Bangjie Li1, Junqian Rui1, Xuejian Ding1, Yifan Chen1, Xinghao Yang2. 1. College of Life Sciences, Nanjing Normal University, Nanjing 210023, China. 2. College of Life Sciences, Nanjing Normal University, Nanjing 210023, China. Electronic address: yangxinh@njnu.edu.cn.
Abstract
BACKGROUND: SiNiSan (SNS) is a traditional Chinese medicine (TCM) prescription that has been widely used in the clinical treatment of irritable bowel syndrome (IBS). However, the underlying active substances and molecular mechanisms remain obscure. PURPOSE: A bioinformatics/topology based strategy was proposed for identification of the drug targets, therapeutic agents and molecular mechanisms of SiNiSan against irritable bowel syndrome. MATERIALS AND METHODS: In this work, a bioinformatics/network topology based strategy was employed by integrating ADME filtering, text mining, bioinformatics, network topology, Venn analysis and molecular docking to uncover systematically the multicomponent synergy mechanisms. In vivo experimental validation was executed in a Visceral Hypersensitivity (VHS) rat model. RESULTS: 76 protein targets and 109 active components of SNS were identified. Bioinformatics analysis revealed that 116 disease pathways associated with IBS therapy could be classified into the 19 statistically enriched functional sub-groups. The multi-functional co-synergism of SNS against IBS were predicted, including inflammatory reaction regulation, oxidative-stress depression regulation and hormone and immune regulation. The multi-component synergetic effects were also revealed on the herbal combination of SNS. The hub-bottleneck genes of the protein networks including PTGS2, CALM2, NOS2, SLC6A3 and MAOB, MAOA, CREB1 could become potential drug targets and Paeoniflorin, Naringin, Glycyrrhizic acid may be candidate agents. Experimental results showed that the potential mechanisms of SiNiSan treatment involved in the suppression of activation of Dopaminergic synapse and Amphetamine addiction signaling pathways, which are congruent with the prediction by the systematic approach. CONCLUSION: The integrative investigation based on bioinformatics/network topology strategy may elaborate the multicomponent synergy mechanisms of SNS against IBS and provide the way out to develop new combination medicines for IBS.
BACKGROUND: SiNiSan (SNS) is a traditional Chinese medicine (TCM) prescription that has been widely used in the clinical treatment of irritable bowel syndrome (IBS). However, the underlying active substances and molecular mechanisms remain obscure. PURPOSE: A bioinformatics/topology based strategy was proposed for identification of the drug targets, therapeutic agents and molecular mechanisms of SiNiSan against irritable bowel syndrome. MATERIALS AND METHODS: In this work, a bioinformatics/network topology based strategy was employed by integrating ADME filtering, text mining, bioinformatics, network topology, Venn analysis and molecular docking to uncover systematically the multicomponent synergy mechanisms. In vivo experimental validation was executed in a Visceral Hypersensitivity (VHS) rat model. RESULTS: 76 protein targets and 109 active components of SNS were identified. Bioinformatics analysis revealed that 116 disease pathways associated with IBS therapy could be classified into the 19 statistically enriched functional sub-groups. The multi-functional co-synergism of SNS against IBS were predicted, including inflammatory reaction regulation, oxidative-stress depression regulation and hormone and immune regulation. The multi-component synergetic effects were also revealed on the herbal combination of SNS. The hub-bottleneck genes of the protein networks including PTGS2, CALM2, NOS2, SLC6A3 and MAOB, MAOA, CREB1 could become potential drug targets and Paeoniflorin, Naringin, Glycyrrhizic acid may be candidate agents. Experimental results showed that the potential mechanisms of SiNiSan treatment involved in the suppression of activation of Dopaminergic synapse and Amphetamine addiction signaling pathways, which are congruent with the prediction by the systematic approach. CONCLUSION: The integrative investigation based on bioinformatics/network topology strategy may elaborate the multicomponent synergy mechanisms of SNS against IBS and provide the way out to develop new combination medicines for IBS.
Authors: Rong Tang; Xiaoqing Peng; Xiaohong Zhou; Zhimin Zheng; Jiayu Yin; Hong Liu Journal: Evid Based Complement Alternat Med Date: 2022-04-01 Impact factor: 2.629