Protein Dynamics in Drug Combinations: a Linear Superposition of Individual-Drug Responses
Author(s) -
Naama GevaZatorsky,
E. Dekel,
Ariel Cohen,
Tamar Da,
Lydia Cohen,
Uri Alon
Publication year - 2010
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2010.02.011
Subject(s) - drug , biology , superposition principle , dynamics (music) , computational biology , proteomics , drug response , protein dynamics , biological system , pharmacology , protein structure , physics , genetics , biochemistry , quantum mechanics , acoustics , gene
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.
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