Biomedical subjects

Linda J Broadbelt

Publications and source records attributed to Linda J Broadbelt.

12 recordsLinked to original sources

PubMed2006

Thermodynamics-based metabolic flux analysis.

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.

Escherichia coli↗

PubMed2006

Analysis of the maximum theoretical yield for the synthesis of erythromycin precursors in Escherichia coli.

The heterologous biosynthesis of complex polyketides in Escherichia coli was recently achieved through metabolic engineering. However, it was observed that less than 10% of the propionate carbon source is transformed into the erythromycin precursor, 6-deoxyerythronolide B (6dEB), resulting in a 1.4% molar yield. Therefore, metabolic flux analysis was performed using a model of the Escherichia coli metabolism with the addition of the enzymes required for 6dEB synthesis. The analysis shows that the maximum theoretical yield for 6dEB synthesis in E. coli is 11%. The maintenance energy requirement of E. coli and limitations in the specific oxygen uptake rate can further decrease the yield, suggesting that the observed 6dEB yield of 1.4% can be the result of these two factors. In addition, the results suggest that an increase in the specific carbon and oxygen uptake rates will increase the yield of 6dEB. The use of glucose as an alternative carbon source was also evaluated using metabolic flux analysis and the results suggest that the choice of glucose as the carbon source will allow a small improvement in performance relative to a propionate-based process.

Anti-Bacterial Agents↗

PubMed2006

Quantum chemical investigation of low-temperature intramolecular hydrogen transfer reactions of hydrocarbons.

The B3LYP functional was evaluated as a method to calculate reaction barriers and structure-reactivity relationships for intramolecular hydrogen transfer reactions involving peroxy radicals. Nine different basis sets as well as five other MO/DFT and hybrid methods were used in comparing three reactions to available experimental data. It was shown that B3LYP/6-311+G(d,p) offers a good compromise between speed and accuracy for studies in which thermodynamic and kinetic data of many reactions are required. Sixteen reactions were studied to develop structure-reactivity relationships to correlate the activation energy with the heat of reaction. As long as no structural heterogeneities were present in the transition state ring, a simple Evans-Polanyí relationship was shown to capture the activation energy as a function of heat of reaction for reactions in the 1,5-hydrogen shift family. For peroxy radicals undergoing self-abstraction of a hydrogen atom in the 1,5-position, the activation energy was calculated as E(a) (kcal mol(-1)) = 6.3 + Delta H(rxn) (kcal mol(-1)). For reactions with a carbonyl group embedded in the ring of the transition state, the activation energy of peroxy radicals undergoing self-abstraction was correlated as E(a) (kcal mol(-1)) = 18.1 + 0.74 Delta H(rxn) (kcal mol(-1)). The impact of the size of the transition state ring on the activation energy and pre-exponential factor was also probed, and it was shown that these effects can be described using simple nonlinear and linear fits, respectively.

Journal Article↗

PubMed2005

Genome-scale thermodynamic analysis of Escherichia coli metabolism.

Genome-scale metabolic models are an invaluable tool for analyzing metabolic systems as they provide a more complete picture of the processes of metabolism. We have constructed a genome-scale metabolic model of Escherichia coli based on the iJR904 model developed by the Palsson Laboratory at the University of California at San Diego. Group contribution methods were utilized to estimate the standard Gibbs free energy change of every reaction in the constructed model. Reactions in the model were classified based on the activity of the reactions during optimal growth on glucose in aerobic media. The most thermodynamically unfavorable reactions involved in the production of biomass in E. coli were identified as ATP phosphoribosyltransferase, ATP synthase, methylene-tetra-hydrofolate dehydrogenase, and tryptophanase. The effect of a knockout of these reactions on the production of biomass and the production of individual biomass precursors was analyzed. Changes in the distribution of fluxes in the cell after knockout of these unfavorable reactions were also studied. The methodologies and results discussed can be used to facilitate the refinement of the feasible ranges for cellular parameters such as species concentrations and reaction rate constants.

ATP Phosphoribosyltransferase↗

PubMed2005

Structural relaxation of polymer glasses at surfaces, interfaces, and in between.

We analyzed the glassy-state structural relaxation of polymers near surfaces and interfaces by monitoring fluorescence in multilayer films. Relative to that of bulk, the rate of structural relaxation of poly(methyl methacrylate) is reduced by a factor of 2 at a free surface and by a factor of 15 at a silica substrate interface; the latter exhibits a nearly complete arresting of relaxation. The distribution in relaxation rates extends more than 100 nanometers into the film interior, a distance greater than that over which surfaces and interfaces affect the glass transition temperature.

Journal Article↗

PubMed2005

Theoretical considerations and computational analysis of the complexity in polyketide synthesis pathways.

