| Quality control has been one of the most important and difficult issues for the modernization of traditional Chinese drugs (TCDs), while efficient constituents screening supplies the prerequisite and foundation for quality control. However, efficient constituents of most TCDs are still not clear due to the their complexcities, especially, the limitation of study ideas and methods. In this context, the current quality control pattern for TCD, mainly focused on the qualitative and quantitative determination of chemical components, will be difficultly related with effectiveness, leading to some difficulty to control and evaluate the quality of TCD according to the existing content standard.To find a breakthrough of the efficient constituents screening and quality control for TCD, a new pattern based on component knock-out/knock-in strategy was introduced in this paper to accurately screen for the key efficient constituents (main efficient components/effectiveness-related components) and explore the interaction properties of them by component knock-out strategy, further, to set reasonable content standard of these key efficient constituents according to their quantity-efficiacy relationships by component knock-in strategy. All the results will provide some reference for meeting with the requirements of the effectiveness-related, quantitative and accurate, controllable and assessablelquality control standards.In this paper, artificial Calculus bovis (C. bovis), a drug used commonly in clinic with relatively clear pharmacological components, was chosen as the model TCD to prelimilarily validate the feasibility of component knock-out/knock-in strategy. And the anti-fungal test was chosen as the pharmacological model to evaluate the anti-fungal activities of this TCD. The main results were summarized as follows:1. It was found that there were large fluctuation among the contents of the main components in natural C. bovis and its substitutes and there were obvious defferences among the internal qualities of in these samples.The results of chemical analysis on fourty batches of natural C. bovis and its substitutes by ultra-performance liquid chromatography coupled with evaporative light scattering detection (UPLC-ELSD) method showed that there were large variations of the contents of six bile acids in these sample. The six bile acids were taurocholate sodium (TCANa), Cholic acid (CA), ursodeoxycholic acid (UDCA), hyodeoxycholic acid (HDCA), chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA). The coefficient of variation of the total contents of six bile acids in thirteen batches of natural C. bovis ranged from 62.44% to 222.56%, and UDCA had the largaest coefficient of variation among the six components. Contrastly, the coefficient of variation in twenty batches of artificial C. bovis ranged from 63.27% to 122.73%, and HDCA had the largaest coefficient of variation. The above results illustrated that there were large fluctuations among the contents of the main components in commercial natural C. bovis and its substitutes, also, there were obvious differences among the internal qualities of these samples. The quality control standard need further improvement and optimization.2. It was found that the use of chemical fingerprinting combined with biological fingerprinting could effectively improve the classification ability for natural C. bovis and its substitutes.(1) The results of similarity analysis on the chemical fingerprints of natural Calculus bovis, artificial C. bovis, artificial cultivated C. bovis, cultured C. bovis and false species showed that the similarities of 90% samples ranged from 0.6 to 0.9. The results of principal component analysis (PCA) on their chemical fingerprints showed that all the fourty batches of samples could be divided into four groups. Most samples could be well classified according to their species and sources, but, some natural C. bovis still overlapped with cultured C. bovis and artificial C. bovis.(2) By analyzing the biological fingerprints of five micro-organisms (Staphylococcus aureus, Bifidobacterium adolescentis, Escherichia coli, Shigella dysenteriae, Candida albicans) affected by fourty batches of natural C. bovis and its substitutes, it could be found that Candida albicans (C. albicans) was the most sensitive micro-organisms to these sampes and was preferred. The results of PCA on the biological fingerprints of C. albicans affected by these samples showed that all these samples could be divided into five groups. Most samples could be well identified according to their species and sources, but, some natural Calculus bovis still overlapped with other substituts.