Microcephaly in Neurometabolic Diseases

Neurometabolic disorders are an important group of diseases that mostly occur in neonates and infants. They are mainly due to the lack or dysfunction of an enzyme or cofactors necessary for a specific biochemical reaction, which leads to a deficiency of essential metabolites in the brain. This, in turn, can cause certain neurometabolic diseases. Disruption of metabolic pathways, and the inhibition at earlier stages, may lead to the storage of reaction intermediates, which are often toxic to the developing brain. Symptoms are caused by the progressive deterioration of mental, motor, and perceptual functions. The authors review the diseases with microcephaly, which may be one of the most visible signs of neurometabolic disorders.

SMGen: A Generator of Synthetic Models of Biochemical Reaction Networks

Several software tools for the simulation and analysis of biochemical reaction networks have been developed in the last decades; however, assessing and comparing their computational performance in executing the typical tasks of computational systems biology can be limited by the lack of a standardized benchmarking approach. To overcome these limitations, we propose here a novel tool, named SMGen, designed to automatically generate synthetic models of reaction networks that, by construction, are characterized by relevant features (e.g., system connectivity and reaction discreteness) and non-trivial emergent dynamics of real biochemical networks. The generation of synthetic models in SMGen is based on the definition of an undirected graph consisting of a single connected component that, generally, results in a computationally demanding task; to speed up the overall process, SMGen exploits a main–worker paradigm. SMGen is also provided with a user-friendly graphical user interface, which allows the user to easily set up all the parameters required to generate a set of synthetic models with any number of reactions and species. We analysed the computational performance of SMGen by generating batches of symmetric and asymmetric reaction-based models (RBMs) of increasing size, showing how a different number of reactions and/or species affects the generation time. Our results show that when the number of reactions is higher than the number of species, SMGen has to identify and correct a large number of errors during the creation process of the RBMs, a circumstance that increases the running time. Still, SMGen can generate synthetic models with hundreds of species and reactions in less than 7 s.

Quantifying biochemical reaction rates from static population variability within complex networks

Quantifying biochemical reaction rates within complex cellular processes remains a key challenge of systems biology even as high-throughput single-cell data have become available to characterize snapshots of population variability. That is because complex systems with stochastic and non-linear interactions are difficult to analyze when not all components can be observed simultaneously and systems cannot be followed over time. Instead of using descriptive statistical models, we show that incompletely specified mechanistic models can be used to translate qualitative knowledge of interactions into reaction rate functions from covariability data between pairs of components. This promises to turn a globally intractable problem into a sequence of solvable inference problems to quantify complex interaction networks from incomplete snapshots of their stochastic fluctuations.

Metabolic regulation of species-specific developmental rates

Animals display significant inter-specific variation in the rate of embryonic development despite broad conservation of the overall sequence of developmental events. Differences in biochemical reaction speeds, including the rates of protein production and degradation, are thought to be responsible for distinct species-specific rates of development. However, the cause of differential biochemical reaction speeds between species remains unknown. Using pluripotent stem cells, we have established an in vitro system that recapitulates the two-fold difference in developmental rate between early mouse and human embryos. This system provides a quantitative measure of developmental speed as revealed by the period of the segmentation clock, a molecular oscillator associated with the rhythmic production of vertebral precursors. Using this system, we showed that mass-specific metabolic rates scale with developmental rate and are therefore elevated in mouse cells compared to human cells. We further showed that reducing these metabolic rates by pharmacologically inhibiting the electron transport chain slows down the segmentation clock. The effect of the electron transport chain on the segmentation clock is mediated by the cellular NAD+/NADH redox balance independent of ATP production and, further downstream, by the global rate of protein synthesis. These findings represent a starting point for the manipulation of developmental rate, which would find multiple translational applications including the acceleration of human pluripotent stem cell differentiation for disease modeling and cell-based therapies.

The strategy developed for high conversion and the multiplicity problems of biochemical reaction in a real CSTR with Cholette’s model

In this paper we used the examples for four kinetic schemes under substrate and product inhibition of a biochemical reaction occurring in a real CSTR with Cholette’s model to demonstrate the strategy for high conversion and the multiplicity problem. In addition, it is found that the non-ideal mixing indeed influences the necessary and sufficient conditions for input multiplicity and output multiplicity. Meanwhile, for each of four kinetic schemes under substrate and product inhibition of a biochemical reaction, the input multiplicity regions are found inside the output multiplicity regions. This fact reveals that when deriving an operating strategy to obtain a high conversion and to avoid the control problem, only the output multiplicity is needed to consider even in the CSTR with the input and output multiplicity occurring simultaneously.

