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Comparison of the molecular mechanisms of Fuzi Lizhong Pill and Huangqin decoction in the treatment of the cold and heat syndromes of ulcerative colitis based on network pharmacology

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机构: [1]Key Laboratory of Computer-Aided Drug Design of Dongguan City, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, 523710, China [2]Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Dongguan, 523808, China [3]Hubei Key Laboratory of Wudang Local Chinese Medicine Research, School of Pharmaceutical Sciences, Hubei University of Medicine, Shiyan, 442000, China [4]Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang, 524023, China
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关键词: Network pharmacology Fuzi-Lizhong Pill Huangqin decoction Intermingled cold and heat Ulcerative colitis

摘要:
The aim of this study was to illuminate the similarities and differences of two prescriptions as "cold" and "heat" drugs for treating ulcerative colitis (UC) with the simultaneous occurrence of heat and cold syndrome via network pharmacology.(1) Active compounds of Fuzi-Lizhong Pill (FLP) and Huangqin Decoction (HQT) were retrieved from the TCMSP database, and their common active compounds were compared using the Venn diagram. (2) Potential proteins targeted to three sets of compounds either (i) shared by FLP and HQT, (ii) unique to FLP or (iii) unique to HQT were screened from the STP, STITCH and TCMSP databases, and three corresponding core compound sets were identified in Herb-Compound-Target (H-C-T) networks. (3) Targets related to UC were identified from the DisGeNET and GeneCards databases and compared with the FLP-HQT common targets to identify potential targets of FLP-HQT compounds related to UC. (4) Three potential target sets were imported into the STRING database for protein‒protein interaction (PPI) analysis, and three core target sets were defined. (5) The binding capabilities and interacting modes between core compounds and key targets were verified by molecular docking via Discovery Studio 2019 and molecular dynamics (MD) simulations via Amber 2018. (6) The target sets were enriched for KEGG pathways using the DAVID database.(1) FLP and HQT included 95 and 113 active compounds, respectively, with 46 common compounds, 49 FLP-specific compounds and 67 HQT-specific compounds. (2) 174 targets of FLP-HQT common compounds, 168 targets of FLP-specific compounds, and 369 targets of HQT-specific compounds were predicted from the STP, STITCH and TCMSP databases; six core compounds specific to FLP and HQT were screened in the FLP-specific and HQT-specific H-C-T networks, respectively. (3) 103 targets overlapped from the 174 predicted targets and the 4749 UC-related targets; two core compounds for FLP-HQT were identified from the FLP-HQT H-C-T network. (4) 103 FLP-HQT-UC common targets, 168 of FLP-specific targets and 369 of HQT-specific targets had shared core targets (AKT1, MAPK3, TNF, JUN and CASP3) based on the PPI network analysis. (5) Molecular docking demonstrated that naringenin, formononetin, luteolin, glycitein, quercetin, kaempferol and baicalein of FLP and HQT play a critical role in treating UC; meanwhile, MD simulations revealed the stability of protein‒ligand interactions. (6) The enriched pathways indicated that most targets were related to anti-inflammatory, immunomodulatory and other pathways. Compared with the pathways identified using traditional methods, FLP-specific pathways included the PPAR signaling pathway and the bile secretion pathway, and HQT-specific pathways included the vascular smooth muscle contraction pathway and the natural killer cell-mediated cytotoxicity pathway etc. CONCLUSION: In this study, we clarified the common mechanisms of FLP and HQT in treating UC and their specific mechanisms in treating cold and heat syndrome in UC through compound, target and pathway distinction and a literature comparison based on network pharmacology; these results provide a new perspective on the detailed mechanism of "multidrugs and single-disease" thought in traditional Chinese medicine.Copyright © 2023 Elsevier Ltd. All rights reserved.

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出版当年[2022]版:
大类 | 2 区 工程技术
小类 | 1 区 数学与计算生物学 2 区 工程:生物医学 2 区 生物学 3 区 计算机:跨学科应用
最新[2025]版:
大类 | 2 区 医学
小类 | 1 区 数学与计算生物学 2 区 生物学 2 区 计算机:跨学科应用 2 区 工程:生物医学
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第一作者机构: [1]Key Laboratory of Computer-Aided Drug Design of Dongguan City, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, 523710, China [2]Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Dongguan, 523808, China
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通讯作者:
通讯机构: [1]Key Laboratory of Computer-Aided Drug Design of Dongguan City, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, 523710, China [2]Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Dongguan, 523808, China [3]Hubei Key Laboratory of Wudang Local Chinese Medicine Research, School of Pharmaceutical Sciences, Hubei University of Medicine, Shiyan, 442000, China [4]Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang, 524023, China [*1]Guangdong Medical University, Dongguan, 523808, China. [*2]Hubei University of Medicine, Shiyan, 442000, China
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