Model Of Transduction Research Articles

Conformational Dynamics in a Nicotinic Receptor Homologue Probed by Simulations

Recently discovered bacterial homologues of eukaryotic pentameric ligand-gated ion channels (LGICs) are increasingly used as structural and functional models of signal transduction in the nervous system. The available structural knowledge of LGICs increased lately with two crystal structures of bacterial homologs in distinct conformations. We crystallized the receptor from the bacteria Gloeobacter violaceus (GLIC), which is gated by protons, at acidic pH [1]. The structure reveals an open pore and molecular dynamics simulations suggest that the protein is stable on a 20 ns timescale when embedded in a lipid bilayer [1]. It can undergo large motion at neutral pH, and we will present a one-microsecond long molecular dynamics simulation of the GLIC channel pH stimulated gating mechanism [2]. The crystal structure of GLIC obtained at acidic pH in an open channel form is equilibrated in a membrane environment and then instantly set to neutral pH. The simulation shows a channel closure that rapidly takes place at the level of the hydrophobic furrow and a progressively increasing quaternary twist. The observed transitions suggest a possible two-step domino-like tertiary mechanism that takes place between adjacent subunits. Further simulations are underway to better understand the influence of sidechain protonation states on the open state of this receptor at acidic pH, as well as its interactions with general anesthetics. [1] N. Bocquet et al., Nature 457, 111-114 (2009) [2] H. Nury et al., PNAS 107, 6275-80 (2010)

Force Distribution Analysis of Allosteric Mechanisms

Revealing the pathways of signal transfer in allosteric proteins has remained a challenge for today's biophysical methods. Previous approaches are primarily based on the comparison of active and inactive structures and thermodynamic concepts. However, stiff regions of the protein might mask signal propagation, even though they are able to carry signals in form of high internal stresses.We here present a new method, force distribution analysis(FDA Stacklies et al,2009a/b), that detects the distribution of stress upon external perturbations in macromolecules like proteins, other (bio-)polymers or even solids with high sensitivity. For tracing signal transfer through a protein structure, FDA calculates the changes, here caused by ligand binding, in the inter-atomic forces of the protein as sampled in Molecular Dynamics simulations.The analyzed proteins are two homologues of the chaperone Hsp90 and the catabolite activator protein CAP.We propose a new model for the signal transduction in the E.Coli(HtpG) and Yeast(Hsp82) homologues of Hsp90. The force differences between the apo, ADP and ATP bound states obtained by FDA based on all-atom trajectories totalling 540 ns revealed a cross-talk between the binding site and the middle domain via distinct paths.The catabolite activator protein(CAP) is a major player in the lac-operon. CAP features a negative cooperativity for the binding of cAMP, which is interestingly based not on a change in structure but in flexibility (Popovych et al.,2006). FDA of the apo, single- and double-bound state revealed a signaling network in CAP, which transfers a signal (first cAMP is bound) to the second binding niche without obvious structural changes, thereby explaining the observed cooperativity.This work describes the effectiveness of FDA for resolving allosteric communication pathways, which are directly testable by experiments. As such, it has broad implications for our view on protein internal strain and function.

Model of cell signal transduction in a three-dimensional domain

Intracellular signalling molecules form pathways inside the cell. These pathways carry a signal to target proteins which results in cellular responses. We consider a spherical cell with two internal compartments containing localized activating enzymes where as deactivating enzymes are spread uniformly through out the cytosol. Two diffusible signalling molecules are activated at the compartments and later deactivated in the cytosol due to deactivating enzymes. The two signalling molecules are a single link in a cascade reaction and form a self regulated dynamical system involving positive and negative feedback. Using matched asymptotic expansions we obtain approximate solutions of the steady state diffusion equation with a linear decay rate. We obtain three-dimensional concentration profiles for the signalling molecules. We also investigate an extension of the above system which has multiple cascade reactions occurring between multiple signalling molecules. Numerically, we show that the speed of the signal is an increasing function of the number of links in the cascade.

