首页|Measuring drug similarity using drug-drug interactions

Measuring drug similarity using drug-drug interactions

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
Combination therapy is a promising approach to address the challenge of antimicrobial resistance,and computational models have been proposed for predicting drug-drug interactions.Most existing models rely on drug simi-larity measures based on characteristics such as chemical structure and the mechanism of action.In this study,we focus on the network structure itself and propose a drug similarity measure based on drug-drug interaction networks.We explore the potential applications of this measure by combining it with unsupervised learning and semi-supervised learning ap-proaches.In unsupervised learning,drugs can be grouped based on their interactions,leading to almost monochromatic group-group interactions.In addition,drugs within the same group tend to have similar mechanisms of action(MoA).In semi-supervised learning,the similarity measure can be utilized to construct affinity matrices,enabling the prediction of unknown drug-drug interactions.Our method exceeds existing approaches in terms of performance.Overall,our experiments demonstrate the effectiveness and practicability of the proposed similarity measure.On the one hand,when combined with clustering algorithms,it can be used for functional annotation of compounds with unknown MoA.On the other hand,when combined with semi-supervised graph learning,it enables the prediction of unknown drug-drug interactions.

drug similaritydrug-drug interactionsdrug combinationssynergy effectclusteringsemi-supervised learning

Ji Lv、Guixia Liu、Yuan Ju、Houhou Huang、Ying Sun

展开 >

College of Computer Science and Technology,Jilin University,Changchun,China

Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun,China

Sichuan University Library,Sichuan University,Chengdu,China

College of Chemistry,Jilin University,Changchun,China

Department of Respiratory Medicine,The First Hospital of Jilin University,Changchun,China

展开 >

2024

10.1002/qub2.38

定量生物学(英文版)

定量生物学(英文版)

ISSN：
年,卷(期)：2024.12(2)