Computational Kinetic Modeling Research Articles

Trace Br- Inhibits Halogenated Byproduct Formation in Saline Wastewater Electrochemical Treatment.

The electrochemical technology provides a practical and viable solution to the global water scarcity issue, but it has an inherent challenge of generating toxic halogenated byproducts in treatment of saline wastewater. Our study reveals an unexpected discovery: the presence of a trace amount of Br- not only enhanced the electrochemical oxidation of organic compounds with electron-rich groups but also significantly reduced the formation of halogenated byproducts. For example, in the presence of 20 μM Br-, the oxidation rate of phenol increased from 0.156 to 0.563 min-1, and the concentration of total organic halogen decreased from 59.2 to 8.6 μM. Through probe experiments, direct electron transfer and HO• were ruled out as major contributors; transient absorption spectroscopy (TAS) and computational kinetic models revealed that trace Br- triggers a shift in the dominant reactive species from Cl2•- to Br2•-, which plays a key role in pollutant removal. Both TAS and electron paramagnetic resonance identified signals unique to the phenoxyl and carbon-centered radicals in the Br2•--dominated system, indicating distinct reaction mechanisms compared to those involving Cl2•-. Kinetic isotope experiments and density functional theory calculations confirmed that the interaction between Br2•- and phenolic pollutants follows a hydrogen atom abstraction pathway, whereas Cl2•- predominantly engages pollutants through radical adduct formation. These insights significantly enhance our understanding of bromine radical-involved oxidation processes and have crucial implications for optimizing electrochemical treatment systems for saline wastewater.

Translational buffering by ribosome stalling in upstream open reading frames.

Upstream open reading frames (uORFs) are present in over half of all human mRNAs. uORFs can potently regulate the translation of downstream open reading frames through several mechanisms: siphoning away scanning ribosomes, regulating re-initiation, and allowing interactions between scanning and elongating ribosomes. However, the consequences of these different mechanisms for the regulation of protein expression remain incompletely understood. Here, we performed systematic measurements on the uORF-containing 5' UTR of the cytomegaloviral UL4 mRNA to test alternative models of uORF-mediated regulation in human cells. We find that a terminal diproline-dependent elongating ribosome stall in the UL4 uORF prevents decreases in main ORF protein expression when ribosome loading onto the mRNA is reduced. This uORF-mediated buffering is insensitive to the location of the ribosome stall along the uORF. Computational kinetic modeling based on our measurements suggests that scanning ribosomes dissociate rather than queue when they collide with stalled elongating ribosomes within the UL4 uORF. We identify several human uORFs that repress main ORF protein expression via a similar terminal diproline motif. We propose that ribosome stalls in uORFs provide a general mechanism for buffering against reductions in main ORF translation during stress and developmental transitions.

DJ-1 is not a deglycase and makes a modest contribution to cellular defense against methylglyoxal damage in neurons.

Human DJ‐1 is a cytoprotective protein whose absence causes Parkinson's disease and is also associated with other diseases. DJ‐1 has an established role as a redox‐regulated protein that defends against oxidative stress and mitochondrial dysfunction. Multiple studies have suggested that DJ‐1 is also a protein/nucleic acid deglycase that plays a key role in the repair of glycation damage caused by methylglyoxal (MG), a reactive α‐keto aldehyde formed by central metabolism. Contradictory reports suggest that DJ‐1 is a glyoxalase but not a deglycase and does not play a major role in glycation defense. Resolving this issue is important for understanding how DJ‐1 protects cells against insults that can cause disease. We find that DJ‐1 reduces levels of reversible adducts of MG with guanine and cysteine in vitro. The steady‐state kinetics of DJ‐1 acting on reversible hemithioacetal substrates are fitted adequately with a computational kinetic model that requires only a DJ‐1 glyoxalase activity, supporting the conclusion that deglycation is an apparent rather than a true activity of DJ‐1. Sensitive and quantitative isotope‐dilution mass spectrometry shows that DJ‐1 modestly reduces the levels of some irreversible guanine and lysine glycation products in primary and cultured neuronal cell lines and whole mouse brain, consistent with a small but measurable effect on total neuronal glycation burden. However, DJ‐1 does not improve cultured cell viability in exogenous MG. In total, our results suggest that DJ‐1 is not a deglycase and has only a minor role in protecting neurons against methylglyoxal toxicity.

