References of "Kolodkin, Alexey 50002121"
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See detailA kinetic model and design principles study of cellular ROS defence and its failure in Parkinson’s disease
Kolodkin, Alexey UL; Simeonidis, Vangelis UL; Brady, Nathan et al

Poster (2012, August)

Mitochondrial generation of reactive oxygen species (ROS) is an unavoidable side effect of oxidative phosphorylation. To counteract the production of ROS, the cell employs two main strategies. The first ... [more ▼]

Mitochondrial generation of reactive oxygen species (ROS) is an unavoidable side effect of oxidative phosphorylation. To counteract the production of ROS, the cell employs two main strategies. The first one is to increase the consumption of ROS; this mechanism involves the superoxide dismutase enzyme and various antioxidants. The second strategy is to reduce the production of ROS by decreasing mitochondrial membrane potential and by increasing mitophagy. The precise tuning of the latter is crucial for cell survival: if mitophagy is too active, all mitochondria are lost and the cell suffers from reduced ATP capacity; if mitophagy is not active enough, dysfunctional mitochondria accumulate, more ROS is produced, and the cell undergoes unwanted programmed cell death. We hypothesize that a ROS-activated regulatory network is employed to coordinate the regulation of the rate of mitophagy, the expression of uncoupling proteins and the production of antioxidants, including SOD. In Parkinson’s disease (PD), the activities of several components of this regulatory network (e.g. KEAP1, PARK7, VDAC1, SQSTM1) are altered. This makes the cell susceptible to ROS damage. In the case of dopaminergic neurons, this effect can be particularly severe, because an additional pool of non-mitochondrial ROS generated during ROS-induced degradation of dopamine. In order to understand the functioning of the ROS-activated regulatory network in normal function and disease, we have built a kinetic model. Our model includes 39 species and 45 reactions, with 56 kinetic parameters, either fitted or obtained from literature. Our model allows the simulation of PD-related ROS generation and mitochondrial damage and the identification of the design principles underlying the functioning of the network; for example, showing and explaining the synergy between the down-regulation of both VDAC1 and PARK7 occurring during PD. The kinetic model has great potential use for better understanding of the pathophysiology of PD and for the suggestion of novel mitochondria-related PD treatments. [less ▲]

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See detailSulfolobus Systems Biology: Cool hot design for metabolic pathways
Kouril, T.; Kolodkin, Alexey UL; Zaparty, M. et al

in Systems Biology of Microorganisms (2012)

Life at high temperature challenges the stability of macromolecules and cellular components, but also the stability of metabolites, which has received little attention. For the cell, the thermal ... [more ▼]

Life at high temperature challenges the stability of macromolecules and cellular components, but also the stability of metabolites, which has received little attention. For the cell, the thermal instability of metabolites means it has to deal with the loss of free energy and carbon, or in more extremes, it might result in the accumulation of dead-end compounds. In order to elucidate the requirements and principles of metabolism at high temperature, we used a comparative blueprint modelling approach of the lower part of the glycolysis cycle. The conversion of glyceraldehyde 3-phosphate to pyruvate from the thermoacidophilic Crenarchaeon Sulfolobus solfataricus P2 (optimal growth-temperature 80ºC) was modelled based on the available blueprint model of the eukaryotic model organism Saccharomyces cerevisiae (optimal growth-temperature of 30ºC). In S. solfataricus only one reaction is different, namely glyceraldehyde-3-phosphate is directly converted into 3-phosphoglycerate by the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase, omitting the extremely heat-instable 1,3-bisphosphoglycerate. By taking the temperature dependent non-enzymatic (spontaneous) degradation of 1,3-bisphosphoglycerate in account, modelling reveals that a hot lifestyle requires a cool design. [less ▲]

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See detailEmergence of the silicon human and network targeting drugs
Kolodkin, Alexey UL; Boogerda, Fred C.; Plantb, Nick et al

in European Journal of Pharmaceutical Sciences (2012), 46(4), 190-197

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the ... [more ▼]

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the normal physiological range. From the view point of systems biology, homeostasis emerges from the interactions within the network of biomolecules (e.g. DNA, mRNA, proteins), and, hence, understanding how drugs impact upon the entire network should improve their efficacy at returning the network (body) to physiological homeostasis. Large, mechanism-based computer models, such as the anticipated human whole body models (silicon or virtual human), may help in the development of such network-targeting drugs. Using the philosophical concept of weak and strong emergence, we shall here take a more general look at the paradigm of network-targeting drugs, and propose our approaches to scale the strength of strong emergence. We apply these approaches to several biological examples and demonstrate their utility to reveal principles of bio-modeling. We discuss this in the perspective of building the silicon human. [less ▲]

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See detailLow stress weekends promote adaptation to stressful weeks: The design principles of the biological response to stress
Yilmaz, Nilgun; Kolodkin, Alexey UL; Plant, Nick et al

Poster (2012)

Robustness is a fundamental and essential property of evolvable biological systems. It provides system to conserve its functionalities against internal/external perturbations and uncertainties. Product ... [more ▼]

