Levels of pro-apoptotic regulator Bad and anti-apoptotic regulator Bcl-xL determine the type of the apoptotic logic gate

Identifying Bayesian optimal experiments for uncertain biochemical pathway models

Pharmacodynamic (PD) models are mathematical models of cellular reaction networks that include drug mechanisms of action. These models are useful for studying predictive therapeutic outcomes of novel drug therapies in silico. However, PD models are known to possess significant uncertainty with respect to constituent parameter data, leading to uncertainty in the model predictions. Furthermore, experimental data to calibrate these models is often limited or unavailable for novel pathways. In this study, we present a Bayesian optimal experimental design approach for improving PD model prediction accuracy. We then apply our method using simulated experimental data to account for uncertainty in hypothetical laboratory measurements. This leads to a probabilistic prediction of drug performance and a quantitative measure of which prospective laboratory experiment will optimally reduce prediction uncertainty in the PD model. The methods proposed here provide a way forward for uncertainty quantification and guided experimental design for models of novel biological pathways.

A comparative analysis of daunorubicin and its metabolite daunorubicinol interaction with apoptotic and drug resistance proteins using in silico approach

Daunorubicin (DNR) is a chemotherapeutic drug associated with multiple side effects, including drug resistance. As the molecular mechanism related to these side effects remain unclear and mostly hypothesized, this study addresses and compares the role of DNR and its metabolite Daunorubicinol (DAUNol) to induce apoptosis and drug resistance using molecular docking, Molecular Dynamics (MD) simulation, MM-PBSA and chemical pathway analysis. The results showed that DNR's interaction was stronger with Bax protein, Mcl-1:mNoxaB and Mcl-1:Bim protein complexes than DAUNol. On the other hand, contrasting results were obtained for drug resistance proteins where stronger interaction was obtained with DAUNol compared to DNR. Further, MD simulation performed for 100 ns provided the details of protein-ligand interaction. Most notable was the interaction of Bax protein with DNR, resulting in conformational changes at α-helices 5, 6 and 9, leading to Bax activation. Finally, the chemical signalling pathway analysis also revealed the regulation of different signalling pathways by DNR and DAUNol. It was observed that DNR majorly impacted the signalling associated with apoptosis while DAUNol mainly targeted pathways related to multidrug resistance and cardiotoxicity. Overall, the results highlight that DNR biotransformation reduces its capability to induce apoptosis while enhancing its ability to induce drug resistance and off-target toxicity.Communicated by Ramaswamy H. Sarma.

Novel fluorinated pyrazole-based heterocycles scaffold: cytotoxicity, in silico studies and molecular modelling targeting double mutant EGFR L858R/T790M as antiproliferative and apoptotic agents

Hepatocellular carcinoma (HCC), also known as hepatoma, is the most prevalent type of primary liver cancer. It begins in the hepatocytes, the liver’s major cell type. Cancer that began in another region of the body but has spread to the liver is known as secondary cancer of life; several still unmet demands for better, less toxic therapy to treat this malignant tumor. Several novel pyrazolo[1,5-a]pyrimidine derivatives were synthesized as part of our goal to develop promising anticancer drugs. All the synthesized hybrids have been screened for their cytotoxicity effect against three cancer cell lines which are; HepG-2, HCT-116, and MCF-7. The liver cancer cells were found to be the most sensitive to the effect of the new molecules. A subsequent set of in vitro biological evaluation studies has been conducted on the most promising derivatives to identify their effect on such a cancer type. In HepG-2 cells, four derivatives (8a, 8b, 10c, and 11b) demonstrated good anticancer activity. The most efficacious compounds were 8b and 10c, which had IC50 values of 2.36 ± 0.14 and 1.14 ± 0.063 μM, respectively, higher than the reference medication Imatinib. The latter’s putative molecular effect has been investigated further by looking at its influence on the cell cycle, EGFR, and specific apoptotic and anti-apoptotic markers in HepG-2 cells. These findings indicated that 8b and 10c could trigger apoptosis by upregulating BAX and caspase-3 and cell cycle at the Pre-G1 and G2-M stages. The compounds 8b and 10c showed high potency for EGFR with IC50 equal to 0.098 and 0.079 μM, respectively. Compound 10c had the most effective inhibitory activity for EGFR L858R-TK with IC50 (36.79 nM). Additionally, in silico ADMET and docking studies were done for the most active hits, representing good results.