It Is Good to Be Flexible: Energy Transport Facilitated by Conformational Fluctuations in Light-Harvesting Polymers.

We investigate the mechanism of energy transfer between ruthenium(II) (Ru) and osmium(II) (Os) polypyridyl complexes affixed to a polyfluorene backbone (PF-RuOs) using a combination of time-resolved emission spectroscopy and coarse-grained molecular dynamics (CG MD). Photoexcitation of a Ru chromophore initiates Dexter-style energy hopping along isoenergetic complexes followed by sensitization of a lower-energy Os trap. While we can determine the total energy transfer rate within an ensemble of solvated PF-RuOs from time-dependent Os* emission spectra, heterogeneity of the system and inherent polymer flexibility give rise to highly multiexponential kinetics. We developed a three-part computational kinetic model to supplement our spectroscopic results: (1) CG MD model of PF-RuOs that simulates molecular motions out to 700 ns, (2) energy transfer kinetic simulations in CG MD PF-RuOs that produce time-resolved Ru and Os excited-state populations, and (3) computational experiments that interrogate the mechanisms by which motion aids energy transfer. Good agreement between simulated and experimental emission transients reveals that our kinetic model accurately simulates the molecular motion of PF-RuOs during energy transfer. Simulated results indicate that pendant flexibility allows 81% of the excited state to sensitize an Os trap compared to a 48% occupation when we treat pendants statically. Our computational experiments show how static pendants are only able to engage in local energy transfer. The excited state equilibrates across a domain of complexes proximal to the initial excitation and becomes trapped within that unique, frozen locality. Side-chain flexibility enables pendants to swing in and out of the original domain spreading the excited state out to ±30 pendant complexes away from the initial excitation.

Removal of Antibiotic Resistant Bacteria and Genes by UV-Assisted Electrochemical Oxidation on Degenerative TiO2 Nanotube Arrays.

Antibiotic resistance has become a global crisis in recent years, while wastewater treatment plants (WWTPs) have been identified as a significant source of both antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). However, commonly used disinfectants have been shown to be ineffective for the elimination of ARGs. With the goal of upgrading the conventional UV disinfection unit with stronger capability to combat ARB and ARGs, we developed a UV-assisted electrochemical oxidation (UV-EO) process that employs blue TiO2 nanotube arrays (BNTAs) as photoanodes. Inactivation of tetracycline- and sulfamethoxazole-resistant E. coli along with degradation of the corresponding plasmid coded genes (tetA and sul1) is measured by plate counting on selective agar and qPCR, respectively. In comparison with UV254 irradiation alone, enhanced ARB inactivation and ARG degradation is achieved by UV-EO. Chloride significantly promotes the inactivation efficiency due to the electrochemical production of free chlorine and the subsequent UV/chlorine photoreactions. The fluence-based first-order kinetic rate coefficients of UV-EO in Cl- are larger than those of UV254 irradiation alone by a factor of 2.1-2.3 and 1.3-1.8 for the long and short target genes, respectively. The mechanism of plasmid DNA damage by different radical species is further explored using gel electrophoresis and computational kinetic modeling. The process can effectively eliminate ARB and ARGs in latrine wastewater, though the kinetics were retarded.

Controlled Multifactorial Coagulopathy: Effects of Dilution, Hypothermia, and Acidosis on Thrombin Generation In Vitro.

