A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.
Ontology highlight
ABSTRACT:
SUBMITTER: Dai Y
PROVIDER: S-EPMC7803147 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Traditional Chinese medicines (TCM) have a long history of use because of its potential complementary therapy and fewer adverse effects. However, the toxicity and safety issues of TCM have drawn considerable attention in the past two decades. Metabolomics is an "omics" approach that aims to comprehensively analyze all metabolites in biological samples. In agreement with the holistic concept of TCM, metabolomics has shown great potential in efficacy and toxicity evaluation of TCM. Recently, a large amount of metabolomic researches have been devoted to exploring the mechanism of toxicity induced by TCM, such as hepatotoxicity, nephrotoxicity, and cardiotoxicity. In this paper, the application of metabolomics in toxicity evaluation of bioactive compounds, TCM extracts and TCM prescriptions are reviewed, and the potential problems and further perspectives for application of metabolomics in toxicological studies are also discussed.
| S-EPMC6278008 | biostudies-other
Project description:Adhesion is a frequent complication after abdominal surgery. Although various methods have been applied to prevent and treat postoperative abdominal adhesion (PAA), few modern drugs designed for clinical applications have reached the expected preventive or therapeutic effect so far. There is an imperative to develop some new strategies for the treatment of PAA. Traditional Chinese medicine (TCM) has been widely practiced for thousands of years and played an indispensable role in the prevention and treatment of diseases. Modern medicine researchers have accepted the therapeutic effects of many active components derived from Chinese medicinal herbs. The review stresses the most commonly used TCM treatment, including Chinese medicinal herbals and monomers, TCM formulas, and acupuncture treatment.
| S-EPMC7199640 | biostudies-literature
Project description:UnlabelledBackgroundIn this work, we analyzed and compared the distribution profiles of a wide variety of molecular properties for three compound classes: drug-like compounds in MDL Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD).ResultsThe comparison of the property distributions suggests that, when all compounds in MDDR, ACD and TCMCD with molecular weight lower than 600 were used, MDDR and ACD are substantially different while TCMCD is much more similar to MDDR than ACD. However, when the three subsets of ACD, MDDR and TCMCD with similar molecular weight distributions were examined, the distribution profiles of the representative physicochemical properties for MDDR and ACD do not differ significantly anymore, suggesting that after the dependence of molecular weight is removed drug-like and non-drug-like molecules cannot be effectively distinguished by simple property-based filters; however, the distribution profiles of several physicochemical properties for TCMCD are obviously different from those for MDDR and ACD. Then, the performance of each molecular property on predicting drug-likeness was evaluated. No single molecular property shows good performance to discriminate between drug-like and non-drug-like molecules. Compared with the other descriptors, fractional negative accessible surface area (FASA-) performs the best. Finally, a PCA-based scheme was used to visually characterize the spatial distributions of the three classes of compounds with similar molecular weight distributions.ConclusionIf FASA- was used as a drug-likeness filter, more than 80% molecules in TCMCD were predicted to be drug-like. Moreover, the principal component plots show that natural compounds in TCMCD have different and even more diverse distributions than either drug-like compounds in MDDR or non-drug-like compounds in ACD.
| S-EPMC3538521 | biostudies-literature
Project description:Traditional Chinese medicines (TCMs) represent one form of complementary and alternative medicine. The popularity and complexity in production make them attractive and vulnerable to adulteration in stages ranging from planting to production. Adulteration refers to the addition of extraneous, improper, or inferior ingredients that should not be present in TCMs. To detect and combat adulterated TCMs, supplementary testing methods (STMs), which expand the capability of routine testing standards, have been applied in China since 2003. From 2003 to 2017, a total of 184 STMs for TCMs were approved by the Chinese national drug regulatory authority. By assessing these STMs, this research intends to identify those TCMs vulnerable to adulteration, to list common adulterants, and to characterize the techniques of analysis. The results show that adulteration of TCMs can be classified into three main categories: the addition of undeclared drugs/chemical substances, substitution with non-drug components, and the addition of foreign non-drug materials. The top five therapeutic areas of TCMs vulnerable to adulteration are diabetes, calm and sleep, sexual dysfunction, pain relief, and rheumatism. A total of 166 adulterants were detected in the adulterated TCM preparations and herbal products studied here, with 158 adulterants in TCM preparations and 43 in herbal products, with 35 adulterants in common. Each STM consists of different pharmaceutical analysis techniques, including tests for physical-chemical properties, chromatography, spectroscopic techniques, and mass spectrometry. The analytical methodology of STMs relies on the combination of these techniques, with HPLC ranking the highest percentage (76.1%) and physical-chemical techniques the lowest percentage (11.4%). This research shows that STMs have played a crucial role in combating adulterated TCMs. However, STMs represent merely a product testing-centered regulatory strategy. The inspection of cultivation and manufacturing processes should also be strengthened. More importantly, the awareness and self-discipline of TCM manufacturers in implementing good manufacturing practices and regulating the planting and cultivation of raw materials should be improved.
