In metabolism, available free energy is limited and must be divided across pathway steps to maintain a negative ΔG throughout. For each reaction, ΔG is log proportional both to a concentration ratio (reaction quotient to equilibrium constant) and to a flux ratio (backward to forward flux). Here we use isotope labeling to measure absolute metabolite concentrations and fluxes in Escherichia coli, yeast and a mammalian cell line. We then integrate this information to obtain a unified set of concentrations and ΔG for each organism. In glycolysis, we find that free energy is partitioned so as to mitigate unproductive backward fluxes associated with ΔG near zero. Across metabolism, we observe that absolute metabolite concentrations and ΔG are substantially conserved and that most substrate (but not inhibitor) concentrations exceed the associated enzyme binding site dissociation constant (Km or Ki). The observed conservation of metabolite concentrations is consistent with an evolutionary drive to utilize enzymes efficiently given thermodynamic and osmotic constraints.

Current approaches for identifying synergistic targets use cell culture models to see if the combined effect of clinically available drugs is better than predicted by their individual efficacy. New techniques are needed to systematically and rationally identify targets and pathways that may be synergistic targets. Here, we created a tool to screen and identify molecular targets that may synergize with new inhibitors of target of rapamycin (TOR), a conserved protein that is a major integrator of cell proliferation signals in the nutrient-signaling pathway. Although clinical results from TOR complex 1 (TORC1)-specific inhibition using rapamycin analogs have been disappointing, trials using inhibitors that also target TORC2 have been promising. To understand this increased therapeutic efficacy and to discover secondary targets for combination therapy, we engineered Tor2 in S. cerevisiae to accept an orthogonal inhibitor. We used this tool to create a chemical epistasis miniarray profile (ChE-MAP) by measuring interactions between the chemically inhibited Tor2 kinase and a diverse library of deletion mutants. The ChE-MAP identified known TOR components and distinguished between TORC1- and TORC2-dependent functions. The results showed a TORC2-specific interaction with the pentose phosphate pathway, a previously unappreciated TORC2 function that suggests a role for the complex in balancing the high energy demand required for ribosome biogenesis.