Coagulopathy and hemostatic abnormalities remain a challenge in patients following trauma and major surgery. Coagulopathy in this setting has a multifactorial nature due to tissue injury, hemodilution, hypothermia, and acidosis, the severity of which may vary. In this study, we combined computational kinetic modeling and in vitro experimentation to investigate the effects of multifactorial coagulopathy on thrombin, the central enzyme in the coagulation system. We measured thrombin generation in platelet-poor plasma from 10 healthy volunteers using the calibrated automated thrombogram assay (CAT). We considered 3 temperature levels (31°C, 34°C, and 37°C), 3 pH levels (6.9, 7.1, and 7.4), and 3 degrees of dilution with normal saline (no dilution, 3-fold dilution, and 5-fold dilution). We measured thrombin-generation time courses for all possible combinations of these conditions. For each combination, we analyzed 2 scenarios: without and with (15 nM) supplementation of thrombomodulin, a key natural regulator of thrombin generation. For each measured thrombin time course, we recorded 5 quantitative parameters and analyzed them using multivariable regression. Moreover, for multiple combinations of coagulopathic conditions, we performed routine coagulation tests: prothrombin time (PT) and activated partial thromboplastin time (aPTT). We compared the experimental results with simulations using a newly developed version of our computational kinetic model of blood coagulation. Regression analysis allowed us to identify trends in our data (P < 10). In both model simulations and experiments, dilution progressively reduced the peak of thrombin generation. However, we did not experimentally detect the model-predicted delay in the onset of thrombin generation. In accord with the model predictions, hypothermia delayed the onset of thrombin generation; it also increased the thrombin peak time (up to 1.30-fold). Moreover, as predicted by the kinetic model, the experiments showed that hypothermia increased the area under the thrombin curve (up to 1.97-fold); it also increased the height of the thrombin peak (up to 1.48-fold). Progressive acidosis reduced the velocity index by up to 24%; acidosis-induced changes in other thrombin generation parameters were much smaller or none. Acidosis increased PT by 14% but did not influence aPTT. In contrast, dilution markedly prolonged both PT and aPTT. In our experiments, thrombomodulin affected thrombin-generation parameters mainly in undiluted plasma. Dilution with normal saline reduced the amount of generated thrombin, whereas hypothermia increased it and delayed the time of thrombin accumulation. In contrast, acidosis in vitro had little effect on thrombin generation.

Determinants of Isoform-Specific Gating Kinetics of hERG1 Channel: Combined Experimental and Simulation Study.

IKr is the rapidly activating component of the delayed rectifier potassium current, the ion current largely responsible for the repolarization of the cardiac action potential. Inherited forms of long QT syndrome (LQTS) (Lees-Miller et al., 1997) in humans are linked to functional modifications in the Kv11.1 (hERG) ion channel and potentially life threatening arrhythmias. There is little doubt now that hERG-related component of IKr in the heart depends on the tetrameric (homo- or hetero-) channels formed by two alternatively processed isoforms of hERG, termed hERG1a and hERG1b. Isoform composition (hERG1a- vs. the b-isoform) has recently been reported to alter pharmacologic responses to some hERG blockers and was proposed to be an essential factor pre-disposing patients for drug-induced QT prolongation. Very little is known about the gating and pharmacological properties of two isoforms in heart membranes. For example, how gating mechanisms of the hERG1a channels differ from that of hERG1b is still unknown. The mechanisms by which hERG 1a/1b hetero-tetramers contribute to function in the heart, or what role hERG1b might play in disease are all questions to be answered. Structurally, the two isoforms differ only in the N-terminal region located in the cytoplasm: hERG1b is 340 residues shorter than hERG1a and the initial 36 residues of hERG1b are unique to this isoform. In this study, we combined electrophysiological measurements for HEK cells, kinetics and structural modeling to tease out the individual contributions of each isoform to Action Potential formation and then make predictions about the effects of having various mixture ratios of the two isoforms. By coupling electrophysiological data with computational kinetic modeling, two proposed mechanisms of hERG gating in two homo-tetramers were examined. Sets of data from various experimental stimulation protocols (HEK cells) were analyzed simultaneously and fitted to Markov-chain models (M-models). The minimization procedure presented here, allowed assessment of suitability of different Markov model topologies and the corresponding parameters that describe the channel kinetics. The kinetics modeling pointed to key differences in the gating kinetics that were linked to the full channel structure. Interactions between soluble domains and the transmembrane part of the channel appeared to be critical determinants of the gating kinetics. The structures of the full channel in the open and closed states were compared for the first time using the recent Cryo-EM resolved structure for full open hERG channel and an homology model for the closed state, based on the highly homolog EAG1 channel. Key potential interactions which emphasize the importance of electrostatic interactions between N-PAS cap, S4-S5, and C-linker are suggested based on the structural analysis. The derived kinetic parameters were later used in higher order models of cells and tissue to track down the effect of varying the ratios of hERG1a and hERG1b on cardiac action potentials and computed electrocardiograms. Simulations suggest that the recovery from inactivation of hERG1b may contribute to its physiologic role of this isoform in the action potential. Finally, the results presented here contribute to the growing body of evidence that hERG1b significantly affects the generation of the cardiac Ikr and plays an important role in cardiac electrophysiology. We highlight the importance of carefully revisiting the Markov models previously proposed in order to properly account for the relative abundance of the hERG1 a- and b- isoforms.

