Systematic elucidation of the effective constituents and potential mechanisms of Scrophulariae Radix against neoplasm based on LC-MS, network pharmacology, and molecular docking approaches

Shujie Yu^1,2Xiaobin Kong^1,3Mengyi Shan^1,2Peilu Wang^1,2Wenlong Li^1,2Peiyuan Zhao^1,4Yunjie Sheng^1,2Bingqian He^1,5Qi Shi^1,2Huaqiang Li^1,2Luping Qin^1,2Xiongyu Meng^1,2*

• ¹Zhejiang Chinese Medical University, Hangzhou, China
• ²School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, Jiangsu Province, China
• ³School of Basic Medical Sciences and School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China
• ⁴Institute of Interdisciplinary Integrative Biomedical Research, Shanghai University of Traditional Chinese Medicine, Shanghai, Shanghai Municipality, China
• ⁵Academy of Chinese Medical Science, Zhejiang Chinese Medical University, Hangzhou, China

Scrophulariae Radix is a traditional Chinese medicine used to treat neoplasms in previous publications. Nevertheless, how the Scrophulariae Radix chemical constituents treat neoplasm still needs to be clarified. Herein, we combined the response surface method, UPLC-ESI-MS/MS, network pharmacology, molecular docking, and molecular dynamics (MD) simulation to characterize bioactive constituents in Scrophulariae Radix and further uncover their potential mechanisms against neoplasm. As a result, the material-liquid ratio was significantly reduced from 100 g/mL to 32 g/mL; and the extraction efficiency was 1.332%, which was close to the predicted value of 1.346% in the response surface method, indicating that the Algorithm model had a good fit. Next, totally 738 compounds, including 161 terpenoids, 144 phenolic acids, 51 alkaloids, 24 flavonoids, 34 saccharides, 32 lignans and coumarins, 45 amino acids and derivatives, 23 organic acids, 134 lipids, 22 nucleotides and derivatives, and 59 others ingredients, were characterized from Scrophulariae Radix based on the accurate precursor and product ions, retention time, standards, fragmentation patterns, and previous publications. Subsequently, to screen which constituents were most effective, the network pharmacology was constructed, and 96 active compounds and 488 key neoplasm-related targets were identified, leading to the establishment of the "Drug-Compound-Target" network and PPI network. The top four components and targets were selected for the presentation of MD simulation, including cytosporone C, cystomexicone A, mediterraneone, and bestim, with the highest degree related targets Carbonic Anhydrase 12 (CA12), Carbonic Anhydrase 2 (CA2), Carbonic Anhydrase 9 (CA9), and Carbonic Anhydrase 1 (CA1) were considered as the core compounds and targets. GO pathway analysis was closely related to hormone, protein phosphorylation, and protein kinase activity. KEGG pathway enrichment primarily involved pathways in cancer and the cAMP signaling pathway in cancer. Overall, this integration method provided guiding significance for the exploration of TCM treatment.