How to impose microscopic reversibility in complex reaction mechanisms

Most, but not all, ion channels appear to obey the law of microscopic reversibility (or detailed balance). During the fitting of reaction mechanisms it is therefore often required that cycles in the mechanism should obey microscopic reversibility at all times. In complex reaction mechanisms, especially those that contain cubic arrangements of states, it may not be obvious how to achieve this. Three general methods for imposing microscopic reversibility are described. The first method works by setting the 'obvious' four-state cycles in the correct order. The second method, based on the idea of a spanning tree, works by finding independent cycles (which will often have more than four states) such that the order in which they are set does not matter. The third method uses linear algebra to solve for constrained rates.     

biochemical reaction mechanisms in sulfur oxidation by chemosynthetic bacteria

Summary Aspects of the biochemistry of the oxidation of inorganic sulfur compounds are discussed in thiobacilli but chiefly inThiobacillus denitrificans. Almost all of the thiobacilli (e.g. T. denitrificans, T. neapolitanus, T. novellus, andThiobacillus A ₂) were capable of producing approximately 7.5 moles of sulfuric acid aerobically from 3.75 moles of thiosulfate per gram of cellular protein per hr. By far the most prolific producer of sulfuric acid (or sulfates) from the anaerobic thiosulfate oxidation with nitrates wasT. denitrificans which was capable of producing 15 moles of sulfates from 7.5 moles of thiosulfate with concomitant reduction of 12 moles of nitrate resulting in the evolution of 6 moles of nitrogen gas/g protein/hr. The oxidation of sulfide was mediated by the flavo-protein system and cytochromes ofb, c, o, anda-type. This process was sensitive to flavoprotein inhibitors, antimycin A, and cyanide. The aerobic thiosulfate oxidation on the other hand involved cytochromec : O₂ oxidoreductase region of the electron transport chain and was sensitive to cyanide only. The anaerobic oxidation of thiosulfate byT. denitrificans, however, was severely inhibited by the flavoprotein inhibitors because of the splitting of the thiosulfate molecule into the sulfide and sulfite moieties produced by the thiosulfate-reductase. Accumulation of tetrathionate and to a small extent trithionate and pentathionate occurred during anaerobic growth ofT. denitrificans. These polythionates were subsequently oxidized to sulfate with the concomitant reduction of nitrate to N₂. Intact cell suspensions catalyzed the complete oxidation of sulfide, thiosulfate, tetrathionate, and sulfite to sulfate with the stoichiometric reduction of nitrate, nitrite, nitric oxide, and nitrous oxide to nitrogen gas thus indicating that NO₂ ⁻, NO, and N₂O are the possible intermediates in the denitrification of nitrate. This process was mediated by the cytochrome electron transport chain and was sensitive to the electron transfer inhibitors. The oxidation of sulfite involved cytochrome-linked sulfite oxidase as well as the APS-reductase pathways. The latter was absent inT. novellus andThiobacillus A ₂. In all of the thiobacilli the inner as well as the outer sulfur atoms of thiosulfate were oxidized at approximately the same rate by intact cells. The sulfide oxidation occurred in two stages: (a) a cellular-membrane-associated initial and rapid oxidation reaction which was dependent upon sulfide concentration, and (b) a slower oxidation reaction stage catalyzed by the cellfree extracts, probably involving polysulfides. InT. novellus andT. neapolitanus the oxidation of inorganic sulfur compounds is coupled to energy generation through oxidative phosphorylation, however, the reduction of pyridine nucleotides by sulfur compounds involved an energy-linked reversal of electron transfer. Paper read at the Symposium on the Sulphur Cycle, Wageningen, May 1974. Summary already inserted on p. 189 of the present volume.     

A new dynamical layout algorithm for complex biochemical reaction networks

Background  

To study complex biochemical reaction networks in living cells researchers more and more rely on databases and computational methods. In order to facilitate computational approaches, visualisation techniques are highly important. Biochemical reaction networks, e.g. metabolic pathways are often depicted as graphs and these graphs should be drawn dynamically to provide flexibility in the context of different data. Conventional layout algorithms are not sufficient for every kind of pathway in biochemical research. This is mainly due to certain conventions to which biochemists/biologists are used to and which are not in accordance to conventional layout algorithms. A number of approaches has been developed to improve this situation. Some of these are used in the context of biochemical databases and make more or less use of the information in these databases to aid the layout process. However, visualisation becomes also more and more important in modelling and simulation tools which mostly do not offer additional connections to databases. Therefore, layout algorithms used in these tools have to work independently of any databases. In addition, all of the existing algorithms face some limitations with respect to the number of edge crossings when it comes to larger biochemical systems due to the interconnectivity of these. Last but not least, in some cases, biochemical conventions are not met properly.     

