Chemogenomic profiling predicts antifungal synergies |
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| Authors: | Elias Epp Amélie Fredette Jamie Surprenant Doreen Harcus Elaine Tan Tamiko Nishimura Malcolm Whiteway Michael Hallett David Y Thomas |
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| Affiliation: | 1. Genetics Group, Biotechnology Research Institute, National Research Council of Canada, Montréal, Québec, Canada;2. Department of Biology, McGill University, Montréal, Québec, Canada;3. Department of Biochemistry, Faculty of Medicine, McGill University, Montréal, Québec, Canada;4. McGill Centre for Bioinformatics, McGill University, Montréal, Québec, Canada;5. School of Computer Science, McGill University, Montréal, Québec, Canada;6. Rosalind and Morris Goodman Cancer Centre, McGill University, Montréal, Québec, Canada |
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| Abstract: | Chemotherapies, HIV infections, and treatments to block organ transplant rejection are creating a population of immunocompromised individuals at serious risk of systemic fungal infections. Since single‐agent therapies are susceptible to failure due to either inherent or acquired resistance, alternative therapeutic approaches such as multi‐agent therapies are needed. We have developed a bioinformatics‐driven approach that efficiently predicts compound synergy for such combinatorial therapies. The approach uses chemogenomic profiles in order to identify compound profiles that have a statistically significant degree of similarity to a fluconazole profile. The compounds identified were then experimentally verified to be synergistic with fluconazole and with each other, in both Saccharomyces cerevisiae and the fungal pathogen Candida albicans. Our method is therefore capable of accurately predicting compound synergy to aid the development of combinatorial antifungal therapies. |
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| Keywords: | antifungal chemical genomics drug profiling synergy predictor |
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