Modeling Signal Transduction in Classical Conditioning with Network Motifs

Biological networks are constructed of repeated simplified patterns, or modules, called network motifs. Network motifs can be found in a variety of organisms including bacteria, plants, and animals, as well as intracellular transcription networks for gene expression and signal transduction processes in neuronal circuits. Standard models of signal transduction events for synaptic plasticity and learning often fail to capture the complexity and cooperativity of the molecular interactions underlying these processes. Here, we apply network motifs to a model for signal transduction during an in vitro form of eyeblink classical conditioning that reveals an underlying organization of these molecular pathways. Experimental evidence suggests there are two stages of synaptic AMPA receptor (AMPAR) trafficking during conditioning. Synaptic incorporation of GluR1-containing AMPARs occurs early to activate silent synapses conveying the auditory conditioned stimulus and this initial step is followed by delivery of GluR4 subunits that supports acquisition of learned conditioned responses (CRs). Overall, the network design of the two stages of synaptic AMPAR delivery during conditioning describes a coherent feed-forward loop (C1-FFL) with AND logic. The combined inputs of GluR1 synaptic delivery AND the sustained activation of 3-phosphoinositide-dependent protein-kinase-1 (PDK-1) results in synaptic incorporation of GluR4-containing AMPARs and the gradual acquisition of CRs. The network architecture described here for conditioning is postulated to act generally as a sign-sensitive delay element that is consistent with the non-linearity of the conditioning process. Interestingly, this FFL structure also performs coincidence detection. A motif-based approach to modeling signal transduction can be used as a new tool for understanding molecular mechanisms underlying synaptic plasticity and learning and for comparing findings across forms of learning and model systems.

Investigation of IL-6 and IL-10 signalling via mathematical modelling

Steatosis, i.e., the accumulation of fat in hepatocytes, plays an important role in the progression of non-alcoholic fatty liver disease (NAFLD). It has been shown that STAT3 activation is involved in a decrease of lipid accumulation while C∕EBP is correlated with an increase of fat content and steatosis. It is known that STAT3 and C∕EBP are activated by IL-6 and that IL-6 signalling is also affected by IL-10, even though the exact mechanism is unclear. This paper develops a model for IL-6 and IL-10 signal transduction and then investigates the effect that stimulation with these cytokines has on the transcription factor dynamics. In an initial step, some parameters of a previously developed IL-6 signalling model are re-estimated based upon newly developed experimental data for the Jak-STAT pathway. Furthermore, the Erk-C∕EBP pathway model is extended to also include the activated transcription factor C∕EBP in the nucleus. Since IL-10 signals through the Jak-STAT but not the Erk-C∕EBP pathway, a model was developed which includes interaction between IL-6 and IL-10 signalling as both mechanisms share signal transduction through the Jak-STAT pathway. Based upon the model, the activity ratio of Jak-STAT and Erk-C∕EBP was investigated for different stimulation levels of IL-6 and IL-10.

Prebiotically relevant mixed fatty acid vesicles support anionic solute encapsulation and photochemically catalyzed trans-membrane charge transport

The spontaneous assembly of amphiphile-based compartments in aqueous solution is widely viewed as a key step in models for the abiotic formation of primitive cell-like structures. Proposed organic components for such systems consist of mixed short chain fatty acids (FA) and polycyclic aromatic hydrocarbon (PAH) species, the composition of which have been modeled after organic extracts of carbonaceous meteorites. Self-assembly of amphiphiles from these extracts into aqueous suspensions of bilayer structures was long ago demonstrated, although little has since been reported concerning the stability and potential functionality of these complex mixtures. This work explores the thermodynamic and kinetic stability of vesicles prepared from complex mixtures of short chain FA species (CH3COOH–C9H19COOH) with membrane solubilized PAH species. Critical vesicle concentration measurements and ultrafiltration analyses of decanoic acid in the presence of other shorter chain FA species indicate the formation of mixed component vesicle phases composed mainly of C10–C8 FA components. An electrostatic barrier to trans-membrane diffusion of negative charges allows observation of stably encapsulated poly-anionic solutes inside these vesicles. As a model for primitive energy transduction, trans-membrane electron transfer between EDTA and encapsulated ferricyanide was demonstrated, driven catalytically via PAH photochemistry without substantial decomposition of the chromophores or vesicles. These results indicate a plausible role for compartmentalization and catalysis by short chain fatty acids and PAH species in prebiotic vesicle-encapsulated systems.

