RESUMO
Traditional Chinese medicines (TCMs) have wide pharmacological activities, and the ingredients in individual TCMs determine their efficacies. To understand the "efficacy-nature-structure" relationship of TCM, compounds from 2444 kinds of herbs were collected, and the associations between family, structure, nature, and biological activities were mined and analyzed. Bernoulli Naïve Bayes profiling and a data analysis method were used to predict the targets of compounds. The results show that genetic material determined the representation of ingredients from herbs and the nature of TCMs and that the superior scaffolds of compounds of cold nature were 2-phenylochrotinone, anthraquinone, and coumarin, while the compounds of hot nature were cyclohexene. The results of the similarity analysis and distribution for molecular descriptors of compounds show that compounds associated with the same nature were similar and compounds associated with different natures occurred as a transition in part. As for integral compounds from 2-phenylochrotinone, anthraquinone, coumarin, and cyclohexene, the value of the shape index increased, indicating the transition of scaffolds from a spherical structure to a linear structure, with various molecular descriptors decreasing. Three medicines and three recipes prescribed based on "efficacy-nature-structure" had a higher survival rate in the clinic and provided powerful evidence for TCM principles. The research improves the understanding of the "efficacy-nature-structure" relationship and extends TCM applications.
RESUMO
ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) has been widely used as an approach worldwide. Chinese Medicines (CMs) had been used to treat and prevent viral infection pneumonia diseases for thousands of years and had accumulated a large number of clinical experiences and effective prescriptions. AIM OF THE STUDY: This research aimed to systematically excavate the classical prescriptions of Chinese Medicine (CM), which have been used to prevent and treat Pestilence (Wenbing, Wenyi, Shiyi or Yibing) for long history in China, to obtain the potential prescriptions and ingredients to alternatively treat COVID-19. MATERIALS AND METHODS: We developed the screening system based on data mining, molecular docking and network pharmacology. Data mining and association network were used to mine the high-frequency herbs and formulas from ancient prescriptions. Virtual screening for the effective components of high frequency CMs and compatibility Chinese Medicine was explored by a molecular docking approach. Furthermore, network pharmacology method was used to preliminarily uncover the molecule mechanism. RESULTS: 574 prescriptions were obtained from 96,606 classical prescriptions with the key words to treat "Warm diseases (Wenbing)", "Pestilence (Wenyi or Yibing)" or "Epidemic diseases (Shiyi)". Meanwhile, 40 kinds of CMs, 36 CMs-pairs, 6 triple-CMs-groups existed with high frequency among the 574 prescriptions. Additionally, the key targets of SARS-COV-2, namely 3CL hydrolase (Mpro) and angiotensin-converting enzyme 2(ACE2), were used to dock the main ingredients from the 40 kinds by the LigandFitDock method. A total of 66 compounds components with higher frequency were docked with the COVID-19 targets, which were distributed in 26 kinds of CMs, among which Gancao (Glycyrrhizae Radix Et Rhizoma), HuangQin (Scutellariae Radix), Dahuang (Rhei Radix Et Rhizome) and Chaihu (Bupleuri Radix) contain more potential compounds. Network pharmacology results showed that Gancao (Glycyrrhizae Radix Et Rhizoma) and HuangQin (Scutellariae Radix) CMs-pairs could also interact with the targets involving in immune and inflammation diseases. CONCLUSIONS: These results we obtained probably provided potential candidate CMs formulas or active ingredients to overcome COVID-19. Prospectively, animal experiment and rigorous clinic studies are needed to confirm the potential preventive and treat effect of these CMs and compounds.