of data from citrate synthase to determine and parameterize a kinetic scheme in terms of biochemical species, in which the effects of pH, ionic strength, and cation binding to biochemical species are explicitly accounted for in the analysis of the data. This analysis provides a mechanistic model that is consistent with the data that have been used support competing hypotheses regarding the catalytic mechanism of this enzyme

Ecosystem biogeochemistry considered as a distributed metabolic network ordered by maximum entropy production

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of The Royal Society for personal use, not for redistribution. The definitive version was published in Philosophical Transactions of the Royal Society B 365 (2010): 1417-1427, doi:10.1098/rstb.2009.0272.We examine the application of the maximum entropy production principle for describing ecosystem biogeochemistry. Since ecosystems can be functionally stable despite changes in species composition, we utilize a distributed metabolic network for describing biogeochemistry, which synthesizes generic biological structures that catalyze reaction pathways, but is otherwise organism independent. Allocation of biological structure and regulation of biogeochemical reactions is determined via solution of an optimal control problem in which entropy production is maximized. However, because synthesis of biological structures cannot occur if entropy production is maximized instantaneously, we propose that information stored within the metagenome allows biological systems to maximize entropy production when averaged over time. This differs from abiotic systems that maximize entropy production at a point in space-time, which we refer to as the steepest descent pathway. It is the spatiotemporal averaging that allows biological systems to outperform abiotic processes in entropy production, at least in many situations. A simulation of a methanotrophic system is used to demonstrate the approach. We conclude with a brief discussion on the implications of viewing ecosystems as self organizing molecular machines that function to maximize entropy production at the ecosystem level of organization.The work presented here was funded by the PIE-LTER program (NSF OCE-0423565), as well as from NSF CBET-0756562, NSF EF-0928742 and NASA Exobiology and Evolutionary Biology (NNG05GN61G)

Multiplicity Distributions and Rapidity Gaps

I examine the phenomenology of particle multiplicity distributions, with special emphasis on the low multiplicities that are a background in the study of rapidity gaps. In particular, I analyze the multiplicity distribution in a rapidity interval between two jets, using the HERWIG QCD simulation with some necessary modifications. The distribution is not of the negative binomial form, and displays an anomalous enhancement at zero multiplicity. Some useful mathematical tools for working with multiplicity distributions are presented. It is demonstrated that ignoring particles with pt<0.2 has theoretical advantages, in addition to being convenient experimentally.Comment: 24 pages, LaTeX, MSUHEP/94071

Molecular dynamics simulations of the temperature-induced unfolding of crambin follow the Arrhenius equation

Molecular dynamics simulations have been used extensively to model the folding and unfolding of proteins. The rates of folding and unfolding should follow the Arrhenius equation over a limited range of temperatures. This study shows that molecular dynamic simulations of the unfolding of crambin between 500K and 560K do follow the Arrhenius equation. They also show that while there is a large amount of variation between the simulations the average values for the rate show a very high degree of correlation

Conservation laws and work fluctuation relations in chemical reaction networks

We formulate a nonequilibrium thermodynamic description for open chemical reaction networks (CRN) described by a chemical master equation. The topological properties of the CRN and its conservation laws are shown to play a crucial role. They are used to decompose the entropy production into a potential change and two work contributions, the first due to time dependent changes in the externally controlled chemostats concentrations and the second due to flows maintained across the system by nonconservative forces. These two works jointly satisfy a Jarzynski and Crooks fluctuation theorem. In absence of work, the potential is minimized by the dynamics as the system relaxes to equilibrium and its equilibrium value coincides with the maximum entropy principle. A generalized Landauer's principle also holds: the minimal work needed to create a nonequilibrium state is the relative entropy of that state to its equilibrium value reached in absence of any work.Comment: revtex format: 30 pages (25 + 5 for appendices), 9 figures, 3 tables. v2: published versio

