Identification of XXXX mechanisms through computational systems modeling.

@entity1 @entity17262 @entity19204 @entity2036 @entity5 @entity3624 @entity18615 @entity14
BACKGROUND: @entity14 is one of the most prevalent causes of @entity5 . It has been studied extensively for a long time, and numerous genetic and epigenetic events have been associated with the disease. However, its molecular mechanisms are still unclear. High-throughput metabolomics data, combined with customized computational systems modeling, can assist our understanding of some of these mechanisms by revealing connections between alterations in enzymatic activities and their consequences for a @entity1 's metabolic profile. Of particular importance in this context is @entity17262 metabolism, as it provides the @entity2036 needed for cell proliferation. METHODS AND FINDINGS: We employ a computational systems approach to infer molecular mechanisms associated with @entity17262 metabolism in @entity14 . The approach uses a dynamic model of @entity17262 metabolism as the simulation system and metabolomics data as input. The execution of large-scale Monte Carlo simulations and optimization with the model permits a step-wise reduction in possibly affected enzyme mechanisms, from which likely targets emerge. CONCLUSIONS: According to our results, some enzymes in the @entity17262 pathway system are very unlikely the targets of @entity14 . In fact, only three enzymatic steps emerge with statistical confidence as most likely being affected, namely: @entity19204 ( @entity19204 ), @entity18615 (5NUC), and the @entity3624 oxidase/dehydrogenase (XD) reactions. The first of these enzymes catalyzes the first committed step of de novo @entity17262 biosynthesis, while the other two enzymes are associated with critical @entity17262 salvage pathways. The identification of these enzymes is statistically significant and robust. In addition, the results suggest potential secondary targets. The computational method cannot discern whether the inferred mechanisms constitute symptoms of @entity14 , or whether they might be causative and critical components of the uncontrolled cellular growth in @entity5 . The inferred molecular mechanisms present testable hypotheses that suggest targeted experiments for future studies of @entity14 and might eventually lead to improved diagnosis and treatment.