The effect of solvation on the reactivity of 1,1-substituted ethylenes in hydroperoxyl radical addition reactions

The effect of solvation on the rate constants of hydroperoxyl radical addition to the double bonds of 1,1-substituted ethylene vinyl compounds was studied in the medium of different polarity solvents. The values of rate constants of this process were determined in a series of experiments on the co-oxidation of diphenylethylene (was used as the source of hydroperoxyl radicals) with the studied vinyl compounds at 323 K using the method of microvolumetry in combination with ESR spectroscopy and computer kinetic modeling. The observed linear relationship between the values of rate constant logarithms and the dielectric permittivity of reaction medium in coordinates of the Kirkwood–Onsager equation allows for the conclusion that the effect of nonspecific solvation due to the electrostatic forces does take place in the studied systems.

Computational Kinetic Modeling of the Catalytic Cycle of Glutathione Peroxidase Nanomimic: Effect of Nucleophilicity of Thiols on the Catalytic Activity.

The catalytic cycle of a new derivative of ebselen, 1, was elucidated via three steps by the density functional theory and solvent-assisted proton exchange procedure involving indirect proton exchange through a hydrogen-bonded transfer network. Different behaviors of the aromatic and aliphatic thiols were investigated in the reduction of selenoxide (step 2 → 3) and selenurane (step 3 → 1) based on their nucleophilicity. The reduction of selenoxide in the presence of thiophenol (ΔG‡ = 15.9 kcal·mol-1) is faster than that of methanethiol (ΔG‡ = 29.3 kcal·mol-1), and methanethiol makes the reduction of selenoxide unspontaneous and kinetically unfavorable (ΔG = 2.8 kcal·mol-1). The nucleophilic attack may be enhanced by using the thiophenol backbone at the selenium center to lower the energy barrier of the selenoxide reduction (ΔG‡ = 15.9 kcal·mol-1). On the basis of the turnover frequency calculations, during the catalytic cycle, the rate of the reaction was analyzed and discussed. Low values of the electron density and Laplacian at the transition states are the evidence of the covalent O-H and O-O bonds rupture in the presence of methanethiol and thiophenol. The nature of the critical bond points was characterized, using the quantum theory of atoms in molecules, based on the electron location function and localized orbital locator values. Finally, the charge transfer process at the rate-determining step was investigated based on the natural bond orbital analysis.

Computational kinetic modeling of the selenol catalytic activity as the glutathione peroxidase nanomimic

Density functional theory and solvent-assisted proton exchange methods have been applied for computational modeling of the catalytic cycle of selenol zwitterion anion from the kinetic and thermodynamic viewpoints. Selenol zwitterion anion has been represented as an effective glutathione peroxidase nanomimic. It reduces peroxides through a three-step pathway. In the first step, seleninic acid is produced through deprotonating of the selenol zwitterion anion in the presence of the hydrogen peroxide. Seleninic acid reacts with a thiol to form selenylsulfide in the second step. In the last step, selenylsulfide is reduced by the second thiol and regenerates selenolate anion through disulfide formation. Selenol zwitterion anion in comparison to more widely studied compounds such as ebselen has a good activity to react with hydrogen peroxide and producing seleninic acid. The energy barrier of this reaction is 11.7kcalmol−1 which is smaller than the reported enzyme mimics. Moreover, the reactions of seleninic acid and selenylsulfide with methanethiol, which is used as a nucleophile, are exothermic by −18.4 or −57.0kcalmol−1, respectively. Based on the global electron density transfer value of −0.507 e from the natural atomic charge analysis, an electronic charge depletion at the transition state (TS), electron-donor substitutions on the selenolate facilitates the reduction reaction, effectively. Finally, the nature of the bond formation/cleavage at the TS has been quantitatively described by using the topological analyses.

