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NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease

Authors :
Xu, Tingjun
Gao, Wenxing
Zhu, Lixin
Chen, Wanning
Niu, Chaoqun
Yin, Wenjing
Ma, Liangxiao
Zhu, Xinyue
Ling, Yunchao
Gao, Sheng
Liu, Lei
Jiao, Na
Chen, Weiming
Zhang, Guoqing
Zhu, Ruixin
Wu, Dingfeng
Source :
Journal of Chemical Information and Modeling; April 2024, Vol. 64 Issue: 7 p2817-2828, 12p
Publication Year :
2024

Abstract

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease with a broad spectrum of histologic manifestations. The rapidly growing prevalence and the complex pathologic mechanisms of NAFLD pose great challenges for treatment development. Despite tremendous efforts devoted to drug development, there are no FDA-approved medicines yet. Here, we present NAFLDkb, a specialized knowledge base and platform for computer-aided drug design against NAFLD. With multiperspective information curated from diverse source materials and public databases, NAFLDkb presents the associations of drug-related entities as individual knowledge graphs. Practical drug discovery tools that facilitate the utilization and expansion of NAFLDkb have also been implemented in the web interface, including chemical structure search, drug-likeness screening, knowledge-based repositioning, and research article annotation. Moreover, case studies of a knowledge graph repositioning model and a generative neural network model are presented herein, where three repositioning drug candidates and 137 novel lead-like compounds were newly established as NAFLD pharmacotherapy options reusing data records and machine learning tools in NAFLDkb, suggesting its clinical reliability and great potential in identifying novel drug-disease associations of NAFLD and generating new insights to accelerate NAFLD drug development. NAFLDkb is freely accessible at https://www.biosino.org/nafldkband will be updated periodically with the latest findings.

Details

Language :
English
ISSN :
15499596 and 1549960X
Volume :
64
Issue :
7
Database :
Supplemental Index
Journal :
Journal of Chemical Information and Modeling
Publication Type :
Periodical
Accession number :
ejs63010909
Full Text :
https://doi.org/10.1021/acs.jcim.3c00395