title: Protein dynamics in drug combinations: a linear superposition of individual-drug responses.
abstract: Drugs and drug combinations have complex biological effects on cells and organisms. Little is known about how drugs affect protein dynamics that determine these effects. Here, we use a dynamic proteomics approach to accurately follow 15 protein levels in human cells in response to 13 different drugs. We find that protein dynamics in response to combinations of drugs are described accurately by a linear superposition (weighted sum) of their response to individual drugs. The weights in this superposition describe the relative impact of each drug on each protein. Using these weights, we show that one can predict the dynamics in a three-drug or four-drug combination on the basis of the dynamics in drug pairs. Our approach might eliminate the need to increase the number of experiments exponentially with the number of drugs and suggests that it might be possible to rationally control protein dynamics with specific drug combinations.
authors.affiliation: Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
authors.forename: Naama
authors.initials: N
authors.lastname: Geva-Zatorsky
authors.forename: Erez
authors.initials: E
authors.lastname: Dekel
authors.forename: Ariel A
authors.initials: AA
authors.lastname: Cohen
authors.forename: Tamar
authors.initials: T
authors.lastname: Danon
authors.forename: Lydia
authors.initials: L
authors.lastname: Cohen
authors.forename: Uri
authors.initials: U
authors.lastname: Alon
mesh_terms: D045744:Cell Line, Tumor; D004305:Dose-Response Relationship, Drug; D004338:Drug Combinations; D004347:Drug Interactions; D015870:Gene Expression / Q000187:drug effects*; D006801:Humans; D011506:Proteins / Q000737:chemistry*
chemical_list: D004338:Drug Combinations; D011506:Proteins