Objective: The analgesic effect of Paeonia Lactiflora has been widely accepted in traditional Chinese medicine. But little is known about the potential mechanism. This study aims to elucidate the effective components ...Objective: The analgesic effect of Paeonia Lactiflora has been widely accepted in traditional Chinese medicine. But little is known about the potential mechanism. This study aims to elucidate the effective components and analgesic mechanism based on network pharmacology. Methods: TCMSP was screened to collect the possible active ingredients and their CAS and SMILES was searched in Pubchem and further be used for reverse molecular docking in Swiss Target Prediction database to obtain potential targets. Pain-related molecules were obtained from GeenCards database, and the predicted targets of Paeonia Lactiflora for pain treatment were selected by Wayne diagram. For mechanism analysis, the protein-protein interactions were constructed by String, the GO analysis and KEGG analysis were conducted in DAVID. Results: Through GO analysis and KEGG analysis, we found that the pain related signaling pathways mainly involved in serotonergic synapse, calcium signaling pathway, inflammatory mediator TRP channels. Using network-based systems biology and molecular docking analyses, we predicted that 11 active ingredients in Paeonia Lactiflora has the analgesic effects with 97 potential targets. PRKCA, CASP3, ALOX15, SLC6A4, PRKCG, ALOX5, PRKCB, ALOX12, EGFR, ADRB2, RYR3, RYR1, NOS2, PTAFR, PRKCQ, and PRKCD were involved in the analgesic effects of Paeonia Lactiflora. Conclusion: Paeonia Lactiflora may alleviate pain through inflammatory mediator regulation of TRP channels, Ca2+ signaling pathway and 5-HT receptor. PRKCA, PRKCB, PRKCD,PRKCQ, and PRKCG may be new targets for pain treatment.展开更多
基金the National Natural Science Foundation of China (Grant No. 81874404).
文摘Objective: The analgesic effect of Paeonia Lactiflora has been widely accepted in traditional Chinese medicine. But little is known about the potential mechanism. This study aims to elucidate the effective components and analgesic mechanism based on network pharmacology. Methods: TCMSP was screened to collect the possible active ingredients and their CAS and SMILES was searched in Pubchem and further be used for reverse molecular docking in Swiss Target Prediction database to obtain potential targets. Pain-related molecules were obtained from GeenCards database, and the predicted targets of Paeonia Lactiflora for pain treatment were selected by Wayne diagram. For mechanism analysis, the protein-protein interactions were constructed by String, the GO analysis and KEGG analysis were conducted in DAVID. Results: Through GO analysis and KEGG analysis, we found that the pain related signaling pathways mainly involved in serotonergic synapse, calcium signaling pathway, inflammatory mediator TRP channels. Using network-based systems biology and molecular docking analyses, we predicted that 11 active ingredients in Paeonia Lactiflora has the analgesic effects with 97 potential targets. PRKCA, CASP3, ALOX15, SLC6A4, PRKCG, ALOX5, PRKCB, ALOX12, EGFR, ADRB2, RYR3, RYR1, NOS2, PTAFR, PRKCQ, and PRKCD were involved in the analgesic effects of Paeonia Lactiflora. Conclusion: Paeonia Lactiflora may alleviate pain through inflammatory mediator regulation of TRP channels, Ca2+ signaling pathway and 5-HT receptor. PRKCA, PRKCB, PRKCD,PRKCQ, and PRKCG may be new targets for pain treatment.
