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In recent years, network pharmacology has been developed rapidly, and especially, the concept of ″network target″ has brought a new era in the field of traditional Chinese medicine (TCM). The integrity and systematicness emphasized in network pharmacology comply with the characteristics of holistic view and treatment in Chinese medicine. It can provide deeper insights into the underlying mechanisms of TCM theories, including the illustration on action mechanism of Chinese medicine, selection of pharmacodynamic materials and the combination principles of various Chinese herbs, etc. Therefore, this theory is more suitable for TCM academic characteristics and practical conditions. The key problem in network pharmacology is how to efficiently and quickly identify the interactions between large amounts of drugs and target proteins. As an efficient and high throughput way, drug-target prediction technology can reduce costs, quickly predict the component targets, and provide foundation for the application of TCM network pharmacology. In view of the large amount of compounds and target databases, different prediction methods and technologies have been developed, and used to predict the drug-target interactions. Many virtual screening technologies have been successfully applied to network pharmacology. Based on different prediction principles, drug-target prediction technology can be generally divided into four types： ligand-based prediction, receptor-based prediction, machine learning and combined prediction. In this paper, we are going to review the prediction methods of drug-target interactions and give acomprehensive elaboration of their application in network pharmacology of TCM, hoping to provide beneficial references for various Chinese medicine researchers.

Nao-Mai-Tong (NMT), a Chinese herbal formula, is used for treating ischemia cerebral apoplexy. To discover the components of NMT with potential in vivo bioactivity and investigate the differences between NMT and its single herb components, this study rigorously compared plasma samples collected from rats dosed with NMT and single-herb extracts at different times through LC-high resolution-MS/MS and data processing (Metworks). The plasma of the NMT group contained a total of 66 identified compounds (25 prototypes and 41 metabolites), including anthraquinones, triterpenoid saponins, isoflavones and phthalides. Additionally, glucuronidation, sulfation and cysteine conjugation were the major reactions through which the compounds in NMT were metabolized. The comparison of the groups revealed two metabolites that were only detected in the plasma from the NMT-dosed group, whereas seven prototype ingredients (chrysophanol-8-O-glucoside, ginsenoside Rf, Rg2, Rh1, F1, F2 and chikusetsusaponin IVa) and 12 metabolites (two novel triterpenoid saponins) were only discovered in the plasma samples from the single-herb-dosed groups. Moreover, the trends in the chemical compounds detected presented marked differences between NMT-dosed rat plasma and plasma samples from the single-herb-dosed groups. The above data indicate that prescription compatibility affects the assimilation and elimination of ingredients and provides useful information for further pharmacokinetic studies.

Background:Root of Panax ginseng C. A. Mey (Renseng in Chinese) is a famous Traditional Chinese Medicine. Ginsenosides are the major bioactive components. However, the shortage and high cost of some ginsenoside reference standards make it is difficult for quality control of P. ginseng.Objective:A method, single standard for determination of multicomponents (SSDMC), was developed for the simultaneous determination of nine ginsenosides in P. ginseng (ginsenoside Rg1, Re, Rf, Rg2, Rb1, Rc, Rb2, Rb3, Rd).Materials and Methods:The analytes were separated on Inertsil ODS-3 C18 (250 mm × 4.6 mm, 5 μm) with gradient elution of acetonitrile and water. The flow rate was 1 mL/min and detection wavelength was set at 203 nm. The feasibility and accuracy of SSDMC were checked by the external standard method, and various high-performance liquid chromatographic (HPLC) instruments and chromatographic conditions were investigated to verify its applicability. Using ginsenoside Rg1 as the internal reference substance, the contents of other eight ginsenosides were calculated according to conversion factors (F) by HPLC.Results:The method was validated with linearity (r2 ≥ 0.9990), precision (relative standard deviation [RSD] ≤2.9%), accuracy (97.5%–100.8%, RSD ≤ 1.6%), repeatability, and stability. There was no significant difference between the SSDMC method and the external standard method.Conclusion:New SSDMC method could be considered as an ideal mean to analyze the components for which reference standards are not readily available.SUMMARY A method, single standard for determination of multicomponents (SSDMC), was established by high-performance liquid chromatography for the simultaneous determination of nine ginsenosides in Panax ginseng (ginsenoside Rg1, Re, Rf, Rg2, Rb1, Rc, Rb2, Rb3, Rd)Various chromatographic conditions were investigated to verify applicability of FsThe feasibility and accuracy of SSDMC were checked by the external standard method. Abbreviations used: DRT: Different value of retention time; F: Conversion factor; HPLC: High-performance Liquid Chromatography; LOD: Limit of detection; LOQ: Limit of quantitation; PD: Percent difference; PPD: 20(S)-protopanaxadiol; PPT: 20(S)-protopanaxatriol; RSD: Relative standard deviation; SSDMC: Single Standard for Determination of Multicomponents; TCM: Traditional Chinese Medicine.