(3) The results of PCA on the chemical fingerprints of fourty samples and biological fingerprints of C. albicans affected by these samples showed that all these samples could be divided into five groups. Tirty-eight samples could be well classified, and only two artificial C. bovis overlapped with the false species. The above results illustrated that the use of chemical fingerprinting combined with biological fingerprinting could effectively improve the classification ability for natural C. bovis and its substitutes, which would have wide application in the identification of C. bovis and other valuable and rare TCDs.3. The key efficient constitutents with anti-fungal activities in artificial C. bovis were prelimilarily and quickly screened by component knock-out strategy.(1) Eight target constituents were knocked out by separating the artificial C. bovis sample using thin-layer chromatography (TLC). The eight constituents, which were marked as X+, were A+ (TCANa), B+ (unknown constituents), C+ (unknown constituents), D+ (UDCA), E+(HDCA), F+ (CA), G+ (CDCA and DCA) and H+ (unknown constituents), respectively. The sequence of anti-fungal activities of the eight target constituents were H+>G+>E+>C+>F+>A+>B+>D+.(2) The total value of inhibition ratio (I,%) of the eight knocked-out constituents (216.78%) on C. albicans was 6-fold of the I value of artificial C. bovis sample (36.07%), showing that the eight knocked-out constituents had strong antagonistic effects with each other in artificial C. Bovis sample. Also the eight knocked-out constituents all had strong antagonistic effects with their own negative samples, which were obtained by knocking out the target constituents from artificial C. bovis sample and were marked as X-. The sequence of their antagonistic effects was (H+) vs (H-)> (E+) vs (E-)> (G+) vs (G-)> (F+) vs (F-)> (A+) vs (A-)> (C+) vs (C-)> (D+) vs (D-) > (B+) vs (B-).(3) The eight knocked-out constituents may be composed of a class of components with similar structures. When they interacted with C. albicans, they would compete for the same targets resulting in competitive antagonism, which will further lead to the antagonistic effects among these components and constituents.At present, the antagonistic effects among complex components of TCDs have been given little attention. Based on the antagonistic effects among the constituents in artificial C. bovis in this study, the prescription of artificial C. bovis need to be further optimized. Some antagonistic components may be deleted from the prescription to achieve better pharmacological efficiacy.4. The qulity control standards of the key efficient constituents of artificial C. bovis were prelimilarily set by component knock-in strategy.(1) The quantity-efficiacy relationships of the eight knocked-out constituents were established by knocking the eight constituents into their negative samples.(2) Based on the quantity-efficiacy relationships, the minimal contents of the eight constituents in artificial C. bovis were prelimilarily obtained, which were also set as the lowest limits of them for quality control. The minimal contents of the eight constituents in artificial C. bovis were 0.062 mg/mL for constituent A+,0.274 mg/mL for constituent B+,0.162 mg/mL for constituent C+,0.025 mg/mL for constituent D+, 0.231 mg/mL for constituent E+,0.343 mg/mL for constituent F+,0.151 mg/mL for constituent G+ and 0.062 mg/mL for constituent H+, respectively.(3) Some constituents with antagonistic effect may lower the pharmacological actions of other constituents in TCD. Based on the quantity-efficiacy relationships, the maximal contents of the eight constituents in artificial C. bovis were prelimilarily obtained, which were also set as the highest limits of them for quality control. The maximal contents of the eight constituents in artificial C. bovis were 0.062 mg/mL for constituent A+,0.358 mg/mL for constituent B+,0.393 mg/mL for constituent C+, 0.031 mg/mL for constituent D+,0.362 mg/mL for constituent E+,0.361 mg/mL for constituent F+,0.391 mg/mL for constituent G+ and 0.40 mg/mL for constituent H+, respectively.(4) The optimal contents of the eight constituents in artificial C. bovis were further obtained as 0.062 mg/mL for constituent A+,0.35 mg/mL for constituent B+, 0.375 mg/mL for constituent C+,0.025 mg/mL for constituent D+,0.30 mg/mL for constituent E+,0.35 mg/mL for constituent F+,0.375 mg/mL for constituent G+ and 0.35 mg/mL for constituent H+, respectively. The antifungal activity of the sample, which were obtained by combining the eight constituents according to their optimal contents, was increased 92.21% of artificial C. bovis. This study presented a feasible passway to develop the multiple-component Chinese medicine for achieving better pharmacological efficiacy. The interaction properties of multiple constituents and the quantity-efficiacy relationships of these constituents could be found by component knock-out/knock-in strategy, providing some useful ideas for the development of multiple-component Chinese medicine.In summary, a new pattern based on component knock-out/knock-in strategy was prelimilarily established for screening the key efficient constituents and setting their content standards in this paper. These results provided some useful study ideas and a pragmatic pattern for efficient constituents recognition and quality control of TCD.
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