Stochastic Modelling of Subcellular Biochemical Systems

Stochastic approaches are needed for modelling many cellular processes to capture noise effects. The difficulty of solving the chemical master equation, the most common formulation of stochastic models, is circumvented by stochastic simulations and analytical approximations. The central theme here is one such approximation, the two-moment approximation (2MA) which represents the mean-covariance coupling. Our 2MA formulation allows non-elementary reactions and relative concentrations. The approach is applied to the fission yeast cell cycle model. The analytical model reproduces the relevant experimental data.Die Modellierung zellulärer Prozesse erfordert oft die Anwendung von stochastischen Methoden. Das Problem, die master equation für biochemische Systeme zu lösen kann auf zweierlei Weise umgangen werden. Entweder durch stochastische Simulationen oder durch analytische Approximation. Das Herzstück hier ist die Entwicklung einer solchen Approximation, der zwei-Momenten Approximation, welcher die Verknüpfung von Mittelwert und Kovarianz repräsentiert und es erlaubt Modelle mit nicht elementaren Reaktionen sowie relativen Konzentrationen zu analysieren. Dieser neue Ansatz , angewandt auf ein anerkanntes Modell des Zellzyklus in der Bäckerhefe, reproduziert vorhandene experimentell Daten

Computational Modeling of IP3 Receptor Function and Intracellular Mechanisms in Synaptic Plasticity

Learning and memory in the brain have been shown to involve complex molecular interactions. In the field of computational neuroscience, mathematical modeling and computer simulations are combined with laboratory experiments to better understand the dynamics of these interactions. A vast number of computational models related to intracellular molecular mechanisms calls for means to compare them to each other. In this thesis, computational models and methods for understanding specific molecular mechanisms in synaptic plasticity, a phenomenon involved in learning, are studied and compared both quantitatively and qualitatively. The focus is set on the IP3 receptor kinetics and the intracellular molecular mechanisms including processing of calcium ions in the postsynaptic neuron. Calcium has been shown to play an important role in different types of synaptic plasticity, only the mechanisms and dynamics for elevation of cytosolic calcium concentration vary. The IP3 receptor, an intracellular calcium releasing channel, is one of the major factors responsible for the calcium elevation in neurons. Firstly, the applicability of deterministic and stochastic approaches in modeling the IP3 receptor kinetics, involving small number of molecules, is studied. In this case, the study shows that stochastic approach, especially Gillespie stochastic simulation algorithm, should be favored. Secondly, since a well-established model for IP3 receptor function in neurons is lacking, this thesis provides not only tools for model comparison but also an insight to which model of the tens of models to choose. Using stochastic simulations, four IP3 models are compared to experimental data to clarify how well they model the measured features in neurons. The results show that there are major differences in the statistical properties of the IP3 receptor models although the models have originally been developed to describe the same phenomenon. Thirdly, this study shows that the models for postsynaptic signaling in synaptic plasticity are becoming more sophisticated by involving stochastic properties, incorporating electrophysiolocial properties of the entire neuron, or having diffusion of signaling molecules. Computational comparison of these models reveals that when using the same input, models describing the phenomenon in the same neuron type produce different results. One of the future goals of computational neuroscience is to find predictive computational models for biochemical and biophysical mechanisms of synaptic plasticity in different brain areas and cells of mammals. When describing a system of molecular events, the selection of modeling and simulation approach should be done carefully by keeping the properties of the modeled biological system in mind. Not only do theoreticians and modelers need to consider experimental findings, but the experimental progress could also be enhanced by using simulations to select the most promising experiments. As discussed in this thesis, attention paid to these issues should improve the utility of modeling approaches for investigating molecular mechanisms of synaptic plasticity. Only then is it possible to use the models to learn something new about the mammalian brain function

Structure and mechanism to function: allosteric activation of phosphomannomutase 1 and substrate selectivity in Hotdog Fold thioesterases

Two superfamilies were used to explore the structure/function relationship as it pertains to enzyme specificity. The structures and mechanisms of phosphatases belonging to the Haloalkanoate Dehalogenase Superfamily (HADSF) and thioesterases of the Hotdog Fold Superfamily (HDFSF) were determined using X-ray crystallography and other biophysical tools in combination with steady-state kinetics and site-directed mutagenesis. Together, the specific structural components of enzymes crucial for substrate recognition, substrate promiscuity, and catalysis were uncovered. In the HADSF, the phosphomannomutases (PMMs) catalyze the interconversion of mannose 6-phosphate and mannose 1-phosphate, an essential step in the protein glycosylation pathway. In humans, two isoforms PMM1 and PMM2 catalyze this reaction. Deficiency in PMM2 activity is the major cause of congenital disorders of glycosylation (CDG-1a). However, PMM1 activity is not sufficient to replace PMM2 in protein glycosylation. Instead, PMM1 functions as a glucose-1,6-bisphosphate phosphatase in the presence of IMP and enables the temporary rescue of glycolysis during brain ischemia. Herein, the structure of IMP bound to PMM1 in combination with kinetics revealed a mechanism for the differential substrate preference and the mechanistic switch from a mutase to phosphatase activity. In the HDFSF, the majority of which function as thioesterases of aliphatic or aromatic compounds bound to coenzyme A or acyl carrier protein (ACP), the structural determinants for substrate preference were identified in PA1618, an enzyme with high substrate promiscuity. The structural determinants of the specific thiosterases MA0038 and BVU1957 were also identified. The variation in substrate range observed among these enzymes, from specific to promiscuous, led to the design of a comprehensive thioester screen to identify HDFSF thioesterase substrates. The profiles of substrate specificities from 42 previously uncharacterized thioesterases were determined allowing comparison of the sequence/substrate relationships across a representative selection of thioesterases. Examples drawn from both HADSF and HDFSF enzymes suggested a model relating substrate promiscuity and specificity to regions of protein flexibility. The motion of a domain within a multidomain protein or a flexible loop near the active site was correlated with the occurrence of substrate promiscuity/specificity