Graphical Abstract

Modeling of DNA Damage Repair and Cell Response in Relation to p53 System Exposed to Ionizing Radiation

Repair of DNA damage induced by ionizing radiation plays an important role in the cell response to ionizing radiation. Radiation-induced DNA damage also activates the p53 system, which determines the fate of cells. The kinetics of repair, which is affected by the cell itself and the complexity of DNA damage, influences the cell response and fate via affecting the p53 system. To mechanistically study the influences of the cell response to different LET radiations, we introduce a new repair module and a p53 system model with NASIC, a Monte Carlo track structure code. The factors determining the kinetics of the double-strand break (DSB) repair are modeled, including the chromosome environment and complexity of DSB. The kinetics of DSB repair is modeled considering the resection-dependent and resection-independent compartments. The p53 system is modeled by simulating the interactions among genes and proteins. With this model, the cell responses to low- and high-LET irradiation are simulated, respectively. It is found that the kinetics of DSB repair greatly affects the cell fate and later biological effects. A large number of DSBs and a slow repair process lead to severe biological consequences. High-LET radiation induces more complex DSBs, which can be repaired by slow processes, subsequently resulting in a longer cycle arrest and, furthermore, apoptosis and more secreting of TGFβ. The Monte Carlo track structure simulation with a more realistic repair module and the p53 system model developed in this study can expand the functions of the NASIC code in simulating mechanical radiobiological effects.

Capturing Biomarkers and Molecular Targets in Cellular Landscapes From Dynamic Reaction Network Models and Machine Learning

Computational dynamic ODE models of cell function describing biochemical reactions have been created for decades, but on a small scale. Still, they have been highly effective in describing and predicting behaviors. For example, oscillatory phospho-ERK levels were predicted and confirmed in MAPK signaling encompassing both positive and negative feedback loops. These models typically were limited and not adapted to large datasets so commonly found today. But importantly, ODE models describe reaction networks in well-mixed systems representing the cell and can be simulated with ordinary differential equations that are solved deterministically. Stochastic solutions, which can account for noisy reaction networks, in some cases, also improve predictions. Today, dynamic ODE models rarely encompass an entire cell even though it might be expected that an upload of the large genomic, transcriptomic, and proteomic datasets may allow whole cell models. It is proposed here to combine output from simulated dynamic ODE models, completed with omics data, to discover both biomarkers in cancer a priori and molecular targets in the Machine Learning setting.

Interactions of multidomain pro-apoptotic and anti-apoptotic proteins in cancer cell death

Cancer is a global public health concern that is characterized by the uncontrolled growth of tumor cells. It is regarded as the subsequent cause of death after cardiovascular disease. The most common types of cancer include breast, colorectal, lung, and prostate. The risk factors attributed to the development of common types of cancer are tobacco smoking, excessive alcohol consumption, dietary factors, ultraviolet radiation (UV), and lack of physical activities. Two major cellular apoptotic pathways targeted in cancer therapies are intrinsic and extrinsic. These two pathways are regulated by different types of proteins, the multidomain pro-apoptotic proteins (Bak, Bax, and Bok), BH3-only pro-apoptotic proteins (Bid, Bim, Bad, Noxa, and Puma), and the anti-apoptotic proteins (Mcl-1, Bfl-1, Bcl-XL, Bcl-2, Bcl-w, and Bcl-B). Other significant molecules/factors that are known to execute cellular apoptotic pathways include bioactive compounds, and reactive oxygen species (ROS). Proteolytic caspases are known to play a vital role in the initiation of apoptotic activities in cancerous cells. Based on their functions, they are categorized into initiators and executioners. Nanotechnology has produced novel outcomes in modern medicine. The green synthesis of nanoparticles has demonstrated prospective improvements in cancer therapies in combination with the existing therapies including photodynamic therapy. This review aims at highlighting the association between pro-apoptotic and anti-apoptotic proteins, and their significance in cancer therapy.