Deducing corticotropin-releasing hormone receptor type 1 signaling networks from gene expression data by usage of genetic algorithms and graphical Gaussian models.

BackgroundDysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a hallmark of complex and multifactorial psychiatric diseases such as anxiety and mood disorders. About 50-60% of patients with major depression show HPA axis dysfunction, i.e. hyperactivity and impaired negative feedback regulation. The neuropeptide corticotropin-releasing hormone (CRH) and its receptor type 1 (CRHR1) are key regulators of this neuroendocrine stress axis. Therefore, we analyzed CRH/CRHR1-dependent gene expression data obtained from the pituitary corticotrope cell line AtT-20, a well-established in vitro model for CRHR1-mediated signal transduction. To extract significantly regulated genes from a genome-wide microarray data set and to deduce underlying CRHR1-dependent signaling networks, we combined supervised and unsupervised algorithms.ResultsWe present an efficient variable selection strategy by consecutively applying univariate as well as multivariate methods followed by graphical models. First, feature preselection was used to exclude genes not differentially regulated over time from the dataset. For multivariate variable selection a maximum likelihood (MLHD) discriminant function within GALGO, an R package based on a genetic algorithm (GA), was chosen. The topmost genes representing major nodes in the expression network were ranked to find highly separating candidate genes. By using groups of five genes (chromosome size) in the discriminant function and repeating the genetic algorithm separately four times we found eleven genes occurring at least in three of the top ranked result lists of the four repetitions. In addition, we compared the results of GA/MLHD with the alternative optimization algorithms greedy selection and simulated annealing as well as with the state-of-the-art method random forest. In every case we obtained a clear overlap of the selected genes independently confirming the results of MLHD in combination with a genetic algorithm.With two unsupervised algorithms, principal component analysis and graphical Gaussian models, putative interactions of the candidate genes were determined and reconstructed by literature mining. Differential regulation of six candidate genes was validated by qRT-PCR.ConclusionsThe combination of supervised and unsupervised algorithms in this study allowed extracting a small subset of meaningful candidate genes from the genome-wide expression data set. Thereby, variable selection using different optimization algorithms based on linear classifiers as well as the nonlinear random forest method resulted in congruent candidate genes. The calculated interacting network connecting these new target genes was bioinformatically mapped to known CRHR1-dependent signaling pathways. Additionally, the differential expression of the identified target genes was confirmed experimentally.

Dominant inhibition of Akt/protein kinase B signaling by the matrix protein of a negative-strand RNA virus.

Vesicular stomatitis virus (VSV) is a rhabdovirus that alters host nuclear and cytoplasmic function upon infection. We have investigated the effect of VSV infection on cellular signaling through the phosphatidylinositol-3 kinase (PI3k)/Akt signaling pathway. Akt phosphorylation at both threonine 308 (Thr308) and serine 473 (Ser473) was inhibited in cells infected with VSV. This inhibition was rapid (beginning within the first 2 to 3 h postinfection) and correlated with the dephosphorylation of downstream effectors of Akt, such as glycogen synthase kinase 3β (GSK3β) and mammalian target of rapamycin (mTOR). The dephosphorylation of Akt occurred in the presence of growth factor stimulation and was not overcome through constitutive membrane targeting of Akt or high levels of phosphatidylinositol-3,4,5-triphosphate (PIP3) accumulation in the membrane. Akt dephosphorylation was not a result of alterations in PDK1 phosphorylation or activity, changes in phosphatase and tensin homologue deleted on chromosome 10 (PTEN) levels, or the downregulation of PI3k signaling. Inactivation of Akt was caused by the expression of the viral M protein in the absence of other viral components, and an M protein mutant that does not inhibit RNA polymerase II (Pol II) transcription and nuclear/cytoplasmic transport was also defective in inhibiting Akt phosphorylation. These data illustrate that VSV utilizes a novel mechanism to alter this central player in cell signaling and oncogenesis. It also suggests an inside-out model of signal transduction where VSV interruption of nuclear events has a rapid and significant effect on membrane signaling events.

