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UniTCM: A Computational Reverse Pharmacology Framework for Decoding Formula–disease Interactions in Traditional Chinese Medicine

This article is a preprint and has not been certified by peer review.

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Keywords
Traditional Chinese Medicine; Reverse Pharmacology; Artificial Intelligence; Natural Product; Target Prediction

Abstract

Traditional Chinese Medicine (TCM) offers rich clinical wisdom for modern drug discovery. Reverse pharmacology provides an effective strategy to decode these complex remedies by moving from clinical efficacy to molecular mechanisms. However, applying this paradigm to multi-component formulas remains difficult due to fragmented research workflows and the lack of integrated platforms. To address this challenge, we developed UniTCM (https://unitcm.qfxulab.com), a unified computational reverse pharmacology framework. UniTCM integrates five functional modules covering terminology standardization, disease-formula mining, AI target prediction, multi-omics verification, and analytical toolkits. Using this framework, we investigated Wutou Tang (WTD) for the treatment of rheumatoid arthritis through combined target profiling, pharmacological assays, and metabolomics. This study successfully decoded the compatibility mechanism of WTD and identified the TNF-α/NF-κB/PTGS2 pathway as its core therapeutic axis. Overall, UniTCM provides a practical bedside-to-bench platform to accelerate TCM-inspired drug discovery.

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2026-08-31

How to Cite

Zheng, X., Luo, Y., Hu, M., Chen, W., Wang, Y., Li, H., Zhang, J., Li, Y., Zhao, J., Chen, Y., Liu, X., Zeng, S., & Xu, T. (2026). UniTCM: A Computational Reverse Pharmacology Framework for Decoding Formula–disease Interactions in Traditional Chinese Medicine. LangTaoSha Preprint Server. https://doi.org/10.65215/LTSpreprints.2026.08.31.000322

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Declaration of Competing Interests

The authors declare no competing interests to disclose.