Piece-wise linear models of biological systems-Application, analysis, and comparison with nonlinear models using the example of the p53 regulatory module

In this paper, we propose to use a linear system with switching methodology for description and analysis of complex biological systems. We show advantages of the proposed approach over the one usually used, which is based on ODE. We propose the detailed methodology of a full analysis of developed models, including analytical determination of the location and type of equilibrium points, finding an analytical solution, stability and bifurcation analysis. We illustrate the above with the example of the well-known p53 signalling pathway comparing the results with the results of a nonlinear, ODE-based version of the proposed model. The complex methodology proposed by us, especially due to the definition of model structure, which is easy to understand for biologists and medics, may be a bridge for closer cooperation between them and engineers in the future.

Renoprotective Effects of Alpha-1 Antitrypsin against Tacrolimus-Induced Renal Injury

The protective effects of alpha-1 antitrypsin (AAT) in tacrolimus (TAC)-induced renal injury was evaluated in a rat model. The TAC group rats were subcutaneously injected with 2 mg/kg TAC every day for four weeks. The TAC with AAT group was cotreated with daily subcutaneous injections of TAC and intraperitoneal injections of AAT (80 mg/kg) for four weeks. The effects of AAT on TAC-induced renal injury were evaluated using serum biochemistry, histopathology, and Western blotting. The TAC injection significantly increased renal interstitial fibrosis, inflammation, and apoptosis as compared to the control treatment. The histopathological examination showed that cotreatment of TAC and AAT attenuated interstitial fibrosis (collagen, fibronectin, and α-SMA staining), and α-SMA expression in Western blotting was also decreased. Immunohistochemical staining for inflammation (osteopontin and ED-1 staining) revealed improved interstitial inflammation in the TAC with AAT group compared to that in the TAC group. The TAC treatment increased renal apoptosis compared to the control treatment, based on the results of increased immunohistochemical staining of terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL), increased caspase-3 activity, and lower Bcl-2 to Bad expression ratio. However, AAT cotreatment significantly changed these markers and consequently showed decreased apoptosis. AAT protects against TAC-induced renal injury via antifibrotic, anti-inflammatory, and antiapoptotic effects.

Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods

Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochemical processes. In this paper, we present a unified set of decision-theoretic, machine learning and statistical signal processing methods and metrics to model the precision of signaling decisions, in the presence of uncertainty, using single cell data. First, we introduce erroneous decisions that may result from signaling processes and identify false alarms and miss events associated with such decisions. Then, we present an optimal decision strategy which minimizes the total decision error probability. Additionally, we demonstrate how graphing receiver operating characteristic curves conveniently reveals the trade-off between false alarm and miss probabilities associated with different cell responses. Furthermore, we extend the introduced framework to incorporate the dynamics of biochemical processes and reactions in a cell, using multi-time point measurements and multi-dimensional outcome analysis and decision-making algorithms. The introduced multivariate signaling outcome modeling framework can be used to analyze several molecular species measured at the same or different time instants. We also show how the developed binary outcome analysis and decision-making approach can be extended to more than two possible outcomes. As an example and to show how the introduced methods can be used in practice, we apply them to single cell data of PTEN, an important intracellular regulatory molecule in a p53 system, in wild-type and abnormal cells. The unified signaling outcome modeling framework presented here can be applied to various organisms ranging from viruses, bacteria, yeast and lower metazoans to more complex organisms such as mammalian cells. Ultimately, this signaling outcome modeling approach can be utilized to better understand the transition from physiological to pathological conditions such as inflammation, various cancers and autoimmune diseases.

