Traditional Chinese medicine (TCM) is not only an effective solution for primary health care, but also a great resource for drug innovation and discovery. To meet the increasing needs for TCM-related data resources, we developed ETCM, an Encyclopedia of Traditional Chinese Medicine. ETCM includes comprehensive and standardized information for the commonly used herbs and formulas of TCM, as well as their ingredients. The herb basic property and quality control standard, formula composition, ingredient drug-likeness, as well as many other information provided by ETCM can serve as a convenient resource for users to obtain thorough information about a herb or a formula. To facilitate functional and mechanistic studies of TCM, ETCM provides predicted target genes of TCM ingredients, herbs, and formulas, according to the chemical fingerprint similarity between TCM ingredients and known drugs. A systematic analysis function is also developed in ETCM, which allows users to explore the relationships or build networks among TCM herbs, formulas,ingredients, gene targets, and related pathways or diseases. ETCM is freely accessible at http://www.nrc.ac.cn:9090/ETCM/. We expect ETCM to develop into a major data warehouse for TCM and to promote TCM related researches and drug development in the future.

Compound Danshen Formula (CDF) is a widely used Traditional Chinese Medicine (TCM) which has been extensively applied in clinical treatment of cardiovascular diseases (CVDs). However, the underlying mechanism of clinical administrating CDF on CVDs is not clear. In this study, the pharmacological effect of CDF on CVDs was analyzed at a systemic point of view. A systems-pharmacological model based on chemical, chemogenomics and pharmacological data is developed via network reconstruction approach. By using this model, we performed a high-throughput in silico screen and obtained a group of compounds from CDF which possess desirable pharmacodynamical and pharmacological characteristics. These compounds and the corresponding protein targets are further used to search against biological databases, such as the compound-target associations, compound-pathway connections and disease-target interactions for reconstructing the biologically meaningful networks for a TCM formula. This study not only made a contribution to a better understanding of the mechanisms of CDF, but also proposed a strategy to develop novel TCM candidates at a network pharmacology level.

Buchang naoxintong capsule (BNC) is a traditional Chinese medicine approved for the treatment of cerebrovascular and cardiovascular diseases. However, little is known about the specific protective function or mechanism by which BNC protects against myocardial injury. This research was designed to investigate the cardioprotective effects of BNC in vitro model of hydrogen peroxide (H₂O₂)-induced H9c2 rat cardiomyoblasts. BNC intestinal absorption liquid was used in this study instead of drug-containing serum or extracting solution. Our study revealed that BNC preconditioning enhanced antioxidant function by increasing the activities of total-antioxygen capacity, total-superoxide dismutase, and catalase and by decreasing the production of reactive oxygen species and malondialdehyde. BNC preconditioning also activated extracellular signal-regulated kinases (ERK1/2) and inhibited apoptosis-related proteins such as poly ADP-ribose polymerase (PARP) and caspase-3. Additionally, preincubation with BNC reduced intracellular Ca²⁺concentration, improved mitochondrial membrane potential, and decreased the apoptosis rate of H9c2 cells in a dose-dependent manner. These data demonstrated that BNC protects H9c2 cardiomyoblasts from H₂O₂-induced oxidative injury by increasing antioxidant abilities, activating ERK1/2, and blocking Ca²⁺-dependent and mitochondria-mediated apoptosis. Based on our results, the potency of BNC for protecting H9c2 cells from oxidative damage is comparable to that of trimetazidine.

QiXueHe Capsule (QXHC) is a Chinese patent drug that is extensively used for the treatment of menstrual disorders. However, its underlying pharmacological mechanisms have not been fully elucidated. A list of QXHC putative targets were predicted using MetaDrug. An interaction network using links between QXHC putative targets and the known therapeutic targets of menstrual disorders was constructed. QXHC candidate targets were also identified via calculating the topological feature values of nodes in the network. Additionally, molecular docking simulation was performed to determine the binding efficiency of QXHC compound-putative target pairs. A total of 1022 putative targets were predicted for 311 chemical components containing in QXHC. Following the calculation of topological features of QXHC putative target-known therapeutic target of menstrual disorder network, 66 QXHC candidate targets for the treatment of menstrual disorders were identified. Functionally, QXHC candidate targets were significantly associated with several biological pathways, such as VEGF and Chemokine signaling pathways, Alanine/aspartate/glutamate metabolism, Long-term depression and T/B cell receptor signaling pathway. Moreover, molecular docking simulation demonstrated that there were 20 pairs of QXHC chemical component-candidate target had the strong binding free energy. This novel and scientific network pharmacology-based study holistically deciphers that the pharmacological mechanisms of QXHC in the treatment of menstrual disorders may be associated with its involvement into hemopoiesis, analgesia, nutrients absorption and metabolism, mood regulation, as well as immune modulation.

Traditional Chinese medicine (TCM) is one of the oldest East Asian medical systems. The present study adopted a systems biology-based approach to provide new insights relating to the active constituents and molecular mechanisms underlying the effects of dragon's blood (DB) tablets for the treatment of colitis. This study integrated chemical analysis, prediction of absorption, distribution, metabolism, and excretion (ADME), and network pharmacology. Firstly, a rapid, reliable, and accurate ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry method was employed to identify 48 components of DB tablets. In silico prediction of the passive absorption of these compounds, based on Caco-2 cell permeability, and their P450 metabolism enabled the identification of 22 potentially absorbed components and 8 metabolites. Finally, networks were constructed to analyze interactions between these DB components/metabolites absorbed and their putative targets, and between the putative DB targets and known therapeutic targets for colitis. This study provided a great opportunity to deepen the understanding of the complex pharmacological mechanisms underlying the effects of DB in colitis treatment.