Search algorithms as a framework for the optimization of drug combinations.

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms -- originally developed for digital communication -- modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs using only one-third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.

Metabolomic and flux-balance analysis of age-related decline of hypoxia tolerance in Drosophila muscle tissue.

The fruitfly Drosophila melanogaster is increasingly used as a model organism for studying acute hypoxia tolerance and for studying aging, but the interactions between these two factors are not well known. Here we show that hypoxia tolerance degrades with age in post-hypoxic recovery of whole-body movement, heart rate and ATP content. We previously used (1)H NMR metabolomics and a constraint-based model of ATP-generating metabolism to discover the end products of hypoxic metabolism in flies and generate hypotheses for the biological mechanisms. We expand the reactions in the model using tissue- and age-specific microarray data from the literature, and then examine metabolomic profiles of thoraxes after 4 h at 0.5% O(2) and after 5 min of recovery in 40- versus 3-day-old flies. Model simulations were constrained to fluxes calculated from these data. Simulations suggest that the decreased ATP production during reoxygenation seen in aging flies can be attributed to reduced recovery of mitochondrial respiration pathways and concomitant overdependence on the acetate production pathway as an energy source.

Flexibility in energy metabolism supports hypoxia tolerance in Drosophila flight muscle: metabolomic and computational systems analysis.

The fruitfly Drosophila melanogaster offers promise as a genetically tractable model for studying adaptation to hypoxia at the cellular level, but the metabolic basis for extreme hypoxia tolerance in flies is not well known. Using (1)H NMR spectroscopy, metabolomic profiles were collected under hypoxia. Accumulation of lactate, alanine, and acetate suggested that these are the major end products of anaerobic metabolism in the fly. A constraint-based model of ATP-producing pathways was built using the annotated genome, existing models, and the literature. Multiple redundant pathways for producing acetate and alanine were added and simulations were run in order to find a single optimal strategy for producing each end product. System-wide adaptation to hypoxia was then investigated in silico using the refined model. Simulations supported the hypothesis that the ability to flexibly convert pyruvate to these three by-products might convey hypoxia tolerance by improving the ATP/H(+) ratio and efficiency of glucose utilization.