Erianin Induces Apoptosis and Autophagy in Oral Squamous Cell Carcinoma Cells

Oral squamous cell carcinoma (OSCC) is a leading cause of cancer-related deaths worldwide. It has a very poor prognosis with over a 5-year survival rate of only 50%. Thus, it is important to identify effective therapeutic interventions against oral cancer. Apoptosis and autophagy have reported genetically regulated in physiology and diseases, which close relationship. Many natural compound study objects anticancer effect have been studied between apoptosis and autophagy relationship. The present study was designed to evaluate the effect of erianin on human oral cancer cell proliferation. Results of the study revealed that treatment with erianin significantly reduced the viability of different OSCC cell lines. Erianin exerted its cytotoxic effect by inducing cell cycle arrest and caspase-dependent apoptotic pathways. Both intrinsic and extrinsic pathways were found to be involved in erianin-mediated cell death. In addition, treatment with erianin also increased autophagy in OSCC cells. With further analysis, it was found that erianin induced both apoptosis and autophagy by regulating MAPK signaling pathways. Taken together, our study indicates that erianin plays an important role in reducing oral cancer cell viability, and thus, can be considered as a potential anticancer agent.

Information processing in the NF-κB pathway

The NF-κB pathway is known to transmit merely 1 bit of information about stimulus level. We combined experimentation with mathematical modeling to elucidate how information about TNF concentration is turned into a binary decision. Using Kolmogorov-Smirnov distance, we quantified the cell’s ability to discern 8 TNF concentrations at each step of the NF-κB pathway, to find that input discernibility decreases as signal propagates along the pathway. Discernibility of low TNF concentrations is restricted by noise at the TNF receptor level, whereas discernibility of high TNF concentrations it is restricted by saturation/depletion of downstream signaling components. Consequently, signal discernibility is highest between 0.03 and 1 ng/ml TNF. Simultaneous exposure to TNF or LPS and a translation inhibitor, cycloheximide, leads to prolonged NF-κB activation and a marked increase of transcript levels of NF-κB inhibitors, IκBα and A20. The impact of cycloheximide becomes apparent after the first peak of nuclear NF-κB translocation, meaning that the NF-κB network not only relays 1 bit of information to coordinate the all-or-nothing expression of early genes, but also over a longer time course integrates information about other stimuli. The NF-κB system should be thus perceived as a feedback-controlled decision-making module rather than a simple information transmission channel.

Concurrent infection with porcine reproductive and respiratory syndrome virus and Haemophilus parasuis in two types of porcine macrophages: apoptosis, production of ROS and formation of multinucleated giant cells

Porcine reproductive and respiratory syndrome (PRRS) is one of the most significant and economically important infectious diseases affecting swine worldwide and can predispose pigs to secondary bacterial infections caused by, e.g. Haemophilus parasuis. The aim of the presented study was to compare susceptibility of two different types of macrophages which could be in contact with both pathogens during infection with PRRS virus (PRRSV) and in co-infection with H. parasuis. Alveolar macrophages (PAMs) as resident cells provide one of the first lines of defence against microbes invading lung tissue. On the other hand, monocyte derived macrophages (MDMs) represent inflammatory cells accumulating at the site of inflammation. While PAMs were relatively resistant to cytopathogenic effect caused by PRRSV, MDMs were much more sensitive to PRRSV infection. MDMs infected with PRRSV increased expression of pro-apoptotic Bad, Bax and p53 mRNA. Increased mortality of MDMs may be also related to a higher intensity of ROS production after infection with PRRSV. In addition, MDMs (but not PAMs) infected with H. parasuis alone formed multinucleated giant cells (MGC); these cells were not observed in MDMs infected with both pathogens. Higher sensitivity of MDMs to PRRSV infection, which is associated with limited MDMs survival and restriction of MGC formation, could contribute to the development of multifactorial respiratory disease of swine.

Feedbacks, Bifurcations, and Cell Fate Decision-Making in the p53 System

The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the “apoptotic” steady state is enabled by the existence of a subcritical Neimark—Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line).

Cancers are diseases of signaling networks. Transcription factor p53 is a pivotal node of a network that integrates a variety of stress signals and governs critical processes of DNA repair, cell cycle arrest, and apoptosis. Somewhat paradoxically, despite the fact that carcinogenesis is prevalently caused by p53 network malfunction, most of our knowledge about p53 signaling is based on cancer or immortalized cell lines. In this paper, we construct a mathematical model of intact p53 network to understand dynamics of non-cancerous cells and then dynamics of cancerous cells by introducing perturbations to the regulatory system. Cell fate decisions are enabled by the presence of interlinked feedback loops which give rise to a rich repertoire of behaviors. We explain and analyze by means of numerical simulations how the dynamical structure of the regulatory system allows for generating unambiguous single-cell fate decisions, also in the case when the cell population splits into an apoptotic and a surviving subpopulation. Perturbation analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of p53 regulators can exhibit a broad spectrum of responses to DNA damage.

