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NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease
论文作者 Xu, TJ; Gao, WX; Zhu, LX; Chen, WN; Niu, CQ; Yin, WJ; Ma, LX; Zhu, XY; Ling, YC; Gao, S; Liu, L; Jiao, N; Chen, WM; Zhang, GQ; Zhu, RX; Wu, DF
期刊/会议名称 JOURNAL OF CHEMICAL INFORMATION AND MODELING
论文年度 2023
论文类别 Article; Early Access
摘要 Nonalcoholic fatty liver disease (NAFLD) is the mostcommon chronicliver disease with a broad spectrum of histologic manifestations.The rapidly growing prevalence and the complex pathologic mechanismsof NAFLD pose great challenges for treatment development. Despitetremendous efforts devoted to drug development, there are no FDA-approvedmedicines yet. Here, we present NAFLDkb, a specialized knowledge baseand platform for computer-aided drug design against NAFLD. With multiperspectiveinformation curated from diverse source materials and public databases,NAFLDkb presents the associations of drug-related entities as individualknowledge graphs. Practical drug discovery tools that facilitate theutilization and expansion of NAFLDkb have also been implemented inthe web interface, including chemical structure search, drug-likenessscreening, knowledge-based repositioning, and research article annotation.Moreover, case studies of a knowledge graph repositioning model anda generative neural network model are presented herein, where threerepositioning drug candidates and 137 novel lead-like compounds werenewly established as NAFLD pharmacotherapy options reusing data recordsand machine learning tools in NAFLDkb, suggesting its clinical reliabilityand great potential in identifying novel drug-disease associationsof NAFLD and generating new insights to accelerate NAFLD drug development.NAFLDkb is freely accessible at https://www.biosino.org/nafldkb and will be updated periodically with the latest findings.
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