| S-EPMC6895211 | biostudies-literature
Project description:Traditional Chinese medicines (TCMs) have proven to possess advantages in counteracting virus infections according to clinical practices. It's therefore of great value to discover novel antivirals from TCMs. In this paper, One hundred medicinal plants which have been included in TCM prescriptions for antiviral treatment were selected and prefractionated into 5 fractions each by sequentially using cyclohexane, dichloromethane, ethyl acetate, n-butanol, and water. 500 TCM-simplified extracts were then subjected to a phenotypic screening using a recombinant IAV expressing Gaussia luciferase. Ten TCM fractions were identified to possess antiviral activities against influenza virus. The IC50's of the hit fractions range from 1.08 to 6.45 μg/mL, while the SIs, from 7.52 to 98.40. Furthermore, all the ten hit fractions inhibited the propagation of progeny influenza virus significantly at 20 μg/mL. The hit TCM fractions deserve further isolation for responsible constituents leading towards anti-influenza drugs. Moreover, a library consisting of 500 simplified TCM extracts was established, facilitating antiviral screening in quick response to emerging and re-emerging viruses such as Ebola virus and current SARS-CoV-2 pandemic.
| S-EPMC7584957 | biostudies-literature
Project description:Differential proteomics, which has been widely used in studying of traditional Chinese medicines (TCMs) during the past 10 years, is a powerful tool to visualize differentially expressed proteins and analyzes their functions. In this paper, the applications of differential proteomics in exploring the action mechanisms of TCMs on various diseases including cancers, cardiovascular diseases, diabetes, liver diseases, kidney disorders and obesity, etc. were reviewed. Furthermore, differential proteomics in studying of TCMs identification, toxicity, processing and compatibility mechanisms were also included. This review will provide information for the further applications of differential proteomics in TCMs studies.
| S-EPMC6325846 | biostudies-literature
Project description:The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a global pandemic. Up to now, numerous medicines have been applied or approved for the prevention and control of the virus infection. However, the efficiency of each medicine or combination is completely different or still unknown. In this review, we discuss the types, characteristics, antiviral mechanisms, and shortcomings of recommended candidate medicines for SARS-CoV-2 infection, as well as perspectives of the drugs for the disease treatment, which may provide a theoretical basis for drug screening and application.
| S-EPMC7313518 | biostudies-literature
Project description:Experiential and sensory evaluation is an ancient method that remains important in the current quality control system of Traditional Chinese Medicines (TCMs). The process is rapid and convenient when evaluating the quality of crude materials in TCM markets. However, sensory evaluation has been met with skepticism because it is mainly based on experience and lacks a scientific basis. In this study, rhubarb was selected to demonstrate how color-based sensory evaluation could differentiate the quality of herbal medicines objectively. The colors of the rhubarb samples, expressed as RGB values, were obtained from different parts and forms of the plant, including the plant's surface, fracture surface color, and a powdered form with or without treatment with a color-developing reagent. We first divided the rhubarb samples into three grades based on the total content of five hydroxyanthraquinone derivatives, the major pharmacological components in rhubarb. Then, a three-layer back-propagation artificial neural network (BP-ANN), calibrated with selected training samples, was used to correlate the quality of the rhubarb with its color. The color of the rhubarb powder after coloration attained the highest accuracy (92.3%) in predicting the quality grade of the test samples with the established artificial neural networks. Finally, a standardized colorimetric grading scale was created based on the spatial distribution of the rhubarb samples in a two-dimensional chromaticity diagram according to the colors of the powdered rhubarb after color enhancement. By comparing the color between the scale and the tested samples, similar to performing a pH test with indicator paper, subjects without sensory evaluation experience could quickly determine the quality grade of rhubarb. This work illustrates the technical feasibility of the color-based grading of rhubarb quality and offers references for quantifying and standardizing the sensory evaluation of TCMs, foods and other products.
| S-EPMC3492245 | biostudies-literature
Project description:UnlabelledBackgroundIn order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared.ResultsFirst, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets.ConclusionThe analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design.
| S-EPMC3561156 | biostudies-literature
Project description:The application of multi-locus DNA metabarcoding in traditional medicines
| PRJEB25620 | ENA