Luffa echinata Roxb. Induced Apoptosis in Human Colon Cancer Cell (SW-480) in the Caspase-dependent Manner and Through a Mitochondrial Apoptosis Pathway

BACKGROUND

Luffa echinata Roxb. (LER) (Cucurbitaceae) showed tremendous medicinal importance and are being used for the treatment of different ailments.

OBJECTIVE

In this study, the antiproliferative properties and cell death mechanism induced by the extract of the fruits of LER were investigated.

MATERIALS AND METHODS

MTT and LDH assay were used to test the antiproliferative and cytotoxicity of LER extract, respectively. The intracellular ROS were measured by a fluorometric assay. The expression of several apoptotic-related proteins in SW-480 cells treated by LER was evaluated by Western blot analysis.

RESULTS

The methanolic extract of LER fruits inhibited the proliferation of human colon cancer cells (SW-480) in both dose- and time-dependent manners. The LER-treated cells showed obvious characteristics of cell apoptosis, including cell shrinkage, destruction of the monolayer, and condensed chromatin. In addition, treatments of various concentrations of LER extracts caused the release of lactate dehydrogenase as a dose-dependent manner via stimulation of the intracellular metabolic system. LER induced apoptosis, DNA fragmentation, and cellular ROS accumulation in SW-480 cells. Treatment of LER on SW-480 cells promoted the expression of caspases, Bax, Bad, and p53 proteins and decreased the levels of Bcl-2 and Bcl-XL.

CONCLUSIONS

These results indicated that treatment with LER-induced cell death in mitochondrial apoptosis pathway by regulating pro-apoptotic proteins via the up regulation of the p53 protein. These findings highlight the potentials of LER in the treatment of human colon cancer.

SUMMARY

LER induced apoptosis, DNA fragmentation, and cellular ROS accumulation in SW-480 cells. Treatment of LER on SW-480 cells promoted the expression of caspases, Bax, Bad, and p53 proteins and decreased the levels of Bcl-2 and Bcl-XL.

TrkB-Mediated Neuroprotective and Antihypoxic Properties of Brain-Derived Neurotrophic Factor

The neuroprotective and antihypoxic effects of brain-derived neurotrophic factor (BDNF) on dissociated hippocampal cultures in a hypoxia model were investigated. These experiments demonstrate that 10 minutes of normobaric hypoxia increased the number of dead cells in primary culture, whereas a preventive application of BDNF increased the number of viable cells. Spontaneous bioelectrical and calcium activity in neural networks was analyzed using multielectrode arrays and functional intravital calcium imaging. The results indicate that BDNF affects the functional parameters of neuronal networks in dissociated hippocampal cultures over the 7-day posthypoxic period. In addition, the effects of k252a, an antagonist of tropomyosin-related kinase B (TrkB), on functional bioelectrical activity during and after acute hypoxia were investigated. It was shown that the protective effects of BDNF are associated with binding to the TrkB receptor. Finally, intravital fluorescent mRNA probes were used to study the role of NF-κB1 in the protective effects of BDNF. Our experiments revealed that BDNF application stimulates NF-κB1 mRNA synthesis in primary dissociated hippocampal cells under normal conditions but not in hypoxic state.

