title: Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism.
abstract: The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery.
authors.affiliation: Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.|Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5.
authors.forename: Jan
authors.initials: J
authors.lastname: Wildenhain
authors.affiliation: Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.|Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5.
authors.forename: Michaela
authors.initials: M
authors.lastname: Spitzer
authors.affiliation: Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada M5G 1X5.
authors.forename: Sonam
authors.initials: S
authors.lastname: Dolma
authors.affiliation: Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada M5G 1X5.
authors.forename: Nick
authors.initials: N
authors.lastname: Jarvik
authors.affiliation: Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.
authors.forename: Rachel
authors.initials: R
authors.lastname: White
authors.affiliation: Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.
authors.forename: Marcia
authors.initials: M
authors.lastname: Roy
authors.affiliation: Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5.
authors.forename: Emma
authors.initials: E
authors.lastname: Griffiths
authors.affiliation: Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada M5G 1X5.
authors.forename: David S
authors.initials: DS
authors.lastname: Bellows
authors.affiliation: Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada L8N 3Z5.
authors.forename: Gerard D
authors.initials: GD
authors.lastname: Wright
authors.affiliation: Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.|Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Quebec, Canada H3C 3J7.
authors.forename: Mike
authors.initials: M
authors.lastname: Tyers
mesh_terms: D000935:Antifungal Agents / Q000737:chemistry / Q000494:pharmacology; D019295:Computational Biology; D055808:Drug Discovery; D004357:Drug Synergism; D005800:Genes, Fungal; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics; D013329:Structure-Activity Relationship
chemical_list: D000935:Antifungal Agents