---
_id: '1823'
abstract:
- lang: eng
  text: Abstract Drug combinations are increasingly important in disease treatments,
    for combating drug resistance, and for elucidating fundamental relationships in
    cell physiology. When drugs are combined, their individual effects on cells may
    be amplified or weakened. Such drug interactions are crucial for treatment efficacy,
    but their underlying mechanisms remain largely unknown. To uncover the causes
    of drug interactions, we developed a systematic approach based on precise quantification
    of the individual and joint effects of antibiotics on growth of genome-wide Escherichia
    coli gene deletion strains. We found that drug interactions between antibiotics
    representing the main modes of action are highly robust to genetic perturbation.
    This robustness is encapsulated in a general principle of bacterial growth, which
    enables the quantitative prediction of mutant growth rates under drug combinations.
    Rare violations of this principle exposed recurring cellular functions controlling
    drug interactions. In particular, we found that polysaccharide and ATP synthesis
    control multiple drug interactions with previously unexplained mechanisms, and
    small molecule adjuvants targeting these functions synthetically reshape drug
    interactions in predictable ways. These results provide a new conceptual framework
    for the design of multidrug combinations and suggest that there are universal
    mechanisms at the heart of most drug interactions. Synopsis A general principle
    of bacterial growth enables the prediction of mutant growth rates under drug combinations.
    Rare violations of this principle expose cellular functions that control drug
    interactions and can be targeted by small molecules to alter drug interactions
    in predictable ways. Drug interactions between antibiotics are highly robust to
    genetic perturbations. A general principle of bacterial growth enables the prediction
    of mutant growth rates under drug combinations. Rare violations of this principle
    expose cellular functions that control drug interactions. Diverse drug interactions
    are controlled by recurring cellular functions, including LPS synthesis and ATP
    synthesis. A general principle of bacterial growth enables the prediction of mutant
    growth rates under drug combinations. Rare violations of this principle expose
    cellular functions that control drug interactions and can be targeted by small
    molecules to alter drug interactions in predictable ways.
article_number: '807'
article_processing_charge: No
author:
- first_name: Guillaume
  full_name: Chevereau, Guillaume
  id: 424D78A0-F248-11E8-B48F-1D18A9856A87
  last_name: Chevereau
- first_name: Mark Tobias
  full_name: Bollenbach, Mark Tobias
  id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
  last_name: Bollenbach
  orcid: 0000-0003-4398-476X
citation:
  ama: Chevereau G, Bollenbach MT. Systematic discovery of drug interaction mechanisms.
    <i>Molecular Systems Biology</i>. 2015;11(4). doi:<a href="https://doi.org/10.15252/msb.20156098">10.15252/msb.20156098</a>
  apa: Chevereau, G., &#38; Bollenbach, M. T. (2015). Systematic discovery of drug
    interaction mechanisms. <i>Molecular Systems Biology</i>. Nature Publishing Group.
    <a href="https://doi.org/10.15252/msb.20156098">https://doi.org/10.15252/msb.20156098</a>
  chicago: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery
    of Drug Interaction Mechanisms.” <i>Molecular Systems Biology</i>. Nature Publishing
    Group, 2015. <a href="https://doi.org/10.15252/msb.20156098">https://doi.org/10.15252/msb.20156098</a>.
  ieee: G. Chevereau and M. T. Bollenbach, “Systematic discovery of drug interaction
    mechanisms,” <i>Molecular Systems Biology</i>, vol. 11, no. 4. Nature Publishing
    Group, 2015.
  ista: Chevereau G, Bollenbach MT. 2015. Systematic discovery of drug interaction
    mechanisms. Molecular Systems Biology. 11(4), 807.
  mla: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of
    Drug Interaction Mechanisms.” <i>Molecular Systems Biology</i>, vol. 11, no. 4,
    807, Nature Publishing Group, 2015, doi:<a href="https://doi.org/10.15252/msb.20156098">10.15252/msb.20156098</a>.
  short: G. Chevereau, M.T. Bollenbach, Molecular Systems Biology 11 (2015).
corr_author: '1'
date_created: 2018-12-11T11:54:12Z
date_published: 2015-04-01T00:00:00Z
date_updated: 2025-09-23T13:38:00Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15252/msb.20156098
ec_funded: 1
external_id:
  isi:
  - '000354022300005'
file:
- access_level: open_access
  checksum: 4289b518fbe2166682fb1a1ef9b405f3
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:14:34Z
  date_updated: 2020-07-14T12:45:17Z
  file_id: '5087'
  file_name: IST-2015-395-v1+1_807.full.pdf
  file_size: 1273573
  relation: main_file
file_date_updated: 2020-07-14T12:45:17Z
fulldoi: https://doi.org/10.15252/msb.20156098
has_accepted_license: '1'
intvolume: '        11'
isi: 1
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P27201-B22
  name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
  grant_number: RGP0042/2013
  name: Revealing the fundamental limits of cell growth
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '303507'
  name: Optimality principles in responses to antibiotics
publication: Molecular Systems Biology
publication_status: published
publisher: Nature Publishing Group
publist_id: '5283'
pubrep_id: '395'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Systematic discovery of drug interaction mechanisms
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 11
year: '2015'
...