WinBEST-KIT: Biochemical Reaction Simulator for Analyzing Multi-Layered Metabolic Pathways

We previously developed the biochemical reaction simulator WinBEST-KIT. In recent years, research interest has shifted from analysis of individual biochemical reactions to analysis of metabolic pathways as systems. These large-scale and complicated metabolic pathways can be considered as characteristic multi-layered structures, which, for convenience, are separated from whole biological systems according to their specific roles. These pathways include reactants having the same name but with unique stoichiometric coefficients arranged across many different places and connected between arbitrary layers. Accordingly, in this study, we have developed a new version of WinBEST-KIT that allows users (1) to utilize shortcut symbols that can be arranged with multiple reactants having the same name but with unique stoichiometric coefficients, thereby providing a layout that is similar to metabolic pathways depicted in biochemical textbooks; (2) to create layers that divide large-scale and complicated metabolic pathways according to their specific roles; (3) to connect the layers by using shortcut symbols; and (4) to analyze the interactions between these layers. These new and existing features allow users to create and analyze such multi-layered metabolic pathways efficiently. Furthermore, WinBEST-KIT supports SBML, making it possible for users to utilize these new and existing features to create and publish SBML models.

SMGen: A generator of synthetic models of biochemical reaction networks

Several software tools for the simulation and analysis of biochemical reaction networks have been developed in the last decades; however, assessing and comparing their computational performance in executing the typical tasks of Computational Systems Biology can be limited by the lack of a standardized benchmarking approach. To overcome these limitations, we propose here a novel tool, named SMGen, designed to automatically generate synthetic models of biochemical reaction networks that, by construction, are characterized by both features (e.g. system connectivity, reaction discreteness) and emergent dynamics resembling real biological networks. The generation of synthetic models in SMGen is based on the definition of an undirected graph consisting in a single connected component, which generally results in a computationally demanding task. To avoid any burden in the execution time, SMGen exploits a Main-Worker paradigm to speed up the overall process. SMGen is also provided with a user-friendly Graphical User Interface that allows the user to easily set up all the parameters required to generate a set of synthetic models with any used-defined number of reactions and species. We analysed the computational performance of SMGen by generating batches of symmetric and asymmetric RBMs of increasing size, showing how a different number of reactions and/or species affects the generation time. Our results show that when the number of reactions is higher than the number of species, SMGen has to identify and correct high numbers of errors during the creation process of the RBMs, a circumstance that increases the overall running time. Though, SMGen can create synthetic models with 512 species and reactions in less than 7 seconds. The open-source code of SMGen is available on GitLab: https://gitlab.com/sgr34/smgen.

Ether Oxidation by an Evolved Fungal Heme-Peroxygenase: Insights into Substrate Recognition and Reactivity

Ethers can be found in the environment as structural, active or even pollutant molecules, although their degradation is not efficient under environmental conditions. Fungal unspecific heme-peroxygenases (UPO were reported to degrade low-molecular-weight ethers through an H2O2-dependent oxidative cleavage mechanism. Here, we report the oxidation of a series of structurally related aromatic ethers, catalyzed by a laboratory-evolved UPO (PaDa-I) aimed at elucidating the factors influencing this unusual biochemical reaction. Although some of the studied ethers were substrates of the enzyme, they were not efficiently transformed and, as a consequence, secondary reactions (such as the dismutation of H2O2 through catalase-like activity and suicide enzyme inactivation) became significant, affecting the oxidation efficiency. The set of reactions that compete during UPO-catalyzed ether oxidation were identified and quantified, in order to find favorable conditions that promote ether oxidation over the secondary reactions.

Geometry and symmetry in biochemical reaction systems

Complex systems of intracellular biochemical reactions have a central role in regulating cell identities and functions. Biochemical reaction systems are typically studied using the language and tools of graph theory. However, graph representations only describe pairwise interactions between molecular species and so are not well suited to modelling complex sets of reactions that may involve numerous reactants and/or products. Here, we make use of a recently developed hypergraph theory of chemical reactions that naturally allows for higher-order interactions to explore the geometry and quantify functional redundancy in biochemical reactions systems. Our results constitute a general theory of automorphisms for oriented hypergraphs and describe the effect of automorphism group structure on hypergraph Laplacian spectra.

RECENTS TRENDS OF HEPATOPROTECTIVE MEDICINE

The liver is the key organ for maintaining the body’s internal environment and it plays a very significant role in the metabolism of various compounds like carbohydrate, proteins and fats, it also controls the flow of nutrients, it's maintaining body authenticity. It is useful in, dispose of exogenous toxins or beneficial agent, biochemical reaction. As its performances the numerous functions it has more risk for hepatotoxicity. The hepatotoxicity is generally created due to chemicals like artificial chemical includes CCl4, Galactosamine, Lithocholic acid and Anti-TB drugs, apart from artificial some Natural like microcystins and Herbal remedies such as Cascara Sagrada can also induce hepatotoxicity. In this, we provide the information regarding various plants and their extract studies for the protective effect on the liver against hepatotoxicity along with their specified isolated compounds like colchicine, kolaviron,indigtona,rubiadin, baicalin,wogonin, punicalin, for their hepatoprotective activity Keywords: Hepatoprotective, liver disease, Hepatocytes