Robustness is a fundamental and essential property of evolvable biological systems. It provides system to conserve its functionalities against internal/external perturbations and uncertainties. Product inhibition, feed-forward and feed-back inhibition and stimulation, and regulatory loops within signal transduction networks are a few of the approaches generated by biological systems to maintain both their robustness and adaptability. In this study, we are able to show the interaction of the stress hormone cortisol with its two nuclear receptors, the high affinity glucocorticoid receptor (GR) and the low affinity pregnane X-receptor (PXR) by using a mathematical model based on realistic kinetic parameters. We checked the importance of regulatory loops, within this network, in terms of pharmacodynamic and pharmacokinetic responses. Then, we demonstrate the alterations in the system response with respect to variable cortisol perturbations, such as initial single peak in cortisol, and repeated stimuli of cortisol with differing frequencies and time frames. As a conclusion, we reveal that the network is robust towards low frequency perturbations, shows adaptation at moderate stress frequencies, but transitions to an altered steady state at high frequency stimulation, which we believe is a predisposing factor towards stress-induced pathologies. [less ▲]

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See detailUnderstanding complexity in neurodegenerative diseases: in silico reconstruction of emergence.
Kolodkin, Alexey UL; Simeonidis, Evangelos UL; Balling, Rudi UL et al

in Frontiers in Physiology (2012), 3

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent ... [more ▼]

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent property, emerging from a perturbation of the network. On the one hand, the biomolecular network of every individual is unique and this is evident when similar disease-producing agents cause different individual pathologies. Consequently, a personalized model and approach for every patient may be required for therapies to become effective across mankind. On the other hand, diverse combinations of internal and external perturbation factors may cause a similar shift in network functioning. We offer this as an explanation for the multi-factorial nature of most diseases: they are "systems biology diseases," or "network diseases." Here we use neurodegenerative diseases, like Parkinson's disease (PD), as an example to show that due to the inherent complexity of these networks, it is difficult to understand multi-factorial diseases with simply our "naked brain." When describing interactions between biomolecules through mathematical equations and integrating those equations into a mathematical model, we try to reconstruct the emergent properties of the system in silico. The reconstruction of emergence from interactions between huge numbers of macromolecules is one of the aims of systems biology. Systems biology approaches enable us to break through the limitation of the human brain to perceive the extraordinarily large number of interactions, but this also means that we delegate the understanding of reality to the computer. We no longer recognize all those essences in the system's design crucial for important physiological behavior (the so-called "design principles" of the system). In this paper we review evidence that by using more abstract approaches and by experimenting in silico, one may still be able to discover and understand the design principles that govern behavioral emergence. [less ▲]

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See detailDesign principles of nuclear receptor signalling: How complex networking improves signal transduction
Kolodkin, Alexey UL; Bruggeman, Frank J.; Plant, Nick et al

in Toxicology (2011), 290(2-3), 131-132

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See detailA systems biology approach towards understanding nuclear receptor interactions: Implications at the endocrine-xenobiotic signalling interface
Kolodkin, Alexey UL; Phillips, Anna; Hood, Steve et al

in Toxicology (2011), 290(2-3), 131-131

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See detailNuclear receptors as controlling factors in chemical metabolism: Determination of regulatory signal network crucial for co-ordinating cellular response to chemicals
Kolodkin, Alexey UL; Phillips, Anna; Hood, Steve R. et al

in Drug Metabolism Reviews (2010), 42(1), 279-280

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See detailDesign principles of nuclear receptor signaling: how complex networking improves signal transduction.
Kolodkin, Alexey UL; Bruggeman, Frank J.; Plant, Nick et al

in Molecular Systems Biology (2010), 6

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of 'design' aspects of the topology of these networks that ... [more ▼]

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of 'design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic 'nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. [less ▲]

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See detailSystems biology towards life in silico: mathematics of the control of living cells.
Westerhoff, Hans V.; Kolodkin, Alexey UL; Conradie, Riaan et al

in Journal of Mathematical Biology (2009), 58(1-2), 7-34

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart ... [more ▼]

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart Heinrich, this paper discusses the origin and evolution of the new part of systems biology that relates to metabolic and signal-transduction pathways and extends mathematical biology so as to address postgenomic experimental reality. Various approaches to modeling the dynamics generated by metabolic and signal-transduction pathways are compared. The silicon cell approach aims to describe the intracellular network of interest precisely, by numerically integrating the precise rate equations that characterize the ways macromolecules' interact with each other. The non-equilibrium thermodynamic or 'lin-log' approach approximates the enzyme rate equations in terms of linear functions of the logarithms of the concentrations. Biochemical Systems Analysis approximates in terms of power laws. Importantly all these approaches link system behavior to molecular interaction properties. The latter two do this less precisely but enable analytical solutions. By limiting the questions asked, to optimal flux patterns, or to control of fluxes and concentrations around the (patho)physiological state, Flux Balance Analysis and Metabolic/Hierarchical Control Analysis again enable analytical solutions. Both the silicon cell approach and Metabolic/Hierarchical Control Analysis are able to highlight where and how system function derives from molecular interactions. The latter approach has also discovered a set of fundamental principles underlying the control of biological systems. The new law that relates concentration control to control by time is illustrated for an important signal transduction pathway, i.e. nuclear hormone receptor signaling such as relevant to bone formation. It is envisaged that there is much more Mathematical Biology to be discovered in the area between molecules and Life. [less ▲]

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