A mathematical model of glucose metabolism in hospitalized patients with diabetes and stress hyperglycemia

The human body employs several mechanisms to regulate the concentration of glucose in the bloodstream. The rates of glucose uptake and release from specific organs within the body are modulated directly by the concentrations of metabolites and hormones, and indirectly by the autonomic nervous system. The negative feedback relationship between glucose and the anabolic hormone, insulin, dominates the process of glycemic regulation. The binding of insulin to its receptor begins a cascade of intracellular events that increases glucose uptake into the liver and peripheral tissue and reduces glucose release from the liver. However, this mechanism can be overwhelmed during the acute stress typified by a moderate surgical procedure. Cellular damage and tissue trauma cause a surge in catabolic hormones and cytokines, leading to insulin resistance and marked hyperglycemia. The focus of this study is the mathematical descriptions of the processes that regulate glucose production and uptake. Such descriptions model the complex relationships between metabolites and hormones and their effects on glycemia. Descriptive models that are accurate and robust have the potential to guide the development of tools designed to manage glycemia in hospitalized patients with diabetes and stress-induced hyperglycemia. Specifically, we investigate the validity of a glucose metabolism model published by John Sorensen in a 1985 doctoral thesis. The model is a set of 22 first-order time-invariant nonlinear differential equations describing the interaction of glucose, insulin and glucagon and their effect on organ-level glucose uptake and release. We modified the model to incorporate recent experimental data, including data we have collected in clinical trials. The model was expanded to include a description of epinephrine and its effects on glycemia.Ph.D., Biomedical Engineering -- Drexel University, 200

Structure And Function Of The FMO Protein From The Photosynthetic Green Sulfur Bacteria

The Fenna-Matthews-Olson: FMO) bacteriochlorophyll a protein has served as a model antenna system for understanding pigment-protein interaction and the energy transfer mechanism. The FMO protein has been extensively studied by a wide range of spectroscopic and theoretical techniques due to its stability, spectral resolution of pigments, water-soluble nature and availability of high-resolution structural information. A new 1.3 Å FMO structure: PDB: 3EOJ) revealed an 8th pigment at the monomer connection region with partial occupancy. To understand the nature and stoichiometry of this new pigment, the molecular weight of the whole FMO complex was measured by the recently developed mass spectrometry: MS) technique called native spray MS. The first non-natural FMO complex was generated by replacing the phytol tail of BChl a with geranylgeraniol. The recently discovered sixth phylum of photosynthetic species - the Candidatus Chloracidobacterium thermophilum: Cab), also contains the FMO protein, which is significantly divergent from the FMO found in green sulfur bacteria: GSB). This FMO has two distinct structural regions different from the FMOs from GSB and also shows distinct spectral properties. The collection of these different FMO complexes has greatly facilitated our understanding of this protein. The FMO connects the chlorosome to the reaction center in the cytoplasmic membrane and functionally forms a bridge to transfer the excitation energy. The orientation of the FMO protein on the membrane in vivo was revealed by chemical labeling and MS5. The orientational information places the newly discovered 8th pigment near the chlorosome, and it is proposed to serve as an energy transfer intermediate between the chlorosome and the rest of the FMO protein. The detailed interaction between the FMO protein and the baseplate: CsmA) protein was studied by hydrogen/deuterium exchange coupled with MS. The identified binding region first confirms the FMO orientation on the membrane; secondly this region is located at one of the two structurally different regions on the Cab-FMO protein, and the highly conserved region in the baseplate of GSB is not conserved in that of Cab

Annotation-based storage and retrieval of models and simulation descriptions in computational biology

This work aimed at enhancing reuse of computational biology models by identifying and formalizing relevant meta-information. One type of meta-information investigated in this thesis is experiment-related meta-information attached to a model, which is necessary to accurately recreate simulations. The main results are: a detailed concept for model annotation, a proposed format for the encoding of simulation experiment setups, a storage solution for standardized model representations and the development of a retrieval concept.Die vorliegende Arbeit widmete sich der besseren Wiederverwendung biologischer Simulationsmodelle. Ziele waren die Identifikation und Formalisierung relevanter Modell-Meta-Informationen, sowie die Entwicklung geeigneter Modellspeicherungs- und Modellretrieval-Konzepte. Wichtigste Ergebnisse der Arbeit sind ein detailliertes Modellannotationskonzept, ein Formatvorschlag für standardisierte Kodierung von Simulationsexperimenten in XML, eine Speicherlösung für Modellrepräsentationen sowie ein Retrieval-Konzept