Crystal and solution structures of an odorant-binding protein from the southern house mosquito complexed with an oviposition pheromone.

Culex mosquitoes introduce the pathogens responsible for filariasis, West Nile virus, St. Louis encephalitis, and other diseases into humans. Currently, traps baited with oviposition semiochemicals play an important role in detection efforts and could provide an environmentally friendly approach to controlling their populations. The odorant binding proteins (OBPs) in the female's antenna play a crucial, if yet imperfectly understood, role in sensing oviposition cues. Here, we report the X-ray crystallography and NMR 3D structures of OBP1 for Culex quinquefasciatus (CquiOBP1) bound to an oviposition pheromone (5R,6S)-6-acetoxy-5-hexadecanolide (MOP). In both studies, CquiOBP1 had the same overall six-helix structure seen in other insect OBPs, but a detailed analysis revealed an important previously undescribed feature. There are two models for OBP-mediated signal transduction: (i) direct release of the pheromone from an internal binding pocket in a pH-dependent fashion and (ii) detection of a pheromone-induced conformational change in the OBP·pheromone complex. Although CquiOBP1 binds MOP in a pH-dependent fashion, it lacks the C terminus required for the pH-dependent release model. This study shows that CquiOBP binds MOP in an unprecedented fashion using both a small central cavity for the lactone head group and a long hydrophobic channel for its tail.

RhoH modulates pre-TCR and TCR signalling by regulating LCK

Pre-T-cell receptor (pre-TCR) and TCR signals govern the development of T-lymphocytes. RhoH, a hematopoietic-specific and GTPase-deficient member of the RhoGTPase family, is required in the development of T-lymphocytes. Here we found that RhoH binds and modulates LCK, the non-receptor tyrosine kinase crucial in initiating pre-TCR and TCR signallings. In both pre-TCR and TCR signalling transduction, LCK is phosphorylated by CSK to maintain the inactive state of LCK at rest. Upon being activated, CSK phosphorylation is removed and LCK autophosphorylation leads to LCK activation and further phosphorylates ZAP70 to initiate further downstream signalling. At rest, LCK may be recruited to the plasma membrane by RhoH, which also binds CSK, resulting in LCK inactivation. Additionally, the presence of RhoH enhances the inactivation phosphorylation of LCK by CSK. RhoH was found to bind preferentially inactive LCK, indicating that, upon ligand-mediated TCR activation, LCK is dephosphorylated resulting in LCK autoactivation and its release from RhoH. Thus RhoH is a critical part of the microenvironment for maintaining the inactive state of LCK. Furthermore, we found that the reduction of RhoH levels results in LCK autoactivation and constitutive activation of the TCR pathway. Our findings indicate that RhoH is a key adapter protein that maintains LCK in the inactive state, contributing to the regulation of both pre-TCR and TCR signalling during T-cell development. The data also supports a model for ligand-independent signal transduction by pre-TCR.

