A computational model of mitochondrial metabolism and electrophysiology is introduced and applied to analysis of data from isolated cardiac mitochondria and data on phosphate metabolites in striated muscle in vivo. This model is constructed based on detailed kinetics and thermodynamically balanced reaction mechanisms and a strict accounting of rapidly equilibrating biochemical species. Since building such a model requires introducing a large number of adjustable kinetic parameters, a correspondingly large amount of independent data from isolated mitochondria respiring on different substrates and subject to a variety of protocols is used to parameterize the model and ensure that it is challenged by a wide range of data corresponding to diverse conditions. The developed model is further validated by both in vitro data on isolated cardiac mitochondria and in vivo experimental measurements on human skeletal muscle. The validated model is used to predict the roles of NAD and ADP in regulating the tricarboxylic acid cycle dehydrogenase fluxes, demonstrating that NAD is the more important regulator. Further model predictions reveal that a decrease of cytosolic pH value results in decreases in mitochondrial membrane potential and a corresponding drop in the ability of the mitochondria to synthesize ATP at the hydrolysis potential required for cellular function.Mitochondrial energy metabolism centers on the tricarboxylic acid cycle reactions, oxidative phosphorylation, and associated transport reactions. It is a system in which biochemical reactions are coupled to membrane electrophysiology, nearly every intermediate acts as an allosteric regulator of several enzymes in the system, and nearly all intermediates are transported into and out of the mitochondria via a host of electroneutral and electrogenic exchangers and cotransporters. Thus, it is a system with a level of complexity that begs for computational modeling to aid in analysis of experimental data and development and testing of quantitative hypotheses. In addition, as is demonstrated in this work, computer modeling of mitochondrial function facilitates the translation of observations made in one experimental regime (isolated ex vivo mitochondria) to another (in vivo cellular energy metabolism).In addition, the developed model provides the basis for examining how mitochondrial energetics is controlled in vivo. The model is used to predict the roles of NAD and ADP on regulating tricarboxylic acid cycle dehydrogenase fluxes, demonstrating that NAD is the more important regulator. The mitochondrial redox state in turn is affected by cytoplasmic P i concentration, since inorganic phosphate is a co-factor for transport of tricarboxylic acid cycle substrates a substrate for the tricarboxylic acid cycle. Since ADP and P i are the biochemical substrates for oxidative phosphorylation, the primary mechanism of control of mitochondrial energy metabolism (tricarboxylic acid cycle and oxidative phosphorylation) in striated muscle is feedback of the products of ATP hydrolysis....

Lidocaine and bupivacaine induce apoptosis of breast tumor cells at clinically relevant concentrations. Our results reveal previously unrecognized beneficial actions of local anesthetics and call for further studies to assess the oncologic advantages of their use during breast cancer surgery.

Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0-24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte-Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced.

Analysis of biochemical systems requires reliable and self-consistent databases of thermodynamic properties for biochemical reactions. Here a database of thermodynamic properties for the reactions of glycolysis and the tricarboxylic acid cycle is developed from measured equilibrium data. Species-level free energies of formation are estimated based on comparing thermodynamic model predictions for reaction-level equilibrium constants to previously reported data obtained under different experimental conditions. Matching model predictions to the data involves applying state corrections for ionic strength, pH, and metal ion binding for each input experimental biochemical measurement. By archiving all of the raw data, documenting all model assumptions and calculations, and making the computer package and data available, this work provides a framework for extension and refinement by adding to the underlying raw experimental data in the database and/or refining the underlying model assumptions. Thus the resulting database is a refinement of preexisting databases of thermodynamics in terms of reliability, self-consistency, transparency, and extensibility.

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Liver receptor homolog‐1 (LRH‐1; NR5A2) is an orphan member of the nuclear receptor superfamily, mainly expressed in endoderm‐derived tissues and in the ovary. In ovarian granulosa and luteal cells, LRH‐1 regulates the expression of genes associated with ovarian steroidogenesis. LRH‐1 can be transported to transcriptionally inactive nuclear bodies after conjugation with small ubiquitin‐related modifier (SUMO). In the present study, we investigated the effects of SUMO modification at five lysine residues of LRH‐1 in rat granulosa cells. Lysine 289 could be conjugated with SUMO‐1 in vitro, and the mutation K289R increased transcriptional activity of LRH‐1, suggesting that SUMO conjugation is associated with transcription repression. Coexpression of SUMO‐1 targets LRH‐1 to the dot‐like nuclear bodies, but the effect of lysine mutations on blocking subnuclear localization depended on the cell type. In COS‐7 cells, mutation of either K173 or K289 prevented SUMO‐1‐mediated translocation of LRH‐1 into nuclear bodies and also reduced the conjugation by SUMO‐1, suggesting that K289 and K173 are two important sites involved in SUMO‐1 modification. In granulosa cells, three or more altered lysine residues were required for nucleoplasm retention. This result suggests that multiple lysine residues are targets for SUMO conjugation in vivo and granulosa cells are more sensitive to SUMO‐1‐mediated LRH‐1 localization to nuclear bodies. Nuclear body localization of LRH‐1 was suppressed by forskolin and cholera toxin. Forskolin treatment obviously influences the expression of members involved in the SUMO pathway. The results obtained in the present study suggest that cAMP signaling could change the dynamic process of sumoylation and repress LRH‐1 targeting to nuclear speckles in rat granulosa cells.

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SUMO protease SENP1 is elevated in multiple carcinomas including prostate cancer (PCa). SENP1 exhibits carcinogenic properties; it promotes androgen receptor-dependent and -independent cell proliferation, stabilizes HIF1a, increases VEGF, and supports angiogenesis. However, mice expressing an androgen-responsive promoter driven SENP1-transgene (SENP1-Tg) develop high-grade prostatic intraepithelial neoplasia, but not carcinoma. We now show that tumor suppressive PTEN signaling is induced in SENP1-Tg to enhance prostate epithelial cell apoptosis. SENP1 blocks SUMO1-dependent ubiquitylation and degradation of PTEN. In the absence of SENP1, SUMO1-modified PTEN is sequestered in the cytosol, where binding to ubiquitin-E3 ligase WWP2 occurs. Concurrently, WWP2 is also SUMOylated, which potentiates its interaction with PTEN. Thus, SENP1 directs ubiquitin-E3-substrate association to control PTEN stability. PTEN serves as a barrier for SENP1-mediated prostate carcinogenesis as SENP1-Tg mice develop invasive carcinomas only after PTEN reduction. Hence, SENP1 modulates multiple facets of carcinogenesis and may serve as a target specifically for aggressive PTEN-deficient PCa.