Department of Pharmaceutical Analysis, School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, PR China.
Department of Ultrasound, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, PR China.
Talanta. 2020 May 1;211:120710. doi: 10.1016/j.talanta.2020.120710. Epub 2020 Jan 3.
Screening diagnostic biomarkers can be challenging due to the complexity of traditional Chinese medicine (TCM) and ambiguous pharmacological mechanisms. In this study, we reported an integrated strategy for accurately screening diagnostic biomarkers based on metabolomics coupled with network pharmacology. First, a feasible pharmacological model was established through systems pharmacology and based on metabolomics-based techniques to explore diagnostic biomarkers. While the components satisfying the q-value < 0.05, fold change (FC) ≥ 1.2 or FC ≤ 0.8, coefficient of variance (CV) ≤ 30%(QC) and the variable importance in the project (VIP) value > 1 are considered to be diagnostic biomarkers. Second, the ingredients were retained only when oral bioavailability (OB), Caco-2 permeability, drug half-life, TPSA and drug likeness (DL) satisfied the criteria (OB ≥ 40%; Caco-2 ≥ -0.4; HL ≥ 4 h; TPSA˂140; DL ≥ 0.18) suggested by the TCMSP database. Moreover, ingredients that exhibit extensive biological activity in TCM are also retained. Third, the effect targets of TCM were screened using the TCMSP database, Swiss Target Prediction and STICH online software. Disease targets were gathered from the therapeutic target database (TTD), PharmGkb and TCMSP database. Hub genes were screened by potential protein-protein interaction (PPI) network pharmacology analysis. Finally, a metabolic network pathway is established between the diagnostic biomarker and the hub gene. In the network analysis of metabolic pathways, most of the genes involved in this pathway are the second-step-obtained hub genes, which can explain the accuracy of the identified biomarkers. The proposed integrated strategy was successfully applied to explore the mechanism of action of Pulsatilla decoction (PD) in the treatment of acute ulcerative colitis (UC). Based on this integrated strategy, 23 potential biomarkers of acute UC treated with PD were identified. In conclusion, the integrated strategy provides novel insights into network pharmacology and metabolomics as effective tools to illuminate the mechanism of action of TCM.
由于中药(TCM)的复杂性和药理学机制的模糊性,筛选诊断生物标志物具有挑战性。在这项研究中,我们报告了一种基于代谢组学和网络药理学的准确筛选诊断生物标志物的综合策略。首先,通过系统药理学和基于代谢组学的技术建立可行的药理学模型,以探索诊断生物标志物。当满足 q 值 < 0.05、倍数变化(FC)≥ 1.2 或 FC≤ 0.8、系数变化(CV)≤ 30%(QC)和项目中的变量重要性(VIP)值> 1 时,认为符合标准。其次,仅保留口服生物利用度(OB)、Caco-2 通透性、药物半衰期、TPSA 和药物相似性(DL)符合 TCMSP 数据库建议标准(OB≥40%;Caco-2≥-0.4;HL≥4 h;TPSA<140;DL≥0.18)的成分。此外,还保留了在 TCM 中表现出广泛生物活性的成分。第三,使用 TCMSP 数据库、Swiss Target Prediction 和 STICH 在线软件筛选 TCM 的作用靶点。从治疗靶点数据库(TTD)、PharmGkb 和 TCMSP 数据库收集疾病靶点。通过潜在的蛋白质-蛋白质相互作用(PPI)网络药理学分析筛选出枢纽基因。最后,在诊断生物标志物和枢纽基因之间建立代谢网络途径。在代谢途径网络分析中,该途径涉及的大多数基因都是第二步获得的枢纽基因,这可以解释所鉴定生物标志物的准确性。所提出的综合策略成功地应用于探索白头翁汤(PD)治疗急性溃疡性结肠炎(UC)的作用机制。基于该综合策略,鉴定了 23 种治疗急性 UC 的 PD 潜在生物标志物。总之,该综合策略为网络药理学和代谢组学提供了新的见解,为阐明 TCM 的作用机制提供了有效工具。