Early abscisic acid signal transduction mechanisms: newly discovered components and newly emerging questions

The plant hormone abscisic acid (ABA) regulates many key processes in plants, including seed germination and development and abiotic stress tolerance, particularly drought resistance. Understanding early events in ABA signal transduction has been a major goal of plant research. The recent identification of the PYRABACTIN (4-bromo-N-[pyridin-2-yl methyl]naphthalene-1-sulfonamide) RESISTANCE (PYR)/REGULATORY COMPONENT OF ABA RECEPTOR (RCAR) family of ABA receptors and their biochemical mode of action represents a major breakthrough in the field. The solving of PYR/RCAR structures provides a context for resolving mechanisms mediating ABA control of protein-protein interactions for downstream signaling. Recent studies show that a pathway based on PYR/RCAR ABA receptors, PROTEIN PHOSPHATASE 2Cs (PP2Cs), and SNF1-RELATED PROTEIN KINASE 2s (SnRK2s) forms the primary basis of an early ABA signaling module. This pathway interfaces with ion channels, transcription factors, and other targets, thus providing a mechanistic connection between the phytohormone and ABA-induced responses. This emerging PYR/RCAR-PP2C-SnRK2 model of ABA signal transduction is reviewed here, and provides an opportunity for testing novel hypotheses concerning ABA signaling. We address newly emerging questions, including the potential roles of different PYR/RCAR isoforms, and the significance of ABA-induced versus constitutive PYR/RCAR-PP2C interactions. We also consider how the PYR/RCAR-PP2C-SnRK2 pathway interfaces with ABA-dependent gene expression, ion channel regulation, and control of small molecule signaling. These exciting developments provide researchers with a framework through which early ABA signaling can be understood, and allow novel questions about the hormone response pathway and possible applications in stress resistance engineering of plants to be addressed.

Drosophila TRPN( = NOMPC) Channel Localizes to the Distal End of Mechanosensory Cilia

BackgroundA TRPN channel protein is essential for sensory transduction in insect mechanosensory neurons and in vertebrate hair cells. The Drosophila TRPN homolog, NOMPC, is required to generate mechanoreceptor potentials and currents in tactile bristles. NOMPC is also required, together with a TRPV channel, for transduction by chordotonal neurons of the fly's antennal ear, but the TRPN or TRPV channels have distinct roles in transduction and in regulating active antennal mechanics. The evidence suggests that NOMPC is a primary mechanotransducer channel, but its subcellular location—key for understanding its exact role in transduction—has not yet been established.Methodology/Principal FindingsHere, by immunostaining, we locate NOMPC at the tips of mechanosensory cilia in both external and chordotonal sensory neurons, as predicted for a mechanotransducer channel. In chordotonal neurons, the TRPN and TRPV channels are respectively segregated into distal and proximal ciliary zones. This zonal separation is demarcated by and requires the ciliary dilation, an intraciliary assembly of intraflagellar transport (IFT) proteins.ConclusionsOur results provide a strong evidence for NOMPC as a primary transduction channel in Drosophila mechansensory organs. The data also reveals a structural basis for the model of auditory chordotonal transduction in which the TRPN and TRPV channels play sequential roles in generating and amplifying the receptor potential, but have opposing roles in regulating active ciliary motility.

An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

A maximum likelihood estimator for parameter distributions in heterogeneous cell populations

Abstract In many biologically relevant situations, cells of a clonal population show a heterogeneous response upon a common stimulus. The computational analysis of such situations requires the study of cell-cell variability and modeling of heterogeneous cell populations. In this work, we consider populations where the behavior of every single cell can be described by a system of ordinary differential equations. Heterogeneity among individual cells is modeled via differences in parameter values and initial conditions. Both are subject to a distribution function which is part of the cell population model. We present a novel approach to estimate the distribution of parameters and initial conditions from single cell measurements, e.g. flow cytometry and cytometric fluorescence microscopy. Therefore, a maximum likelihood estimator for the distribution is derived. The resulting optimization problem is reformulated via a parameterization of the distribution of parameters and initial conditions to allow the use of convex optimization techniques. To evaluate the proposed method, artificial data from a model of TNF signal transduction are considered. It is shown that the proposed method yields a good estimate of the parameter distributions in case of a limited amount of noise corrupted data.