Heterojunction Electrode Designed for Saline Wastewater Electrolysis

Electrochemical oxidation is a promising candidate for decentralized wastewater treatment, due to its modular design, convenient operation, and small carbon footprint. In this process, pollutants are oxidized at the anode, while valuable hydrogen is produced at the cathode. Different from water splitting, the ideal anodes in EO process should have high activity toward oxidant generation rather than oxygen evolution. The need to develop highly efficient and durable anode material is a never-ending challenge. Chloride, as a ubiquitous component in wastewater, can be oxidized readily to reactive chlorine species (RCS = OCl­-, HOCl, Cl·, and Cl2·-) to remove pollutants such as organics, ammonium and bacteria. However the speciation of RCS in saline water electrolysis is lacking of quantitative description. The contribution of each RCS species to pollutant removal is still under debate. The first approach of this study is to develop multi-layer heterojunction anode for RCS generation. IrO2 is an excellent catalyst for water splitting. By depositing a thin film of TiO2 on IrO2 (Ti/Ir), the oxygen evolution reaction is hindered while the selectivity toward chlorine production is greatly enhanced. The further deposition of Sb-SnO2 islands on TiO2layer (Sn/Ti/Ir) provides additional active sites for radical generation. As our second approach, a computational kinetic model covering chlorine generation and radical production is established. Combing it with experimental data, chlorine evolution and the furuther oxidation of chlorine to ClO3- and ClO4 - on Ti/Ir anode can be simulated. It is found that Cl·and HO· is produced concomitantly with chlorine on Sn/Ti/Ir anode and Cl2·-is the dominant radical after reaching equilibrium. The rate constant of Cl· production is two to three orders of magnitude lower than that of chlorine generation. The model predicts that the increase of chloride concentration will enhance the chlorine production but quench more radicals, which is in consistance with experimental results. The best performing Sn/Ti/Ir anode was applied to human wastewater electrolysis. Although Cl2·- is more oxidative than chlorine, chlorine is the major contributor to the removal of organics and ammonium due to its higher concentration. Figure 1

A computational kinetic model of diffusion for molecular systems

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

Mathematical Modelling of Polyamine Metabolism in Bloodstream-Form Trypanosoma brucei: An Application to Drug Target Identification

We present the first computational kinetic model of polyamine metabolism in bloodstream-form Trypanosoma brucei, the causative agent of human African trypanosomiasis. We systematically extracted the polyamine pathway from the complete metabolic network while still maintaining the predictive capability of the pathway. The kinetic model is constructed on the basis of information gleaned from the experimental biology literature and defined as a set of ordinary differential equations. We applied Michaelis-Menten kinetics featuring regulatory factors to describe enzymatic activities that are well defined. Uncharacterised enzyme kinetics were approximated and justified with available physiological properties of the system. Optimisation-based dynamic simulations were performed to train the model with experimental data and inconsistent predictions prompted an iterative procedure of model refinement. Good agreement between simulation results and measured data reported in various experimental conditions shows that the model has good applicability in spite of there being gaps in the required data. With this kinetic model, the relative importance of the individual pathway enzymes was assessed. We observed that, at low-to-moderate levels of inhibition, enzymes catalysing reactions of de novo AdoMet (MAT) and ornithine production (OrnPt) have more efficient inhibitory effect on total trypanothione content in comparison to other enzymes in the pathway. In our model, prozyme and TSHSyn (the production catalyst of total trypanothione) were also found to exhibit potent control on total trypanothione content but only when they were strongly inhibited. Different chemotherapeutic strategies against T. brucei were investigated using this model and interruption of polyamine synthesis via joint inhibition of MAT or OrnPt together with other polyamine enzymes was identified as an optimal therapeutic strategy.