Species differential regulation of COX2 can be described by an NFκB-dependent logic AND gate

Cyclooxygenase 2 (COX2), a key regulatory enzyme of the prostaglandin/eicosanoid pathway, is an important target for anti-inflammatory therapy. It is highly induced by pro-inflammatory cytokines in a Nuclear factor kappa B (NFκB)-dependent manner. However, the mechanisms determining the amplitude and dynamics of this important pro-inflammatory event are poorly understood. Furthermore, there is significant difference between human and mouse COX2 expression in response to the inflammatory stimulus tumor necrosis factor alpha (TNFα). Here, we report the presence of a molecular logic AND gate composed of two NFκB response elements (NREs) which controls the expression of human COX2 in a switch-like manner. Combining quantitative kinetic modeling and thermostatistical analysis followed by experimental validation in iterative cycles, we show that the human COX2 expression machinery regulated by NFκB displays features of a logic AND gate. We propose that this provides a digital, noise-filtering mechanism for a tighter control of expression in response to TNFα, such that a threshold level of NFκB activation is required before the promoter becomes active and initiates transcription. This NFκB-regulated AND gate is absent in the mouse COX2 promoter, most likely contributing to its differential graded response in promoter activity and protein expression to TNFα. Our data suggest that the NFκB-regulated AND gate acts as a novel mechanism for controlling the expression of human COX2 to TNFα, and its absence in the mouse COX2 provides the foundation for further studies on understanding species-specific differential gene regulation.

Effects of VBMDMP on the reversal of cisplatin resistance in human lung cancer A549/DDP cells

Tumor drug resistance is a major obstacle to cancer chemotherapy. We previously constructed a fusion protein based on two tumstatin-derived sequences named recombinant VBMDM (rVBMDMP). We preliminarily confirmed its inhibition of HUVEC and colon cancer cell growth. The present study further systematically observed the inhibitory effect of rVBMDMP on lung cancer cell growth and analyzed a possible mechanism to provide a theoretical basis for the development of new antitumor protein drugs. The effect of rVBMDMP on human lung adenocarcinoma (A549) and cisplatin-resistant human lung adenocarcinoma (A549/DDP) cell proliferation was evaluated by MTS assay. Hoechst 33342 staining performed together with fluorescence microscopy and immunoblot analysis were used to examine the effects of rVBMDMP on the apoptosis of A549/DDP cells. A protein phosphorylation chip was used to identify changes in rVBMDMP-induced signaling protein phosphorylation. Changes in the phosphatidylinositol 3 kinase (PI3K)/Akt signal transduction pathway and expression of multidrug resistance protein (MRP-2)-related molecules following rVBMDMP treatment in A549/DDP cells were evaluated by western blot analysis. A lung cancer xenograft model was used to evaluate the reversal effect of rVBMDMP on drug-resistance of A549/DDP cell tumors to cisplatin in vivo. The results demonstrated that rVBMDMP increased the phosphorylation of 79 signaling proteins, including focal adhesion kinase (FAK), caspase-6, Fas, FasL and FAF1 and downregulated 30 signaling proteins, including integrin αV, integrin β3, PI3K/Akt, NF-κB and MRP-2 compared with the controls. rVBMDMP also increased the sensitivity of A549 and A549/DDP cells to cisplatin and directly induced apoptosis, which may be related to MRP-2 and Bcl-2 downregulation. The effects of growth inhibition and apoptosis induction of rVBMDMP on A549/DDP cells may be related to the inhibition of integrin αVβ3 and PI3K/Akt protein phosphorylation. Finally, we observed an increase in cancer cell sensitivity to cisplatin by rVBMDMP using the A549/DDP cell xenograft model in nude mice. Our study suggests that rVBMDMP may be an effective potential chemotherapy sensitizer and may be a viable drug candidate in anticancer therapies.

Modeling molecular pathways of neuronal ischemia

Neuronal ischemia, the consequence of a stroke (cerebrovascular accident), is a condition of reduced delivery of nutrients to brain neurons. The brain consumes more energy per gram of tissue than any other organ, making continuous blood flow critical. Loss of nutrients, most critically glucose and O2, triggers a large number of interacting molecular pathways in neurons and astrocytes. The dynamics of these pathways take place over multiple temporal scales and occur in multiple interacting cytosolic and organelle compartments: in mitochondria, endoplasmic reticulum, and nucleus. The complexity of these relationships suggests the use of computer simulation to understand the interplay between pathways leading to reversible or irreversible damage, the forms of damage, and interventions that could reduce damage at different stages of stroke. We describe a number of models and simulation methods that can be used to further our understanding of ischemia.