Biochemical reaction network topology defines dose-dependent Drug-Drug interactions.
Combination therapy
Drug
Enzyme
Reaction network
Topology
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
03 2023
03 2023
Historique:
received:
20
09
2022
revised:
28
12
2022
accepted:
22
01
2023
pubmed:
23
2
2023
medline:
15
3
2023
entrez:
22
2
2023
Statut:
ppublish
Résumé
Drug combination therapy is a promising strategy to enhance the desired therapeutic effect, while reducing side effects. High-throughput pairwise drug combination screening is a commonly used method for discovering favorable drug interactions, but is time-consuming and costly. Here, we investigate the use of reaction network topology-guided design of combination therapy as a predictive in silico drug-drug interaction screening approach. We focused on three-node enzymatic networks, with general Michaelis-Menten kinetics. The results revealed that drug-drug interactions critically depend on the choice of target arrangement in a given topology, the nature of the drug, and the desired level of change in the network output. The results showed a negative correlation between antagonistic interactions and the dosage of drugs. Overall, the negative feedback loops showed the highest synergistic interactions (the lowest average combination index) and, intriguingly, required the highest drug doses compared to other topologies under the same condition.
Identifiants
pubmed: 36805215
pii: S0010-4825(23)00049-5
doi: 10.1016/j.compbiomed.2023.106584
pii:
doi:
Substances chimiques
Drug Combinations
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
106584Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None Declared.