Article
Pharmacology & Pharmacy
Wuai Zhou, Kuo Yang, Jianyang Zeng, Xinxing Lai, Xin Wang, Chaofan Ji, Yan Li, Peng Zhang, Shao Li
Summary: Traditional Chinese medicine formulas have been widely used for thousands of years, and with the development of artificial intelligence and network pharmacology, an intelligent recommendation system called FordNet has been proposed to improve clinical diagnosis and treatment. By integrating phenotype and molecular information, FordNet shows significantly better performance compared to baseline methods, demonstrating the potential to advance TCM research and practice.
PHARMACOLOGICAL RESEARCH
(2021)
Review
Pharmacology & Pharmacy
Mengyue Fan, Ching Jin, Daping Li, Yingshan Deng, Lin Yao, Yongjun Chen, Yu-Ling Ma, Taiyi Wang
Summary: The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Computational approaches play a pivotal role in simulating various pharmacological processes of TCM, and network analysis provides an effective means to explain the pharmacological mechanisms. However, homogeneity is a current issue in the development and application of TCM databases.
FRONTIERS IN PHARMACOLOGY
(2023)
Review
Integrative & Complementary Medicine
Xianmin Dai, Jiayi Feng, Yi Chen, Si Huang, Xiaofei Shi, Xia Liu, Yang Sun
Summary: This article summarizes the advantages and obstacles of traditional Chinese medicine in the treatment of nonalcoholic fatty liver disease, and discusses the combined mechanism of herbs in TCM compounds.
Review
Chemistry, Medicinal
Yuxin Bai, Wenlong Wei, Changliang Yao, Shifei Wu, Wei Wang, De-an Guo
Summary: This review summarized the chemical compositions, pharmacology, and safety of Yupingfeng San (YPFS), a commonly used traditional Chinese medicine formula for various respiratory diseases. It highlighted the importance of its chemical constituents in specific pathological processes and provided essential data and references for clinical applications of YPFS.
Article
Biochemical Research Methods
Qikai Niu, Hongtao Li, Lin Tong, Sihong Liu, Wenjing Zong, Siqi Zhang, SiWei Tian, Jingai Wang, Jun Liu, Bing Li, Zhong Wang, Huamin Zhang
Summary: Traditional Chinese medicine (TCM) has a long history in herbal therapy, but the use of herbal formulas still relies on personal experience. This study proposes a herbal formula prediction approach (TCMFP) that integrates TCM therapy experience, artificial intelligence, and network science algorithms to efficiently screen optimal herbal formulas for diseases. The approach includes a herb score (Hscore) based on network target importance, a pair score (Pscore) based on empirical learning, and a herbal formula predictive score (FmapScore) based on intelligent optimization and genetic algorithm. TCMFP successfully generated herbal formulas for Alzheimer's disease, asthma, and atherosclerosis, and functional enrichment and network analysis verified the efficacy of the predicted optimal herbal formulas.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Plant Sciences
Li Tang, Feixia Wang, Lingyan Xiao, Min Shen, Siwei Xia, Zili Zhang, Feng Zhang, Shizhong Zheng, Shanzhong Tan
Summary: YQJPF ameliorates liver injury by suppressing hypoxic injury and ROS-mediated hepatocyte apoptosis through modulating the PI3K/AKT pathway.
JOURNAL OF ETHNOPHARMACOLOGY
(2021)
Article
Plant Sciences
Qianqian Zhao, Jinwei Bai, Yiwei Chen, Xin Liu, Shangfeng Zhao, Guixia Ling, Shubing Jia, Fei Zhai, Rongwu Xiang
Summary: This study explored the efficacy and molecular mechanisms of traditional Chinese medicine (TCM) in the treatment of APAP-induced acute liver injury and provided a method for optimizing TCM formulas. The results showed that TCM could affect the development of liver fibrosis through multiple pathways, including inflammation, immunity, angiogenesis, and antioxidants. Core TCM combinations such as Bupleurum, Astragalus, and Salvia miltiorrhiza were identified as having a significant role in liver injury.
JOURNAL OF ETHNOPHARMACOLOGY
(2022)
Article
Pharmacology & Pharmacy
Songzhe Li, Yang Sun, Yue Sun
Summary: In this study, systems pharmacology and gene chip technology were used to predict targets of a traditional Chinese medicine formula, showing differences in the identified targets but consistency in core drug and small molecule predictions.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Endocrinology & Metabolism
Xuewen Li, Hongyan Chen, Hongyan Yang, Jian Liu, Yang Li, Yue Dang, Jiajing Wang, Lei Wang, Jun Li, Guangning Nie
Summary: This study investigated the potential mechanisms of Tonifying Kidney and Removing Dampness Formula (TKRDF) in treating postmenopausal dyslipidemia through network pharmacology, molecular docking, and in vitro and in vivo experiments. The results show that TKRDF improves postmenopausal dyslipidemia by regulating hormone levels, inhibiting inflammation, promoting angiogenesis, and inhibiting lipid synthesis, which are related to its regulation of the ERK1/2 and PI3K/AKT signaling pathways.