Computational Thermodynamic and Kinetic Modeling of High-Entropy Alloys and Amorphous Alloys

The first subset topic of this issue concerns computational modeling of high-entropy alloys (HEAs). In contrast to conventional alloys that are based on one principal element such as steels and aluminum alloys, HEAs contain multiple principal elements, often five or more in equimolar or near-equimolar ratios. According to the Gibbs phase rule, the number of phases (P) in a given alloy at constant pressure in equilibrium condition is:

Polyreactive antibodies in multidonor-derived immunoglobulin G: Theory and conclusions drawn from experiments

Multidonor-derived (md) preparations of IgG antibodies, agents of therapeutic potential, contain molecules interacting at clonal concentrations (concns) and with affinities recently estimated to cover a considerable range. Here we demonstrate that polyreactivity of the monomeric molecules represents the essential driving force of formation of the main reaction product, the IgG-dimers. This conclusion is obtained by applying the principles of the law of mass action to dimer formation by polyreactive monomeric reactants. In addition, general interrelationships involving the mean number of reactants per reactor, the experimental dimer portion (w/w) and the mean concentrations of monomers in a polyreactive and monoreactive antibody system are derived. These interrelationships, together with quantitative results obtained from simplified computational kinetic models of polyreactive antibodies, allow to estimate a remarkably high value for the mean number of reactants per reactor, exceeding 60 for the underlying IgG preparation obtained from pooled human plasma units of 5000 donors. Moreover, the potential origin and other consequences of polyreactivity are outlined.

Computational kinetic model of VEGF trapping by soluble VEGF receptor-1: effects of transendothelial and lymphatic macromolecular transport

Vascular endothelial growth factor (VEGF) signal transduction through the cell surface receptors VEGFR1 and VEGFR2 regulates angiogenesis-the growth of new capillaries from preexistent microvasculature. Soluble VEGF receptor-1 (sVEGFR1), a nonsignaling truncated variant of VEGFR1, has been postulated to inhibit angiogenic signaling via direct sequestration of VEGF ligands or dominant-negative heterodimerization with surface VEGFRs. The relative contributions of these two mechanisms to sVEGFR1's purported antiangiogenic effects in vivo are currently unknown. We previously developed a computational model for predicting the compartmental distributions of VEGF and sVEGFR1 throughout the healthy human body by simulating the molecular interaction networks of the VEGF ligand-receptor system as well as intercompartmental macromolecular biotransport processes. In this study, we decipher the dynamic processes that led to our prior prediction that sVEGFR1, through its ligand trapping mechanism alone, does not demonstrate significant steady-state antiangiogenic effects. We show that sVEGFR1-facilitated tissue-to-blood shuttling of VEGF accounts for a counterintuitive and drastic elevation in plasma free VEGF concentrations after both intramuscular and intravascular sVEGFR1 infusion. While increasing intramuscular VEGF production reduces free sVEGFR1 levels through increased VEGF-sVEGFR1 complex formation, we demonstrate a competing and opposite effect in which increased VEGF occupancy of neuropilin-1 (NRP1) and the corresponding reduction in NRP1 availability for internalization of sVEGFR1 unexpectedly increases free sVEGFR1 levels. In conclusion, dynamic intercompartmental transport processes give rise to our surprising prediction that VEGF trapping alone does not account for sVEGFR1's antiangiogenic potential. sVEGFR1's interactions with cell surface receptors such as NRP1 are also expected to affect its molecular interplay with VEGF.

A statistical methodology for computational models of hepatic metabolism and sensitivity analysis

The computational kinetic models of liver metabolism that we consider follow the changes in time of the profiles of metabolites in tissue and blood. A major challenge of complex kinetic models is the assignment of values to the large number of parameters in the kinetic expressions for reaction fluxes and transport rates, as well as the determination of initial concentrations of metabolites and intermediates. The novelty of our approach is that, by modeling the unknowns as random variables, we look not for single numerical estimates but for distributions of values. This approach, which follows the paradigm of Bayesian statistical inference, can account for uncertainty in the experimental data utilized and takes advantage of any type of a priori information available about the parameters and the system. The ensemble of models thus obtained is used to predict time courses of metabolites and fluxes of interest. The collection of model predictions can be further analyzed to identify hidden dependencies among metabolic pathways.