Complexity in signal transduction

This review is focused on complexity in cell signaling. Signaling experiments have demonstrated that many different stimuli activate the same signaling pathways yet result in different outcomes. Differences in the cellular machinery between cells explain response variation between cell types, but for a single cell type an appealing explanation is still lacking. The kinetic disconnect between cell signal transduction and a cellular action is highlighted; possible explanations for this disconnect, such as a series of cascading autocrine signaling molecules and new research suggesting that cells experience multiple rounds of reactivation in numerous cell signaling pathways, are reviewed. Additionally, evidence that kinase pathways exhibit frequency and amplitude modulation is examined. From this review, a new model of signal transduction is proposed whereby multiple signal transduction pathways are reactivated over time to orchestrate unique outcomes in physiological processes.

One-microsecond molecular dynamics simulation of channel gating in a nicotinic receptor homologue

Recently discovered bacterial homologues of eukaryotic pentameric ligand-gated ion channels, such as the Gloeobacter violaceus receptor (GLIC), are increasingly used as structural and functional models of signal transduction in the nervous system. Here we present a one-microsecond-long molecular dynamics simulation of the GLIC channel pH stimulated gating mechanism. The crystal structure of GLIC obtained at acidic pH in an open-channel form is equilibrated in a membrane environment and then instantly set to neutral pH. The simulation shows a channel closure that rapidly takes place at the level of the hydrophobic furrow and a progressively increasing quaternary twist. Two major events are captured during the simulation. They are initiated by local but large fluctuations in the pore, taking place at the top of the M2 helix, followed by a global tertiary relaxation. The two-step transition of the first subunit starts within the first 50 ns of the simulation and is followed at 450 ns by its immediate neighbor in the pentamer, which proceeds with a similar scenario. This observation suggests a possible two-step domino-like tertiary mechanism that takes place between adjacent subunits. In addition, the dynamical properties of GLIC described here offer an interpretation of the paradoxical properties of a permeable A13'F mutant whose crystal structure determined at 3.15 A shows a pore too narrow to conduct ions.

A Dynamic Model of Interactions of Ca2+, Calmodulin, and Catalytic Subunits of Ca2+/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca2+ into the postsynaptic spine through the pores of activated N-methyl-d-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca2+ influx during the first few seconds of activity is interpreted within the Ca2+-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca2+/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca2+ ions. As a first step toward clarifying how the Ca2+-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca2+, calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca2+ play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing of Ca2+ signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca2+ is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca2+ transients arises from the kinetics of interaction of fluctuating Ca2+ with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning.

Maf1 regulation: A model of signal transduction inside the nucleus

RNA polymerase III (Pol III) is responsible for the synthesis of 5S ribosomal RNA (rRNA) and transfer RNAs (tRNAs) essential for protein synthesis and cell growth. Pol III is tightly controlled by growth signals such as nutrients and deregulation of Pol III-dependent transcription can lead to oncogenic transformation. In response to extracellular stimuli, the target of rapamycin complex 1 (TORC1) regulates Pol III activity through Maf1, a key conserved Pol III repressor. Recent studies have unraveled intricate mechanisms by which Maf1 activity is controlled at multiple levels, including nuclear transport and phoshorylation at specific chromatin loci. These studies suggest an emerging mode of gene regulation by extracellular signals inside the nucleus.

An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis

An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis

A micro-sequenced CMOS model for cell signalling pathway using G-protein and phosphorylation cascade

Communication between cells in multi-cellular organisms such as animals, humans and plants is essential for co-ordinating the organismic activities of fertilization, growth, survival and reproduction. This bio-chemical communication between trillions of cells in organisms can be more complex than the Internet. This paper develops a CMOS circuit model of signal reception and signal transduction within a cell in response to extra-cellular molecular signals. A micro-sequenced model has been developed where the signal transduction steps are clocked by circadian time intervals. The model converts the chemical signaling pathway into a CMOS multi-step logical transformation cascade transducing a received signal molecule into an activated cellular protein response. This modeling technique leads to understanding cellular malfunctions (diseases) in the form of logical (electrical) faults in a circuit.