INTEDE 2.0: the metabolic roadmap of drugs.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
01 Nov 2023
Historique:
accepted: 19 10 2023
revised: 13 10 2023
received: 15 09 2023
medline: 6 11 2023
pubmed: 6 11 2023
entrez: 6 11 2023
Statut: aheadofprint

Résumé

The metabolic roadmap of drugs (MRD) is a comprehensive atlas for understanding the stepwise and sequential metabolism of certain drug in living organisms. It plays a vital role in lead optimization, personalized medication, and ADMET research. The MRD consists of three main components: (i) the sequential catalyses of drug and its metabolites by different drug-metabolizing enzymes (DMEs), (ii) a comprehensive collection of metabolic reactions along the entire MRD and (iii) a systematic description on efficacy & toxicity for all metabolites of a studied drug. However, there is no database available for describing the comprehensive metabolic roadmaps of drugs. Therefore, in this study, a major update of INTEDE was conducted, which provided the stepwise & sequential metabolic roadmaps for a total of 4701 drugs, and a total of 22 165 metabolic reactions containing 1088 DMEs and 18 882 drug metabolites. Additionally, the INTEDE 2.0 labeled the pharmacological properties (pharmacological activity or toxicity) of metabolites and provided their structural information. Furthermore, 3717 drug metabolism relationships were supplemented (from 7338 to 11 055). All in all, INTEDE 2.0 is highly expected to attract broad interests from related research community and serve as an essential supplement to existing pharmaceutical/biological/chemical databases. INTEDE 2.0 can now be accessible freely without any login requirement at: http://idrblab.org/intede/.

Identifiants

pubmed: 37930837
pii: 7335751
doi: 10.1093/nar/gkad1013
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : 82373790
Organisme : Natural Science Foundation of Zhejiang Province
ID : LR21H300001
Organisme : National Key R&D Program of China
ID : 2022YFC3400501
Organisme : Leading Talent of the 'Ten Thousand Plan' National High-Level Talents Special Support Plan of China
Organisme : The Double Top-Class Universities
ID : 181201*194232101
Organisme : Fundamental Research Funds for Central Universities
ID : 2018QNA7023
Organisme : Key R&D Program of Zhejiang Province
ID : 2020C03010
Organisme : Westlake Laboratory (Westlake Laboratory of Life Science & Biomedicine); Alibaba Cloud
Organisme : Information Technology Center of Zhejiang University
Organisme : Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare
Organisme : Hebei Provincial Department of Science and Technology
ID : 21372601D
Organisme : Natural Science Foundation of Hebei Province
ID : H2021206448

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.

Auteurs

Yang Zhang (Y)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Xingang Liu (X)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Fengcheng Li (F)

College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
The Children's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310052, China.

Jiayi Yin (J)

College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Department of Clinical Pharmacy, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China.

Hao Yang (H)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Xuedong Li (X)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Xinyu Liu (X)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Xu Chai (X)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Tianle Niu (T)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Su Zeng (S)

College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.

Qingzhong Jia (Q)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.

Feng Zhu (F)

School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.
College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China.

Classifications MeSH