Experimental Studies on Protein Folding in the Presence of the Hsp70 Chaperone System

The Hsp70 chaperone system (including DnaK, DnaJ and GrpE in bacteria) plays a vital role in preventing aggregation and assisting protein folding. While a lot of the chaperone biochemistry has already been worked out, very little is know about the interaction of DnaK and DnaJ with substrates. So far, such interaction had only been probed with small peptide or protein substrates incapable of independent/efficient refolding. This paucity of information has precluded studies on the competition between inter-molecular binding and intra-molecular folding. Such competition is important for cell viability because the accessibility of DnaK to substrate binding is modulated by the intrinsic rates of substrate folding/unfolding and by the substrate's thermodynamic stability.We developed a computational kinetic model to predict the interaction of protein substrates exhibiting two-state folding behavior with DnaK, DnaJ and GrpE. We found that, under physiological conditions, only proteins that fold slowly and/or have moderate thermodynamic stability are predicted to bind chaperones during their folding cycle.Experimental protein folding kinetics followed by stopped-flow in the presence and absence of the Hsp70 chaperone system shows good agreement with the predictions by the computational model. Furthermore, gel filtration and reverse phase chromatography data further support the stopped-flow results by providing evidence for DnaK-DnaJ-substrate interactions at equilibrium. This result is in agreement with the predictions of the computational model. In summary, the combination of experiments and computational predictions developed in this work is a powerful tool to help unveiling the relations between protein folding and chaperone binding.

Experimental and modeling study of the effect of CH 4 and pulverized coal on selective non-catalytic reduction process

The reduction of nitric oxide using ammonia combined with methane and pulverized coal additives has been studied in a drop tube furnace reactor. Simulated flue gas with 1000 ppm NO x and 3.4% excess oxygen was generated by cylinder gas. Experiments were performed in the temperature range of 700–1200 °C to investigate the effects of additives on the DeNO x performance. Subsequently, a kinetic mechanism was modified and validated based on experimental results, and a computational kinetic modeling with CHEMKIN was conducted to analyze the secondary pollutants. For both methane and pulverized coal additives, the temperature window is shifted towards lower temperatures. The appropriate reaction temperature is shifted to about 900 and 800 °C, respectively with 1000 ppm methane and 0.051 g min −1 pulverized lignite coal. The addition of methane and pulverized coal widens the temperature window towards lower temperature suggesting a low temperature application of the process. Furthermore, selective non-catalytic reduction (SNCR) reaction rate is accelerated evidently with additives and the residence time to complete the reaction is shortened distinctly. NO x reduction efficiency with 80% is achieved in about 0.3 s without additive at 1000 °C. However, it is achieved in only about 0.2 s with 100 ppm methane as additive, and only 0.07 and 0.05 s are needed respectively for the cases of 500 and 1000 ppm methane. The modified kinetic modeling agrees well with the experimental results and reveals additional information about the process. Investigation on the byproducts where NO 2 and N 2O were analyzed by modeling and the others were investigated by experimental means indicates that emissions would not increase with methane and pulverized coal additions in SNCR process and the efficacious temperature range of SNCR reaction is widened approximately with 100 °C.

Systems biology of mucosal injury in cancer patients

9634 Background: Mucosal injury (mucositis) caused by high-dose or targeted cancer therapy can result in significant morbidity and financial cost. Understanding the causative complex molecular pathways of this toxicity will enhance design of new therapies. Computational reaction kinetic biological models represent an important strategic advance in this regard. These simulations are cost- and time- efficient and can identify new hypotheses and projected experimental outcomes. The technology also permits integration of complex models based on animal and human data. Methods: A mucositis reaction network structure was developed using COX-2 pathway data derived from literature-based animal and human studies as well as pre- and post-transplant oral mucosal biopsies from three hematopoietic cell transplant patients. Virtual Cell software was used to simulate network dynamics. Results: The nonlinear network mucositis model incorporated feedback loops and accounted for dynamic response of COX-1, COX-2, TNF-α, PGE-...