The emergence of antimicrobial resistance has led to an increase in research directed toward the engineering of novel polyketides. To date, less than 10 000 polyketide structures have been discovered experimentally; however, the theoretical analysis of polyketide biosynthesis performed suggests that over a billion possible structures can be synthesized. Polyketide synthesis, which involves the formation of a linear chain and its subsequent cyclization, is catalyzed by an enzyme complex called polyketide synthase (PKS). There are a number of variables in the linear chain synthesis controlled by the PKS: the number, identity, stereochemistry and sequence of the monomer units used in the elongation steps, and the degree of reduction that occurs after each of the condensation reactions. The theoretical analysis performed demonstrates that changes in these variables lead to the formation of different polyketide linear chains and, consequently, a high diversity of polyketide structures. The complexity in the number of possible structures led to the implementation of this system in BNICE, a computational framework that generates all possible biochemical pathways using a given set of enzyme reaction rules. This formulation allowed the analysis of the evolution of diversity in the synthesis mechanism and the construction of the pathway architecture of polyketide biosynthesis. It is expected that, after future implementation of the cyclization reactions, this framework can be used to identify all possible polyketides and their corresponding synthesis pathways. Consequently, this formulation would prove useful in guiding experimental approaches to engineer novel polyketides, a number of which will likely have medicinal properties.

Computational Biology↗

PubMed2004

Exploring the diversity of complex metabolic networks.

MOTIVATION: Metabolism, the network of chemical reactions that make life possible, is one of the most complex processes in nature. We describe here the development of a computational approach for the identification of every possible biochemical reaction from a given set of enzyme reaction rules that allows the de novo synthesis of metabolic pathways composed of these reactions, and the evaluation of these novel pathways with respect to their thermodynamic properties. RESULTS: We applied this framework to the analysis of the aromatic amino acid pathways and discovered almost 75,000 novel biochemical routes from chorismate to phenylalanine, more than 350,000 from chorismate to tyrosine, but only 13 from chorismate to tryptophan. Thermodynamic analysis of these pathways suggests that the native pathways are thermodynamically more favorable than the alternative possible pathways. The pathways generated involve compounds that exist in biological databases, as well as compounds that exist in chemical databases and novel compounds, suggesting novel biochemical routes for these compounds and the existence of biochemical compounds that remain to be discovered or synthesized through enzyme and pathway engineering. AVAILABILITY: Framework will be available via web interface at http://systemsbiology.northwestern.edu/BNICE (site under construction). CONTACT: vassily@northwestern.edu or broadbelt@northwestern.edu SUPPLEMENTARY INFORMATION: http://systemsbiology.northwestern.edu/BNICE/publications.

Amino Acids, Aromatic↗

PubMed2004

Metabolic networks: enzyme function and metabolite structure.

Metabolism is one of the most complex cellular processes. Connections between biochemical reactions via substrate and product metabolites create complex metabolic networks that may be analyzed using network theory, stoichiometric analysis, and information on protein structure/function and metabolite properties. These frameworks take into consideration different aspects of enzyme chemistry, enzyme structure and metabolite structure, and demonstrate the impact of metabolic biochemistry on the systemic properties of metabolism. The integration of these approaches and the systematic classification of enzyme function and the chemical structure of metabolites will enhance our understanding of metabolism, and could improve our ability to predict enzyme function and novel metabolic pathways.

Enzymes↗

PubMed2002

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

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

Animals↗

PubMedDate not supplied

Many-body optimization using an ab initio monte carlo method.

Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.

Journal Article↗

PubMedDate not supplied

Encoding of polycyclic Si-containing molecules for determining species uniqueness in automated mechanism generation.

Automated mechanism generation is an attractive way to understand the fundamental kinetics of complex reaction systems such as silicon hydride clustering chemistry. It relies on being able to tell molecules apart as they are generated. The graph theoretic foundation allows molecules to be identified using unique notations created from their connectivity. To apply this technique to silicon hydride clustering chemistry, a molecule canonicalization and encoding algorithm was developed to handle complex polycyclic, nonplanar species. The algorithm combines the concepts of extended connectivity and the idea of breaking ties to encode highly symmetric molecules. The connected components in the molecules are encoded separately and reassembled using a depth-first search method to obtain the correct string codes. A revised cycle-finding algorithm was also developed to properly select the cycles used for ring corrections when thermodynamic properties were calculated using group additivity. In this algorithm, the molecules are expressed explicitly as trees, and all linearly independent cycles of every size in the molecule are found. The cycles are then sorted according to their size and functionality, and the cycles with higher priorities will be used to include ring corrections. Applying this algorithm, more appropriate cycle selection and more accurate estimation of thermochemical properties of the molecules can be obtained.

Journal Article↗

PubMedDate not supplied

Ab initio stochastic optimization of conformational and many-body degrees of freedom.

Moderate to large size molecules in solution have complex energy surfaces due to intramolecular (conformational) and intermolecular (many-body) interactions. The first principles Monte Carlo (FPMC) method, previously shown to effectively locate minimum-energy structures for systems with only many-body complexity, has been extended to address conformational flexibility by adding three new Monte Carlo move types. The primary advantage of the FPMC method is the ability to efficiently locate minimum energy structures of molecules with conformational flexibility in the presence of explicit solvent molecules using highly accurate quantum chemical calculations. The additions to FPMC were validated by studying conformers of glycerol, glyceraldehyde, and a large humic acid monomer unit. The structure of glyceraldehyde in the presence of one and two water molecules was also explored to demonstrate the power of FPMC to study systems with both conformational and many-body degrees of freedom.

Journal Article↗