Adverse side effects and toxicity are a primary cause for failure of late stage drug candidates or withdrawal/restricted use of drugs on the market. However, the discovery of safe and effective drugs requires a deeper understanding of disease and drug mechanisms in order to design/choose drugs with minimal potential of  harmful side effects.  The overall objective of our research here is to develop our computational models, specifically designed to use existing biological knowledge of cellular level neurotoxicity to systematically identify optimal cellular targets for drug development ultimately leading to the discovery of safe and effective treatment options. The same methodology can be applied in the treatment of mechanical brain injury. Example applications are shown below.

Organophosphorus Compound Neurotoxicity

Organophosphate (OP)-based compounds (insecticides, pesticides, herbicides, and military nerve agents) are well known to be neurotoxic to humans. In this project with US Army MRMC Detailed metabolic and signaling pathway models describing organophosphorus compound toxicity were constructed utilizing relevant scientific literature and pathway databases. These pathway models accurately predicted Modified Cytosensor Microphysiometer (Vanderbilt University, Nashville) measured dopamine release from a neurotypical rat pheochromocytoma (PC12) cell line exposed to parathion. Additionally, sensitivity analysis of the pathway models indicated that protein kinase C (PKC) exerted the most control over the cytosolic calcium concentration by several orders of magnitude. Figure xxx is a plot of the sensitivity coefficients of all 32 enzymes participating in the signaling and calcium dynamics cascade. This figure indicates that PKC control is maximally exerted through the action of the RAS cascade, and in a secondary manner through the MAPK cascade. The sensitivity analysis indicates that PKC and associated activators and inhibitors have the largest impact on the steady state calcium concentration upon exposure to OP compounds.

Toxin Discrimination

In a collaborative effort with Vanderbilt University, CFDRC has assembled a fully mass-conserving, dynamic, predictive metabolic pathway model encompassing glycolysis, pentose phosphate, and TCA cycle/oxidative phosphorylation.  The pathway consists of 73 species and 52 reactions.  CFDRC has used this model to construct a virtual Microphysiometer environment that fully couples the mechanical action of the instrument to the predictive, dynamic model of cellular metabolism.  The transport coupled metabolic model has been validated against MMP measurements of CHO cells’ response to sodium fluoride exposure. The Fluoride ion is a potent inhibitor of enolase, decreasing the production of pyruvate, ultimately causing the cell to increase the carbon flux through the TCA cycle in order to maintain ATP concentrations.  The ability of this model to reproduce accurately the dynamics of cellular response to fluoride ion exposure confirms the quantitative nature of our approach and the suitability of this system for analysis of metabolic response to a suite of natural and man-made toxins.