Central Research Institute, Shanghai Pharmaceuticals Holding Co., Ltd., Shanghai, 201203, China.
Central Research Institute, Shanghai Pharmaceuticals Holding Co., Ltd., Shanghai, 201203, China; The MOE Key Laboratory for Standardization of Chinese Medicines and the SATCM Key Laboratory for New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
J Ethnopharmacol. 2020 Jul 15;257:112827. doi: 10.1016/j.jep.2020.112827. Epub 2020 Apr 7.
Yixin Ningshen tablet is a CFDA-approved TCM formula for treating depression clinically. However, little is known about its active compounds and related potential target proteins, so far, no researches have been performed to investigate its mechanism of action for the treatment of depression.
Here we develop an original bioinformatics pipeline composed of text mining tools, database querying and systems biology combinatorial analysis, which is applied to rapidly explore the mechanism of action of Yixin Ningshen tablet in treating depression.
Text mining and database query were applied to identify active compounds in Yixin Ningshen tablet for the treatment of depression. Then SwissTargetPrediction was used to predict their potential target proteins. PubMed was retrieved to summarize known depression related systems biology results. Ingenuity Pathway Analysis (IPA) tools and STRING were applied to construct a compound-target protein-gene protein-differential protein-differential metabolite network with the integration of compound-target interaction and systems biology results, as well as enrich the target proteins related pathways. ChEMBL and CDOCKER were used to validate the compound-target interactions.
62 active compounds and their 286 potential target proteins were identified in Yixin Ningshen tablet for the treatment of depression. The construction of compound-target protein-gene protein-differential protein-differential metabolite network shrinked the number of potential target proteins from 286 to 133. Pathway enrichment analysis of target proteins indicated that Neuroactive ligand-receptor interaction, Calcium signaling pathway, Serotonergic synapse, cAMP signaling pathway and Gap junction were the common primary pathways regulated by both Yixin Ningshen Tablet and anti-depressant drugs, and MAPK, Relaxin, AGE-RAGE, Estrogen, HIF-1, Jak-STAT signaling pathway, Endocrine resistance, Arachidonic acid metabolism and Regulation of actin cytoskeleton were the specifically main pathways regulated by Yixin Ningshen tablet for the treatment of depression. Further validations based on references and molecular docking results demonstrated that Yixin Ningshen tablet could primarily target MAPT, CHRM1 and DRD1, thus regulating serotonergic neurons, cholinergic transmission, norepinephrine and dopamine reuptake for the treatment of depression.
This study displays the power of extensive mining of public data and bioinformatical repositories to provide answers for a specific pharmacological question. It furthermore demonstrates how the usage of such a combinatorial approach is advantageous for the biologist in terms of experimentation time and costs.
益心宁神片是 CFDA 批准的用于治疗临床抑郁症的中药配方。然而，目前对于其活性化合物及其相关潜在靶蛋白知之甚少，因此，迄今为止，尚未有研究对其治疗抑郁症的作用机制进行研究。
本研究开发了一种原始的生物信息学分析流程，该流程由文本挖掘工具、数据库查询和系统生物学组合分析组成，用于快速探索益心宁神片治疗抑郁症的作用机制。
应用文本挖掘和数据库查询技术，鉴定益心宁神片中治疗抑郁症的活性化合物。然后使用 SwissTargetPrediction 预测其潜在的靶蛋白。从 PubMed 检索中总结已知的与抑郁症相关的系统生物学结果。应用 IPA 工具和 STRING 构建一个化合物-靶蛋白-基因-蛋白-差异蛋白-差异代谢物网络，整合化合物-靶蛋白相互作用和系统生物学结果，并丰富与靶蛋白相关的途径。使用 ChEMBL 和 CDOCKER 验证化合物-靶蛋白相互作用。
在益心宁神片中鉴定出 62 种活性化合物及其 286 个潜在靶蛋白，用于治疗抑郁症。化合物-靶蛋白-基因-蛋白-差异蛋白-差异代谢物网络的构建将潜在靶蛋白的数量从 286 个缩小到 133 个。靶蛋白的通路富集分析表明，神经活性配体-受体相互作用、钙信号通路、5-羟色胺能突触、cAMP 信号通路和缝隙连接是益心宁神片和抗抑郁药共同调节的主要通路，MAPK、松弛素、AGE-RAGE、雌激素、HIF-1、Jak-STAT 信号通路、内分泌抵抗、花生四烯酸代谢和肌动蛋白细胞骨架的调节是益心宁神片治疗抑郁症的特异性主要通路。基于参考文献和分子对接结果的进一步验证表明，益心宁神片主要靶向 MAPT、CHRM1 和 DRD1，从而调节 5-羟色胺能神经元、胆碱能传递、去甲肾上腺素和多巴胺再摄取，用于治疗抑郁症。
本研究展示了广泛挖掘公共数据和生物信息学资源以回答特定药理学问题的能力。此外，它还展示了这种组合方法在实验时间和成本方面对生物学家的优势。
