Systematic Prediction of Antifungal Drug Synergy by Chemogenomic Screening in .

Since the earliest days of using natural remedies, combining therapies for disease treatment has been standard practice. Combination treatments exhibit synergistic effects, broadly defined as a greater-than-additive effect of two or more therapeutic agents. Clinicians often use their experience and expertise to tailor such combinations to maximize the therapeutic effect. Although understanding and predicting biophysical underpinnings of synergy have benefitted from high-throughput screening and computational studies, one challenge is how to best design and analyze the results of synergy studies, especially because the number of possible combinations to test quickly becomes unmanageable. Nevertheless, the benefits of such studies are clear-by combining multiple drugs in the treatment of infectious disease and cancer, for instance, one can lessen host toxicity and simultaneously reduce the likelihood of resistance to treatment. This study introduces a new approach to characterize drug synergy, in which we extend the widely validated chemogenomic HIP-HOP assay to drug combinations; this assay involves parallel screening of comprehensive collections of barcoded deletion mutants. We identify a class of "combination-specific sensitive strains" that introduces mechanisms for the synergies we observe and further suggest focused follow-up studies.