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Some traditional Chinese medicine (TCM) compounds can improve obesity by increasing energy consumption. This study aimed to identify and verify TCM compounds that promote adipose thermogenesis to alleviate obesity via transcriptomic analysis, molecular docking, network pharmacology, and Connectivity Map (CMap) analysis. Thirty\u2010six TCMs related to adipose tissue thermogenesis were first collected to generate transcriptomic data. Then a ranking method based on integrated transcriptomic data was used to select emodin from the TCM Da Huang for network pharmacology to explore its potential mechanisms and further experimental validation. CMap analysis of thermogenesis signature genes from ProFAT and GEO datasets identified triptolide as another compound for improving obesity through enhanced thermogenesis. In\u00a0vitro experiments with 3T3\u2010L1 cells and in\u00a0vivo experiments with zebrafish were conducted. The results showed that both emodin and triptolide could upregulate the NAD\n                    <jats:sup>+<\/jats:sup>\n                    \/NADH ratio, increase AMPK and SIRT1 expression, suppress lipid accumulation, and promote lipolysis, as verified by both in\u00a0vitro and in\u00a0vivo experiments. They also upregulated thermogenesis\u2010related genes (e.g., UCP1, PGC1\u03b1, and PRDM16), lipolysis\u2010related genes (e.g., PKA, ATGL, and HSL), mitochondrial biogenesis\u2010related genes (e.g., NRF1, NRF2, and TFAM), and \u03b2\u2010oxidation\u2010related genes (e.g., CPT1\u03b1 and CPT1\u03b2). Meanwhile, they downregulated lipogenesis\u2010related genes such as FASN, SREBP1, and ACC. These results provide a basis for understanding the effects of emodin and triptolide on obesity. The findings highlight the effectiveness of combined screening approaches in exploring compounds with beneficial metabolic effects.\n                  <\/jats:p>","DOI":"10.1002\/ptr.70407","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T01:44:32Z","timestamp":1784166272000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Transcriptome Inference and Systematic Approaches to Investigate\n                    <scp>TCM<\/scp>\n                    Compounds With Beneficial Metabolic Effects"],"prefix":"10.1002","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[{"name":"School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR China"},{"name":"Warshel Institute for Computational Biology, School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR China"},{"name":"Guangdong Provincial Key Laboratory of Digital Biology and Drug Development The Chinese University of Hong Kong  Shenzhen Guangdong PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang\u2010Chi\u2010Dung","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR China"},{"name":"Warshel Institute for Computational Biology, School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR China"},{"name":"Guangdong Provincial Key Laboratory of Digital Biology and Drug Development The Chinese University of Hong Kong  Shenzhen Guangdong PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hsi\u2010Yuan","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR China"},{"name":"Warshel Institute for Computational Biology, School of Medicine, the Chinese University of Hong Kong  Shenzhen Guangdong PR 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