Monophasic synovial sarcoma of the pharynx: a case report

Synovial sarcomas are a rare form of soft tissue sarcomas. We present a case of a 62 year-old male presenting with a left thyroid lump initially though to be a thyroid adenoma but subsequently diagnosed as a monophasic synovial sarcoma of the pharynx. We discuss the diagnosis and treatment of this case

Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

<p>Abstract</p> <p>Background</p> <p>In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.</p> <p>Results</p> <p>To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of <it>Escherichia coli </it>(931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.</p> <p>Conclusion</p> <p>Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.</p

Molybdenum and Phosphorus Interact to Constrain Asymbiotic Nitrogen Fixation in Tropical Forests

Biological di-nitrogen fixation (N2) is the dominant natural source of new nitrogen to land ecosystems. Phosphorus (P) is thought to limit N2 fixation in many tropical soils, yet both molybdenum (Mo) and P are crucial for the nitrogenase reaction (which catalyzes N2 conversion to ammonia) and cell growth. We have limited understanding of how and when fixation is constrained by these nutrients in nature. Here we show in tropical forests of lowland Panama that the limiting element on asymbiotic N2 fixation shifts along a broad landscape gradient in soil P, where Mo limits fixation in P-rich soils while Mo and P co-limit in P-poor soils. In no circumstance did P alone limit fixation. We provide and experimentally test a mechanism that explains how Mo and P can interact to constrain asymbiotic N2 fixation. Fixation is uniformly favored in surface organic soil horizons - a niche characterized by exceedingly low levels of available Mo relative to P. We show that soil organic matter acts to reduce molybdate over phosphate bioavailability, which, in turn, promotes Mo limitation in sites where P is sufficient. Our findings show that asymbiotic N2 fixation is constrained by the relative availability and dynamics of Mo and P in soils. This conceptual framework can explain shifts in limitation status across broad landscape gradients in soil fertility and implies that fixation depends on Mo and P in ways that are more complex than previously thought

Free Energy Simulations of a GTPase: GTP and GDP Binding to Archaeal Initiation Factor 2

International audienceArchaeal initiation factor 2 (aIF2) is a protein involved in the initiation of protein biosynthesis. In its GTP-bound, "ON" conformation, aIF2 binds an initiator tRNA and carries it to the ribosome. In its GDP-bound, "OFF" conformation, it dissociates from tRNA. To understand the specific binding of GTP and GDP and its dependence on the ON or OFF conformational state of aIF2, molecular dynamics free energy simulations (MDFE) are a tool of choice. However, the validity of the computed free energies depends on the simulation model, including the force field and the boundary conditions, and on the extent of conformational sampling in the simulations. aIF2 and other GTPases present specific difficulties; in particular, the nucleotide ligand coordinates a divalent Mg(2+) ion, which can polarize the electronic distribution of its environment. Thus, a force field with an explicit treatment of electronic polarizability could be necessary, rather than a simpler, fixed charge force field. Here, we begin by comparing a fixed charge force field to quantum chemical calculations and experiment for Mg(2+):phosphate binding in solution, with the force field giving large errors. Next, we consider GTP and GDP bound to aIF2 and we compare two fixed charge force fields to the recent, polarizable, AMOEBA force field, extended here in a simple, approximate manner to include GTP. We focus on a quantity that approximates the free energy to change GTP into GDP. Despite the errors seen for Mg(2+):phosphate binding in solution, we observe a substantial cancellation of errors when we compare the free energy change in the protein to that in solution, or when we compare the protein ON and OFF states. Finally, we have used the fixed charge force field to perform MDFE simulations and alchemically transform GTP into GDP in the protein and in solution. With a total of about 200 ns of molecular dynamics, we obtain good convergence and a reasonable statistical uncertainty, comparable to the force field uncertainty, and somewhat lower than the predicted GTP/GDP binding free energy differences. The sign and magnitudes of the differences can thus be interpreted at a semiquantitative level, and are found to be consistent with the experimental binding preferences of ON- and OFF-aIF2