title: Chemical combination effects predict connectivity in biological systems.
abstract: Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured.
authors.affiliation: CombinatoRx, Incorporated, Cambridge, MA 02142, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Lehár
authors.forename: Grant R
authors.initials: GR
authors.lastname: Zimmermann
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Krueger
authors.forename: Raymond A
authors.initials: RA
authors.lastname: Molnar
authors.forename: Jebediah T
authors.initials: JT
authors.lastname: Ledell
authors.forename: Adrian M
authors.initials: AM
authors.lastname: Heilbut
authors.forename: Glenn F
authors.initials: GF
authors.lastname: Short
authors.forename: Leanne C
authors.initials: LC
authors.lastname: Giusti
authors.forename: Garry P
authors.initials: GP
authors.lastname: Nolan
authors.forename: Omar A
authors.initials: OA
authors.lastname: Magid
authors.forename: Margaret S
authors.initials: MS
authors.lastname: Lee
authors.forename: Alexis A
authors.initials: AA
authors.lastname: Borisy
authors.forename: Brent R
authors.initials: BR
authors.lastname: Stockwell
authors.forename: Curtis T
authors.initials: CT
authors.lastname: Keith
mesh_terms: D003198:Computer Simulation; D004338:Drug Combinations; D004357:Drug Synergism; D015966:Gene Expression Regulation, Fungal / Q000187:drug effects; D045325:HCT116 Cells; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000187:drug effects*; D008954:Models, Biological; D015233:Models, Statistical; D012441:Saccharomyces cerevisiae / Q000187:drug effects; D013261:Sterols / Q000096:biosynthesis; D049490:Systems Biology
chemical_list: D004338:Drug Combinations; D013261:Sterols