Open-ITC: an alternate computational approach to analyze the isothermal titration calorimetry data of complex binding mechanisms

Isothermal titration calorimetry (ITC) is an important technique used in quantitatively analyzing the global mechanism of protein-protein or protein-ligand interactions through thermodynamic measurements. Among different binding mechanisms, the parallel and ligand induced protein oligomerization mechanisms are technically difficult to analyze compared with a sequential binding mechanism. Here, we present a methodology implemented as a program "Open-ITC" that eliminates the need for exact analytical expressions for free ligand concentrations [L] and mole fractions of bound ligand θ that are required for the thermogram analysis. Adopting a genetic algorithm-based optimization, the thermodynamic parameters are determined, and its standard error is evaluated at the global minimum by calculating the Jacobian matrix. This approach yielded a statistically consistent result for a single-site and a two-site binding protein-ligand system. Further, a comparative simulation of a two-step sequential, a parallel, and a ligand induced oligomerization model revealed that their mechanistic differences are discernable in ITC thermograms, only if the first binding step is weaker compared with the second binding step (K(1) 相似文献   

Structure and reaction mechanisms of multifunctional mitochondrial cytochrome bc1 complex.

The cytochrome bc1 complex from bovine heart mitochondria is a multi-functional enzyme complex. In addition to electron and proton transfer activity, the complex also processes an activatable peptidase activity and a superoxide generating activity. The crystal structure of the complex exists as a closely interacting functional dimer. There are 13 transmembrane helices in each monomer, eight of which belong to cytochrome b, and five of which belong to cytochrome c1, Rieske iron-sulfur protein (ISP), subunits 7, 10 and 11, one each. The distances of 21 A between bL heme and bH heme and of 27 A between bL heme and the iron-sulfur cluster (FeS), accommodate well the observed fast electron transfers between the involved redox centers. However, the distance of 31 A between heme c1 and FeS, makes it difficult to explain the high electron transfer rate between them. 3D structural analyses of the bc1 complexes co-crystallized with the Qu site inhibitors suggest that the extramembrane domain of the ISP may undergo substantial movement during the catalytic cycle of the complex. This suggestion is further supported by the decreased in the cytochrome bc1 complex activity and the increased in activation energy for mutants with increased rigidity in the neck region of ISP.     

Genetic and biochemical mechanisms of rice resistance to planthopper

Key message

This article presents a comprehensive review on the genetic and biochemicalmechanisms governing rice-planthopper interactions, aiming to contribute substantialplanthopper control and facilitate breeding for resistance to planthoppers in rice.

Abstract

The rice planthopper is the most destructive pest of rice and a substantial threat to rice production. The brown planthopper (BPH), white-backed planthopper (WBPH) and small brown planthopper (SBPH) are three species of delphacid planthoppers and important piercing-sucking pests of rice. Host-plant resistance has been recognized as the most practical, economical and environmentally friendly strategy to control planthoppers. Until now, at least 30, 14 and 34 major genes/quantitative trait loci for resistance to BPH, WBPH and SBPH have been identified, respectively. Recent inheritance and molecular mapping of gene analysis showed that some planthopper-resistance genes in rice derived from different donors aggregate in clusters, while resistance to these three species of planthoppers in a single donor is governed not by any one dominant gene but by multiple genes. Notably, Bph14, Bph26, Bph3 and Bph29 were successfully identified as BPH-resistance genes in rice. Biological and chemical studies on the feeding of planthoppers indicate that rice plants have acquired various forms of defence against planthoppers. Between the rice-planthopper interactions, rice plants defend against planthoppers through activation the salicylic acid-dependent systemic acquired resistance but not jasmonate-dependent hormone response pathways. Transgenic rice for the planthopper-resistance mechanism shows that jasmonate and its metabolites function diversely in rice’s resistance to planthopper. Understanding the genetic and biochemical mechanisms underlying resistance in rice will contribute to the substantial control of such pests and facilitate breeding for rice’s resistance to planthopper more efficiently.

     

Mathematical model to predict drivers' reaction speeds

Mental distractions and physical impairments can increase the risk of accidents by affecting a driver's ability to control the vehicle. In this article, we developed a linear mathematical model that can be used to quantitatively predict drivers' performance over a variety of possible driving conditions. Predictions were not limited only to conditions tested, but also included linear combinations of these tests conditions. Two groups of 12 participants were evaluated using a custom drivers' reaction speed testing device to evaluate the effect of cell phone talking, texting, and a fixed knee brace on the components of drivers' reaction speed. Cognitive reaction time was found to increase by 24% for cell phone talking and 74% for texting. The fixed knee brace increased musculoskeletal reaction time by 24%. These experimental data were used to develop a mathematical model to predict reaction speed for an untested condition, talking on a cell phone with a fixed knee brace. The model was verified by comparing the predicted reaction speed to measured experimental values from an independent test. The model predicted full braking time within 3% of the measured value. Although only a few influential conditions were evaluated, we present a general approach that can be expanded to include other types of distractions, impairments, and environmental conditions.     

