Application Of Spectrum-effect Correlation Analysis In The Study Of Ganoderma Immune Activity

The chemical components of traditional Chinese medicine are complex,so it is difficult to evaluate the quality of traditional Chinese medicine comprehensively by single or several chemical components.The application of fingerprint can comprehensively and completely reflect the types and contents of chemical components.However,it is difficult to evaluate the efficacy of traditional Chinese medicine by chemical fingerprint.And the therapeutic effect of traditional Chinese medicine is based on the complex interaction of chemical components as a whole system,so there is a need for methods to control the quality of complex system.Therefore,by combining the chemical fingerprint with the efficacy of traditional Chinese medicine,the relationship between the spectrum and the efficacy of traditional Chinese medicine is establelished through linear or nonlinear mathematical treatment,the material basis of the efficacy of traditional Chinese medicine is clarified,and the compound groups related to the efficacy are determined.Aims: To study the immunoregulatory components of Ganoderma.Based on the combination of single factor experiment and orthogonal experiment,the optimal extraction process of the active components in Ganoderma was optimized,and the BP neural network model was established to predict efficacy and extraction amount.Methods: 1.HPLC fingerprint and spectrum-effect relationship of Ganoderma were established to predict the active compounds.The target compounds were identified by high resolution mass spectrometry.BP neural network model was established to predict the efficacy.2.The concentration of ionic liquid,ultrasonic power,ultrasonic time,centrifugal speed and solid-liquid ratio were optimized by single factor experiment and orthogonal experiment.BP neural network model was established to predict the extraction yield of target compounds.Results: 1.HPLC fingerprint and spectrum-effect relationship of Ganoderma ethanol extract were established,and BP neural network was established to predict the efficacy.2.P7,P8,P13,P14,p17,P22,p23,P26,P28,P31,P32,P33,p41 and P45 were positively correlated with the enhancement of immune activity,P3,p34,P39 and p43 were negatively correlated with the enhancement of immune activity.It was identified by high resolution mass spectrometry that lucidenic acid N(P14)ganoderenic acid B(P16),ganoderenic acid K(P18),ganoderic acid A(P22),lucidenic acid A(P24),ganoderic acid D(P26),ganoderic acid F(P28)and ganoderic acid J(30).When the concentration of the sample was 200 μg/m L,P14,P22,P26 and p28 were consistent with the results of "spectral effect relationship".BP neural network was trained with the common peak area and immune efficacy index of Ganoderma fingerprint as samples,and a combined evaluation system of Ganoderma fingerprint efficacy was established.The correlation coefficient r of BP network model was 0.98643,and the error of pharmacodynamic prediction results was in the ideal range.2.The optimal extraction process of the active components in Ganoderma was: ionic liquid concentration 1.4 M,ultrasonic power 400 W,ultrasonic time 20 min,centrifugal speed 4000 r/min,solid-liquid ratio 1 g: 20 m L.Under the optimal conditions,the total yield of extraction was 3.31 mg/g.The Levenberg-Marquardt back-propagation algorithm was used to optimize the three-layered neural network to predict the extraction yield of target compounds from Ganoderma.The configuration of 9 neurons in the hidden layer conducted to the high correlation coefficient(r = 0.93332)and the error of pharmacodynamic prediction results was in the ideal range.Conclusions: When the concentration was 200 μg/m L,lucidenic acid N,ganoderenic acid B,ganoderenic acid K,ganoderic acid A,ganoderic acid D and ganoderic acid F were the effective components to activate RAW264.7 cells,which could enhance the immune function.lucidenic acid A,ganoderic acid J were the effective components to inhibit RAW264.7 cells,which can inhibit the immune function.At the same time,the evaluation system of Ganoderma spectrum effect combination was established to evaluate the efficacy of Ganoderma by measuring its fingerprint,so as to evaluate the quality of Ganoderma by spectrum effect combination mode.The extraction yields of the present approach may increase by 36.21%,compared with traditional methods.Thus,for target compounds from Ganoderma,the IL-UAE was a highly efficient and rapid extraction technique.For the considered experimental conditions,neural network modeling could effectively simulate the experimental data and reproduce the process behavior.