FRONTIERS IN ENDOCRINOLOGY
(2022)
Review
Pharmacology & Pharmacy
Xue Zhu, Qi Yao, Pengshuo Yang, Dan Zhao, Ronghua Yang, Hong Bai, Kang Ning
Summary: This article reviews the application and importance of multi-omics approaches in traditional Chinese medicine (TCM) research, including TCM quality assessment, therapeutic mechanism deciphering, network analysis, and database evaluation. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Pharmacology & Pharmacy
Bradley S. Fleenor, Nicholas A. Carlini, An Ouyang, Matthew P. Harber
Summary: Cardiovascular diseases are the leading cause of death in modern societies, and arterial stiffening plays a crucial role in the development of these diseases. Perivascular adipose tissue, a relatively understudied fat depot, has direct and profound effects on arterial stiffening. Identifying it as a therapeutic target to lower arterial stiffness and reduce cardiovascular disease risk has significant clinical implications.
PHARMACOLOGICAL RESEARCH
(2022)
Article
Multidisciplinary Sciences
Emilie Crouchet, Simonetta Bandiera, Naoto Fujiwara, Shen Li, Hussein El Saghire, Mirian Fernandez-Vaquero, Tobias Riedl, Xiaochen Sun, Hadassa Hirschfield, Frank Juhling, Shijia Zhu, Natascha Roehlen, Clara Ponsolles, Laura Heydmann, Antonio Saviano, Tongqi Qian, Anu Venkatesh, Joachim Lupberger, Eloi R. Verrier, Mozhdeh Sojoodi, Marine A. Oudot, Francois H. T. Duong, Ricard Masia, Lan Wei, Christine Thumann, Sarah C. Durand, Victor Gonzalez-Motos, Danijela Heide, Jenny Hetzer, Shigeki Nakagawa, Atsushi Ono, Won-Min Song, Takaaki Higashi, Roberto Sanchez, Rosa S. Kim, C. Billie Bian, Karun Kiani, Tom Croonenborghs, Aravind Subramanian, Raymond T. Chung, Beate K. Straub, Detlef Schuppan, Maliki Ankavay, Laurence Cocquerel, Evelyne Schaeffer, Nicolas Goossens, Anna P. Koh, Milind Mahajan, Venugopalan D. Nair, Ganesh Gunasekaran, Myron E. Schwartz, Nabeel Bardeesy, Alex K. Shalek, Orit Rozenblatt-Rosen, Aviv Regev, Emanuele Felli, Patrick Pessaux, Kenneth K. Tanabe, Mathias Heikenwaelder, Catherine Schuster, Nathalie Pochet, Mirjam B. Zeisel, Bryan C. Fuchs, Yujin Hoshida, Thomas F. Baumert
Summary: The lack of suitable models for clinical translation hampers drug and target discovery for advanced liver disease. The authors present a human liver cell-based system modeling a clinical prognostic signature, proposing nizatidine for treatment of advanced liver fibrosis and hepatocellular carcinoma prevention. This research identifies urgently needed targets and therapeutics for treatment of advanced liver disease and cancer prevention.
NATURE COMMUNICATIONS
(2021)
Article
Cell Biology
Chen Zhang, Yaqi Li, Bohao Liu, Chao Ning, Yimin Li, Ying Wang, Zhuan Li
Summary: This study developed specific SIRT7 inhibitors through structure prediction and virtual screening, and identified two compounds (2800Z and 40569Z) that could specifically inhibit SIRT7 activity and exhibit therapeutic effects on liver cancer in vivo.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2022)
Article
Pharmacology & Pharmacy
Jingxia Zhao, Yan Wang, Weiwen Chen, Jing Fu, Yu Liu, Tingting Di, Cong Qi, Zhaoxia Chen, Ping Li
Summary: This study used a systems pharmacology approach, metabolomics, and experimental evaluation to investigate the anti-psoriatic mechanism of the LXJD herbal formula. The study revealed that LXJD formula exerts its therapeutic effect by inhibiting the MAPK, PI3K/AKT, and NF-kappa B signaling pathways. The results offer a reliable strategy to elucidate the complex therapeutic mechanism of this Chinese herbal formula in psoriasis from a holistic perspective.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Pharmacology & Pharmacy
Zheng Lian, Jun-Xian Song, Shi-Ran Yu, Li-Na Su, Yu-Xia Cui, Su-Fang Li, Chong-Yoo Lee, Hui-Zhu Liang, Hong Chen
Summary: The study utilized network pharmacology approach and experiments to explore the potential targets underlying the effect of rosuvastatin on heart failure, identifying 35 therapeutic targets and 13 significant treatment pathways related to HF. The therapeutic mechanism of rosuvastatin against HF may be closely related to the inhibition of the expression of apoptosis-related proteins, inflammatory factors, and fibrosis-related genes, with IL-1B being one of the most important target genes.
EUROPEAN JOURNAL OF PHARMACOLOGY
(2021)