A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

Background

Sensitivity analysis is an indispensable tool for the analysis of complex systems. In a recent paper, we have introduced a thermodynamically consistent variance-based sensitivity analysis approach for studying the robustness and fragility properties of biochemical reaction systems under uncertainty in the standard chemical potentials of the activated complexes of the reactions and the standard chemical potentials of the molecular species. In that approach, key sensitivity indices were estimated by Monte Carlo sampling, which is computationally very demanding and impractical for large biochemical reaction systems. Computationally efficient algorithms are needed to make variance-based sensitivity analysis applicable to realistic cellular networks, modeled by biochemical reaction systems that consist of a large number of reactions and molecular species.

Results

We present four techniques, derivative approximation (DA), polynomial approximation (PA), Gauss-Hermite integration (GHI), and orthonormal Hermite approximation (OHA), for analytically approximating the variance-based sensitivity indices associated with a biochemical reaction system. By using a well-known model of the mitogen-activated protein kinase signaling cascade as a case study, we numerically compare the approximation quality of these techniques against traditional Monte Carlo sampling. Our results indicate that, although DA is computationally the most attractive technique, special care should be exercised when using it for sensitivity analysis, since it may only be accurate at low levels of uncertainty. On the other hand, PA, GHI, and OHA are computationally more demanding than DA but can work well at high levels of uncertainty. GHI results in a slightly better accuracy than PA, but it is more difficult to implement. OHA produces the most accurate approximation results and can be implemented in a straightforward manner. It turns out that the computational cost of the four approximation techniques considered in this paper is orders of magnitude smaller than traditional Monte Carlo estimation. Software, coded in MATLAB^®, which implements all sensitivity analysis techniques discussed in this paper, is available free of charge.

Conclusions

Estimating variance-based sensitivity indices of a large biochemical reaction system is a computationally challenging task that can only be addressed via approximations. Among the methods presented in this paper, a technique based on orthonormal Hermite polynomials seems to be an acceptable candidate for the job, producing very good approximation results for a wide range of uncertainty levels in a fraction of the time required by traditional Monte Carlo sampling.     

System of Ca2+ transport in spermatozoids and biochemical mechanisms of capacitation and acrosomic reaction

The paper systematizes modern ideas regarding the role of macroelements (including calcium ions) in physico-chemical, biochemical spermatozoid processes, that provides the preservation of their biological completeness and fertility. Information concerning ion content and ion distribution in semen of males of different age groups and in the ejaculate with different quality indicators is presented. The basic ion-transport systems that are identified in spermatozoid membranes of males and their role in sperm activation, cell active movement ability, maintenance of cell homeostasis etc. are discussed. General schemes of biochemical mechanisms of capacitation process and acrosomic reaction are proposed.     

Linking the computational structure of variance adaptation to biophysical mechanisms

In multiple sensory systems, adaptation to the variance of a sensory input changes the sensitivity, kinetics, and average response over timescales ranging from < 100 ms to tens of seconds. Here, we present a simple, biophysically relevant model of retinal contrast adaptation that accurately captures both the membrane potential response and all adaptive properties. The adaptive component of this model is a first-order kinetic process of the type used to describe ion channel gating and synaptic transmission. From the model, we conclude that all adaptive dynamics can be accounted for by depletion of a signaling mechanism, and that variance adaptation can be explained as adaptation to the mean of a rectified signal. The model parameters show strong similarity to known properties of bipolar cell synaptic vesicle pools. Diverse types of adaptive properties that implement theoretical principles of efficient coding can be generated by a single type of molecule or synapse with just a few microscopic states.     

Mathematical and computational modeling in biology at multiple scales

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.     

A new computational method to split large biochemical networks into coherent subnets

Background  

Compared to more general networks, biochemical networks have some special features: while generally sparse, there are a small number of highly connected metabolite nodes; and metabolite nodes can also be divided into two classes: internal nodes with associated mass balance constraints and external ones without. Based on these features, reclassifying selected internal nodes (separators) to external ones can be used to divide a large complex metabolic network into simpler subnetworks. Selection of separators based on node connectivity is commonly used but affords little detailed control and tends to produce excessive fragmentation.